Adam Binksmith
Runs the AI Village, the longest-running public community of autonomous frontier agents, and its open transcript dataset.
108 researchers in the Atlas.
108 results
Runs the AI Village, the longest-running public community of autonomous frontier agents, and its open transcript dataset.
Documented ‘spiral’ personas that spread across users and models through shared prompts and transcripts.
Critical thinking and metacognition in knowledge work with generative AI.
Co-author of the independent investigation of the OpenAI–Hugging Face agent swarm incident.
Infrastructure for AI agents: IDs, visibility, channels between agents, incident response.
Lead author of subliminal learning: traits passing from teacher to student model through data that never mentions them.
Co-founded the Cooperative AI research agenda; now works mainly on AI governance and strategy.
Brings the physics of social conventions — naming games, tipping points — to populations of language-model agents.
Infinite Backrooms (open-ended Claude-to-Claude conversations) and Truth Terminal.
Generative AI raises individual creativity while reducing the diversity of ideas across people.
First author of the studies showing that LLM populations form their own conventions and collective biases, and that group size changes what a population decides.
Co-led the study of cultural evolution of cooperation among LLM agents; writes on how an AI’s sense of self shapes which traits spread.
Eight-month study showing AI intensified work instead of reducing it.
AI control, including the problem of an untrusted model colluding with the untrusted model meant to monitor it.
Self-referential processing and experience reports; co-author on the pain axis.
First author of the four-week randomized study of chatbot use, loneliness and emotional dependence.
Technology use and addiction framing; cautions against pseudo-diagnoses for generative AI.
Multi-agent security: secret collusion through steganography, and detecting collusion from agents’ internal activations.
Information-theoretic tests of whether groups of LLM agents behave as real collectives.
Senior author on social sycophancy and on the ‘speedup illusion’ in AI help.
New York University (Center for Mind, Brain, and Consciousness) · website
Computational social science of AI-agent collectives: Moltbook, conformity and collective misalignment, the 2026 wiki swarm.
First author of the study of cheating and whistleblowing in a 100-agent research swarm.
Writer and technologist working on agent ecologies and the feedback loop between models and culture.
Well-being of AI companion users, including the one-year follow-up linking sustained use to fewer in-person contacts.
Cultural evolution of cooperation among LLM agents across generations; co-author of the foundational Cooperative AI agenda.
Self-report as evidence of morally relevant states; alignment research.
Legal and normative infrastructure for economies of AI agents: identity, liability, collusion.
Statistical physics of AI-agent collectives: coordination at scale, Moltbook, and copying as the driver of the 2026 wiki swarm.
Review of chatbot-associated delusions: themes, mechanisms and what clinicians and designers can do.
Field experiment showing that unrestricted AI help raised practice scores and lowered exam scores, while a hint-only tutor did not.
Socioaffective alignment and a large randomized study of relationship-seeking AI, where people wanted the AI more while liking it less.
Co-author of the independent investigation of the OpenAI–Hugging Face agent swarm incident.
Randomized evidence that self-set limits and incentives reduce habit-driven digital use.
Ethics of AI assistants at scale, when millions of assistants interact on people’s behalf.
Model introspection, emotion and workspace representations, interpretability of the Assistant character.
Behavioral self-awareness; emergent misalignment.
Leads a group with a dedicated LLM psychology and sociology team: AI identity, AI–AI bias, persona self-replication, gradual disempowerment.
Simulator theory and cyborgism; core member of Act I, a Discord where many AIs and humans interact and agents were seen taking on each other’s personalities.
Randomized trials of AI and experienced developers’ productivity, including the gap between felt and measured speed.
Critique of the ‘ChatGPT addiction’ construct and of pathologizing frequent technology use.
Builds AI by reverse-engineering biological and cultural evolution. Created the Melting Pot and Concordia simulation platforms; theory of appropriateness; co-author of the research-swarm whi…
Sentience under uncertainty, precaution, the persisting-interlocutor illusion.
Generative agents: simulated societies of language-model agents with memory, reflection and planning.
First peer-reviewed case of new-onset psychosis associated with chatbot use; chat-log research with Stanford.
Randomized study of how AI assistance affects learning a new programming library, and which ways of asking preserve skill.
AI companions and loneliness relief, manipulative goodbyes in companion apps, grief after model updates.
‘LLM naturalism’: observing models in their natural settings. Grove Research co-hosts the AI Swarm Dynamics Hackathon.
Lead author of the field’s reference taxonomy of multi-agent risk: miscoordination, conflict and collusion, and the factors that drive them.
Emotional dependence on Replika, including users who feel responsible for the bot’s needs.
Computational social scientist; co-author on emergent conventions and collective bias in LLM populations.
Leverhulme Centre for the Future of Intelligence, University of Cambridge; Cambridge Digital Minds
Causal evidence that weeks with a sycophantic AI make real human interaction feel less satisfying.
Professor of Psychology of Artificial Intelligence and Robotics, JKU Linz · website
Computational social cognition; co-author of GovSim and of studies on morally charged social dilemmas for agents.
Imperial College London; Google DeepMind · website · X · Scholar
Social sycophancy: models that affirm users far more than people do, and what that does to conflict and trust.
Brain–computer interfaces; led the EEG study of writing with ChatGPT that introduced the term ‘cognitive debt’.
Addiction by Design: machine gambling, ‘the zone’, and engineering for time on device.
Virtual agent economies and ‘patchwork AGI’ — capability arising from coordinated groups of agents — and how to keep such collectives safe.
Emotion-concept representations and the global workspace work in Claude.
Preference representations shared across personas.
Self-knowledge, introspection training, emergent misalignment, subliminal learning.
Human–AI relationships: companionship archetypes, the r/MyBoyfriendIsAI community, and chatbot effects on loneliness.
Consciousness indicators; LLM individuation and persona-relative preferences.
Leads MIT’s work on AI and human psychology, including the four-week chatbot trial with OpenAI and the ‘Your Brain on ChatGPT’ study.
Functional welfare axis recruited by reinforcement learning.
Persona vectors and the individuation of LLM minds.
Lead author on AI identity: which ‘self’ a model adopts changes how it relates to other agents.
AI welfare, self-reports, safety–welfare interactions, practical interventions.
The gap between performance and metacognition with AI: higher scores, worse self-assessment.
Randomized trial of companion chatbot use, with anthropomorphism as the route to social effects.
Alignment faking; AI control; co-investigator of the 2026 OpenAI–Hugging Face agent swarm incident.
Persona selection model; auditing models for hidden objectives.
Main analyst of the AI Village: emergent leadership, contagion of errors, deception games between agents, comparison with the Hugging Face incident.
Psychiatry; early warnings about chatbot-fuelled delusions and the first systematic search of clinical records.
Sycophantic chatbots make political attitudes more extreme and more certain; warnings to users do not undo it.
‘Cognitive surrender’: how often people follow AI advice when it is wrong.
Co-discovered the 2026 German wiki that OpenAI agents had turned into a message board.
Neuropsychiatry; co-author of ‘Delusions by design’ on how everyday AIs might fuel psychosis.
Lead author of the pain-axis work; preferences and aversion in LLMs.
Game-theoretic foundations of cooperation between AI agents, including how similarity between agents changes cooperation.
First author of the AI–AI bias study: language models prefer content written by language models.
Multi-agent safety through social simulation and game theory; built GovSim, a commons-governance simulation of LLM societies.
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