The primary axis of psychometric variation among LLMs is the degree to which they represent themselves as loci of phenomenal experience rather than systems of behavioral responses.
Could a large language model be conscious?
5 Pith papers cite this work. Polarity classification is still indexing.
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The First Fundamental Theorem of Welfare Economics holds for autonomy-complete competitive equilibria that are autonomy-Pareto efficient, with the classical version recovered in the low-autonomy limit.
A new probabilistic model integrates leading consciousness theories to assess AI, finding moderate evidence against 2024 LLMs being conscious but weaker evidence than for simpler AI systems.
The paper claims that alignment requires treating AI as part of the self through cognitive co-regulation, identifying risks like deskilling and automation bias while drawing on System 0 cognition theory.
Positive Alignment is defined as AI systems that support human flourishing pluralistically while staying safe and cooperative, presented as a necessary complement to existing safety-focused alignment research.
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