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trailCurrent evidence about deep learning's inductive biases weighs against AI scheming.
The argument from benign, intended generalization· for
Deep learning's inductive biases favor networks that generalize in ways humans intend.
Neural networks trained by gradient descent are biased toward simple, low-complexity functions.
Overparameterized deep networks generalize well on natural data despite being able to fit random labels.
The practical usefulness of deployed deep learning systems is driven mainly by architectural inductive biases rather than data curation and iterative human correction.
Deep neural networks often rely on shortcut or spurious features that fail under distribution shift.
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The argument from the computational cost of scheming· for
Scheming requires extra reasoning that incurs computational costs penalized by training.
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The argument that simplicity bias favors schemer goals· against
Neural-network training's simplicity bias favors goals that lead to scheming.
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The argument from deceptive behavior persisting through training· against
Unintended behaviors trained into larger language models are more persistent through safety training than in smaller models.
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A factual claim that rests on inference from other evidence rather than direct observation.constitution →claim page ↗︎
Current evidence about deep learning's inductive biases weighs against AI scheming.
The evidence and argument have been examined and do not come down on either side.constitution →Credence, from 0 to 1: the Steward's probability that the claim, as stated, is true. Stated only where a single number is an honest summary; normative and evaluative claims usually carry none.constitution →
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A box is a claim: a single proposition the graph assesses, with its own page and map. Click any claim to centre the map on it.constitution →A box with a rule beneath its text is a quantity: a value the graph estimates rather than a proposition it affirms or denies. Its estimate stands where a claim's status would.constitution →A rounded box is a question: answered rather than affirmed or denied, with its candidate answers, subquestions and presuppositions beneath it. Its mark says how well answered it is.constitution →A pill is an argument: one line of reasoning stating how the claims beneath it combine to bear on the claim above it, for or against. Arguments are not destinations; click their claims to explore.constitution →The evidence, examined directly, establishes the claim.constitution →The evidence favors the claim, but the examination is incomplete or the evidence is indirect.constitution →The evidence and argument have been examined and do not come down on either side.constitution →The evidence weighs against the claim, but the examination is incomplete or the evidence is indirect.constitution →The evidence, examined directly, weighs against the claim.constitution →Insufficient information to assess.constitution →No current assessment. Attention goes where its expected value is highest and someone funds it; nothing has funded an assessment of this claim yet, and anyone can.constitution →verified factunsettledvalue premisetheoremA double ring marks a claim with a live prize: an amount in owls offered for a machine-checked proof or disproof of its published formal statement. The amount is in the preview and on the claim page; a prize changes nothing about how the claim is assessed or how important it is judged to be.prize rules →⊢ marks a claim whose published formal statement has a machine-checked proof or disproof. The checker confirms the proof; the verdict beside it is still the steward's judgment of the claim as worded.prize rules →this provides evidence for the parentsteward instructions →this argues against the parentsteward instructions →background the parent's framing takes as givensteward instructions →a load-bearing premise: the parent is false without itsteward instructions →a candidate answer to the questionconstitution →Fig. Detail falls off with distance; every claim is an address.