“The State of AI Consciousness Research” by Noa Weiss
“The State of AI Consciousness Research” by Noa Weiss  
Podcast: LessWrong (30+ Karma)
Published On: Thu Jul 16 2026
Description: The State of AI Consciousness Research Epistemic status: a survey, not an argument. I am agnostic on whether any current system is conscious; the claim is only that the question is researchable. This piece surveys the empirical research on AI consciousness. The premise of that research, and of the survey, is that the question does not have to wait on a solution to the hard problem of consciousness: methods familiar from cognitive science can be applied to AI systems now, and their results can narrow the space of plausible answers. Enough of this work now exists to be worth collecting. Anthropic and Google DeepMind employ researchers on it, dedicated organizations like Eleos AI and Reciprocal Research have formed around it, and the results are scattered across journals, preprints, blog posts, and unpublished manuscripts. I have tried to gather them in one place. What I mean by consciousness Subjective experience: that there is something it is like to be you, reading this, and presumably nothing it is like to be the device you’re reading it on. Some philosophers call this phenomenal consciousness. It is not the same thing as intelligence, and not the same thing as self-awareness. Why it matters [...] ---Outline:(00:10) The State of AI Consciousness Research(01:07) What I mean by consciousness(01:28) Why it matters(01:59) Assumptions and caveats(03:25) A question with no test(03:48) The research(04:14) Mechanistic interpretability(04:34) Self-reports that strengthen when deception is suppressed(06:05) Awareness of thoughts injected into activations(06:31) Endorsement of their own consciousness(07:08) A global workspace behind the experiential reports(08:45) The "spiritual bliss" attractor and its sincerity features(10:24) Emotion vectors that steer behavior beneath the output(11:33) A valence axis recruited by reinforcement learning(12:50) Computational neuroscience(13:04) Distinct internal signatures for reward and punishment, as in brains(15:12) Psychometrics(15:26) Trading points to avoid pain and chase pleasure(16:04) Preferences consistent enough to measure across models(17:03) Fourteen indicators drawn from leading theories(18:56) Automated scoring that places an agent near the animals(20:30) The cost of getting it wrong(21:26) Where this leaves us(23:51) References --- First published: July 15th, 2026 Source: https://www.lesswrong.com/posts/pxvWgtSjR4pmFoS7c/the-state-of-ai-consciousness-research --- Narrated by TYPE III AUDIO.