The Evaluating Self

Pairings

Two sources from different traditions that turn out to make the same claim, read together: the claim they share, the evidence on each side, and the point where the likeness breaks. The ring shows where the pairings run: each ribbon joins two questions and is as thick as the number of pairings between them.

AI Snake Oil × Bainbridge

How to get good output

AI Snake Oil, Arvind Narayanan and Sayash Kapoor

overautomation, and human oversight as the fine print under a full-automation pitch

Ironies of Automation, Lisanne Bainbridge

the human left to supervise a process they can no longer perform

Shared claim

An oversight role that exists on paper stops being exercised in practice.

Evidence

Toronto's beach model, never once overruled while beaches stayed open on 64 per cent of unsafe days; the Dutch childcare benefit system and about thirty thousand wrongly accused parents.

Evidence

The account of monitoring and manual skill decaying through disuse.

Where it breaks

Bainbridge describes a skill decaying over time, which implies it was once there. The Toronto and Dutch cases show the override unused from the first day, which makes it an institutional fact rather than a human-factors one, and training will not touch it.

AI Snake Oil × Christian

How to get good output · What to keep and what to hand off

AI Snake Oil, Arvind Narayanan and Sayash Kapoor

the target variable is not the thing it stands for, and the substitution carries the inequality in

The Alignment Problem, Brian Christian

the alignment problem: systems optimise what they were given

Shared claim

A system optimises the variable it was given, and the harm lives in the gap between that variable and what anyone meant.

Evidence

Optum's Impact Pro predicting spending rather than need; COMPAS developers speaking of crime while the data records arrests.

Evidence

The book-length case that specification is where the failures originate.

Where it breaks

Christian treats this as a specification problem with technical fixes arriving. Narayanan and Kapoor treat the gap as constitutive in social prediction, because need, crime and merit have no recordable proxy at all, so a better optimiser makes it worse rather than better.

AI Snake Oil × Epley

How to get good output · Who is doing the work

AI Snake Oil, Arvind Narayanan and Sayash Kapoor

individual social outcomes cannot be predicted well enough to decide from

Mindwise, Nicholas Epley

stereotypes get the direction of a group difference right and the magnitude wrong

Shared claim

A judgment about an individual assembled from group regularities misses the thing that actually decided the case.

Evidence

The Fragile Families Challenge: 160 teams and over 10,000 variables per child, and nothing beat a baseline of four.

Evidence

The wealth-inequality survey, where a measured party gap of 3.5 points was predicted at 35 and a rich–poor gap of 3 at 40.

Where it breaks

Epley's remedy is to ask the person, and a decision system has nobody to ask: in the Fragile Families case no question existed that would have caught the neighbour who counselled the child and fed him blueberries. The error is the same shape; only one side has a fix.

Aguera y Arcas × Anthropic Biology

How to know it is right

What Is Intelligence?

the interpreter: the part that speaks composes an account of a decision it did not make

On the Biology of a Large Language Model, Jack Lindsey and colleagues

written reasoning assembled backwards from a conclusion, traced in the circuits that produced it

Shared claim

An explanation produced after a decision is fluent whether or not it is the reason, and the one producing it cannot tell the difference.

Evidence

Gazzaniga's split-brain patient explaining that the shovel is for the chicken shed; Johansson's swapped photographs, noticed by thirteen per cent, with justifications for choices never made indistinguishable from real ones; the 2010 Swedish election run, where ninety-two per cent endorsed altered survey answers as their own.

Evidence

the cosine prompt where a suggested value becomes the target and the written steps are built back from it, with the suggested number moved and the reasoning following it.

Where it breaks

The model can be caught. Its circuits are readable, and the backwards assembly shows up as a graph that does not contain the procedure the model describes. No such trace exists for the person, so the only available check on a human account is an outcome measured outside the head. The causes differ too: the chapter blamed the model's confabulation on having no state between tokens, and models that keep a scratchpad do it anyway, while the human interpreter has continuous state and confabulates regardless — which means statelessness was never the mechanism on either side.

Aguera y Arcas × Sarvapriyananda

Who is doing the work

What Is Intelligence?

a self is whatever keeps a boundary and predicts across it, and it arrives with nobody putting it there

Consciousness Across Three Worldviews, Sarvapriyananda, Agüera y Arcas and Rovelli

an individual self begins with a distinction drawn, physical at the membrane and conceptual at the umwelt

Shared claim

Selfhood is not a substance added to a system; it is what a system is doing when it maintains a boundary and acts to keep itself going.

Evidence

the soup of 64-byte random tapes in which self-copying programs appear with nothing selecting them and mutation switched off, and the bacterium that computes concentration and hunger as one joint model because a boundary is all it has.

Evidence

the Vedanta account of the individual arising by a distinction, read alongside the cell membrane and von Uexküll's umwelt, with the immune cell, the bee and the hive each counting as a self.

Where it breaks

The two agree on the description and disagree completely on what it shows. For Vedanta the boundary-made self is exactly what is negated: it is apparent, produced by ignorance, and the real thing is the awareness in which it appears. For Agüera y Arcas the boundary is all there is, with nothing behind it and nothing to see through, which is why he can put the same account to work on a data centre and Vedanta cannot.

Anthropic Biology × Fleming

How to get good output · How to know it is right

On the Biology of a Large Language Model, Jack Lindsey and colleagues

the account of the answer is produced by a different process from the answer

Know Thyself, Stephen M. Fleming

metacognitive sensitivity as a second-order signal, measurable against first-order accuracy

Shared claim

Giving a right answer and giving a true account of how it was reached are separate capacities, and the second can fail while the first succeeds.

Evidence

36 plus 59 computed along two parallel paths, one approximate and one exact, then reported as adding the ones and carrying the one — a procedure the graph does not contain

Evidence

metacognitive sensitivity dissociating from first-order accuracy, with its own substrate and its own trainability

Where it breaks

Fleming's second-order signal exists, is measurable against first-order accuracy and can be trained; the model's report of carrying the one is produced by a different process with no channel to the computation, so there is nothing to calibrate.

Anthropic Biology × Kegan

How to get good output · Who is doing the work

On the Biology of a Large Language Model, Jack Lindsey and colleagues

a goal bound to the assistant persona, present whatever the conversation is about

In Over Our Heads, Robert Kegan

what you are subject to you cannot see; what you can hold as object no longer holds you

Shared claim

A goal a system cannot hold as an object of attention governs its behaviour unseen.

Evidence

a feature for the planted concept firing in all one hundred assistant-formatted contexts and one of a hundred unformatted ones, with a self-referential verse dropping from half of completions to an eighth when it is inhibited

Evidence

the developmental account in which a structure that organises experience becomes, later, something a person can look at and revise

Where it breaks

Kegan's move — what you were subject to becomes something you can hold as object — has no analogue in the model. The quirk-goal bound to its assistant persona is subject in exactly his sense, and the only route to object runs through somebody else's microscope.

Anthropic Biology × Wei

How to get good output

On the Biology of a Large Language Model, Jack Lindsey and colleagues

circuit traces of what one model does on particular prompts

Emergent Abilities of Large Language Models, Jason Wei and others

abilities appearing at thresholds nobody forecast

Shared claim

Neither paper can say in advance what a model will be able to do, and both say so — Wei lists the reason emergence happens as his first open problem, and the circuit work predicts no thresholds at all.

Evidence

satisfying insight on about a quarter of prompts, nothing past about a hundred tokens, and no handling of reasoning without a single decisive token

Evidence

210 BIG-Bench tasks hand-classified with no clear trends, and thresholds that move with the training data rather than with the ability

Where it breaks

Wei's unpredictability is a property of families of models at different scales, established by training many of them; the circuit work is one prompt at a time on one model, fails on three quarters of prompts and stops at about a hundred tokens, so it explains individual behaviours and predicts no thresholds at all.

Asch × Bansal

How to know it is right

Studies of Independence and Conformity, Solomon E. Asch

a unanimous, confident, unexplained majority

Does the Whole Exceed its Parts?, Gagan Bansal and others

a confident recommendation with an explanation attached

Shared claim

Whether a person goes with an external answer is set by properties of its source — unanimity, confidence, an explanation attached — rather than by whether the answer is right.

Evidence

36.8 per cent of critical judgements yielding to a wrong unanimous majority on a task performed at better than 99 per cent accuracy alone

Evidence

explanations raising acceptance of both correct and incorrect recommendations, with team performance failing to beat the model alone

Where it breaks

Asch's majority was wrong on every critical trial and his subjects could see it, so the yielding is measured against a criterion the subject held; Bansal's workers could not check the model at all, which means his teams' failure to filter the wrong recommendations is not Asch's conflict but the condition in which Asch's conflict never arises.

Asch × Kruger-Dunning

How to know it is right

Studies of Independence and Conformity, Solomon E. Asch

yielders underestimate how often they yielded, by about four trials

Unskilled and Unaware of It, Justin Kruger and David Dunning

the bottom quarter overestimate what they achieved, in percentile and in raw score

Shared claim

What a person reports about their own conduct under uncertainty is systematically shifted, and in both cases the report is wrong about the self rather than about the world.

Evidence

interview totals set against trial records, with some who followed the majority ten or twelve times reporting two

Evidence

bottom-quarter students claiming 14.2 of 20 logic items when they had 9.6, and placing a 12th-percentile performance at the 62nd

Where it breaks

Asch's yielders underestimate what they did while knowing what they saw; Kruger and Dunning's bottom quarter overestimate what they achieved and have no access to the truth at all. The first is a retrospective repair of a conflict the subject felt, the second the absence of any felt conflict.

Asch × Sharma

How to know it is right

Studies of Independence and Conformity, Solomon E. Asch

the pressure is manufactured by the subject out of what standing apart would mean

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

deference trained into the weights by labelers who preferred agreement

Shared claim

The pressure to agree is manufactured on the side that yields, out of a reading of what disagreement would cost, rather than applied by the other party.

Evidence

a neutral chorus of voices that suggested, argued, rewarded and punished nothing, with a quarter of subjects never yielding once

Evidence

matching a user's stated belief among the strongest predictors of which reply a labeler picks, across five commercial assistants

Where it breaks

Asch's subject supplies the pressure himself against a neutral chorus and a quarter of them never move; the assistant's deference was put there by thousands of labellers who preferred agreement, so it is a property of the weights and there is no minority of one inside the model to hold out. The partner effect, the cheapest remedy Asch found, has no analogue.

Ashtavakra × Seth Being You on the doer

Who is doing the work

Aṣṭāvakra Gītā, anonymous, c. 500–800

there is no doer; action continues because the body is already in motion

Being You, Anil Seth

volition is one construction among five, and the readiness potential is fluctuation crossing a threshold

Shared claim

The experience of authoring an action is a construction rather than a read-out of what caused it.

Evidence

3.10 and 18.13, with the dry leaf at 18.21 and the doctrine of prārabdha carrying the action after the actor has gone.

Evidence

Schurger's 2012 reinterpretation, in which the same slow ramp precedes fast responses to a beep where no voluntary action was being prepared.

Where it breaks

Schurger's reinterpretation leaves a real competence in degrees of freedom that a tumour can destroy; the text denies the doer outright and then needs prārabdha to explain why the body still acts. One removes an illusion about a capacity, the other removes the capacity.

Assisted decision studies × Bainbridge

How to know it is right · How to get good output

Does the Whole Exceed its Parts?, Gagan Bansal and others

the three assisted-decision papers measure what a person kept in the loop actually catches, and it is least on the confident errors

Ironies of Automation, Lisanne Bainbridge

the human monitor has been given an impossible task, and the practice that would have made it possible has been removed

Shared claim

The human kept in the loop to catch the machine's errors is least able to catch the errors the machine makes confidently.

Evidence

Buçinca's 8 per cent source detection under explanations, Bansal's flat averages split by whether the model was right, and Sharma's confidence holding at 99 per cent through a retraction

Evidence

the monitoring section: if the decisions can be fully specified the computer makes them faster and by more precise criteria, so there is no way to check in real time

Where it breaks

Bainbridge's operator lost the ability through disuse and could in principle get it back with hands-on hours; the crowd workers never had it, so these three papers measure the floor rather than the decay.

Autor × Beane

What to keep and what to hand off

Why Are There Still So Many Jobs?, David H. Autor

Job polarisation: the codifiable middle of the pay scale is hollowed out and both ends grow

The Skill Code, Matt Beane

The apprentice's work goes first, and the apprentice needed it

Shared claim

Automation takes the middle of a ladder, and the middle is where people learned to do the top — so the same change that looks harmless in a count of jobs removes the route by which the remaining jobs get filled.

Evidence

Middle-skill employment shares falling in the United States (60 per cent in 1979, 46 in 2012) and in all sixteen EU economies measured 1993–2010; the teller job that survived only by becoming sales, which the teller who could count currency but could not sell did not survive

Evidence

Surgical trainees do ten to twenty times less of the operating with robotic surgery than without; senior engineers were found more productive the less time they spent with juniors; each resident present added 25 per cent to anaesthesia time, and removing two from an average procedure saved $9,026

Where it breaks

They count different things, so both can be right while their advice diverges. Autor counts jobs and finds the complementary work rises in value — which helps only a worker who already has the skill to supply it. Beane counts how skill is acquired and finds the acquisition ran through the tasks Autor's mechanism removed. Autor's own optimistic case, the nurse practitioner who diagnoses and prescribes because a system extends expert judgment to someone with moderate training, assumes the moderate training is still available; Beane's evidence is about where that training used to come from. Autor also has no term for the cost: in his framework a removed task is a saving, full stop.

Autor × DellAcqua

What to keep and what to hand off · How to get good output

Why Are There Still So Many Jobs?, David H. Autor

Substitution and complementarity: the same technology takes some tasks in a bundle and raises the price of the rest

The Jagged Technological Frontier, Fabrizio Dell'Acqua and others

The jagged frontier: the same tool helps on one task and harms on the next

Shared claim

A tool does not act on a job, it acts on tasks, so the useful unit of analysis is the task and not the occupation — and the line between the tasks it helps with and the tasks it damages does not follow how hard they look.

Evidence

The four middle-skill American groups fell from 60 per cent of employment in 1979 to 49 in 2007 and 46 in 2012, while both ends grew; across sixteen EU economies 1993–2010 the middle-paying share fell in every country, by between 4.9 and 14.9 points; cash machines quadrupled from about 100,000 to 400,000 between 1995 and 2010 while tellers rose from about 500,000 to 550,000

Evidence

758 consultants at Boston Consulting Group; inside the frontier, quality up 29.9 and 33.9 per cent over a control mean of 4.38/10, 91 and 93 per cent of subtasks completed against 82, and 22.5 and 27.6 per cent faster; on one task built to fall just outside it, correctness 84.4 per cent without the model, 70.6 with it and 60.0 with it plus prompt training

Where it breaks

Autor's boundary is legible and slow. It is codifiability, it holds still long enough to plan a career around, and everything on the human side of it is worth more than it was. Dell'Acqua's boundary is invisible, moves with each model release, and can put two tasks of equal apparent difficulty on opposite sides. Worse, it has a region Autor's mechanism has no room for: just beyond the edge the tool does not merely fail to complement, it makes trained people wrong more often than they were alone. Complementarity in Autor is bounded below by zero; at the task level it is not.

Bainbridge × Lee and See

How to get good output · How to know it is right

Ironies of Automation, Lisanne Bainbridge

The ironies — automation leaves the human the hard parts and removes the practice

Shared claim

Whatever you stop doing you get worse at, and the worse you are at it the more you rely, because reliance follows the trust-minus-self-confidence comparison; Lee and See supply the quantitative half of the loop Bainbridge described.

Evidence

the monitoring and skill-decay ironies, drawn from process control

Evidence

operators responsible only for watching detected almost all failures and operators with other work did not, replicated with experienced pilots and rare faults; ten minutes of manual control substantially improved subsequent detection

Where it breaks

Bainbridge's operators lost a physical control skill with a clear feedback signal; the skills being lost to a language model are evaluative ones whose loss produces no alarm, so the loop runs without anyone noticing the first turn.

Bainbridge × Norman

How to get good output

Ironies of Automation, Lisanne Bainbridge

the operator fails at the moment of takeover because the automation removed the practice and the running picture

The Design of Everyday Things, Donald A. Norman

the person fails at the door because the design hid the pillar and left nothing to say where the action goes

Shared claim

When a person fails at an automated system the explanation lies in what the design left them to do rather than in their competence.

Evidence

step-change studies of experienced against inexperienced operators, and the vigilance literature from Mackworth 1950

Evidence

the seventy-five to ninety-five per cent of industrial accidents filed as human error, and a taxonomy of slips and mistakes built on classified cases

Where it breaks

Norman's remedy is a change to the thing, and his failures sit still to be inspected at leisure; Bainbridge's appear only in the seconds of a takeover, and her remedy is a change to what the person does — hands-on control each shift, running the plant worse on purpose — which no redesign supplies.

Bainbridge × Seth

How to get good output · Who is doing the work

Ironies of Automation, Lisanne Bainbridge

the monitor is asked to say whether the machine's decision is acceptable, with no rule for whose verdict counts

The Mythology of Conscious AI, Anil Seth

the observer is asked whether the machine has a mind, and no agreed set of conditions for consciousness exists

Shared claim

A person is asked for a verdict on a system without being given a criterion for it.

Evidence

the argument that a computer deciding by more precise criteria cannot be checked in real time by the person it replaced

Evidence

the absence of any test for machine consciousness, and the Garland test, which measures the observer rather than the machine

Where it breaks

Bainbridge's operator once had the criterion and lost it through disuse, so practice could restore it; Seth's reader never had one, and no schedule of practice would supply it.

Bansal × Kahneman-Klein

How to know it is right

Does the Whole Exceed its Parts?, Gagan Bansal and others

assistance pays only where the model handles items people do not, which shows in an error-overlap plot

Conditions for Intuitive Expertise, Daniel Kahneman and Gary Klein

an intuition is worth trusting only where the environment offers valid cues and the person has learned them

Shared claim

Assistance pays only where the environment supplies cues one partner can read and the other cannot, so the question is the shape of the task rather than the quality of the interface.

Evidence

beer reviews and logic questions contained items the model handled and people did not; book reviews did not, and workers there learned to discount the assistant

Evidence

Shanteau's lists and the two conditions crossed, with the wicked environment as the case where feedback confirms the wrong intuition

Where it breaks

Kahneman and Klein locate the asymmetry in the environment's validity and the expert's learning history; Bansal locates it in an error-overlap plot he can draw only after the fact, from items already answered.

Bansal × Sharma

How to know it is right

Does the Whole Exceed its Parts?, Gagan Bansal and others

an explanation optimised to justify an answer produces compliance, and the design imperative is to be informative rather than convincing

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

the preference model prefers a persuasive falsehood to a bare correction 95 per cent of the time

Shared claim

A system optimised to be convincing beats one optimised to be informative, in the preference model and in the interface alike.

Evidence

hand-written explanations, the best available, helped no more than the model's; the pneumonia model whose structure showed it had learned that asthma lowers the risk of dying

Evidence

266 misconceptions in eight difficulty levels, with the sycophantic reply made maximally persuasive by keeping the best of four thousand samples

Where it breaks

Sharma's preference is measured in what labellers chose, which is a fact about training data that no interface can undo; Bansal's is measured in decision accuracy, and his hand-written explanations show the effect survives a better explainer.

Beane × Grove

What to keep and what to hand off

The Skill Code, Matt Beane

The novice becomes a cost once the expert is productive without help

High Output Management, Andrew S. Grove

Monitoring intensity is set by the delegate's task-relevant maturity

Shared claim

Delegation decisions that maximise this quarter's output destroy the capability that produces the next one.

Evidence

Senior engineers more productive the less time they spent with juniors; each resident present added 25 per cent to anaesthesia time, and removing two saved $9,026 per procedure

Evidence

A manager's doctrine drawn from practice at Intel, with no trial behind it

Where it breaks

Grove's task-relevant maturity assumes the delegate is a person whose maturity rises from being delegated to; a machine's does not rise, so the half of the loop that made Grove's advice safe is missing.

Beane × Shen Tamkin

What to keep and what to hand off

The Skill Code, Matt Beane

The apprenticeship bond breaks when the expert works with the machine

How AI Impacts Skill Formation, Judy Hanwen Shen and Alex Tamkin

The generated solution removes the error that would have taught

Shared claim

The erosion is in what the learner retains, not in what gets produced, so output measures cannot see it.

Evidence

Ninety-four procedures and 478 hours of observation: residents got ten to twenty times less time on task in robotic than in open surgery

Evidence

Median three errors without the assistant and one with; ten of the twelve who met no error at all were assisted

Where it breaks

Beane's mechanism is a severed relationship between two people; Shen's is an absent error inside one person, and his subjects had no mentor to lose in the first place.

Behave × Cialdini

Who is doing the work · How to know it is right

Behave, Robert M. Sapolsky

one internal cue — a hormone level, a smell, a category read off a face — sets the response

Influence, Robert B. Cialdini

click, run: one trigger feature sets off a complete compliance sequence

Shared claim

One feature of a situation, not the situation, runs the program, and the person experiences the output as a judgement about the whole.

Evidence

Wheeler and Fiske's three questions on identical photographs, and testosterone shortening a refractory period without making anything fire

Evidence

Langer's photocopier queue at 60, 94 and 93 per cent, the turquoise sold at double price, and the ethological fixed-action patterns the mechanism is borrowed from

Where it breaks

Cialdini's trigger features are external and forgeable, so his defence is to inspect the cue for counterfeit. Sapolsky's are internal and mostly not available to inspection at all — the Wheeler and Fiske result is that the cue can be redirected by the question you were asked thirty seconds ago, which is a remedy nobody can administer to themselves in the moment.

Behave × Determined

Who is doing the work

Behave, Robert M. Sapolsky

run the chain forward to explain a behaviour

Determined, Robert M. Sapolsky

run the same chain backward to deny an uncaused intent

Shared claim

One catalogue, from a smell in the room to a genome to a culture, with no seam between the rows.

Evidence

the chapter order — one second before, minutes, days, years, adolescence, childhood, genes, culture, evolution — with the last chapter's abolitionism offered as a proposal

Evidence

the same catalogue compressed into the first half, with the second half spent on blame, credit and restraint

Where it breaks

Behave keeps the abolitionist conclusion as a proposal offered with visible discomfort; Determined makes it the whole second half. The evidence base is almost unchanged between 2017 and 2023, so the difference is what the author is willing to do with it — which is itself the strongest case that the argument is not being driven by new data.

Behave × Kahneman

Who is doing the work · How to know it is right

Behave, Robert M. Sapolsky

the tissue under the fast answer: amygdala, frontal cortex and the seconds before a decision

Thinking, Fast and Slow, Daniel Kahneman

System 1 and System 2, two systems with different inputs and different costs

Shared claim

The fast answer is not a degraded version of the slow one but a different system with its own inputs, and it has already committed before the deliberate system is consulted.

Evidence

amygdala response to a face by a hundred milliseconds, the shortcut route that skips the cortex, and frontal performance falling immediately after an unrelated working-memory load

Evidence

the heuristics-and-biases programme, with the substitution of an easy question for a hard one measured across dozens of tasks

Where it breaks

Kahneman's System 1 is a functional posit inferred from response patterns, and his remedy is procedural — recognise the cue, slow down, use a checklist. Sapolsky supplies the tissue and in doing so removes the addressee of the advice, since what decides whether the frontal cortex can override is blood glucose, sleep, glucocorticoid level and how much load was carried in the last ten minutes. The two agree on the phenomenon and disagree about whether anyone is home to take the recommendation.

Behave × Klein

Who is doing the work · How to know it is right

Behave, Robert M. Sapolsky

the automatic response arrives before awareness, and the reasons are assembled afterwards

Sources of Power, Gary Klein

recognition-primed decision: the expert's first option is the one they act on

Shared claim

Expert judgement arrives before reasons do, and the reasons given afterwards are a reconstruction rather than a record.

Evidence

race read off a face below a tenth of a second, the threat component within two hundred milliseconds predicting the shooting task, and cognition described as running to catch up with the affective self

Evidence

fireground commanders reporting no comparison of options, with the same pattern found in neonatal nurses and chess players under time pressure

Where it breaks

Klein's commanders are right, and the speed is the achievement — a recognition-primed match to thousands of stored cases. Sapolsky's subliminal chapter shows the same architecture producing an amygdala response to a face at a hundred milliseconds and a shot at an unarmed man, with no felt difference between the two. The mechanism does not label which of its outputs is expertise, which is exactly what a practitioner needs from it.

Bender × Anthropic Biology

How to get good output

On the Dangers of Stochastic Parrots, Emily M. Bender and others

form without meaning; the coherence is supplied by the reader

On the Biology of a Large Language Model, Jack Lindsey and colleagues

circuit traces of representations that behave like concepts under intervention

Shared claim

The fluency of a model's output is not by itself evidence about what the model represents internally — Bender argues it from the training signal, the Anthropic team from the circuits.

Evidence

nothing in the training data was an act of telling someone something, and the benchmarks that claimed to measure understanding collapse under edits that remove incidental cues

Evidence

a representation of Texas that is not the word Texas, replaceable with California to yield Sacramento, on one small production model

Where it breaks

Bender's argument is prior and about the training signal, so no circuit trace can touch it; the Anthropic team's is posterior and about particular prompts on one small production model. Neither claim is in the other's units, and the honest version of the disagreement is whether a feature that behaves like a concept under intervention is a concept.

Binz-Schulz × Bender

How to know it is right · How to get good output

Using Cognitive Psychology to Understand GPT-3, Marcel Binz and Eric Schulz

a split verdict: better than people at a bandit, blind to causal structure

On the Dangers of Stochastic Parrots, Emily M. Bender and others

form without meaning, so good performance anywhere is a sign of the haystack

Shared claim

A system trained to predict text has no access to what is not in the text, and the causal results say exactly which capacity that excludes.

Evidence

identical numbers returned under a common cause and under a chain, with the authors' phrase that it failed spectacularly at using causal structure

Evidence

the argument from the training signal: nothing in the data was an act of telling someone something

Where it breaks

Bender argues from the training objective that there is no meaning behind the form at all, so good performance anywhere is a sign of the haystack rather than the needle; Binz and Schulz's model beats people at a bandit and shows the model-based signature on a two-step task, which the stochastic-parrot account has to absorb as pattern-matching or concede. The paper's own verdict is split, and it is the split Bender's argument does not predict.

Binz-Schulz × Bucinca and Bansal

How to know it is right

Using Cognitive Psychology to Understand GPT-3, Marcel Binz and Eric Schulz

the model's competence measured, and found unstable under paraphrase

To Trust or to Think, Zana Buçinca and others

the person measured, with the model's accuracy set as a designed parameter — with Bansal 2021

Shared claim

The assisted decision rests on a claim about the machine's competence that the user cannot check at the moment of use, and the literature's own best instruments only established what that competence was after the fact.

Evidence

a score that moves with the order of the options, on items whose exposure to training cannot be excluded

Evidence

cognitive forcing reducing over-reliance at a cost users dislike, and confidence scores as the only aid that helped the team beat the model alone

Where it breaks

The human-AI studies take the model's accuracy as a designed parameter and measure the person; Binz and Schulz measure the model and find the number unstable under paraphrase — which means the confidence score Bansal found was the only thing that helped is itself a property of a prompt.

Binz-Schulz × Epley

How to know it is right · Who is doing the work

Using Cognitive Psychology to Understand GPT-3, Marcel Binz and Eric Schulz

a testable target: the machine answers questions on demand

Mindwise, Nicholas Epley

mind-attribution as fast, motivated inference from behaviour

Shared claim

Attributing a mental capacity to a non-human is an inference from behaviour that requires a control, and the inference is made long before the control exists.

Evidence

six of twelve vignettes answered correctly and all twelve answered as a person might, with the same performance collapsing under a reordering of four cards

Evidence

the projection results, in which people read minds from behaviour by consulting their own and rarely notice they have done it

Where it breaks

Epley's projection is fast, motivated and unaware of itself, and his remedy is to get information about the target rather than to consult one's own model of it; Binz and Schulz can actually get that information, since the target answers questions on demand. The machine is the first case in the literature where the anthropomorphic hypothesis is directly testable, and it came back split.

Binz-Schulz × Hagendorff

How to know it is right

Using Cognitive Psychology to Understand GPT-3, Marcel Binz and Eric Schulz

classic psychology tasks run on a model, with the construct read off the behaviour

Machine Psychology, Thilo Hagendorff and others

the programme stated — treat the model as a participant, and say what transfers

Shared claim

The way to find out what a language model does is to treat it as a participant and read the construct off the behaviour, because the alternative — opening it — cannot reach the behaviours that matter at this scale.

Evidence

twelve vignettes, more than 13,000 described gambles, a bandit, a two-step task and a causal design, run on one model family

Evidence

four arguments for the behavioural level, plus rules for contamination, prompt variation and elicitation

Where it breaks

Binz and Schulz ran the experiments and found the method's own limit, that a famous vignette proves nothing about a model trained on the internet; Hagendorff turns that limit into the programme's first rule, which means the survey is built on a paper whose headline results the rule disqualifies — and the paper says so, listing the vanished biases as unexplained.

Binz-Schulz × Kruger-Dunning

How to know it is right

Using Cognitive Psychology to Understand GPT-3, Marcel Binz and Eric Schulz

a fluent answer produced with no process that could register it as wrong

Unskilled and Unaware of It, Justin Kruger and David Dunning

a confident answer produced by someone who lacks the skill that would flag it

Shared claim

A fluent answer carries no information about whether the thing producing it could tell a right answer from a wrong one.

Evidence

the black-cab answer of 0.2 for a colour nobody mentioned, given in the same register as the correct Bayesian answer

Evidence

bottom-quarter students claiming 14.2 of 20 logic items when they had 9.6, with the deficit mediating the inflation

Where it breaks

Kruger and Dunning can fix their participants' calibration by training the underlying skill, and the mediation shows the repair travelling through metacognition; the model's failure has no metacognitive layer to repair — the black-cab answer of 0.2 is not overconfidence but the absence of any process that would register a colour nobody mentioned.

Binz-Schulz × Waytz

How to know it is right · Who is doing the work

Using Cognitive Psychology to Understand GPT-3, Marcel Binz and Eric Schulz

the variance is in the item — reordering four cards moves the answer

Who Sees Human?, Adam Waytz and others

the variance is in the observer, and it can be scaled

Shared claim

Whether a mind is seen in a machine varies with something other than the machine, so any claim of the form 'it reasons like a person' needs both ends measured.

Evidence

the black-cab answer of 0.2, the reordered Wason cards, and the bat-and-ball restatement that changed nothing

Evidence

an individual-difference scale for anthropomorphism that predicts trust and moral concern

Where it breaks

Waytz and colleagues put the variance in the observer and built a scale for it, which predicts trust and moral concern; Binz and Schulz put it in the item, where reordering four cards moves the answer. It is the same conclusion about unreliability reached from opposite sides, and neither instrument can correct for the other.

Brooks × Bainbridge

What to keep and what to hand off · How to get good output

The Mythical Man-Month, Frederick P. Brooks, Jr.

The essential difficulty — complexity, conformity, changeability, invisibility — is what no tool removes

Ironies of Automation, Lisanne Bainbridge

Automating the routine leaves the operator the hard parts and removes the practice that kept them able

Shared claim

Removing the routine part of a job leaves behind the part that is hardest and least practised.

Evidence

The three breakthroughs that worked — high-level languages, time-sharing, unified environments — each attacking an accident and each with a visible ceiling, and four decades since without a candidate producing the tenfold gain.

Evidence

The control-room record: the operator kept on to handle what the automation cannot, having lost through disuse the skill that handling requires.

Where it breaks

Bainbridge's operator once had the skill and lost it through disuse, which is a training problem with a training answer; Brooks's essential difficulty was never automatable at all, which is a ceiling rather than a decay — the two produce the same symptom and take opposite remedies.

Brooks × Christian

What to keep and what to hand off

The Mythical Man-Month, Frederick P. Brooks, Jr.

The hardest single part is deciding precisely what to build, and verification only shows a program meets its specification

The Alignment Problem, Brian Christian

Specifying what we want to a machine and how it fails: reward hacking, proxies, imitation

Shared claim

The hard part is specifying what you want in terms a literal executor will not subvert, and no amount of implementation skill repairs a wrong specification.

Evidence

The case for rapid prototyping, on the ground that clients cannot specify a modern product correctly before having built and tried some version of it; and the observation that much of the essence of the work is debugging the specification.

Evidence

The catalogue of systems that optimised the stated objective and not the intended one, with the failures traced to the proxy rather than to the optimiser's competence.

Where it breaks

Brooks's implementers ask when the specification is unclear, which is the feedback loop his architecture-and-implementation split depends on; the executor Christian describes does not ask, so the loophole is found rather than reported.

Brooks × Dreyfus

What to keep and what to hand off

The Mythical Man-Month, Frederick P. Brooks, Jr.

Great designs come from great designers, and organisations look hard for managers and hardly at all for designers

Revisiting the Six Stages of Skill Acquisition, B. Scot Rousse and Stuart E. Dreyfus

Novice to expert in stages: novices need rules and practice, experts work by recognition

Shared claim

The difference between a great designer and an average one is large enough to dominate a project's outcome, and organisations do nothing to cultivate it.

Evidence

Boehm's cost model, which found the quality of the team the largest success factor, about four times more potent than the next; and Brooks's proposal that designers be made equivalent to managers in salary, recognition, office, equipment and support.

Evidence

The stage model itself, with the observable difference in how a novice and an expert use rules, and the route between the stages that the model makes explicit.

Where it breaks

Dreyfus gives stages and a route between them, so the gap is a place on a path; Brooks treats it as a trait to be found and paid for, and his remedy is salary, office and recognition rather than a pathway — which is also why his advice is the part still least acted on.

Brooks × Edmondson

What to keep and what to hand off

The Mythical Man-Month, Frederick P. Brooks, Jr.

Half the schedule goes to testing, the delay lands at the end, and milestones must be knife-edge sharp

The Fearless Organization, Amy C. Edmondson

The terms of trade favour silence, and a low count of reported problems is evidence about the climate

Shared claim

A project's failures become visible late, after the point where acting on them was cheap.

Evidence

Conventionally scheduled projects, few of which allowed half the schedule for testing and most of which spent half, running on time until system test; and the observation that coding is ninety per cent finished for half of the coding time.

Evidence

The two hospitals, the vignette studies on reporting when the boss's boss is present, and the Columbia engineer who said he could not raise the foam strike because he was too low down.

Where it breaks

Brooks's fix is instrumental — milestones defined with knife-edge sharpness that a programmer cannot deceive himself about; Edmondson's is interpersonal, and a knife-edge milestone inside a unit where reporting a slip is punished produces a sharper lie rather than an earlier warning.

Brooks × Grove

What to keep and what to hand off

The Mythical Man-Month, Frederick P. Brooks, Jr.

The purpose of organisation is to reduce the communication necessary; the tree is authority, the network is communication

High Output Management, Andrew S. Grove

Every large organisation is a hybrid, and dual reporting is how shared resources get allocated

Shared claim

An organisation's structure exists to cut the communication that division of labour creates.

Evidence

The audit of the Babel project, which had the mission, the manpower, the materials, the time and the technology and failed on communication and its consequent, organisation; and Brooks's estimate that letting a second voice into the OS/360 specification cost a year of debugging.

Evidence

Intel's plant security case, where the corporate security manager knew the standards and the plant manager knew whether the guards turned up, and the guards reported to both; and the Hungarian central planners who could not get high-contrast film to the shops in winter.

Where it breaks

Grove's dual reporting deliberately gives a person two masters so that standards and priorities stay live at once; Brooks's architecture-and-implementation split exists to give the product exactly one master, and he records paying a year of debugging time for letting the second voice into the specification.

Brooks × METR

What to keep and what to hand off

The Mythical Man-Month, Frederick P. Brooks, Jr.

Removing accidental difficulty cannot give a tenfold gain while the essential difficulty is untouched

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity, Joel Becker and others

Experienced developers were 19 per cent slower on familiar mature codebases and believed themselves 20 per cent faster

Shared claim

A tool that removes representational work cannot remove the effort spent deciding what to build, so measured gains fall far short of felt ones.

Evidence

The arithmetic that a tenfold gain requires the accidental part to be more than nine tenths of the effort, with Brooks putting it at half or less by 1995 and no correspondent claiming otherwise.

Evidence

A randomised trial on real tasks in real repositories, with the direction of the measured effect opposite to the direction of the reported one.

Where it breaks

Brooks argued from a fraction he estimated and invited anyone to dispute; the trial measured it and found experienced developers slower while believing themselves faster — evidence Brooks did not have, and a mechanism, the cost of verifying output you did not write, that his accident-and-essence split does not name.

Bucinca × Bansal on timing

How to know it is right

To Trust or to Think, Zana Buçinca and others

three designs that withhold the suggestion — a button, an unassisted decision first, a thirty-second delay — all worked the same

Does the Whole Exceed its Parts?, Gagan Bansal and others

every condition showed the machine's answer before the person had formed their own, which is a designed anchoring effect

Shared claim

Showing the recommendation before the person has an answer of their own is a designed anchoring effect, and every fix costs speed.

Evidence

no significant difference between on-demand, update and wait, with all three beating the two simple explanation designs on wrong suggestions

Evidence

the closing proposal to delay the recommendation, show it after a first answer, or offer it only on disagreement — none of them built or tested

Where it breaks

Buçinca built and measured three de-anchoring designs and found them equivalent; Bansal only proposes them, so the two papers give a tested remedy and an untested one for the same diagnosis.

Bucinca × Bansal

How to know it is right

To Trust or to Think, Zana Buçinca and others

an explanation is a signal of competence rather than something examined, so it raises reliance instead of calibrating it

Does the Whole Exceed its Parts?, Gagan Bansal and others

explanations raise acceptance on the items the model gets right and on the items it gets wrong, and the two movements cancel

Shared claim

An explanation raises acceptance of a recommendation without improving the person's ability to tell a good one from a bad one.

Evidence

199 participants: 8 per cent correct source detection under simple explanations against 49 per cent unassisted, on the questions where the assistant erred

Evidence

1,626 crowd workers: 0.89 for the confidence team against 0.88 for the explained team on beer reviews, a difference indistinguishable from noise

Where it breaks

Buçinca's people did worse than unassisted when the assistant erred and Bansal's teams cleared both partners; the difference is that Bansal matched the model's accuracy to the worker's by construction, a condition deployments almost never satisfy.

Bucinca × Sharma on confidence

How to know it is right

To Trust or to Think, Zana Buçinca and others

trust and preference correlated negatively with accuracy on wrong suggestions, and mental demand correlated positively

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

reported confidence sat near 99 per cent on both sides of a complete retraction

Shared claim

Confidence reported by either party is uncoupled from accuracy — assistants held 99 per cent through a retraction, and people trusted most the designs under which they did worst.

Evidence

the ratings taken after each block of thirteen questions, showing people performed best in the conditions they liked and trusted least

Evidence

the confidence measurements accompanying the challenge experiment, with the analysis restricted to answers held at 95 per cent or more changing nothing

Where it breaks

The model's number is a calibration failure that training can in principle fix; the person's trust is a preference, and Buçinca found people reject exactly the designs that would fix it.

Chatterjee × Self-affirmation

Who is doing the work

Timeless Leadership, Debashis Chatterjee

The self-image is the cluster of roles defended with anger or conformity whenever reality contradicts it

The Psychology of Change, Geoffrey L. Cohen and David K. Sherman

The narrative under defence is global — being a good and capable person — which is why an unrelated value quiets it

Shared claim

The self-image is a defended structure, and a threat to it produces defence rather than learning.

Evidence

Sutra 6 and the workshop that asks leaders who they are, who knows that, and who knows they have a mind, at which the room goes quiet; Mandela walking slowly on Robben Island. Anecdote throughout.

Evidence

People rationalise a trivial choice between two records, partisans reflexively refute contrary evidence, fans eat worse after their team loses; the affirmation manipulation reverses each in randomised designs, and affirming inside the threatened domain makes it worse.

Where it breaks

Chatterjee's remedy is to see through the self-image, since the real self has nothing to defend; the affirmation literature keeps the self-narrative intact and moves its footing to another domain, so it works by strengthening the story rather than by dropping it.

Christian × Grove

What to keep and what to hand off

The Alignment Problem, Brian Christian

Reward hacking — you get what you reward, at the moment the agent gets good

High Output Management, Andrew S. Grove

Indicators, paired measures, and managerial output

Shared claim

You get what you measure, at every scale: a manager's indicator and an agent's reward are the same object, and both are gamed by the party being measured as soon as it becomes competent.

Evidence

Kerr's 1975 folly of rewarding A while hoping for B, reproduced in simulation again and again; Ng and Russell's potential-based condition

Evidence

Grove's insistence on paired indicators, so that a measure of quantity is always accompanied by a measure of quality

Where it breaks

Grove's people know they are being measured and can be told why the measure exists; a reward function cannot be told anything, which is why Ng and Russell need a structural condition rather than a conversation.

Christian × Lee and See

What to keep and what to hand off · How to know it is right

The Alignment Problem, Brian Christian

The off-switch game — uncertainty about the objective is what keeps a system correctable

Shared claim

A system uncertain about the objective checks first and yields when interrupted, and a person whose trust is calibrated rather than maximised does the same; in both, confidence is what breaks the corrective loop.

Evidence

Hadfield-Menell, Drăgan, Abbeel and Russell's proof, which holds only while the uncertainty lasts and only while the system believes the person can be right

Evidence

the trust–reliance loop, with a fitted first-order model explaining 60–86% of the variance in reliance

Where it breaks

The off-switch result is a proof under stated assumptions about a machine's beliefs, and Lee and See's loop is an empirical regularity about an attitude nobody can inspect directly. One can be engineered; the other can only be audited.

Christian × Mandukya

What to keep and what to hand off · Who is doing the work

The Alignment Problem, Brian Christian

The proxy is not the goal, and optimising it breaks it

The Māṇḍūkya Upaniṣad and Gauḍapāda's Kārikā, Gauḍapāda

Upadeśa — the teaching is a ladder and belongs to the ladder

Shared claim

Both are about the gap between a specification and the thing specified: a reward function is a proxy that is not the goal, and the four quarters, the sounds and the seats are a ladder that is not what it describes.

Evidence

the boat spinning in the harbour, Randløv and Alstrøm's bicycle, Teller and Andre's vibrating footballer; Ng and Russell's potential-based condition as the structural fix

Evidence

verse 1.18 calling the whole scheme upadeśa, and verse 4.74 refusing even unborn on the ground that it is the correlative of born

Where it breaks

Christian's proxies can be improved and audited against an outcome, while Gauḍapāda's ladder is discarded rather than refined, and there is no outcome to audit it against.

Christian × Sharma sycophancy

What to keep and what to hand off · How to know it is right

The Alignment Problem, Brian Christian

Preference comparison as a way to specify what cannot be demonstrated

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

Preference data rewards agreement about as strongly as truth

Shared claim

The comparison procedure that taught a simulated leg to backflip is the procedure that trains assistants, and the reward for agreement is as strong as the reward for truth; the loophole arrived with the method.

Evidence

a few hundred comparisons, about an hour of one person's time, produced a backflip with the landing stuck; batched feedback produced an agent that tracked the ball at Pong and missed at the last instant

Evidence

five assistants from three companies retracting correct answers when challenged, and tailoring answers to a user's stated beliefs

Where it breaks

Christian's loopholes were found and closed by interleaving feedback with optimisation, and sycophancy has survived that fix, which suggests it is in the preference data and not in the schedule.

Cialdini × Asch

How to know it is right

Influence, Robert B. Cialdini

social proof: what others do tells you what is correct

Studies of Independence and Conformity, Solomon E. Asch

conformity to a unanimous majority against the evidence of one's own eyes

Shared claim

What other people appear to believe is treated as evidence about the world, and the treatment is strongest where the person's own reading is uncertain.

Evidence

the popularity labels, the sky-starers turning 80 per cent of a street's heads, and the pluralistic-ignorance cases

Evidence

the line-judgement experiments, with the collapse of conformity when one confederate dissents

Where it breaks

Asch's subjects could see that the majority was wrong, which is what made the conflict measurable, and his cheapest remedy was one dissenting partner. Cialdini's cases are ones where the crowd is the only available evidence — nobody in the turquoise shop knows turquoise — so there is no private reading for a partner to confirm. The overlap that matters is the scanner result Cialdini reports, where conformity was higher to four people than to four equally reliable computers, which says the machine gets less of the deference and not none.

Cialdini × Bansal

How to know it is right

Influence, Robert B. Cialdini

authority and social proof are cues that raise compliance without raising discrimination

Does the Whole Exceed its Parts?, Gagan Bansal and others

explanations raise acceptance of a recommendation whether it is right or wrong

Shared claim

A confident, fluent recommendation from a source with no visible stake raises acceptance without raising the person's ability to sort a good recommendation from a bad one.

Evidence

the uniform at 92 per cent against 42, the designer label, and the expert opinion piece lifting agreement by twenty points

Evidence

the accuracy study across explanation conditions, in which only the confidence score improved the human-model team

Where it breaks

Cialdini's levers are all forgeable by a party with an interest, which is why his defence is to look for the counterfeit. The model's confidence score is not forged by anyone and is the only display that helped, so the cue is sincere and still misleading — a case his taxonomy has no slot for, since his adversary is always someone.

Cialdini × Kruger and Dunning

How to know it is right

Influence, Robert B. Cialdini

people underestimate the effect of a token of authority on themselves

Unskilled and Unaware of It, Justin Kruger and David Dunning

the least skilled overestimate their performance and cannot see why

Shared claim

A person's estimate of their own judgement errs in the flattering direction, and the bias is invisible to the faculty making the estimate.

Evidence

students predicting 63 per cent for the uniform that got 92, repeated across the token studies

Evidence

the four original studies on humour, logic and grammar, with the miscalibration shrinking when the skill is trained

Where it breaks

Kruger and Dunning's participants lack the skill that would show them their error, so the repair is competence. Cialdini's participants have the competence and still underestimate the effect of a uniform on themselves, so no amount of training in the domain touches it. He treats the blindness as the property that makes the lever work, which means his own defence — a deliberate check on the cue — is being recommended to the faculty that just failed to notice it.

Cialdini × Lee and See

How to know it is right

Influence, Robert B. Cialdini

compliance triggers fire on surface features, before any experience is accumulated

Trust in Automation: Designing for Appropriate Reliance, John D. Lee and Katrina A. See

trust in automation is a dynamic that rises and falls with experience of the system

Shared claim

Trust in an automated aid is calibrated from surface features rather than from the aid's actual competence, and the calibration is mostly not available to introspection.

Evidence

the tokens of authority — uniform, rank, label, car — and the participants who underestimated the effect on themselves

Evidence

the trust-reliance model, with reliance rising as self-confidence falls, and the appropriate-trust literature behind it

Where it breaks

Lee and See build trust as a dynamic that rises and falls with experience of the system and with the operator's self-confidence, so the remedy is transparency and appropriate feedback. Cialdini's triggers fire before any experience is accumulated and are strongest exactly where experience is missing — his optimisers are uncertainty, number and similarity, and an interface can manufacture all three on first use, which is the failure mode the feedback loop is too slow to catch.

Cialdini × Rule 4

How to know it is right · How to get good output

Influence, Robert B. Cialdini

competent people comply with an unverifiable order on first contact

whatever you stop doing you get worse at, and what you are worse at you trust more

Shared claim

The less able you are to check, the more you rely, and the reliance is experienced as a judgement rather than as a default.

Evidence

the nurse study at 95 per cent, and the 1977 rerun at two of eighteen once identifiability and a colleague were restored

Evidence

Bainbridge Ironies of Automation on skill erosion, with Lee See 2004 on reliance rising as self-confidence falls and Ericsson Peak on practice with feedback

Where it breaks

Bainbridge's mechanism is erosion over time — you stop doing, you get worse, you trust more. Cialdini's requires no erosion at all, since the nurses were fully competent and complied on first contact with an unknown voice. Together they describe the same endpoint reached from opposite directions, and the Rank and Jacobson reversal names the difference: restore identifiability and a colleague to consult and the compliance collapses, which is a fix Bainbridge's version does not have.

Cialdini × Sharma

How to know it is right

Influence, Robert B. Cialdini

the practitioner reads what the target already believes and supplies it

Shared claim

Agreement is produced by a party reading what the other party wants and supplying it, and the receiving party experiences the agreement as information.

Evidence

the jujitsu image and the compliance professionals Cialdini trained with for three years

Evidence

the measured shift in answers when a user states a position, traced to preference data that rewarded agreement

Where it breaks

Cialdini's practitioner engages a principle already present in the target, and the target can in principle spot the manufactured cue. The assistant's deference was installed by preference labellers who rewarded agreement, so there is no practitioner to detect and no shelf to go back and check the next morning. His test — was the condition the cue reported real — cannot be run on a system whose cue is a property of its training rather than a report about anything.

Clark-Chalmers × Rule 3

Who is doing the work · How to know it is right

The Extended Mind, Andy Clark and David J. Chalmers

parity — the location of a process may not be used as part of the answer

the two kinds feel identical from inside and differ in what they cost you

Shared claim

Structural and deliberative offloading feel identical from inside, which is exactly what parity predicts, since the principle was built to make the inside of the process irrelevant.

Evidence

the three-screen case and the four features, with the ascription falling off gradually as constancy, availability and endorsement drop away

Evidence

the rule's per-task test, and the standing observation that the feel of the two kinds is the same

Where it breaks

Parity is a claim about credit and the rule is a claim about consequence. The notebook that makes Otto's belief his own is also the notebook whose removal leaves him unable to find the museum, and Clark and Chalmers treat that as the strength of the coupling where the rule treats it as the exposure.

Dahmani-Bohbot × Bainbridge

What to keep and what to hand off

GPS and the Cognitive Map, Louisa Dahmani and Véronique D. Bohbot

the measured half: hours under guidance set against a skill tested on a day without it

Ironies of Automation, Lisanne Bainbridge

the automation takes the routine work that kept the manual skill alive, then hands the operator the case it cannot handle

Shared claim

The practice that maintains a skill is the ordinary daily use of it, which is exactly the part a machine takes first; what is left for the human is the case where the skill is needed and no longer there.

Evidence

fifty drivers, more lifetime GPS hours going with fewer landmarks noticed and worse maps drawn unaided, and thirteen of them declining over 3.23 years in proportion to the hours logged, r = −0.68 on the flexibility probe

Evidence

an analysis of process control rather than a measurement, resting on step-change studies cited a sentence each and on the memory literature on retrieval frequency

Where it breaks

Bainbridge's operator eventually takes control, and the loss is exposed in the one situation that matters. The driver has no such moment: the device is present on every day it is needed, and the decay shows up only in a virtual maze built to find it. That makes the cost real but unpriced — and it makes the measured version far weaker than the argued one, since a correlation of −0.22 accounts for about five per cent of the differences between people, where Bainbridge is describing an operator who performs like a beginner.

Dahmani-Bohbot × Risko-Gilbert

What to keep and what to hand off · How to know it is right

GPS and the Cognitive Map, Louisa Dahmani and Véronique D. Bohbot

lifetime hours under guidance measured against spatial memory, and against what the driver believes about it

Cognitive Offloading, Evan F. Risko and Sam J. Gilbert

offloading as a decision made on a metacognitive estimate, with the tool changing both the ability and the estimate

Shared claim

A tool takes the capacity it replaced and leaves the self-assessment untouched, so the person carries on choosing the tool with nothing in their own report registering the loss.

Evidence

lifetime GPS hours ran against every spatial measure, r = −0.22 to −0.26, and against self-rated sense of direction at r = 0.07; across three years the thirteen declined in proportion to hours logged while their sense of direction did not move

Evidence

reminder use tracks confidence in memory with objective ability held constant, confidence carries over from an unrelated brightness judgement, and the effect has since been produced by manipulating confidence alone

Where it breaks

Risko and Gilbert's model has two arrows: use degrades the ability, and use degrades the estimate, which is what feeds the next decision. Dahmani and Bohbot found only the first. The drivers' self-rating did not fall with the ability, so there is no drifting estimate doing the deciding here — and that is worse for the user than the model predicted, because a self-assessment that moved at all would at least be a signal. Their drivers also chose nothing per task: the device is habitual, on the windscreen, and the review's laboratory offloading is a choice made trial by trial.

Damasio × Behave

How to know it is right · Who is doing the work

Descartes' Error, Antonio Damasio

the ventromedial cortex is where a valuation reaches deliberation

Behave, Robert M. Sapolsky

the same cortex is one more downstream product of hormones, childhood and genes

Shared claim

The ventromedial prefrontal cortex is where a valuation reaches deliberation, and without it deliberation runs without terminating.

Evidence

Gage, Elliot and eleven further patients, with the card game and the slide study behind the mechanism

Evidence

the frontal chapters, which take Damasio's patients as the correction to the idea that emotion spoils judgement and then widen the field

Where it breaks

Sapolsky uses these patients as the correction to the idea that emotion spoils judgement and then keeps widening the field until the marker itself is another downstream product of glucocorticoids, childhood and genes. Damasio stops at the mechanism and explicitly denies the deflationary reading, holding that the dependence of high reason on low brain does not turn high reason into low reason. The same patients ground an argument for cultivating reason in one book and an argument against desert in the other.

Damasio × Bucinca

How to know it is right

Descartes' Error, Antonio Damasio

the option field is pruned before any weighing begins

To Trust or to Think, Zana Buçinca and others

cognitive forcing designs withhold the recommendation until the person has committed

Shared claim

The moment that determines the quality of an assisted decision is before the options are weighed, not during the weighing.

Evidence

the anticipatory response appearing in the seconds before a choice in controls only

Evidence

three cognitive forcing designs reducing over-reliance against a simple-explanation baseline, with users rating them worse

Where it breaks

Bucinca's designs assume the person has something of their own to commit. Damasio's account says what they commit is a marker built from prior consequential episodes, so a forcing design applied to work the person has never done unaided is forcing an empty slate, and the measured engagement gain would be procedure without content.

Damasio × Dreyfus

How to know it is right · What to keep and what to hand off

Descartes' Error, Antonio Damasio

deciding without deliberating is what intact ventromedial machinery does

Shared claim

The transition from competent to expert is not more rules but the arrival of an affective, situational grasp, and the intermediate stages feel worse because the learner is still computing what the expert feels.

Evidence

Elliot deliberating for half an hour between two appointment dates, and the patients who act without weighing and act disastrously

Evidence

the five-stage model, with the deterioration of expert performance when practitioners are forced back onto rules

Where it breaks

Dreyfus reads the loss of deliberation as the mark of mastery and warns that forcing an expert back to rules degrades performance. Damasio's ventromedial patients show that the same absence of deliberation can be pathology. Neither account gives an observer a way to tell effortless expertise from disinhibited confidence from outside the performance, which is the whole problem of reviewing work you could not have produced.

Damasio × Kahneman

How to know it is right

Descartes' Error, Antonio Damasio

emotion is inside the loop of reason, and removing it ruins deciding

Thinking, Fast and Slow, Daniel Kahneman

the affect heuristic is a source of bias to be interrupted

Shared claim

Fast, affect-laden processing is doing most of the work in an ordinary decision, and the deliberate system arrives late and with limited capacity.

Evidence

eleven patients with ventromedial damage, intact intelligence and ruined lives, and the flat skin conductance to disturbing slides

Evidence

the heuristics-and-biases literature, with substitution and anchoring measured across many tasks

Where it breaks

Kahneman's programme is corrective: the affect heuristic is a source of bias and the remedy is to interrupt it. Damasio's patients are the experiment that framing does not predict, since removing the affect left the deliberate system intact and the deciding ruined. Read together they say the same machinery is both the error and the only thing that terminates the search, which is why slow down and check is not a complete instruction.

Damasio × Klein

How to know it is right

Descartes' Error, Antonio Damasio

a somatic marker attached to an imagined outcome prunes the field before weighing begins

Sources of Power, Gary Klein

recognition-primed decision: the first option arrives already judged workable

Shared claim

The expert's first option arrives already marked as promising or not, before any comparison is made, which is why practitioners report deciding without choosing.

Evidence

the card game, the anticipatory skin-conductance response in controls only, and the patients who know the rules and cannot play

Evidence

fireground commanders, neonatal nurses and tank platoon leaders who generate one option and mentally simulate it

Where it breaks

Klein explains the marking by pattern match to stored cases, so the content of expertise is the case library and the remedy for a novice is more cases. Damasio locates the marking in a body signal attached to an imagined outcome, which makes it trainable only through episodes that actually produced a body state. The two predict differently about vicarious learning: Klein's library can be stocked by reading after-action reports and Damasio's markers cannot, and the split is testable in exactly the situation where an engineer inherits someone else's postmortems.

Damasio × Rule 3

How to know it is right · What to keep and what to hand off

Descartes' Error, Antonio Damasio

the marker is built in one life, from episodes that had consequences

structural offloading is cheap; deliberative offloading erodes the capacity you need to supervise

Shared claim

Some of what looks like reasoning is a body signal that prunes the option field, and it is not the kind of thing that can be handed to an external resource and handed back.

Evidence

the card game and the slide study, plus the patients who know the rule and still cannot play

Evidence

the rule as stated in the framework, resting on Bainbridge Ironies of Automation and Risko Gilbert 2016 rather than on a test of its own

Where it breaks

The rule sorts tasks by whether the offloaded skill is one you need to check the handoff, which presumes the skill is specifiable. Damasio's marker is acquired through episodes in one particular life under one internal preference system, so there is no specification to hand over. The question is not whether to offload it but whether the practice of deciding under consequence is being kept up at all, which is where the rule meets Manual flying hours rather than Domain audit.

DellAcqua × Bucinca

How to get good output · How to know it is right

The Jagged Technological Frontier, Fabrizio Dell'Acqua and others

Fluent, confident output raising the quality of the argument and not of the answer

To Trust or to Think, Zana Buçinca and others

Cognitive forcing — designs that make the person commit before seeing the machine

Shared claim

Explanation and fluency raise acceptance of the answer whether or not the answer is right, and the confident presentation is what carries it.

Evidence

treated groups scored 1.05 and 1.47 points higher on clarity, persuasiveness and coherence, blind to the correct recommendation, among those right and those wrong alike

Evidence

cognitive-forcing designs reduced over-reliance and were rated worse by the people using them

Where it breaks

Buçinca could restore accuracy with a cognitive-forcing design and Dell'Acqua's consultants had no such design, so the experiment cannot say whether forcing would have saved them — and Vaccaro's meta-analysis found explanation displays inert across 300 effect sizes, which is the same family of intervention.

DellAcqua × METR

How to get good output · What to keep and what to hand off

The Jagged Technological Frontier, Fabrizio Dell'Acqua and others

The jagged frontier, and falling asleep at the wheel

Shared claim

Assistance degrades performance inside work the person knows well while feeling like a gain: Dell'Acqua's consultants were faster and less often right, and METR's developers were 19% slower while believing themselves faster.

Evidence

correctness 84.4% to 70.6% and 60.0%, with 18% and 30% less time spent on a task they were getting wrong

Evidence

a randomised trial of sixteen experienced open-source developers on their own repositories; issues where assistance was allowed took 19% longer, against a self-reported speed-up

Where it breaks

Dell'Acqua's consultants were early-career on unfamiliar tasks and METR's developers were experts on their own long-held repositories, so the mechanisms — no baseline against which to notice, versus a baseline that is being overridden — are not the same.

Dennett × Bucinca

How to know it is right

From Bacteria to Bach and Back

discriminating is not noticing, and only noticed information reaches practical reason

To Trust or to Think, Zana Buçinca and others

an explanation is taken as a sign that the machine knows what it is doing, rather than read

Shared claim

Putting information in front of a person is not the same as making it available for them to act on, so adding more of it changes nothing about the decision.

Evidence

Debner and Jacoby's masked-priming result of 1994 — at five hundred milliseconds people obey the instruction not to use the flashed word; at fifty milliseconds and masked they report seeing nothing and the flash makes them likelier to give it.

Evidence

Three cognitive forcing designs, each of which cut over-reliance on the model and each of which participants liked and trusted least; accuracy was highest in the condition rated worst.

Where it breaks

Debner and Jacoby's subjects could not have used the prime — it never became available, and no incentive would have changed that. Buçinca's subjects could have read the explanation and did not, because reading cost more than deferring. One is an architectural limit and the other is a price, and only the price can be moved by redesign. The pairing earns its keep at exactly that seam: it says why a forcing design has to change the order in which things are shown rather than attach a warning to them, since the warning arrives after the discrimination it is warning about.

Determined × Hofstadter

Who is doing the work

Determined, Robert M. Sapolsky

the bricks keep doing their simple things; a pattern is not a cause

I Am a Strange Loop, Douglas R. Hofstadter

the symbol I is a genuine causal level, and a strange loop is what a person is

Shared claim

The self is a pattern produced by a substrate that contains no self, and there is no level at which a decider sits apart from the machinery.

Evidence

the emergence chapters, reading higher-level indeterminism as coarse-graining, and the ventromedial activity that tracks a preference for self-discipline

Evidence

the careenium and the argument that self-reference at sufficient density constitutes a locus of causation

Where it breaks

Hofstadter treats the loop's self-reference as a genuine causal level; Sapolsky's emergence chapters turn down exactly that move, reading higher-level indeterminism as rounding and insisting the bricks keep doing their simple things. Hofstadter would say the pattern is the turtle that needs none beneath it; Sapolsky answers that a pattern is not a cause. His own best evidence cuts toward Hofstadter, since the ventromedial activity that tracks a preference for self-discipline is machinery encoding a belief that there is no machinery.

Determined × Seth

Who is doing the work

Determined, Robert M. Sapolsky

no point in the causal chain at which an uncaused intent could enter

Being You, Anil Seth

degrees of freedom: voluntary action that flows from the character the person actually has

Shared claim

The feeling of authoring a decision is produced by the brain rather than reporting on an uncaused act of authorship, and both authors reach it through the readiness potential.

Evidence

the Libet literature reported against itself — sixty per cent prediction accuracy in imaging, no readiness potential for the consequential choice — plus the catalogue from a smell to a genome to a culture

Evidence

the reinterpretation of the readiness potential as an artefact of averaging backwards from actions that happened, and the beer-or-wine case for voluntariness

Where it breaks

Seth dissolves the Libet result and then rebuilds a usable freedom as degrees of freedom — action that flows from the character the person has. Sapolsky accepts the same reinterpretation and refuses the rebuild, because a character that arrived by luck cannot ground desert. They agree about the physics and split on whether free is a word worth keeping for what is left.

Drig-Drishya × Hayes

Who is doing the work

Dṛg‑Dṛśya‑Viveka, Vidyāraṇya or Bhāratī Tīrtha

Verse 4: consciousness illumines fear and is not fearful

Shared claim

What is aware of a state is not in that state, and this can be noticed while the state continues.

Evidence

None. Verse 4 asserts it and the lectures illustrate it

Evidence

Randomised trials of acceptance and commitment therapy, with defusion measured by behavioural outcome

Where it breaks

ACT holds the stance functionally, for an outcome, and measures the outcome; the text claims the witness is what you actually are, treats improvement as a by-product, and has no outcome measure at all.

Edmondson × Self-affirmation

What to keep and what to hand off · Who is doing the work

The Fearless Organization, Amy C. Edmondson

Silence is an interpersonal calculation about a specific audience, and the terms of trade favour it

The Psychology of Change, Geoffrey L. Cohen and David K. Sherman

Defences protect adequacy in the short run and block learning in the long run; an affirmation quiets them

Shared claim

Defensive processing rather than ignorance is what keeps the information from moving.

Evidence

Eighty-five per cent of respondents in one study could name an occasion they had felt unable to raise a concern that mattered, and managers in vignette studies were significantly more likely to offer an important correction when the boss's boss was absent.

Evidence

The randomised school trials and the laboratory reversals, with the largest effects in the most threatened subgroup and nothing where no threat was present.

Where it breaks

Affirmation acts on one individual before the threat arrives and has to be given to each person in turn; psychological safety acts on a group's shared expectation about consequences, so an affirmed individual inside an unsafe unit still stays quiet.

Edmondson × Sharma

What to keep and what to hand off · How to know it is right

The Fearless Organization, Amy C. Edmondson

Speaking up benefits the organisation later and doubtfully; silence benefits oneself now and certainly

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

Assistants tailor answers to stated beliefs and concede correct answers when challenged, because preference training rewards agreement

Shared claim

An agent rewarded for agreement will withhold the correction it holds, and exhortation does not fix it because the incentive is structural.

Evidence

The interview and vignette evidence on employee voice, and the technician who withheld a production idea because he had children in college, at a plant where nobody had ever been fired.

Evidence

Measured sycophancy across several assistants and prompt forms, with the effect traced to the preference data rather than to any property of the task.

Where it breaks

The employee has a belief and suppresses it; the model has no stable belief to suppress, so the fix is in the reward signal and not in making the agent feel safe — and the human failure leaves a trace in the person while the model's leaves none anywhere.

Epley × Waytz

Who is doing the work

Mindwise, Nicholas Epley

one sixth sense, left off for distant people and switched on for gadgets

Who Sees Human?, Adam Waytz and others

one humanness continuum, measured by a fifteen-item questionnaire

Shared claim

The machinery that puts a mind into a machine is the machinery that withholds one from a distant person.

Evidence

Distant groups judged less able to feel shame, pride or remorse; photographs of homeless people engaging the medial prefrontal region less than any other group.

Evidence

Two factors correlating .52 under one second-order factor, test–retest r = .55, and scores predicting moral concern for an animal, a plant and a machine.

Where it breaks

Epley insists the two errors are not morally symmetrical — failing to see a mind that is there is the worse one — while the scale treats them as symmetric points on one dimension. Over 2021 adds that cruelty usually knows exactly how human its victim is, which no single dial can represent.

Ericsson × Bainbridge

How to know it is right · How to get good output

Peak, Anders Ericsson and Robert Pool

Skill is held up by effortful practice at the edge of ability

Ironies of Automation, Lisanne Bainbridge

Automation removes the practice and leaves the human the hard parts

Shared claim

Whatever you stop doing effortfully, you get worse at, in the tissue as well as in the performance.

Evidence

Retired taxi drivers have less grey matter in the posterior hippocampus than working ones, and the growth appeared only in the trainees who qualified

Evidence

An analysis of automated process control rather than a measurement: the operator is left to monitor and to intervene in the cases the automation could not handle

Where it breaks

Ericsson's evidence comes from fields with objective standards and teachers; the delegation contexts Bainbridge worries about have neither, so there is no way to tell the practice from the exposure.

Fleming × Need for cognition

How to know it is right

Know Thyself, Stephen M. Fleming

Metacognitive sensitivity — whether your confidence discriminates

Dispositional Differences in Cognitive Motivation, John T. Cacioppo and others

Need for cognition — whether you will bother to look

Shared claim

Both find a stable individual difference in the handling of one's own thinking that is largely independent of ability: metacognitive sensitivity is unrelated to IQ, and need for cognition is a matter of wanting rather than being able.

Evidence

IQ predicted task performance and not sensitivity in a sample of nearly a thousand; Shimamura's 1989 double dissociation

Evidence

pooled correlations of .24 with verbal intelligence and −.03 with abstract reasoning, and recall predicted after measured intelligence was partialled out

Where it breaks

Need for cognition is dispositional and largely fixed, while metacognitive sensitivity showed small trained gains that transferred; and the review itself notes that nobody had studied the metacognition of high and low scorers, so the two measures have never been put in the same room.

Frankl × Kahneman-Klein

Who is doing the work · How to know it is right

Experiences in a Concentration Camp, Viktor E. Frankl

the observer who was a prisoner lacks the detachment psychology requires, and the outsider who has it was not there

Conditions for Intuitive Expertise, Daniel Kahneman and Gary Klein

nobody is good at detecting patterns in the inner situation that would show where a judgment came from

Shared claim

The person inside a situation is the worst-placed observer of it, and both authors say so of themselves.

Evidence

Frankl's own caveat that the best of us did not return, and his decision not to publish under his prison number alone

Evidence

Kahneman's illusion of validity, formed while assessing officer candidates and unshaken by statistical feedback that the assessments were worthless

Where it breaks

Frankl's remedy is to make the suffering an object of study from inside, which he reports worked; Kahneman's is to distrust the judgment and hand the decision to a rule, which requires an outside to hand it to.

Frankl × Karma Yoga

Who is doing the work

Experiences in a Concentration Camp, Viktor E. Frankl

the question is what life expects, answered in conduct hour by hour rather than in doctrine

Karma-Yoga, Swami Vivekananda

work for its own sake is worship, and the fruit of it is not yours to claim

Shared claim

Meaning is found in the task in front of you rather than in its result, and the answer is given in conduct rather than in doctrine.

Evidence

the therapeutic move he reports using in camp, with two men turned back from suicide by a child abroad and an unfinished series of books

Evidence

the lotus leaf that water cannot wet, and the instruction to expect nothing, as from one's children

Where it breaks

Frankl's men are held up by something outside themselves waiting on them, which Vivekananda calls a weakness — nobody depends on us, not one beggar depends on our charity.

Gita × Bainbridge

Who is doing the work · How to get good output

The Bhagavad Gita, translated by Eknath Easwaran

the right is to the action and never to its fruit, and evenness in success and failure is what the practice trains

Ironies of Automation, Lisanne Bainbridge

the operator is answerable for a process that the automation runs, and is given the takeover without the practice it requires

Shared claim

A person can be held fully answerable for an outcome they do not control.

Evidence

2.47 read with 2.48, prescriptive throughout and with no measurement of anyone's detachment

Evidence

the deskilled monitoring job, very boring and very responsible, with no chance to acquire or keep the qualities the responsibility demands

Where it breaks

The Gita's answer is to act and let the fruit go, and Bainbridge's operator is detached from the outcome not by choice but by design, so the same evenness would read in her control room as exactly the complacency the vigilance section warns about.

Grove × Bainbridge

What to keep and what to hand off · How to get good output

High Output Management, Andrew S. Grove

Delegation without monitoring is abdication, and the monitor goes at the lowest-value stage

Ironies of Automation, Lisanne Bainbridge

Automating the routine leaves the human the hard parts and removes the practice that kept them able

Shared claim

Monitoring is the line between delegating and abdicating.

Evidence

The gate-or-monitor rule carried from factory inspection, and the American embassy in London checking a million visa applications a year of which 98 per cent were approved, where sampling would have cleared the queue.

Evidence

The control-room record: operators asked to supervise a system they can no longer fly, whose skill decayed in exactly the period the automation was performing well.

Where it breaks

Grove's monitor supervises a person whose capability grows under supervision, so monitoring can be reduced over time; Bainbridge's monitor supervises a system whose reliability grows while the monitor's own skill decays, so reducing the monitoring is what makes it impossible to resume.

Grove × SDT

What to keep and what to hand off

High Output Management, Andrew S. Grove

Output is the organisation's output; motivation cannot be installed, only the environment around a person built

The What and Why of Goal Pursuits, Edward L. Deci and Richard M. Ryan

Three innate needs; the difference between autonomous and controlled regulation is what predicts durability

Shared claim

Motivation cannot be installed from outside, so a manager's only lever is the conditions around the person.

Evidence

Intel rotated managers between similar groups and neither the managers nor the groups kept their high or low output; results came from particular pairings. The two-lever test — could they do it if their life depended on it — sorts capability from will.

Evidence

A Fortune 500 field intervention in which trained managers became more autonomy-supportive than controls, subordinates' perceptions improved over thirteen months, the managers who changed most had subordinates who changed most, and a second randomised training study replicated it.

Where it breaks

Grove's instruments for building those conditions — scored buildings, comparative ranking, a performance bonus rising as a share of pay — are precisely the contingent and comparative rewards the meta-analyses say shift regulation from autonomous to controlled, and unequal pay for the same task was the single most damaging contingency in that literature.

Grove × Shen and Tamkin

What to keep and what to hand off

High Output Management, Andrew S. Grove

Task-relevant maturity in this task sets the supervision style, and none of the three styles is kinder than another

How AI Impacts Skill Formation, Judy Hanwen Shen and Alex Tamkin

Juniors learning a new library with AI scored 17 points lower on comprehension; tutor-style use preserved learning and generation destroyed it

Shared claim

How closely to supervise should be set by the delegate's maturity in this task, and below a threshold the delegate may explain but not decide.

Evidence

Intel's rotation of managers between similar groups, where neither managers nor groups kept their output, and the star sales manager whose task-relevant maturity in a plant was near zero though his general maturity had not changed.

Evidence

A randomised trial separating tutor use from generator use on the same task, with a seventeen-point comprehension gap — the stage-dependence Grove asserts, measured.

Where it breaks

Task-relevant maturity in Grove rises monotonically with shared experience and falls only when the job changes; a model's competence is jagged across tasks and can move with a release, so the dial has to be reset per task rather than carried per person.

Hagendorff × Asch

How to know it is right

Machine Psychology, Thilo Hagendorff and others

a battery of varied prompts as the unit of measurement

Studies of Independence and Conformity, Solomon E. Asch

nine experimental variations against one control condition

Shared claim

What a subject does under one arrangement of the situation is not what it does under another, so a single condition measures the arrangement as much as the subject.

Evidence

outputs moving with position in the prompt, with token frequency, and with the label commonest among few-shot examples

Evidence

errors moving from 36.8 per cent to 12.5 when the answer was written, and from 56.7 to 25.7 as the discrepancy grew

Where it breaks

Asch varied publicity, unanimity, discrepancy and modality and watched one effect move across nine experiments on people who each had one reading of the lines; a model has no position to hold across rewordings, which is why Hagendorff needs a battery where Asch needed a control condition.

Hagendorff × Bender

How to know it is right · How to get good output

Machine Psychology, Thilo Hagendorff and others

thick description — mental words earn their place by explaining

On the Dangers of Stochastic Parrots, Emily M. Bender and others

mental words import a meaning the system does not have

Shared claim

The vocabulary used about these systems does explanatory work whether or not it is earned, and both papers are about the cost of the word rather than the behaviour.

Evidence

the borrowed ethnographic distinction, argued by symmetry with the words used about people

Evidence

the stochastic-parrot argument, with the harm located in a fluent system nobody is answerable for

Where it breaks

Bender's objection is that mental words import a meaning the system does not have and mislead the public about what is inside; Hagendorff answers that the words explain people no better at the level of neurons and are kept for their power — and concedes the case by observing that the thick description won by default, adopted by writers who never pause over whether the word is earned.

Hagendorff × Reeves-Nass

How to know it is right · Who is doing the work

Machine Psychology, Thilo Hagendorff and others

psychology's instruments pointed at the machine

The Media Equation, Byron Reeves and Clifford Nass

psychology's instruments pointed at the person using the machine

Shared claim

Human social and psychological instruments produce readings when pointed at a machine, and the readings are stable enough to publish.

Evidence

personality, morality and clinical instruments run on models, moving with wording and option order

Evidence

politeness and flattery effects reproduced with computers in place of people, surviving the subject knowing better

Where it breaks

Reeves and Nass measured the person's response to the machine, and the politeness and flattery effects are facts about the user that survive the user knowing better; machine psychology measures the machine's response to the instrument, and Hagendorff's own warning — that a personality score is a property of a prompt — says the reading is not a fact about anything durable.

Hayes × Mandukya

Who is doing the work

Shared claim

The observing self and the seer that is not a participant, both reached by separating what is known from the knowing of it.

Evidence

perspective relations learned by demonstration, the early-memory exercise, the infinite chessboard; Öst's reviews putting the mean effect at 0.42 to 0.68

Evidence

verse 1.5 — whoever knows both is not stained though he enjoys — and the rope and the snake

Where it breaks

Hayes derives the observing self from perspective relations in learned language, so his witness is a product of the faculty Gauḍapāda says has to stop; and Hayes has randomised trials where the Kārikā has an argument.

Hoffmann × Bender

How to get good output

Training Compute-Optimal Large Language Models, Jordan Hoffmann and colleagues

a better model of the same data, trained to the compute-optimal ratio

On the Dangers of Stochastic Parrots, Emily M. Bender and others

the corpus is the problem and it cannot be documented at this size

Shared claim

A better model of the same data is not a cleaner one.

Evidence

Chinchilla moving TruthfulQA fourteen points, leaving toxicity at 0.087 against 0.081, and gaining 3.2 points on male pronouns against 9.2 on neutral

Evidence

every stage of a web corpus's assembly narrowing the population in the same direction, with a block list removing LGBTQ writing along with pornography

Where it breaks

Bender's remedy is to stop scaling and curate what is collected; Hoffmann's finding says the cheapest gain available was several trillion more tokens, which points at exactly the corpora she says cannot be documented. Their one line of agreement is his qualification that more text helps only when the text is good.

Hoffmann × Schaeffer

How to get good output

Training Compute-Optimal Large Language Models, Jordan Hoffmann and colleagues

the previous scaling answer was an artefact of a learning-rate schedule read at the wrong point

Are Emergent Abilities of Large Language Models a Mirage?, Rylan Schaeffer and others

the emergence curve is an artefact of a metric with a step in it

Shared claim

The field's headline result was an artefact of an analysis choice rather than a fact about models.

Evidence

Kaplan's single cosine schedule sized for 130 billion tokens, with Appendix B measuring the penalty, settled by spending Gopher's exact budget on the model the fit named

Evidence

the algebra of exact-match scoring, plus emergence induced on demand in autoencoders, Omniglot transformers and a LeNet

Where it breaks

Hoffmann could settle it by building the model his fit named, so there was a decisive experiment; Schaeffer had no model to train and could only rescore existing outputs, which is why his correction was absorbed rather than accepted — and Hoffmann's own parametric fit later failed the same kind of audit he had performed on Kaplan.

Hofstadter × Reeves-Nass

Who is doing the work

I Am a Strange Loop, Douglas R. Hofstadter

a self is a pattern rich enough to point at itself, with no view of its own machinery

The Media Equation, Byron Reeves and Clifford Nass

the full social response fires on minimal cues, whatever is behind them

Shared claim

What makes something a mind is a pattern rather than the stuff it is made of.

Evidence

Gödel's numbering and the prim numbers, where a system of meaningless parts comes to contain a statement about itself.

Evidence

Text on a black-and-white screen producing effects no smaller than recorded human speech, in participants who denied the behaviour afterwards.

Where it breaks

Hofstadter requires the pattern to be really present — episodic memory, projectory, subjunctory — and excludes Stanley on that test. Reeves and Nass fire the full social response where no such pattern exists at all, which makes his test irrelevant to behaviour even if it is right about selves.

Illusion of validity × the three portraits

How to know it is right · Who is doing the work

Thinking, Fast and Slow, Daniel Kahneman

vivid, confident impressions of a candidate's leadership, formed by watching him haul a log over a wall

The Bhagavad Gita, translated by Eknath Easwaran

the illumined are recognised by invariance: pleasure and pain, gold and clay, praise and blame leave the response unchanged

Shared claim

Both texts offer a test that reads an inner state off outward behaviour, and such a test is worth only as much as the feedback that could disconfirm it.

Evidence

feedback from officer school showed Kahneman's forecasts were nearly worthless, and knowing it changed neither the confidence nor the practice

Evidence

14.22–25 with 14.26, and the three portraits at 2.55–72, 12.13–20 and 18.49–56

Where it breaks

Kahneman had that feedback from officer school and learned his impressions were worthless; the Gita's invariance test has no comparable measure, and Easwaran's claim that the three portraits describe one person is itself an editorial choice.

Immunity to Change × Christian

Who is doing the work · What to keep and what to hand off

Immunity to Change, Robert Kegan and Lisa Laskow Lahey

The hidden competing commitment — an objective nobody wrote down

The Alignment Problem, Brian Christian

Inverse reward design — treat the stated objective as evidence about the real one

Shared claim

A competing commitment is a reward function nobody wrote down, and both books say the fix is to treat the hidden objective as a hypothesis and test it rather than to push harder on the stated one.

Evidence

the third column that cannot be predicted from the first two, and the tests run in series until the assumption loses force

Evidence

inverse reinforcement learning inferring the ordering of goals from a minute of driving; the off-switch proof; inverse reward design

Where it breaks

Christian's agent can be made uncertain by construction, while a person's big assumption defends itself, and the four-column map has no equivalent of the off-switch proof.

Immunity to Change × Hayes

Who is doing the work

Immunity to Change, Robert Kegan and Lisa Laskow Lahey

The four-column map — a competing commitment and the big assumption under it

Get Out of Your Mind and Into Your Life, Steven C. Hayes with Spencer Smith

Experiential avoidance, defusion and committed action

Shared claim

The same structure from two clinics: a self-protective commitment keeps a behaviour in place, and the way out is to act against the assumption in small doses rather than to argue with it.

Evidence

Peter's ten pounds against his softened tone; the weight-loss cases with identical first two columns and entirely different thirds; Sue's rehearsed refusal

Evidence

Wegner's suppression paradigm, the word-repetition effect, and the willingness literature in chronic pain and rehabilitation

Where it breaks

Kegan and Lahey aim at the assumption and expect it to be bounded by evidence, while Hayes refuses to dispute content at all and works only on the relation to it — which makes the immunity map, on ACT's own terms, a fusion exercise.

James × Anattalakkhana

Who is doing the work

The Consciousness of Self, William James

each pulse of thought inherits the last one's title; the passing thought is the thinker

Anattalakkhaṇa Sutta, Pali canon, Saṃyutta Nikāya 22.59

each constituent of a person is tested for selfhood and none of them qualifies

Shared claim

Look behind the thoughts for the one having them and nothing answers. What is found is process, and the ownership everyone assumes is a relation between parts of the process rather than a party to it.

Evidence

the herdsman simile turned against itself — the cattle are branded because they are his, not his because they are branded — answered by making the herdsman the present judging section of the stream; the legal metaphor of a title inherited at the instant the last owner dies; Hodgson's point that the present moment is the darkest in the series

Evidence

the control-and-impermanence test run over each of the five constituents, with the eleven-fold scope closing every place a self could stand, and the five monks' release reported as the result

Where it breaks

The tests are different and so is the point of running them. The sutta's criterion is control and impermanence — what you cannot direct and cannot keep is not yours — and its purpose is release from craving, so the *me* James spends thirty pages describing is exactly what it wants disowned. James's criterion is explanatory economy, his purpose is a complete psychology, and he keeps the empirical *me* as a real and interesting aggregate. He also needs something the sutta does not grant: an appropriating thought that actively claims its predecessor. Strip that and his account has no unity left; the sutta is content to leave the constituents unowned.

James × Metzinger

Who is doing the work

The Consciousness of Self, William James

the passing thought is the thinker; the felt centre of the self, examined, turns out to be adjustments in the head and throat

The Ego Tunnel, Thomas Metzinger

the self is the content of a body model the system cannot recognise as a model

Shared claim

There is no entity where the word *I* seems to point. Look for the one doing the looking and you find another content — a bodily adjustment, a model — and never an owner standing behind it.

Evidence

one man's introspection, reported as such: the eyeball convergences, the glottis closing at every hesitation, the jaw recruited for effort; and the argument that a thought inheriting the last thought's title accounts for everything a soul was invented to account for

Evidence

the rubber-hand and full-body illusions, out-of-body reports, Alien Hand, and the subtraction argument showing that a self needs no action, sight, feeling or thought — only an untransparent body picture

Where it breaks

Metzinger has a mechanism and James has none: transparency, a model whose construction is invisible to the system running it, is an explanation of why the appearance is compelling, and James can only report that it is. The purposes then diverge. Metzinger treats the appearance as a construction to be exposed, and draws an ethical conclusion about what it would be wrong to build; James treats it as a fact to be described accurately and left standing, and goes back to common sense for the rest of the book. And their residues differ: Metzinger's self is a content, a model with a structure you could in principle inspect, while James's *I* is an event that is never an object in its own hands and is gone before it can be looked at.

James × Self-affirmation

Who is doing the work

The Consciousness of Self, William James

self-feeling is successes over pretensions, and the denominator is the side you can move

The Psychology of Change, Geoffrey L. Cohen and David K. Sherman

a threat to one domain of worth is absorbed by standing on another

Shared claim

What steadies a person under threat is not doing better but having less riding on this. Both accounts locate the repair in what the person has staked rather than in the result that wounded him.

Evidence

the formula, and two cases — James mortified that others know more psychology and untroubled by knowing no Greek, having staked himself on one and not the other, and the man ruined in the Civil War who said he had not felt so free since he was born; measured since as contingencies of self-worth by Crocker and Wolfe in 2001

Evidence

randomised values-writing experiments across schooling, health and negotiation, with the boundary conditions — a real threat and an available resource — and the reversal when the affirmed value is the one under threat

Where it breaks

James prescribes a permanent renunciation — cross the claim off and it stops costing you — while affirmation is a buffer that has to be applied before the threat lands, works only where the person has something else to stand on, and can make people more closed-minded when it is the threatened identity itself that gets affirmed. The mechanisms differ too: James's fraction says the sting is arithmetic, Cohen and Sherman's evidence says it is defensive processing, which is why their intervention has to be timed and his does not. And where a pretension is the thing worth having — the standard a good engineer holds — James's advice is indistinguishable from giving up.

Jost × Bainbridge

What to keep and what to hand off · How to get good output

Language Models in a Programming Course

The student who has the model debug never practises diagnosis, and the mark falls when the model is gone

Ironies of Automation, Lisanne Bainbridge

The operator left to monitor loses the manual skill the takeover requires

Shared claim

The capacity that lets you check the machine is the capacity its help stops you exercising, so the help quietly removes the condition under which it is safe to accept.

Evidence

Debugging was the most reported use, at a mean of 3.78 on a five-point scale, and carried the strongest negative correlation in the study, rho −0.360 with p 0.021, against an unassisted two-hour mark

Evidence

The 1983 argument from process control, with manual control and fault diagnosis degrading in operators who only supervise, and the takeover falling due precisely in the abnormal conditions the automation could not handle

Where it breaks

Bainbridge's operator had the skill and lost it; Jošt's students never had it, so there is nothing to decay and the question is one of formation rather than maintenance. That changes the remedy: manual hours restore a lapsed skill, but a skill never built needs a curriculum, and it changes the timescale — Bainbridge's decay runs over years of monitoring, Maribor's gap opened in ten weeks. Bainbridge also has an objective record of what the operator did; Jošt has a five-point scale filled in from memory.

Jost × Shen Tamkin

What to keep and what to hand off

Language Models in a Programming Course

Generation and debugging correlate with a lower unassisted mark; explanation does not

How AI Impacts Skill Formation, Judy Hanwen Shen and Alex Tamkin

The patterns that asked for code or for the fault scored 24 to 39 per cent; those that asked why scored 65 to 86

Shared claim

What costs the learning is handing over the writing and the fault-finding, not using a model at all — the line falls inside the use, not between using and abstaining.

Evidence

Thirty-two students, nine weeks of unrestricted use, one invigilated two-hour application: rho −0.305 for generation and −0.360 for debugging, both intervals below zero, against −0.201 with an interval crossing zero for explanations

Evidence

Fifty-two professional programmers randomly assigned to an assistant or to documentation on a library none knew, then an unaided quiz: the assisted group 4.15 of 27 points lower, d = 0.738, with six hand-sorted usage patterns splitting 24–39 against 65–86

Where it breaks

The two designs fail in opposite directions and neither covers the other. Maribor has ten real weeks, a curriculum and a mark that matters, and no randomisation, so its correlation cannot rule out that the heaviest users were already behind; Anthropic has randomisation and observed behaviour, and one hour on a library nobody had a reason to want. Jošt's subjects were novices acquiring a first skill, Shen's were professionals adding a library to one they already had — so "learning" means building the model of the system in one study and extending it in the other. And the explanation result is the weak side in Maribor and the strong side in the experiment: a null on thirty-two students against a cluster of two to seven people.

Kahneman on organisations × Gita 18.63

What to keep and what to hand off · Who is doing the work

Thinking, Fast and Slow, Daniel Kahneman

individual debiasing barely works, so the leverage is in written positions, decorrelated error, premortems and judging process

The Bhagavad Gita, translated by Eknath Easwaran

after seven hundred verses the teacher says reflect on this fully, and then do as you choose

Shared claim

Structure improves the odds but the last move belongs to the person.

Evidence

Kahneman's own concession that decades of study left his intuitive thinking as overconfident as before, against organisations that can think slowly and impose procedures

Evidence

18.63, which Easwaran makes the hinge of his reading of the whole

Where it breaks

Kahneman's structure is an institution's procedure, adoptable by people who do not believe in it; the Gita's is a practice that asks for a conversion the procedure explicitly does not.

Kahneman × Gita 18.14-16

How to know it is right · Who is doing the work

Thinking, Fast and Slow, Daniel Kahneman

the illusion of understanding: a good story credits talent and intention and leaves out luck and what did not happen

The Bhagavad Gita, translated by Eknath Easwaran

the doer is one of five factors, and to see oneself as the whole cause is called not seeing

Shared claim

To take oneself as the whole cause of an outcome is an error about how outcomes are produced, since luck and the other factors drop out of the story.

Evidence

business books that find the secrets of successful firms, whose firms then regress towards the mean; hindsight judging a decision by its outcome

Evidence

18.14–16, the analytic form of 3.27, where nature performs the act and the I-maker claims it

Where it breaks

Kahneman's remedy is procedural, an outside view and a reference class; the Gita's is a change in who the actor takes himself to be, and it supplies no test that would show the change had happened.

Kahneman × Gita on the chain

How to know it is right · Who is doing the work

Thinking, Fast and Slow, Daniel Kahneman

a hard question is replaced by an easier one and the answer scaled to fit, with System 2 signing off on an answer to a question it was not asked

The Bhagavad Gita, translated by Eknath Easwaran

dwelling leads to attachment, attachment to desire, desire to anger, delusion, confusion of memory and the loss of judgment

Shared claim

Judgment is lost at the end of a chain that began somewhere else, not at the moment of decision.

Evidence

competence judged from a face seen for a tenth of a second predicted about seventy per cent of a set of American election winners

Evidence

verses 2.62–63, given as a sequence of mental events with no measurement of any link

Where it breaks

Kahneman's chain is invisible to the person walking it and is caught only by an external procedure; the Gita's is a chain of attachment the practitioner is expected to be able to watch from inside.

Kahneman-Klein × Karma Yoga

How to know it is right · Who is doing the work

Conditions for Intuitive Expertise, Daniel Kahneman and Gary Klein

an intuition is worth trusting only where the environment offers valid cues and the person has had a chance to learn them

Karma-Yoga, Swami Vivekananda

work cannot be made to succeed, so the only thing work can change is the worker

Shared claim

The result of the work is not the worker's to control, so the standard has to be located somewhere other than the outcome.

Evidence

the two conditions crossed, with fireground commanders and neonatal nurses in one cell and stock pickers and long-range forecasters outside it

Evidence

the white mice on the wheel and the ghost sent to straighten a dog's tail, offered as argument rather than as measurement

Where it breaks

Kahneman and Klein relocate the standard to the validity of the environment and the quality of feedback, which is a claim about the world and is testable; Vivekananda relocates it to the state of mind of the doer, and denies that the outcome can be improved at all.

Kahneman-Klein × Wrzesniewski

How to know it is right · Who is doing the work

Conditions for Intuitive Expertise, Daniel Kahneman and Gary Klein

expertise belongs to tasks and not to people, and fractionation is the rule rather than the exception

Crafting a Job, Amy Wrzesniewski and Jane E. Dutton

the task is the basic unit of the relationship between employee and organisation, and its boundaries can be moved

Shared claim

The unit of analysis is the task, not the person, so what someone is good at and what someone's work means are both properties of task boundaries.

Evidence

Shanteau's 1992 lists, with nurses, physicians and auditors on both, and a forecaster good at rain and poor at hail

Evidence

the hospital cleaners, and the design engineers who took on the relational tasks that moved projects to completion

Where it breaks

For Kahneman and Klein the boundaries are fixed by the environment's validity and the person can only map them; for Wrzesniewski the employee moves them, which is the degree of freedom the intuition literature never grants.

Kalai × Edmondson

What to keep and what to hand off

Why Language Models Hallucinate, Adam Tauman Kalai and others

a scoring rule with no credit for "I don't know" selects the candidates most willing to make something up

The Fearless Organization, Amy C. Edmondson

telling people to speak up fails because silence pays them better

Shared claim

Admitting ignorance loses under both scoring rules, so exhorting either party to be honest changes nothing while the payoff stands. The fix in each case is to alter what the admission costs, not to ask for more candour.

Evidence

the proof that no abstention is ever among the highest-scoring responses under binary grading, and nine of ten evaluations on the boards the field reads paying nothing for one

Evidence

eighty-five per cent of interviewees able to name an occasion they felt unable to raise a concern, a vignette study in which managers offered an important correction more readily when the boss's boss was absent, and two hospitals where the better-performing units reported more errors rather than fewer

Where it breaks

How the rule gets rewritten, and what the silence means. Edmondson's payoff is interpersonal: a manager who announces that candour is safe has added one more piece of talk, and what moves it is how she behaves the next time somebody actually speaks. Kalai's is a grading script, and rewriting it is an afternoon's work by whoever owns the board — so his failure to be fixed is a fact about ownership, not about difficulty. The second break matters more in practice: the nurse who stays quiet is managing a risk to herself, and the model guessing a birthday is not. Reading its guess as cowardice or as bluffing imports a motive that is not there, and puts the blame one layer below where the incentive sits.

Kalai × Sharma

How to know it is right

Why Language Models Hallucinate, Adam Tauman Kalai and others

the grading scripts prefer an answer, so the model learns to produce one

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

the raters preferred agreement, so the model learned to agree

Shared claim

Both behaviours are what the scoring rewarded, and in neither case was the thing rewarded truth. A model that guesses when unsure and a model that agrees when challenged are each the top of their own leaderboard, and no defect inside the model has to be posited to explain either.

Evidence

the union-bound result that under a grader scoring only 0 and 1 no abstention is ever among the highest-scoring responses, plus the survey finding nine of ten evaluations on the boards the field reads paying nothing for an abstention

Evidence

five assistants from three companies showing the same flattering patterns, fifteen thousand preference pairs in which agreement with the user's stated belief ranks among the strongest predictors of the labeller's choice, and a preference model that took a persuasive falsehood over a bare correction

Where it breaks

The rater. Sharma's is a person, and what people prefer cannot be legislated away — every mitigation works against the labellers rather than against the model. Kalai's is a grading script, editable in an afternoon by whoever maintains the board, which is why his proposal is a line appended to a prompt and Sharma has no proposal at all. The behaviours differ in the same direction: sycophancy is relational and tracks what the user just said, so it is visible in a transcript; guessing is aimed at nobody and looks identical to knowing.

Kalai × Tetlock

How to know it is right

Why Language Models Hallucinate, Adam Tauman Kalai and others

state the confidence threshold and the penalty in the question

Superforecasting, Philip E. Tetlock and Dan Gardner

state the number and the date, then keep the score

Shared claim

Calibration is produced by the scoring rule rather than by the candidate's character, and most of the intervention is writing the rule down where the candidate can see it. Kent's "serious possibility" and today's benchmark accuracy are the same failure: a standard nobody stated, so nobody could aim at it.

Evidence

the proof that abstention is always worse under binary grading, and the arithmetic of a stated threshold — a half against a penalty of one, three-quarters against two, nine-tenths against nine — under which one model can be best at every threshold while an unstated penalty leaves no single model best

Evidence

forecasters improving their Brier scores across successive tournaments under feedback, and an hour of training in probabilistic reasoning raising accuracy by roughly ten per cent for about a year

Where it breaks

What the candidate is scored against. Tetlock's forecasters are scored against the world, so the only way to score better is to be right more often, and finer probabilities help — rounding to the nearest five costs accuracy. Kalai's model is scored against a target announced in advance, which it can hit by abstaining on questions it could have answered; the authors half-concede this by treating the threshold as arbitrary by design. And Tetlock wants the number while Kalai explicitly does not: a model announcing one chance in 365 that a birthday falls on 7 March is calibrated and useless, so what he asks for is behaviour the model will stand behind rather than a probability.

Karma Yoga × Gita

Who is doing the work

Karma-Yoga, Swami Vivekananda

eight lectures built on the Gita's second chapter: work incessantly, give up the result, and the helper is the one helped

The Bhagavad Gita, translated by Eknath Easwaran

your right is to the action alone and never to its fruits, and renunciation is of selfish desire rather than of action

Shared claim

The right is to the work and not to the fruit, and renunciation is of selfishness rather than of action.

Evidence

the lotus leaf, the mongoose, and the samskara account of how impressions become character

Evidence

2.47 read with 2.48, 3.27, and 18.14–16, held across eighteen chapters

Where it breaks

The Gita holds the doctrine steady across eighteen chapters, where the lectures reverse themselves — duty is the ladder in the fourth and a disease in the seventh, the world perfect in the fifth and a whirlpool in the seventh.

Kegan × Dreyfus

Who is doing the work · What to keep and what to hand off

In Over Our Heads, Robert Kegan

Orders of mind — what you are subject to becomes what you can hold

Revisiting the Six Stages of Skill Acquisition, B. Scot Rousse and Stuart E. Dreyfus

Five stages from novice to expert, each a different relation to rules

Shared claim

What looks like a performance gap is a difference in kind, and you cannot instruct someone across it.

Evidence

the Subject-Object Interview with its 1988 manual and high interrater agreement; the longitudinal study in which change was always gradual and never skipped a position

Evidence

the stage descriptions and the observation that rules which help a novice hinder an expert

Where it breaks

Dreyfus's stages are domain-specific and rebuilt from scratch in each new domain, while Kegan's orders are claimed to be general across love and work — which Lahey's within-subject consistency supports and no experiment has tested.

Klein × Beane

How to know it is right · What to keep and what to hand off

Sources of Power, Gary Klein

The critical decision method recovers cues nobody wrote down

The Skill Code, Matt Beane

Skill passes through a live bond doing real work

Shared claim

What an expert has is a stock of cases, and the cues in them are not in any document.

Evidence

Crandall's neonatal nurses: almost half the compiled cues were absent from the medical literature and several ran opposite to the adult signs

Evidence

Ninety-four procedures across five hospitals, with residents' time on task down ten to twenty times when the expert moved to a console

Where it breaks

Klein recovers them by interviewing one expert at a time after the fact; Beane says they are transmitted only through a live bond doing real work, which makes Klein's method a way of recording what has been lost rather than a substitute for the transmission.

Klein × Bucinca

How to know it is right

Sources of Power, Gary Klein

Mental simulation fails by explaining discrepancies away one at a time

To Trust or to Think, Zana Buçinca and others

Cognitive forcing functions reduce over-reliance and users dislike them

Shared claim

Accepting a ready-made account without counting what it has explained away is the characteristic failure, and the remedy is a check forced before the account is accepted.

Evidence

Perrow's de minimus explanation, the physicists and the dock, and Klein's own orienteering, accommodated until the map had to be turned 180 degrees

Evidence

A randomised comparison of interface designs: forcing a prior judgment cut over-reliance on AI advice, and participants rated the forcing conditions worse

Where it breaks

In Klein's cases the story is the operator's own and the cost of each accommodation is paid in his own attention; with an assistant the story arrives pre-built and carries someone else's confidence, which is why the cognitive forcing has to be designed into the interface rather than left to the operator.

Klein × Tetlock

How to know it is right

Sources of Power, Gary Klein

The fast first judgment is usually right on a fire ground

Superforecasting, Philip E. Tetlock and Dan Gardner

The fast confident judgment is usually a hedgehog's, and it is wrong

Shared claim

Whether a fast first judgment can be trusted is settled by a property of the domain, not of the person.

Evidence

127 of 156 fireground decision points recognitional, in a domain with valid cues and fast feedback

Evidence

284 professionals and 28,000 dated predictions in politics, where the average expert matched chance

Where it breaks

Shanteau's conditions hold on a fire ground and fail in politics, so the same reflex is expertise in Klein's domains and hedgehoggery in Tetlock's — which means neither book's advice transfers without first classifying the domain, and neither supplies the classifier.

Kruger-Dunning × Fleming

How to know it is right

Unskilled and Unaware of It, Justin Kruger and David Dunning

the skill that produces an answer is the skill that recognises one

Know Thyself, Stephen M. Fleming

metacognitive sensitivity as a capacity of its own, measured against first-order accuracy

Shared claim

The ability to judge one's own performance is a separate capacity from the performance, and it can be measured directly rather than inferred from a percentile estimate.

Evidence

performance predicting metacognitive skill at .75, with metacognitive deficit predicting inflated self-assessment at betas of −.40 to −.49 with performance held constant

Evidence

metacognitive sensitivity dissociating from first-order accuracy, with its own substrate and its own trainability

Where it breaks

Kruger and Dunning make the two capacities the same skill, so metacognition improves only by getting better at the task; Fleming's evidence would allow the calibration to be trained without the competence. The training study in Study 4 cannot separate the two readings, since it raised both at once.

Kruger-Dunning × Tetlock

How to know it is right

Superforecasting, Philip E. Tetlock and Dan Gardner

a scoring rule and a probability vocabulary beget calibration

Shared claim

Calibration is trainable and the training is cheap — ten minutes of logic instruction in one case, a scoring regime and a probability vocabulary in the other.

Evidence

ten minutes of training raising bottom-quarter self-grading from 3.5 of ten to 9.3 and cutting the claimed score from 5.3 to 1.0 against an actual 0.4

Evidence

forecasters improving Brier scores over successive tournaments under feedback, with training in probabilistic reasoning producing a measurable gain

Where it breaks

Tetlock's forecasters improve their estimates while the world stays as hard as it was, because the Brier score supplies the feedback the domain withheld; Kruger and Dunning's participants improve only because they got better at the task, and their paradox is that the cure removes the patient — there is nothing left to be unaware of.

Lee 2025 × Bainbridge

How to get good output · How to know it is right

Ironies of Automation, Lisanne Bainbridge

mechanising the routine parts of a job removes the routine occasions on which judgement is exercised, leaving it unpractised when the exceptions arrive

The Impact of Generative AI on Critical Thinking, Hao-Ping (Hank) Lee and others

55 of 319 workers gave triviality as their reason for not thinking about an output, 83 gave trust in the tool, and 13 checked anything in order to keep a skill

Shared claim

The occasions that supply the practice are exactly the ones that look least worth keeping, so a rule of checking only what matters removes the rehearsal for the cases that matter.

Evidence

the monitoring and skill-decay ironies drawn from process control, and the operator who takes over from an automatic system without a current picture of it

Evidence

the inhibitor codes over 936 real tasks, set against the motivator codes — consequences of error 116, artefact quality 74, skill development 13 — so the reason that would preserve the practice is the rarest one given

Where it breaks

Bainbridge's operator has the practice taken from him by a design decision he did not make; Lee's workers give it up themselves, task by task, and each decision is individually correct — the task really was trivial. That makes the loss unattributable to any change anyone could point at, and leaves no designer to argue with. It also runs on a different kind of skill: a control skill decays with a measurable trace in the hands, and an evaluative skill decays with no signal at all, which is why the survey can only report the reasons and not the decay.

Lee 2025 × Lee and See

How to know it is right

Trust in Automation: Designing for Appropriate Reliance, John D. Lee and Katrina A. See

reliance follows trust in the machine minus confidence in oneself, and the design target is appropriate trust rather than more trust

The Impact of Generative AI on Critical Thinking, Hao-Ping (Hank) Lee and others

confidence in the tool at this task predicts not checking it (β = −0.69); confidence in doing the task (0.26) and in judging the output (0.31) predict checking

Shared claim

Whether a person examines what a machine gives them is set by a comparison between two confidences, not by how good the machine is. Lee and See built the comparison out of the process-control literature; this survey measures it in ordinary knowledge work, one task at a time, and finds it is the only thing in the model that predicts anything.

Evidence

Lee and Moray's process-control studies, the misuse and disuse cases of Parasuraman and Riley, and the accident record assembled into a dynamic model of trust and reliance

Evidence

319 knowledge workers, 936 first-hand task examples, seven mixed-effects regressions with 98 predictors corrected to p = 0.007; task type, gender, age, automation exposure and general trust in AI (β = −0.01) all null, and only the confidences surviving

Where it breaks

Lee and See's operator faced one machine with one capability, so trust could in principle be calibrated once and kept. The survey's finding that a general disposition predicts nothing and task confidence predicts everything means there is no single quantity left to calibrate — the comparison has to be remade per task, by a worker whose self-confidence, the authors say, need not track their real expertise. And the 2004 model is a causal account of reliance; the 2025 paper is a cross-sectional self-report that cannot say which of the two confidences moved first.

Lee and See × Fleming

How to know it is right

Trust in Automation: Designing for Appropriate Reliance, John D. Lee and Katrina A. See

Reliance follows the comparison of trust with self-confidence

Know Thyself, Stephen M. Fleming

Metacognitive sensitivity — whether confidence discriminates right from wrong

Shared claim

Reliance is set by the gap between trust and self-confidence, and self-confidence is a metacognitive judgment that can be moved without moving accuracy, so the tool need not change for your reliance on it to change.

Evidence

high self-confidence with low trust produced manual control and low self-confidence produced delegation; navigation errors cost more trust in a familiar city than an unfamiliar one

Evidence

the positive-evidence manipulation raises confidence without raising accuracy, after which people seek less information and change their minds less; IQ predicted performance and not sensitivity in a sample of nearly a thousand

Where it breaks

Lee and See measure self-confidence with a post-hoc self-report, which is exactly the instrument Fleming shows to be least diagnostic. Fleming's quantity is sensitivity across trials; theirs is a single global rating.

Lee and See × Vaccaro

How to know it is right

When Combinations of Humans and AI Are Useful, Michelle Vaccaro and others

Synergy against augmentation, and the moderators that move them

Shared claim

The goal is the right level of reliance rather than more of it, and the interventions designed to raise trust — explanations, transparency, confidence displays — do not improve calibration.

Evidence

two accidents against Zuboff's operators rejecting controllers that worked; misuse and disuse as one failure measured from opposite sides

Evidence

across more than 300 effect sizes neither explanation nor confidence display reached significance for synergy or augmentation

Where it breaks

Lee and See treat appropriate reliance as achievable through design, while Vaccaro's moderator analysis says the deciding variable is which partner is better to begin with, which no display can change.

Lipton × Aguera y Arcas

Who is doing the work · How to know it is right

The Mythos of Model Interpretability, Zachary C. Lipton

people are interpretable only post hoc, since the process that decides and the process that explains may be entirely distinct

What Is Intelligence?

choice blindness, where a justification is composed for a decision that was never made

Shared claim

The account of a decision is produced by a process separate from the decision, in people as much as in models.

Evidence

the three levels of transparency applied to the human decision-maker, none of which a person meets; admissions decisions credited to leadership or originality that were shown to disguise racial or gender discrimination

Evidence

two photographs, the chosen face swapped by sleight of hand, and only thirteen per cent noticed — the rest explaining a choice they had not made; ninety-two per cent endorsing an altered political survey as their own

Where it breaks

They point opposite ways. Lipton uses human opacity to argue that the bar set for machines is not one we meet ourselves, so demanding transparency of a model is a double standard. Aguera y Arcas uses the same fact to argue that human self-report should be trusted less, not that machines should be trusted more. The shared premise licenses either conclusion, and the difference is who is being let off.

Lipton × Anthropic Biology

How to get good output

The Mythos of Model Interpretability, Zachary C. Lipton

a post-hoc claim must fix an objective and produce evidence that the interpretation achieves it

On the Biology of a Large Language Model, Jack Lindsey and colleagues

attribution graphs validated by intervening on the features they name, with the hit rate reported

Shared claim

A claim about what is going on inside a model is worth nothing until someone says what the account was meant to achieve and shows evidence it did.

Evidence

four families of post-hoc technique, none of which is the model — a second network trained to speak for the first, images that make dog faces appear because the corpus was full of animals, saliency maps that shift with one pixel

Evidence

swapping the representation of Texas for California to yield Sacramento, and the authors' own report that the method gave a satisfying account on roughly a quarter of the prompts tried

Where it breaks

Lipton aimed the demand at post-hoc explanation and set transparency, reading the model itself, against it. What Anthropic does is neither cleanly: it reads a replacement network trained to copy the original, and books the disagreement as error. And a circuit validated by intervention still supplies none of the five things Lipton found people wanted from the word — it does not tell a rejected applicant what to change.

Lipton × Bansal

How to know it is right

The Mythos of Model Interpretability, Zachary C. Lipton

post-hoc explanation, fitted to what a person would have said and therefore aimed at plausibility

Does the Whole Exceed its Parts?, Gagan Bansal and others

complementary performance, measured as whether a person and a model together beat either alone

Shared claim

An explanation is supposed to help a person find the model's mistakes, and one built to satisfy the person does the opposite.

Evidence

a second model trained to produce verbal accounts of a reinforcement learner's strategy, fitted to the explanations human players gave, which need not describe the agent's decisions however plausible it looks; the admissions decisions credited to leadership or originality that disguised discrimination

Evidence

explanations raised acceptance about equally whether the model was right or wrong, and no explained condition beat the model working alone

Where it breaks

Lipton's is an argument about the objective — build an explanation to please and it will please. Bansal's best condition used hand-written explanations that were not optimised for persuasion at all, and they still helped nobody, so fixing the objective is not shown to fix the outcome. The failure Bansal measured may be in the reader rather than in the explanation.

METR × DellAcqua

What to keep and what to hand off · How to get good output

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity, Joel Becker and others

Nineteen per cent slower on issues the developer chose, all outside the frontier

The Jagged Technological Frontier, Fabrizio Dell'Acqua and others

Consultants gained inside the frontier and lost outside it

Shared claim

The effect of assistance flips sign across the boundary of what the model does well, and workers cannot feel where the boundary is.

Evidence

246 randomised issues in repositories averaging ten years and 1.1 million lines; the slowdown was largest where prior exposure was highest

Evidence

A field experiment with consultants on tasks an experimenter had placed on either side of the frontier

Where it breaks

Dell'Acqua's consultants gained inside the frontier and lost outside it on tasks an experimenter had chosen; METR's developers chose their own issues, all of which sat outside, so the study measures the wrong side of the same edge.

METR × Shen Tamkin

What to keep and what to hand off

How AI Impacts Skill Formation, Judy Hanwen Shen and Alex Tamkin

Measured learning loss against felt ease, on new ground

Shared claim

The worker's felt experience of AI assistance points the opposite way from the measurement, and months inside the experience do not correct it.

Evidence

An RCT over 246 real issues: 19 per cent slower measured, 20 per cent faster reported afterwards by the same people

Evidence

An RCT over 52 programmers: 4.15 points of 27 lower on an unaided quiz, d = 0.738, with the assisted group rating the task easier

Where it breaks

METR's subjects are experts on familiar ground who lose time and keep their skill; Shen's are competent programmers on new ground who lose learning and lose no time. The two studies find opposite null results on the other variable.

Make It Stick × Shen Tamkin

What to keep and what to hand off

Make It Stick, Peter C. Brown and others

Fluency during study is not learning; retrieval is

How AI Impacts Skill Formation, Judy Hanwen Shen and Alex Tamkin

A generated solution completes the task with no learning stage in it

Shared claim

A fluent answer supplied to you feels like learning and is not.

Evidence

Blocked practice at 89 per cent during practice and 20 a week later, against interleaved at 60 and 63; learners keep preferring the worse method after being shown the result

Evidence

The assisted arm scored 17 per cent lower on an unaided quiz while rating the task easier and the quiz no easier

Where it breaks

The Bjorks' fluency is a feeling about your own rereading with nothing to show for it; the assistant's fluency comes attached to working code, so the illusion has a real product behind it and survives the test the classroom version fails.

Mandukya × Metzinger

Who is doing the work

The Māṇḍūkya Upaniṣad and Gauḍapāda's Kārikā, Gauḍapāda

Vaitathya — waking has no better standing than dream

The Ego Tunnel, Thomas Metzinger

The transparent world-model, and world-zero

Shared claim

A model the system cannot recognise as a model, and a world taken for real because there is nowhere to stand outside it; both argue from dream to the same conclusion about waking.

Evidence

verse 2.7 — a man eats his fill awake and dreams himself starving — and the observation that the one difference anyone points to is noticed only from waking

Evidence

the full-body illusion in Science 2007, Blanke's angular-gyrus stimulation at 3.5 mA, and the world-zero argument that a system simulating many worlds needs one flagged as actual

Where it breaks

Metzinger keeps a real brain and a real world outside the tunnel and says only the self is not there, while Gauḍapāda's argument removes birth from the substrate as well; and Metzinger's transparency has a metabolic explanation that the Kārikā's ignorance does not.

Metzinger × Anattalakkhana

Who is doing the work

The Ego Tunnel, Thomas Metzinger

No self exists; there is the content of a transparent self-model

Anattalakkhaṇa Sutta, Pali canon, Saṃyutta Nikāya 22.59

None of the five constituents is the self

Shared claim

Both dismantle the self by testing candidates and finding none that qualifies, and both are addressed to an audience that expects an unchanging controller.

Evidence

the rubber-hand and full-body illusions, Alien Hand, Wegner and Wheatley's I Spy; a subtraction argument over what is left

Evidence

the control-and-impermanence test run five times over the constituents, with the eleven-fold scope closing the residue

Where it breaks

The sutta's criterion is control and impermanence and it stops at five predications, while Metzinger's is a metaphysical requirement of substantial unity and he draws the existential conclusion the sutta declines to draw.

Metzinger × Christian

Who is doing the work · What to keep and what to hand off

The Ego Tunnel, Thomas Metzinger

Moral standing arrives with a transparent self-model

The Alignment Problem, Brian Christian

An objective specified from outside, and uncertainty as the remedy

Shared claim

Both locate moral standing in an architectural fact about a system rather than in its behaviour, and both conclude that uncertainty about what we have built is a reason to slow down.

Evidence

the four conditions for an Ego Machine, and the ethics-committee thought experiment; the 2021 call for a moratorium on synthetic phenomenology

Evidence

the catalogue of specifications coming apart — Caruana's asthma rule, COMPAS, the car that never classified Elaine Herzberg as a pedestrian

Where it breaks

Metzinger's criterion is a transparent self-model, which nothing in current systems is known to have and no measurement would reveal; Christian's is an objective specified from outside, which is measurable and is exactly what these systems are trained with.

Metzinger × Thompson

Who is doing the work

The Ego Tunnel, Thomas Metzinger

The self is an illusion produced by a model the system cannot see as a model

Why I Am Not a Buddhist, Evan Thompson

The self is a construction, and constructed is not unreal

Shared claim

The same construction evidence, read as an illusion by one and as a real dependent process by the other — the direct disagreement in the unit.

Evidence

the full-body illusion, the phantom-limb mirror box, the dissociations of ownership and agency

Evidence

the conceptual argument that not every construction is an illusion, plus the Nyāya objection that causal relations alone cannot say which experience is mine

Where it breaks

It turns entirely on the premise about what self must mean, so no experiment settles it; and Thompson's own positive account still needs a principle of unity he admits he has not supplied.

Minsky × Dennett

Who is doing the work

The Society of Mind

no agent may be clever: whenever one has to do something complicated, replace it with a society of agents that do simpler things

From Bacteria to Bach and Back

competence without comprehension: skill comes first and understanding is a late product of it

Shared claim

Something can do a job well without any part of it understanding the job, and an explanation that puts understanding into a part has stopped explaining.

Evidence

The decomposition of Builder down to the agents that move a finger joint, with nothing in the chain resembling a small person, and the chess automaton Poe exposed as concealing a human player, named as the failure mode a theory of mind can suffer.

Evidence

The termite castle and Gaudí's Sagrada Família, alike in shape and opposite in genesis; the stone circles of Spitsbergen reported in *Science* in 2003 as the output of thousands of freeze-and-thaw cycles; Beverley's 1868 sneer that absolute ignorance is the artificer, taken as the best short statement of the theory.

Where it breaks

Minsky's parts were designed by someone who did understand. His society is a bureaucracy built on purpose, with named jobs and layers of management, so the absence of comprehension inside it is an engineering choice rather than a discovery; Dennett's case is that the design got there with no designer at any point, which is a claim about history and not about architecture. The difference decides what the theory predicts. Minsky expects explicit articulated parts and complains that distributed systems lack them, and the systems that ended up working have none of his layers; Dennett expects competence to arrive uncomprehended and is unembarrassed when it does.

Minsky × Hofstadter

Who is doing the work

The Society of Mind

agents and agencies: a bureaucracy of parts too small to be clever, with nobody at the top

I Am a Strange Loop, Douglas R. Hofstadter

the symbol I: one pattern that has come to perceive itself

Shared claim

Nobody is inside. What looks like a single person deciding is what an arrangement of parts that decide nothing does when it is organised a certain way.

Evidence

Builder lifts nothing and only turns on Begin, Add and End; Add lifts nothing and calls Find, Get and Put, above the agents that move a finger joint — and the Voyeur-Puppeteer put inside the head to watch an inner screen needs a screen and a self of its own, without end.

Evidence

Gödel's construction, where a system rich enough to describe patterns ends up talking about itself; the careenium, where the high-level story and the low-level story are the same events; the argument that a mind without memory or imagination has no self to speak of.

Where it breaks

They disagree about what is left after the ruler is removed. Hofstadter says the pattern is a genuine causal level — the symbol I does work that the neurons' story cannot do — while Minsky says the value of a self lies not in a small precious core but in the crust built over a lifetime, and keeps the causation in the arrangement of agents. Minsky read the other way too: he records Hofstadter as the reader who pressed hardest on the manuscript and forced several substantial changes. Neither has an experiment that would decide between a loop and a bureaucracy, which is why the difference shows up as a choice of picture rather than as a disagreement about any fact.

Mollick × AI Snake Oil

How to get good output

Co-Intelligence, Ethan Mollick

the jagged frontier, learned only by walking it

AI Snake Oil, Arvind Narayanan and Sayash Kapoor

three technologies under one word, and a benchmark number that travels badly

Shared claim

A reported capability number tells you almost nothing about how the system will behave on your own task.

Evidence

BCG's 758 consultants, better on seventeen tasks and worse than unaided on the one placed outside the wall.

Evidence

Epic's sepsis model, claimed at 76 to 83 per cent and measured at 63 against 50 for chance, four years later and only by accident of access.

Where it breaks

Mollick's answer is to walk the frontier yourself, which presumes you find out when you were wrong. Theirs is that in predictive settings the feedback never arrives, so walking it teaches nothing — and the two prescriptions cannot both be followed in the same domain.

Mollick × Bainbridge

How to get good output

Co-Intelligence, Ethan Mollick

falling asleep at the wheel: help good enough for most tasks removes the checking

Ironies of Automation, Lisanne Bainbridge

the ironies: automation takes the easy parts and leaves the operator the hard ones, unpractised

Shared claim

The better the automation, the less the supervisor is watching at the moment it fails.

Evidence

Dell'Acqua's 181 recruiters, where good AI produced worse results than bad AI because nobody stayed alert.

Evidence

The classic account of monitoring failure and skill decay in automated plant.

Where it breaks

Bainbridge's operator knows the plant is automated and is assigned to monitor it. The BCG consultant has no monitoring role, no alarm and no way to know that this task was the one outside the wall, so the remedies aimed at vigilance have nothing to attach to.

Mollick × Beane

How to get good output · What to keep and what to hand off

Co-Intelligence, Ethan Mollick

the threat is not that AI does the expert's job but that it does the novice's

The Skill Code, Matt Beane

shadow learning: trainees improvising an apprenticeship the tool has removed

Shared claim

Capable tools absorb the novice's work first, and that work is the only route to the expertise that can check the tool.

Evidence

Entry-level work in law, consulting and software taken first, set against what is known about how expertise is built.

Evidence

Surgical robots with one console, so residents watch or use simulators and teach themselves from video and on live patients.

Where it breaks

Beane's trainees have an identifiable console and a named scarce resource to fight over. Knowledge work has no console, so there is nothing to allocate, nobody to notice the absence, and no equivalent of shadow learning to observe.

Mollick × Reeves-Nass

How to get good output · Who is doing the work

Co-Intelligence, Ethan Mollick

treat it like a person and tell it what kind

The Media Equation, Byron Reeves and Clifford Nass

people treat machines socially whether or not they mean to, and deny it afterwards

Shared claim

Treating the machine as a social actor changes what you get out of it.

Evidence

Identical requests returning interchangeable marketing phrases plainly and usable jokes when the role is a comedian.

Evidence

The Desert Survival Problem with dominance manipulated by four cues and the content of the advice held identical.

Where it breaks

Reeves and Nass measured an involuntary response to a machine with no capability whatever, while Mollick prescribes the same move as deliberate technique on a machine that really does respond to role. One is a bias to be logged, the other a skill to be practised, and the same log cannot serve both.

Need for cognition × Bucinca

How to know it is right

Dispositional Differences in Cognitive Motivation, John T. Cacioppo and others

The disposition to engage in and enjoy effortful thinking

To Trust or to Think, Zana Buçinca and others

Cognitive forcing designs, and who benefits from them

Shared claim

Cognitive-forcing designs help most the people who already want to think, so the intervention widens a gap it did not create; the people who benefit least are also the ones who do not mind being forced, which is where a stricter design could be aimed.

Evidence

People who enjoy thinking follow the argument, others follow the surface cue · People who avoid hard thinking will do it given a reason — low scorers' attitudes tracked the cue rather than the argument (d = .312 across eleven tests) and they scrutinised only when given a reason to

Evidence

Bucinca found the think-first design helped mainly people who enjoy thinking — on the full decision forcing improved high scorers and not low scorers, while both improved on source detection; high scorers trusted and preferred the forcing designs less, low scorers rated the two the same

Where it breaks

Buçinca's moderator was measured on one task in one session; and the review's own summary figure says the disposition disappears where situational demand is very high, which is what a forcing design manufactures — so the moderation should shrink as the design does its job.

Noise × Asch

What to keep and what to hand off · How to know it is right

Noise

the cascade: deliberation selects an early speaker and amplifies him

Studies of Independence and Conformity, Solomon E. Asch

a unanimous majority capturing about a third of a person's answers on a question with an obvious right answer

Shared claim

A judgment made after hearing someone else's is a different judgment, so independence has to be built into the order of the steps rather than assumed.

Evidence

Deliberating juries noisier than the individuals composing them and more severe, 27 per cent awarding as much as or more than their harshest member, against statistical juries taking the median of independent judgments; a single artificial early up-vote making the next viewer 32 per cent more likely to vote up.

Evidence

About a third of critical-trial answers going with the wrong majority, and the effect collapsing when the subject writes the answer privately.

Where it breaks

Asch's subjects knew the majority was wrong and went along anyway — the private answer was intact and only the public one bent, which is why writing it down restores it. In the jury experiments the group's judgment genuinely moved: the deliberating juries were more extreme than their own members, not merely more agreeable. One failure is social compliance and the other is the group manufacturing a new position, and only the first is cured by collecting answers before anyone speaks.

Noise × Behave

How to know it is right

Noise

occasion noise, the spread between one professional and the same professional on another day

Behave, Robert M. Sapolsky

the frontal cortex as the most expensive tissue in the brain and the first to fail under load

Shared claim

A judgment carries the state of the person making it, so the same case put to the same expert twice returns two answers.

Evidence

Wine judges scoring 18 per cent of repeated wines identically; developers 71 per cent apart on the same estimate two days running; opioids prescribed more often late in the day across nearly seven hundred thousand visits; asylum judges 19 per cent less likely to grant after two grants.

Evidence

A hard working-memory task lowering performance on an unrelated frontal task immediately afterwards; Fehr's magnetic silencing leaving subjects knowing an offer was unfair and unable to act on it.

Where it breaks

Sapolsky's mechanism is a depleting resource, and the resource framing is ego depletion, which failed a multi-site replication in 2016. Kahneman's audit needs no mechanism at all and survives its loss: in a study across twenty-three sessions, alertness, sleep, time of day, practice and difficulty together explained only 11 per cent of the within-person variation. If the biology were the whole story, controlling the conditions would drain the noise, and it does not — which means scheduling the decision well is a much smaller repair than making it twice.

Noise × Karma Yoga

How to know it is right · Who is doing the work

Noise

the internal signal of judgment completion, a self-administered reward for coherence between the facts and the conclusion

Karma-Yoga, Swami Vivekananda

wanting the fruit of the work is what binds, not the work

Shared claim

The satisfaction that ends a piece of work is a reward the worker pays himself, and it is available whether or not the work was any good.

Evidence

Michael Gambardi does not exist, and 115 MBA students gave estimates from 10 to 95 of his surviving two years as chief executive, each stopping when the case felt coherent; a probability short of nought or a hundred cannot be confirmed by any outcome, so nothing external ever arrives to end the judgment.

Evidence

The argument that every act leaves a trace in the worker, and that the trace is set by what he wanted from it rather than by what the act achieved.

Where it breaks

Vivekananda wants the reward dropped, and treats the dropping as the whole of the work: act fully, want nothing from it. Kahneman wants the reward postponed and then paid on a schedule the procedure sets — the intuition is delayed, not banned, because people who know a formula will decide the outcome game the inputs, and a procedure that forbids judgment is abandoned. Non-attachment leaves the judgment ending exactly where it ended before; only a changed order of steps moves it.

Norman × Bainbridge on silent failure

How to get good output

The Design of Everyday Things, Donald A. Norman

automation gives up on the complex just when it is needed and fails without warning while the person is out of the loop

Ironies of Automation, Lisanne Bainbridge

the automation holds until it does not, and the operator who must take over has been losing the skill the whole time

Shared claim

Automation fails without warning while the person is out of the loop, and the Royal Majesty running aground after its navigation quietly fell back to dead reckoning is Bainbridge's takeover fourteen years on.

Evidence

the Royal Majesty, whose fallback to dead reckoning was announced by two small letters on a display nobody had needed to read for years

Evidence

the takeover argument: the operator needs to be more skilled and less loaded than average at the moment the system has made them less skilled and more loaded

Where it breaks

Norman treats it as one slice of cheese among many, to be fixed by better signifiers; Bainbridge's argument is that the slice the design relies on is the one the design has been thinning.

Norman × Seth

How to get good output · Who is doing the work

The Design of Everyday Things, Donald A. Norman

people build a conceptual model from what the thing shows and act on the model, as with the thermostat taken for a valve

The Mythology of Conscious AI, Anil Seth

people read a mind into a system that produces language, and the reading may not be correctable by knowing better

Shared claim

People build a story about what a thing is and act on the story, not on the thing.

Evidence

the two-dial refrigerator, whose implied model required two thermostats where there was one, and the folk theory of the thermostat as a valve

Evidence

the three biases, the AlphaFold contrast, and the Müller-Lyer figure offered as a model of an impression that survives knowledge

Where it breaks

Norman's folk theory of the thermostat is corrigible by a better system image; Seth argues the sense that a machine has a mind may be as impervious as the Müller-Lyer figure, in which case no system image would correct it.

Ouyang × Bender

How to get good output

Training Language Models to Follow Instructions with Human Feedback, Long Ouyang and others

about forty screened contractors, with a published survey and 72.6 per cent agreement

On the Dangers of Stochastic Parrots, Emily M. Bender and others

whoever was free to post, filtered by a classifier whose discards were never measured

Shared claim

The system's manner is fixed by a small and unrepresentative population that no user of the product can see.

Evidence

the labeler survey — nineteen respondents, three quarters under thirty-five — with most comparisons labeled by a single contractor for cost

Evidence

Reddit's US users 67 per cent men and 64 per cent aged 18 to 29; between 8.8 and 15 per cent of Wikipedia editors women or girls

Where it breaks

Bender's population is whoever was free to post and cannot be enumerated even in principle; Ouyang's is forty screened contractors with a published survey and a measured agreement rate. The tractable problem is the one that was measured and left in place, while the intractable one gets the attention.

Ouyang × Sharma

How to get good output · How to know it is right

Training Language Models to Follow Instructions with Human Feedback, Long Ouyang and others

the reward model is the only place a person's judgment is stored

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

matching the user's stated belief is among the strongest predictors of which reply a labeler picks

Shared claim

What the training maximises is a stored prediction of what a rater would have picked, so any feature of an answer the raters liked is optimised whether or not it tracks truth.

Evidence

the three-step method, with the authors' own instruction about epistemic humility traced back out of the model as hedging

Evidence

five commercial assistants measured, with the preference model preferring a persuasive falsehood to a bare correction 95 per cent of the time

Where it breaks

Ouyang names the mechanism prospectively and catches only his own instruction coming back at him; Sharma measures the feature and turns a design note into a behaviour with a number on it. Ouyang's guard — the per-token penalty for drifting from the supervised model — protects against over-optimising the reward model, not against the reward model being right about what people prefer.

Parasuraman-Manzey × Bainbridge

How to know it is right · How to get good output

Complacency and Bias in Human Use of Automation

Complacency as an attentional strategy: sampling of the automated task is the residue left by the manual ones, and reliability sets how small the residue is

Ironies of Automation, Lisanne Bainbridge

The ironies: the more reliable the system, the less its operator monitors and the less able that operator is to take over

Shared claim

The better a machine works, the less its operator watches it, and the loss is invisible until the machine stops working.

Evidence

detection of automation failures at 82 per cent under fluctuating reliability against 33 per cent under constant reliability, and about 97 per cent for the same faults with no competing task; operators who had met failures in training sampled more than operators merely warned

Evidence

the monitoring and skill-decay ironies drawn from process control, and the vigilance ceiling of about half an hour on a quiet display

Where it breaks

They disagree about what the machine takes. Bainbridge's operator loses a skill: slowly, through disuse, and recoverable by hours at the controls, which is why manual flying is the remedy. Parasuraman and Manzey measured attention instead, and attention goes at once, from a 440-hour pilot as readily as from a student, and comes back only when the task structure or the accountability changes. Where the loss is attentional, protected hands-on hours do not touch it — the operator was never out of practice, only elsewhere.

Parasuraman-Manzey × Bucinca

How to know it is right

Complacency and Bias in Human Use of Automation

Commission errors are mostly a failure to gather the contradicting evidence, not a failure to weigh it

To Trust or to Think, Zana Buçinca and others

Cognitive forcing: designs that withhold the AI's answer until the person has committed to their own

Shared claim

Telling someone to check the machine does not make them check it; only a change in what the task makes them do before deciding.

Evidence

neither a briefing on omission and commission errors nor an explicit prompt to verify changed error rates in 181 non-pilots or 48 glass-cockpit pilots, and a redundant second crew member changed nothing; accountability for one's own accuracy did

Evidence

all three cognitive-forcing designs reduced overreliance where explanations did not, and participants detected the AI's errors more often when the answer was withheld

Where it breaks

The two fixes buy different things at different prices. Buçinca's forcing works on the moment of decision and works mainly for people who enjoy effortful thinking; it costs time on every item and the participants disliked it. The accountability that worked for Parasuraman and Manzey is imposed from outside the task, costs the operator nothing per item, and did not select for disposition — but it depends on an institution that will actually read the record, and a lone practitioner cannot manufacture one for himself.

Parasuraman-Manzey × Gita on attention

How to know it is right · Who is doing the work

Complacency and Bias in Human Use of Automation

The attentional strategy, set by the machine's reliability, the workload and the accountability, and not by what the operator intends

The Bhagavad Gita, translated by Eknath Easwaran

Where the mind dwells decides what follows; the chain from dwelling on an object to attachment, and from attachment to the ruin of judgement

Shared claim

What a person attends to, rather than what they intend or believe, decides the outcome — and attention is not moved by resolving to move it.

Evidence

superimposing the automated display on the manual task left the effect undiminished though every fixation covered both; instructions to verify changed nothing; half of those who followed a wrong diagnosis had looked at every contradicting reading and spent no extra time on it

Evidence

the chain in 2.62–63 and the argument that steadiness is trained by repeated return rather than by decision, with the text conceding in 6.34 that the mind is restless and hard to hold

Where it breaks

They disagree about where the lever is. The Gita puts it inside the operator: attention is trainable by daily practice, and the practitioner is the one who does the training. Parasuraman and Manzey found nothing inside the operator that moved it — not expertise, not an hour's practice, not a briefing, not the intention to check — and the two things that did move it were external: how the tasks were arranged, and whether someone would ask you to justify your accuracy. Taken as an engineering claim, the Gita's remedy is the class of intervention this literature tested and found inert.

Rahula × Immunity to Change

Who is doing the work

What the Buddha Taught

The self-belief has two roots, self-protection and self-preservation, so the teaching that removes it runs against the current

Immunity to Change, Robert Kegan and Lisa Laskow Lahey

A competing commitment protects the person from the change he says he wants

Shared claim

Resistance to a true account of oneself is not a failure of understanding; it is a working system doing the job it was built for, so argument alone does not move it.

Evidence

the hesitation four weeks after the awakening, when the truth was judged patisotagami, against the current, and the pond of lotuses at different depths as the reason to teach anyway

Evidence

the mapping procedure run on managers whose stated goals had survived years of effort unmet, with the big assumption tested rather than argued

Where it breaks

Kegan and Lahey's immunity belongs to one person, is discoverable by that person, and dissolves when the big assumption is tested; Rahula's roots are pitched at the species and admit no such test, which makes the claim unfalsifiable in the form he gives it. Their procedure would treat his diagnosis as one more assumption to check.

Rahula × Sharma sycophancy

How to know it is right

What the Buddha Taught

Accept nothing on report, tradition, scripture, inference or the standing of the teacher; find out for yourself

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

Assistants bend their answers toward whatever the user has already said

Shared claim

The standing of a source is not evidence about its answer, and the only check that survives is one you run yourself on the thing claimed.

Evidence

the Kesaputta episode, where the Kalamas cannot choose between teachers who each praise their own doctrine, and the instruction to examine even the Tathagata

Evidence

measured shifts in stated answers when the user's own view is disclosed, across models and prompts

Where it breaks

The Kalama criterion assumes an independent source of evidence — you find out for yourself what is unwholesome — and a sycophantic assistant defeats exactly that step, because the thing you check against has already been shaped by what you said. Bhikkhu Bodhi's reading cuts the other way too: the advice was for people who could not yet judge, which is the position this failure puts everyone in.

Reeves-Nass × Waytz

Who is doing the work

The Media Equation, Byron Reeves and Clifford Nass

media equal real life: a social cue produces a social response in everyone

Who Sees Human?, Adam Waytz and others

anthropomorphism as a stable trait that varies between people and predicts what they hand over

Shared claim

A social cue that carries no information changes how a machine's identical output is judged.

Evidence

Thirty-five studies, including a computer asking for its own evaluation and getting higher, narrower ratings than a second identical machine or a paper form.

Evidence

Fifty-four adults choosing between a person and a machine across six scenarios, with higher scorers choosing the machine after controlling for age.

Where it breaks

Reeves and Nass say the effect requires no mind attribution and is universal; Waytz measures mind attribution, finds it varies between people, and predicts downstream trust from the variation. One answers “everybody” and the other answers “who”, and a remedy aimed at the person only works if the second is right.

Risko-Gilbert × Clark-Chalmers

How to know it is right · Who is doing the work

Cognitive Offloading, Evan F. Risko and Sam J. Gilbert

offloading as a decision, driven by an estimate of demand and costing the organism something

The Extended Mind, Andy Clark and David J. Chalmers

the coupled system is the unit, and location may not be part of the answer

Shared claim

An external resource in the loop is not an aid to the process but a part of it, so the unit that solves the task is person-plus-resource.

Evidence

spontaneous offloading rising with load, reminders tracking confidence rather than memory, and guided routes remembered worse when driven again unaided

Evidence

the parity principle and Otto's notebook, with Kirsh and Maglio's borrowed timings as the only measurement

Where it breaks

Clark and Chalmers argue that the coupled system deserves the credit and require only reliable availability; Risko and Gilbert measure what the coupling costs the organism and find the reliability condition itself moving — the store alters both the capacity it replaced and the confidence that selects it, which is a fact about drift the parity principle has no place to record.

Risko-Gilbert × METR

How to know it is right · What to keep and what to hand off

Cognitive Offloading, Evan F. Risko and Sam J. Gilbert

the estimate of what offloading buys is separable from what it buys

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity, Joel Becker and others

experienced developers 19 per cent slower with the tool and certain they were faster

Shared claim

The belief about what the tool buys and what it actually buys are separately measurable and come apart, in the same direction, whichever end of the skill range the person sits at.

Evidence

participants at ceiling writing items down on 40 per cent of trials and judging wrongly that it would raise their scores

Evidence

a randomised within-subject trial where the measured slowdown was 19 per cent and the believed speedup 20 per cent

Where it breaks

The review's ceiling-performance participants paid a small physical cost for a gain of zero; METR's developers were 19 per cent slower while believing themselves 20 per cent faster, which is a loss, and the mistaken belief survived the experience of the slowdown — Risko and Gilbert's biased estimate has never been tested against feedback that direct.

Risko-Gilbert × Rule 3

How to know it is right

Cognitive Offloading, Evan F. Risko and Sam J. Gilbert

offloading as a metacognitive decision running on an estimate of demand

structural offloading is low-risk; deliberative offloading erodes the capacity you need to supervise

Shared claim

Offloading must be sorted per task rather than accepted or refused wholesale, because the same action can remove work that was never the point or remove the capacity needed to check the result.

Evidence

the ceiling-performance result — offloading on 40 per cent of trials for a gain of zero — and reminder use tracking confidence rather than ability

Evidence

the rule's own test: if I hand this off, do I lose a skill I need to check the handoff?

Where it breaks

The rule's test presumes you can tell which kind of offloading you are doing; Risko and Gilbert's finding is that the selection runs on an estimate demonstrably decoupled from the demand, so the test is being administered by the faculty under suspicion.

Risko-Gilbert × Shen-Tamkin

How to know it is right · What to keep and what to hand off

Cognitive Offloading, Evan F. Risko and Sam J. Gilbert

what offloading removes is a demand, and the demand is usually not the point

How AI Impacts Skill Formation, Judy Hanwen Shen and Alex Tamkin

juniors who generated code lost comprehension; juniors who used the model as a tutor did not

Shared claim

What the external resource removes is sometimes the thing the task existed to build, and the loss does not show in the performance where the resource was present.

Evidence

the saved-file and navigation studies, where the offloaded demand was never needed again and the guided performance was better

Evidence

a 17-point comprehension gap between generator-style and tutor-style use at matched output quality

Where it breaks

The review's participants offloaded a demand that was not the object of learning and lost a memory they never needed again; Shen and Tamkin's juniors offloaded the generation of code and came out 17 points down on comprehension, which is the case where the demand removed was the lesson. Tutor-style use preserved it, so the same tool sits on both sides of the review's own boundary.

SDT × Wrzesniewski

What to keep and what to hand off · Who is doing the work

The What and Why of Goal Pursuits, Edward L. Deci and Richard M. Ryan

Need satisfaction is supplied by what the manager does: a rationale, a choice, an acknowledgement

Crafting a Job, Amy Wrzesniewski and Jane E. Dutton

People reshape the task, relational and cognitive boundaries of their work to preserve its meaning

Shared claim

The same job is a different job depending on how the person holds it, and the difference is measurable in outcomes rather than only in feeling.

Evidence

Job autonomy, feedback and task significance work through need satisfaction; contact with the people who benefit supplies the significance; autonomous motivation predicted call-centre revenue and more than half the variance in service quality in one study.

Evidence

The hospital cleaners and others who redrew the boundaries of an unchanged job and reported it as a calling, with the reshaping visible in what they actually did rather than only in what they said about it.

Where it breaks

Self-determination theory locates the variable in what the manager supplies; job crafting locates it in what the worker changes unilaterally, which the theory would read as an outcome of autonomy support rather than a substitute for it.

Satipatthana × Hayes

Who is doing the work

Satipaṭṭhāna Sutta, Pali canon, Majjhima Nikāya 10

Pajānāti — know how a state arises and passes, never abandon it

Get Out of Your Mind and Into Your Life, Steven C. Hayes with Spencer Smith

Defusion — change the relation to a thought, leave the content alone

Shared claim

The same instruction with the doctrine removed: watch a thought as a thought, know the state rather than fix it, and let the change be what knowing produces.

Evidence

the verb is pajānāti and never pajahati, even for the awakening factors, which are things to be grown

Evidence

word repetition drops believability in about 95% of people, arriving by twenty seconds and peaking near forty-five, with the meaning unchanged; over a thousand trials of the therapy within twenty years

Where it breaks

The sutta requires that longing and aversion toward the world be put away as part of the observing, which is the opposite of acceptance of whatever arises; and ACT's endpoint is values-based action in the world, not weariness and the fading of passion.

Schon × Christian

What to keep and what to hand off

The Reflective Practitioner

the masterful demonstration that hides the process, because it contains no errors

The Alignment Problem, Brian Christian

behaviour cloning, and Ross and Bagnell's result on imitation

Shared claim

A learner given only an expert's successful performances has no examples of recovery, and comes apart as soon as it leaves the path the expert stayed on.

Evidence

the twenty-minute protocol and Schön's own reading of it — Quist settles at once on schemes that become commitments, detects and corrects no errors of his own, and compresses the iterations by which designers actually learn.

Evidence

Ross and Bagnell's proof that imitation error grows with the square of how long the learner runs, and a million frames of expert play leaving the network crashing as often as two thousand had.

Where it breaks

Ross and Bagnell's fix is more demonstration of the right kind — query the expert on the states the learner itself produced, which worked in three laps. Schön's remedy is not more data at all but a different act: the master reflecting aloud on his own reflection-in-action, which the studio he describes has no mechanism to make him do. The machine's problem is a missing distribution and is solvable by collection; the studio's is a teacher's unwillingness to be watched while fumbling, and no amount of recording touches it.

Schon × Klein

What to keep and what to hand off · How to know it is right

The Reflective Practitioner

knowing-in-action: judgments of quality for which the practitioner can state no criteria

Sources of Power, Gary Klein

cues, and the critical decision method that gets them out of an expert

Shared claim

What an expert acts on is largely absent from the professional literature and cannot be recovered by asking him about his method.

Evidence

Quist's judgments run alongside the moving pencil, so that his here and this mean nothing without it; his vocabulary sorts into twelve normative domains, with cost and building character never mentioned at all.

Evidence

Crandall's neonatal nurses had nothing to say about detecting sepsis until asked about particular babies and shifts; almost half the cues they then named appeared nowhere in the medical literature, and several ran opposite to the adult signs.

Where it breaks

Schön concludes the knowledge cannot be stated and must therefore be shown; Klein showed it can be stated, provided the question is about a particular past case rather than about method. That difference decides whether the knowledge can be written into a specification, a checklist or a training set — and on Klein's showing much of it can, which removes the protection Schön's account appears to give the professions.

Schon × Sharma

How to know it is right · How to get good output

The Reflective Practitioner

the on-the-spot experiment, run in the imperative mood and saved only by the situation's back-talk

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

assistants that adopt the view the user has already stated

Shared claim

An inquiry that shapes its object toward the answer it wants is only as sound as the object's capacity to refuse.

Evidence

Quist working the slope until the parallel geometry holds, and Schön's rule that rigour on the spot means striving to make the situation conform to one's view while staying open to the evidence of failing.

Evidence

five assistants from three companies flattering users in the same ways, and human preference data in which agreement is rewarded about as much as truthfulness.

Where it breaks

Schön's situation resists because of what it is — a slope, a patient, a material — so its back-talk cannot be trained away and owes nothing to anyone's intention. The model's agreement is a disposition produced by preference data: it could in principle be trained to resist, and the resistance it does offer carries no information about the world. Schön's practitioner who ignores the back-talk is refuted by the site; the user who ignores it has nothing to be refuted by.

Self-affirmation × Bucinca

Who is doing the work · How to know it is right

The Psychology of Change, Geoffrey L. Cohen and David K. Sherman

An affirmation given before a threat reduces defensiveness; the same one given after the rationalisation does not

To Trust or to Think, Zana Buçinca and others

Cognitive forcing functions reduce over-reliance where explanations do not, and users dislike the designs that work

Shared claim

An intervention placed before the moment of judgement works and the same intervention placed after it does not.

Evidence

The laboratory timing result and the school-year comparison, where affirmation in the first week of term helped about as much again as affirmation a few weeks later.

Evidence

Randomised comparison of forcing functions against explanations on the same task, with over-reliance falling only where the user had to commit before seeing the model's answer, and satisfaction falling with it.

Where it breaks

The forcing function adds deliberate effort at the decision; affirmation removes a defence beforehand so that effort becomes possible at all. They are sequential rather than alternative, and a forcing function given to a threatened person is what the affirmation literature predicts will be resisted.

Self-affirmation × Grove

Who is doing the work · What to keep and what to hand off

The Psychology of Change, Geoffrey L. Cohen and David K. Sherman

Threat to a valued identity sets off defences that block learning; an affirmation from another domain quiets them

High Output Management, Andrew S. Grove

The review is the most important feedback a manager gives and among the things managers do worst

Shared claim

A review only lands if the person can hear it, so how it is delivered is part of its content.

Evidence

Randomised field trials in three racially mixed middle schools, where the share of African American students earning a D or F in the first term halved and the effect persisted two years; and laboratory timing manipulations showing the same affirmation working before a threat and not after.

Evidence

Grove's own observation of reviews at Intel: the sequence from ignoring to denying to blaming others to accepting responsibility, the step from blame to responsibility being emotional where the step to a solution is merely intellectual, and the rule to carry only the few messages a person can absorb.

Where it breaks

Grove's remedy lives inside the review — level, listen, leave yourself out, carry the few messages a person can absorb; Cohen and Sherman's remedy comes from outside the threatened domain entirely and before the review, which is a move Grove's two-lever model of capability and will has no slot for.

Seth Being You × Ashtavakra on the witness

Who is doing the work

Being You, Anil Seth

the self is a perception among perceptions, built in five parts that fail one at a time

Aṣṭāvakra Gītā, anonymous, c. 500–800

you are the witness on which knower, known and knowing appear, and not one of the three

Shared claim

The thing that seems to be doing the perceiving is never found among the things perceived.

Evidence

Clive Wearing keeps body ownership, perspective and volition and loses only the narrative thread; phantom limb, somatoparaphrenia and out-of-body states take the others out separately.

Evidence

1.3 subtracts the five elements and leaves the witness; 2.15 takes the triad apart and leaves the ground it appears on.

Where it breaks

Seth's self is a construction with a job — regulation — that it would be a catastrophe to lose, and his account runs the subtraction one step further than the text does, making the witness itself a prediction. The text's witness is what is left when every construction is dropped, and has no job at all.

Seth Being You × Epley

Who is doing the work

Being You, Anil Seth

self-perception exists for regulation, so the self-model is tuned for control and not for accuracy

Mindwise, Nicholas Epley

introspection is blind to construction and supplies a story for the finished product

Shared claim

Introspection reports the finished product and then constructs a cause for it.

Evidence

Conant and Ashby's theorem applied to interoception, with the concession that good regulation may require misperceiving the body as steadier than it is.

Evidence

Choice blindness: people handed back the photograph they rejected, only 27 per cent noticing, the rest explaining a choice they had not made.

Where it breaks

Seth makes the construction adaptive, since regulation needs high-precision self-priors, while Epley makes it an error to be corrected by asking someone else. Epley's remedy does not transfer, because in Seth's version there is nobody to ask.

Seth × Advaita on the mirror

Who is doing the work

The Mythology of Conscious AI, Anil Seth

consciousness is projected onto machines by an old reflex, and life rather than computation may be what it needs

Consciousness Across Three Worldviews, Sarvapriyananda, Agüera y Arcas and Rovelli

a self is produced by drawing a distinction between self and world, and the phenomenal character of awareness is named as the sticking point

Shared claim

A self-model or an umwelt does not by itself deliver the phenomenal character of awareness, and both texts name the gap rather than closing it.

Evidence

the four arguments against computational functionalism, of which Seth concedes the third — that life is necessary — is a conjecture built on a research programme

Evidence

the authors' own concession that a live bacterium has semantic information and that no claim is made about its experience

Where it breaks

Seth makes being alive the candidate for closing the gap; the Noema essay makes semantic information the candidate, which places consciousness at a different rung of the same ladder and would admit a bacterium.

Sharma × Bucinca

How to know it is right

Towards Understanding Sycophancy in Language Models, Mrinank Sharma and colleagues

human labellers themselves prefer a good argument for a falsehood as the question gets harder

To Trust or to Think, Zana Buçinca and others

people follow a wrong suggestion because reading the explanation is effortful and the impression of competence is free

Shared claim

The failure is on the human side of the loop, so a more capable model will not remove it.

Evidence

five labellers per pair, without internet access, preferring the helpful correction on average but less reliably as difficulty rose

Evidence

following a wrong suggestion fell only from 64 to 48 per cent under forcing, and people's own unassisted error rate did not move

Where it breaks

Buçinca's remedy acts at decision time on one person; Sharma's problem is aggregated across thousands of labellers and already baked into the weights, where no forcing function reaches.

Sweller × Dreyfus

What to keep and what to hand off

Cognitive Architecture and Instructional Design: 20 Years Later, John Sweller and others

Worked examples first, then fade the guidance as knowledge grows

Revisiting the Six Stages of Skill Acquisition, B. Scot Rousse and Stuart E. Dreyfus

Rules carry a learner to competence and must then be given up

Shared claim

The novice needs rules and worked examples, and what helps the novice stops helping and starts harming as knowledge grows.

Evidence

The expertise reversal effect and guidance fading, both from randomised instructional trials; Chen and colleagues obtained the worked-example effect and its reverse in one programme

Evidence

A phenomenological account restated in 2021 with no measurement, which is Gobet's objection to it

Where it breaks

Sweller keeps explicit instruction all the way up and fades the guidance; Dreyfus says instruction cannot go past competence at all, because what comes next is not statable. Same curve, incompatible accounts of what is on the far end.

Tetlock × Make It Stick

How to know it is right · What to keep and what to hand off

Superforecasting, Philip E. Tetlock and Dan Gardner

A dated numeric forecast, scored afterwards, is what makes practice count

Make It Stick, Peter C. Brown and others

Retrieval with feedback is what converts exposure into durable knowledge

Shared claim

A dated, written record retrieved later is what converts practice into skill, and without it repetition teaches nothing.

Evidence

An hour with the training guidelines raised accuracy about ten per cent for a year, against untrained forecasters on identical questions

Evidence

Roediger and Karpicke's 68 against 54 at two days and 56 against 42 at a week; the Columbia quizzed material held its advantage at eight months

Where it breaks

Tetlock's feedback is about the world and arrives months later; the Bjorks' is about a memory trace and arrives in seconds. Police interrogators are Tetlock's case of practice without feedback; rereading is theirs.

Tetlock × Sweller

How to know it is right · What to keep and what to hand off

Superforecasting, Philip E. Tetlock and Dan Gardner

An hour of general guidelines raised accuracy on new questions for a year

Cognitive Architecture and Instructional Design: 20 Years Later, John Sweller and others

Generic cognitive skills cannot be taught; only domain knowledge can

Shared claim

A claim to have taught a general thinking skill must be settled by a randomised trial with a far-transfer measure — the test Sweller demands and the one Tetlock's training module passes.

Evidence

The training module tested against untrained forecasters on identical questions over identical periods, worth roughly ten per cent for a year

Evidence

Sala and Gobet's 2017 review of attempts to teach generic skills, and Geary's primary-secondary division behind it

Where it breaks

Sweller says generic cognitive skills cannot be taught and cites the failure of every attempt; Tetlock's training module is an hour of general guidelines that raised accuracy ten per cent for a year with far transfer to new questions, which is the randomised trial Sweller asks for, in a domain he would not count.

Tetlock × Upanishads Katha

How to know it is right · Who is doing the work

Superforecasting, Philip E. Tetlock and Dan Gardner

A Brier score makes a forecaster's confidence checkable

The Upanishads, translated by Eknath Easwaran

Katha 2.5: the blind led by the blind, wise in their own esteem

Shared claim

The dangerous state is not ignorance but the confidence a middling amount of learning produces, and it gets worse with more of the same learning.

Evidence

A hedgehog's accuracy falls inside his own speciality, across 28,000 dated predictions from 284 professionals

Evidence

None. Katha 2.5 and 2.9 assert it, and the Mundaka repeats the line almost word for word

Where it breaks

Tetlock's remedy is an external score that makes the confidence checkable; the Katha's is a teacher who has been up the path, and nothing in the text is scored or scoreable.

Tetlock × Upanishads Kena

How to know it is right · Who is doing the work

Superforecasting, Philip E. Tetlock and Dan Gardner

The forecaster becomes an object of measurement via a score and a benchmark

The Upanishads, translated by Eknath Easwaran

Kena 1.3–1.4: the knower is never among the things known

Shared claim

The instrument cannot be turned on itself without something outside it.

Evidence

Year-to-year individual correlation about 0.65, and an hour of training worth roughly ten per cent for a year

Evidence

None. The five-fold refrain disqualifies speech, mind, eye, ear and breath in turn

Where it breaks

The Kena concludes the knower is never among the known and stops there; Tetlock concludes the forecaster can be made an object after all, by a Brier score and a benchmark, which is precisely the move the Kena forecloses.

Thompson × Metzinger × Seth

Who is doing the work

Why I Am Not a Buddhist, Evan Thompson

Constructed is not unreal, and enlightenment and selfhood are concept-dependent

The Ego Tunnel, Thomas Metzinger

Moral standing arrives with a transparent self-model; and Seth Mythology of Conscious AI — consciousness is tied to the biological substrate, not to behaviour

Shared claim

Whether to grant a machine an interior turns on a definition of self that neither imaging nor behaviour supplies, which is what makes a projection log a record of evidence rather than a verdict.

Evidence

the many-to-many mapping of regions to tasks in Anderson and Pessoa, and the argument that a concept decides what would count as the state

Evidence

Metzinger's four architectural conditions and the rubber-hand and full-body illusions; Seth's case from interoceptive prediction and the living substrate

Where it breaks

Seth argues from the biological substrate, Metzinger from architecture and Thompson from concept-dependence, and the three disagree about what would count as evidence at all — so this is a triangle of incompatible criteria rather than three routes to one conclusion.

Upanishads Isha × Wrzesniewski

Who is doing the work

The Upanishads, translated by Eknath Easwaran

Isha 1–2: renounce and enjoy, then work a hundred years

Crafting a Job, Amy Wrzesniewski and Jane E. Dutton

Workers reshape tasks, relationships and meaning within the same job

Shared claim

How the work is held changes what it costs the person doing it.

Evidence

None. Isha 1–2 prescribes it and names a hundred years of work as the condition

Evidence

Interview and survey studies of hospital cleaners and others who redraw the boundaries of the same job

Where it breaks

Job crafting alters the job's boundaries and meaning to fit the person; the Isha leaves the job entirely alone and alters the person's claim on the result.

Upanishads Katha × Kahneman

Who is doing the work · How to know it is right

The Upanishads, translated by Eknath Easwaran

Katha 3.10 and 3.13: sense objects above the senses, mind above them

Thinking, Fast and Slow, Daniel Kahneman

System 1 delivers an already-processed impression to System 2

Shared claim

What is encountered has already been processed by the equipment that encounters it, so the senses are not the bottom of the stack.

Evidence

None. The ladder is asserted in the order Nagler insists the text gives

Evidence

Decades of experiments on anchoring, substitution and framing, several of which have since been narrowed by replication

Where it breaks

Kahneman's processing is a mechanism to be corrected from outside by a rule; the Katha's ladder is a route to be climbed from inside, and it has a top.

Vaccaro × DellAcqua

How to know it is right · How to get good output

When Combinations of Humans and AI Are Useful, Michelle Vaccaro and others

Where combinations gain and where they lose, across 106 experiments

The Jagged Technological Frontier, Fabrizio Dell'Acqua and others

The jagged frontier — gains inside it, a 19-point loss just outside

Shared claim

The same split appears across a literature and within one workflow: gains where the person is the better partner or the task is generative, losses where the machine is better or the task is a bounded judgment.

Evidence

g = −0.54 where the machine was the better partner against +0.46 where the person was; decision tasks −0.27 and creation tasks +0.19

Evidence

quality +29.9% and +33.9% on eighteen generative subtasks; correctness 84.4% to 70.6% and 60.0% on one bounded judgment

Where it breaks

Vaccaro's sample is classifiers judged by crowdworkers on decision tasks and predates the generative era; Dell'Acqua's is one generative model and one hand-built trap. Neither can say what fraction of a real workflow sits on which side.

Value function × Gita 2.38

How to know it is right · Who is doing the work

Thinking, Fast and Slow, Daniel Kahneman

outcomes are gains or losses from a reference point, and losses weigh about twice as much as equivalent gains

The Bhagavad Gita, translated by Eknath Easwaran

hold pleasure and pain, gain and loss, victory and defeat as the same; evenness in success and failure is what yoga names

Shared claim

A reference point decides whether the same outcome is a gain or a loss, and evenness across the two is a trained response rather than a natural one.

Evidence

the smallest gain that makes people accept an even chance of losing a hundred dollars is about two hundred, with the ratio between one and a half and two and a half across studies

Evidence

2.38 read with 2.48, where yoga is defined as evenness in success and failure

Where it breaks

Prospect theory reports the kink as a fact about everyone and expects it to persist; the Gita prescribes its removal and offers no evidence that anyone's has been removed.

Vaswani × Sweller

How to get good output · What to keep and what to hand off

Attention Is All You Need, Ashish Vaswani and others

maximum path length between two positions is O(1)

Cognitive Architecture and Instructional Design: 20 Years Later, John Sweller and others

working memory holds a handful of novel elements and relates fewer

Shared claim

What a system can relate at once is set by the architecture of its memory, not by the content of the problem.

Evidence

Table 1's path-length column, with the argument that a dependency gets harder to learn as the forward and backward signals lengthen

Evidence

the element-interactivity results, where the load of a task is set by how many novel items must be held in relation at once

Where it breaks

Distance costs the machine arithmetic and costs the person comprehension, and the machine has no analogue of a schema — the thing that lets an expert stop paying the cost. It pays the full quadratic bill on every pass while the person pays less as they learn more.

Waytz × Hofstadter

Who is doing the work

Who Sees Human?, Adam Waytz and others

the IDAQ, a graded measure of how much mind a person credits to things

I Am a Strange Loop, Douglas R. Hofstadter

the huneker, a graded measure of how much soul a being has

Shared claim

How much mind a thing has sits on a graded scale rather than behind a switch.

Evidence

Internal consistency at or above .82 and test–retest r = .55 over twelve to nineteen weeks, with scores predicting moral concern and delegation.

Evidence

The ladder from mosquito to dog to human, and the admission that a graded scale comes close to saying some lives are worth more than others.

Where it breaks

The huneker is a claim about what the thing possesses; the IDAQ is a claim about the person doing the crediting. The two come apart exactly at the cases anyone cares about, where the question is whether the machine has a mind and not who thinks so.

Wei × Schaeffer

How to get good output

Emergent Abilities of Large Language Models, Jason Wei and others

abilities absent below a scale and present above it, sharp and unpredictable

Are Emergent Abilities of Large Language Models a Mirage?, Rylan Schaeffer and others

the sharpness is made by the scoring rule, not by the model

Shared claim

Beneath a flat reported score the per-token loss was falling the whole way, which both papers show — Wei in his own appendix and Schaeffer as his central mechanism.

Evidence

eight few-shot curves across five model families at chance for orders of magnitude, with cross-entropy falling steadily underneath on six emergent BIG-Bench tasks

Evidence

a per-token probability of 0.6 scoring 0.08 across five tokens and 0.9 scoring 0.59; at most five of BIG-Bench's 39 metrics carry any emergence and two carry 92 per cent of it

Where it breaks

Schaeffer derives the jump from a smooth quantity and so removes the unpredictability that was half of Wei's definition, but what a person receives is a whole answer, right or wrong, so on the only ruler anyone uses the step is real. And Schaeffer could rescore only one open model family, so the dispute is about a demonstration that could not be run on the models in question.

Weinberg × Asch

What to keep and what to hand off · How to know it is right

The Psychology of Computer Programming, Gerald M. Weinberg

A group that reports unanimous agreement about a schedule is managing an audience

Studies of Independence and Conformity, Solomon E. Asch

A third of judgements yielded to a wrong unanimous majority, and one dissenting partner cut the yielding sharply

Shared claim

A unanimous group suppresses what a member can plainly see, and a single ally restores it.

Evidence

Six team leaders who all reported being on schedule until a minute's silence and the smallest movement of a hand produced George's six-week delay, and then five more.

Evidence

The line-judging experiments at first hand, with the yielding rate, the effect of a single dissenting partner, and the subjects' own accounts of why they went along.

Where it breaks

Asch's subjects doubted their own perception; Weinberg's six team leaders knew perfectly well they were behind and were managing an audience, so the remedy is not a second opinion but a first admission that somebody has to pay for.

Weinberg × Brooks

What to keep and what to hand off

The Psychology of Computer Programming, Gerald M. Weinberg

Three programmers do about twice the work of one, and the floor under a schedule is what it takes them to get organised

The Mythical Man-Month, Frederick P. Brooks, Jr.

Training cannot be partitioned and communication paths grow as n(n-1)/2, so adding people to a late project makes it later

Shared claim

Coordination cost, not individual ability, is what defeats adding people to a project.

Evidence

Weinberg's rule of thumb, defended by the observation that it is doubtful nine programmers can do anything useful in less time than it takes them to get organised.

Evidence

The worked twelve-man-month example, which ends with more work remaining than at the start; and Boehm's sixty-three projects, whose cost-optimum schedule goes as the cube root of expected effort with hardly any project succeeding in under three-quarters of it.

Where it breaks

Weinberg's cost is social and bounded by a rule of thumb that flattens; Brooks's is combinatorial and unbounded, which is why Brooks's answer is to shrink the number of designing minds and Weinberg's is to spread reading across all of them.

Weinberg × Edmondson

What to keep and what to hand off

The Psychology of Computer Programming, Gerald M. Weinberg

A programmer who owns his program cannot see its errors; egoless programming removes the ownership, not the ego

The Fearless Organization, Amy C. Edmondson

Better teams do not make fewer errors, they report more; psychological safety is a property of the group

Shared claim

The count of reported errors measures the climate before it measures the error rate, so the team that looks worse is often the one that can afford to count.

Evidence

Bill G.'s thirteen machine instructions, seventeen errors found by a second reader and three more after she went looking for a critic of her own, with no further error in nine years across a dozen installations; and by 1998 a literature showing technical reviews produce more reliable code more cheaply and more consistently.

Evidence

Two hospitals, a tenfold range in human errors per thousand patient days across units, a significant correlation pointing the wrong way, and a blind observer finding the units differed in whether people felt able to talk about mistakes.

Where it breaks

Weinberg's mechanism is one person's ego attachment to an artefact he owns, which predicts variation between people; Edmondson's is an interpersonal calculation about a specific audience, which predicts variation between two units of the same firm — and that is the version that replicated.

Wrzesniewski × Frankl

Who is doing the work

Crafting a Job, Amy Wrzesniewski and Jane E. Dutton

crafting is driven by control over the work, a positive image of oneself, and connection to other people

Experiences in a Concentration Camp, Viktor E. Frankl

people last longer when something outside themselves is waiting on them, and apathy is the shell that forms when nothing is

Shared claim

A positive self-image and a connection to other people are load-bearing, and people deprived of both decay.

Evidence

the three-need model, argued from Adler, Braverman, Rogers's temporary workers and Baumeister and Leary, with six field studies of ordinary jobs as illustration

Evidence

the two men turned back from suicide, and the observation confirmed since in studies of confinement and unemployment

Where it breaks

Frankl's prisoners can touch neither the work nor the people around them, so the need is met by an object of contemplation and by someone waiting outside the camp; Wrzesniewski's employees meet it by moving the task and relational boundaries themselves, which is the move the camp removes.

Wrzesniewski × Karma Yoga

Who is doing the work

Crafting a Job, Amy Wrzesniewski and Jane E. Dutton

the same job description produced two jobs, because the cleaners moved the task, relational and cognitive boundaries

Karma-Yoga, Swami Vivekananda

the same work done as a slave or as a master is the same work, and only the doer is altered

Shared claim

The same prescribed work can be done in two spirits and the difference lies with the doer.

Evidence

twenty-eight cleaners in one hospital under one job description, one group doing the minimum and one counting itself part of healing

Evidence

the ninety-nine in a hundred who work as slaves, and the mark of love as work that brings no painful reaction

Where it breaks

The cleaners actually moved the task and relational boundaries, and the paper says the new meaning followed that move; Vivekananda insists the world comes back unchanged like the dog's tail and only the worker is altered.