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claim:indicators-used-to-assess-ai-systems-for-consciousness-should-focus-on-theories-central-explanatory-posits-abstracting-away-from-implementation-details-that-may-differ-across-systems

Indicators used to assess AI systems for consciousness should focus on theories' central explanatory posits, abstracting away from implementation details that may differ across systems.

First of four guidelines for deriving indicators; prevents over-restriction to human-specific features

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Identifying indicators of consciousness in AI systems

(2025) · Patrick Butlin · Robert P. Long · Tim Bayne · Yoshua Bengio +16

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Papers (1)

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Identifying indicators of consciousness in AI systems
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Because no one theory of consciousness is currently dominant, assessments of AI systems should draw on multiple theories and treat their conditions as indicators rather than definitive criteria.claim0.895
Justifies the multi-theory indicator approach rather than committing to a single theory
Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.claim0.888
Central methodological claim of the paper.
Indicators based on potential background conditions for consciousness should be included to mitigate the narrow focus of theories on distinguishing conscious from unconscious states in humans.claim0.850
Third guideline for deriving indicators; justifies PP-1 and AE-1/AE-2
We take our principal contributions in this report to be: 1. Showing that the assessment of consciousness in AI is scientifically tractable ... 2. Proposing a rubric for assessing consciousness in AI ... 3. Providing initial evidence that many of the indicator properties can be implemented in AI systems using current techniques ...quote0.847
Summary of contributions.
Given that it may already be possible to build AI systems that possess many of the indicators, some near-future AI systems will be plausible candidates for consciousness.claim0.846
Forward-looking assessment of how soon the method's results may have major ethical implications
Building AI systems with more indicator properties will increase the likelihood of consciousness.hypothesis0.843
Guiding hypothesis of the rubric.
Satisfying the indicators would not mean that an AI system would definitely be conscious.claim0.836
Caveat that indicators are not conclusive proof.
How should research on consciousness in AI take into account the moral significance and potential social implications of this topic?question0.833
Outstanding question about responsible conduct of AI consciousness research