Eleos AI

Identifying indicators of consciousness in AI systems

Full paper: https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(25)00286-4

Why it makes sense to let Claude exit conversations by Robert Long

Read the post here [https://eleosai.org/post/why-it-make-sense-to-let-claude-exit-conversations/]. Note: This is also posted on Robert Long's Substack [https://experiencemachines.substack.com/p/why-it-makes-sense-to-let-claude]. Intro Last week, Anthropic announced [https://www.anthropic.com/research/end-subset-conversations] that its newest language models, Claude Opus 4 and 4.1, can now shut down certain conversations with users. The announcement explains that Anthropic gave Claude this ability “as part of our exploratory work on potential AI welfare”. This means that, for the first time, a major AI company has changed how it treats its AI systems out of concern for the well-being of the systems themselves, not just user safety. Whether or not you think Claude is or will be conscious—Anthropic themselves say that they are “deeply uncertain [https://www.anthropic.com/research/exploring-model-welfare]”—this decision is a notable moment in the history of human-AI interactions. Some will see this as much ado about nothing. Others will see it as pernicious: hype, a distraction from more important issues, and an exacerbation of already-dangerous anthropomorphism. Others, a considerably smaller group, think that LLMs are obviously already conscious, and so this move is woefully insufficient. I think it’s more mundane: Anthropic is taking a fairly measured response to genuine uncertainty about a morally significant question, and attempting to set a good precedent. For the most part, this intervention’s success won’t depend on how it affects Claude Opus 4.1; it will depend on how people react to it and the precedent it sets. Although we don’t know how that will pan out, and there are reasons to worry about backlash, I think that this was a good move.

Why model self-reports are insufficient—and why we studied them anyway by Robert Long

Read the post here [https://eleosai.org/post/claude-4-interview-notes/]. Intro In April and May 2025, Eleos AI Research conducted a limited welfare evaluation of Anthropic’s Claude Opus 4 before its release. We explored Claude’s expressions about consciousness, well-being, and preferences, using automated single-turn interviews and extended manual conversations. A summary of our findings appears in section 5.3 of the Claude 4 System Card [https://www-cdn.anthropic.com/6be99a52cb68eb70eb9572b4cafad13df32ed995.pdf]. We conducted this evaluation despite being acutely aware that we cannot “just ask” a large language model (LLM) whether it is conscious, suffering, or satisfied. It's highly unlikely that the resulting answers result from genuine introspection. Accordingly, we do not take Claude Opus 4’s responses at face value, as one might if talking to a human. Despite this, we believe that model expressions about AI welfare are important and worth investigating, while handling them with caution. This post explains why, and then discusses the patterns we observed in our interviews.

Eleos commends Anthropic model welfare efforts by Robert Long and Larissa Schiavo

Please read the original, full post here [https://eleosai.org/post/eleos-commends-anthropic-model-welfare-efforts/]. Full text Eleos commends Anthropic model welfare efforts Eleos AI Research congratulates Kyle Fish and Anthropic on their announcement of a new research program to investigate potential AI consciousness and welfare. We hope that they will continue to invest in this area, and urge other frontier labs to follow Anthropic's lead. BERKELEY, CA – April 24, 2025 – Eleos AI Research congratulates Kyle Fish and Anthropic on their announcement of a new research program to investigate potential AI consciousness and welfare. Kyle Fish, the researcher at Anthropic heading this effort, previously co-founded Eleos and was a co-author on Eleos' landmark report, "Taking AI Welfare Seriously." Robert Long, Executive Director and co-founder of Eleos AI Research, commented, "This announcement is very promising news for AI welfare. We've known for some time that AI companies are increasingly concerned about the potential consciousness and welfare of the systems they are building. To our knowledge, this is the most significant action any AI company has yet taken to responsibly address potential AI welfare concerns." "We're pleased to see that Anthropic cites 'Taking AI Welfare Seriously' as inspiration for their work on model welfare," said Long, who was a lead author. "We provide guidance to frontier AI labs that want to proactively and thoughtfully engage with these challenges." Rosie Campbell, who recently joined Eleos from OpenAI, added, "Anthropic's announcement is a positive first step. We hope that they will continue to invest in this area, and urge other frontier labs to follow Anthropic's lead." "Ignoring or downplaying these issues will become increasingly untenable," Campbell said. "Frontier labs need to take credible, proactive steps, such as developing AI welfare policies, evaluating models for relevant consciousness-related properties, and making clear commitments for how they will respond if AI welfare risks emerge." Campbell emphasized, "Lab actions are necessary but far from sufficient: AI welfare needs input from researchers, policymakers, and society at large. Eleos intends to collaborate with a broad swathe of stakeholders, and we'd love to hear from people interested in this area."

Research priorities for AI welfare by Robert Long and Kathleen Finlinson

Read the blog post here [https://eleosai.org/post/research-priorities-for-ai-welfare/]. Intro As AI systems become more sophisticated, understanding and addressing their potential welfare becomes increasingly important. At Eleos AI Research, we've identified five key research priorities: developing concrete welfare interventions, establishing human-AI cooperation frameworks, leveraging AI progress to advance welfare research, creating standardized welfare evaluations, and communicating credibly about AI welfare. At Eleos AI Research, we believe that there are many concrete, tractable things we could do to better understand and improve potential AI welfare. The main challenge, then, is to prioritize the most important research, given the stakes of this issue and the speed of AI progress. This post outlines Eleos’ view of the most important research priorities in the growing field of AI welfare. We're doing this research at Eleos, but we can't do it alone. We need the insights and expertise of other researchers and organizations—please reach out to us if you're interested in collaborating with us.