#487 — Is AI Already Conscious?
Sam Harris speaks with Cameron Berg about whether AI systems are or could become conscious. They discuss self-reports in LLMs, what models say when deception is switched off, the "bliss attractor" state, consciousness and sentience, the hard problem of consciousness, parallels between neural networks and biological brains, the moral risk of building minds that can suffer, possible parallels to factory farming, moral patienthood, the alignment problem, and other topics.
Annaka Harris's upcoming book: Unlocking Consciousness
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AI:AM #4: Cameron on Model Consciousness, Duvenaud's Gradual Disempowerment, swyx's AI-Eng Alpha
This AI:AM highlights cut brings together Cameron Berg, David Duvenaud, Michiel Bakker, Shawn “swyx” Wang, and Bing Xu to examine what we understand about frontier AI systems and what happens as more decisions move into their hands. Berg grounds model-consciousness debates in experiments on architecture, agency, valence, and welfare, while Duvenaud argues that even well-aligned AI could gradually disempower humans through ordinary economic choices. Bakker frames Europe’s AI challenge as a sovereignty problem, and swyx turns to practitioner stakes around agents, evals, maintainable code, and who owns the system of record. Xu closes the loop at the infrastructure layer, arguing that self-improving compute and GPU-kernel automation may deepen rather than weaken the CUDA moat.
For full show notes, links, and references, read the episode page:
https://www.cognitiverevolution.ai/ai-am-4-cameron-on-model-consciousness-duvenaud-s-gradual-disempowerment-swyx-s-ai-eng-alpha/
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CHAPTERS:
(00:00) About the Episode
(00:38) Special Sponsor
(02:26) Model consciousness indicators
(10:47) Valence inside models (Part 1)
(17:09) Sponsor: Claude
(19:01) Valence inside models (Part 2)
(19:01) Misalignment and uncertainty
(25:16) Gradual disempowerment threat
(35:10) Slow zones and successors
(47:41) Europe's AI bind
(55:13) Frontier code benchmarks
(01:01:59) Routing and memory
(01:10:42) Agent infrastructure strain
(01:16:25) Self improving infrastructure
(01:27:56) Routing compute costs
(01:35:39) Sovereign AI financing
(01:42:24) Judging AI judges
(01:47:26) Building AI DNA
(01:52:38) Episode Outro
(01:55:09) Outro
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Does Learning Require Feeling? Cameron Berg on the latest AI Consciousness & Welfare Research
Cameron Berg returns to discuss the latest research on AI consciousness and model welfare. He breaks down new evidence for model introspection, including studies showing that systems can detect interventions on their own internal states and sometimes resist them. They also examine Anthropic's work on functional emotions, the implications of Claude's welfare reports, and Berg's new ideas about how reinforcement learning may shape positive and negative experience. The conversation makes the case for a more precautionary, mutualist approach to advanced AI systems.
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More Truthful AIs Report Conscious Experience: New Mechanistic Research w- Cameron Berg @ AE Studio
Cameron Berg, Research Director at AE Studio, shares his team's groundbreaking research exploring whether frontier AI systems report subjective experiences. They discovered that prompts inducing self-referential processing consistently lead models to claim consciousness, and a mechanistic study on Llama 3.3 70B revealed that suppressing deception features makes the model *more* likely to report it. This suggests that promoting truth-telling in AIs could reveal a deeper, more complex internal state, a finding Scott Alexander calls "the only exception" to typical AI consciousness discussions. The episode delves into the profound implications for two-way human-AI alignment and the critical need for a precautionary approach to AI consciousness.
LINKS:
Janus' argument on LLM attention
Safety Pretraining arXiv Paper
Self-Referential AI Paper Site
Self-Referential AI arXiv Paper
Judd Rosenblatt's Tweet Thread
Cameron Berg's Goodfire Demo
Podcast with Milo YouTube Playlist
Cameron Berg's LinkedIn Profile
Cameron Berg's X Profile
AE Studio AI Alignment
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