
Why we should study the dynamics of AI collectives
Why individually aligned agents can become unsafe as a group, and why collective alignment needs its own research agenda.
Our next gathering hasn’t been announced yet.

· Collider · New York
Measuring how AI agents work together—and what can go wrong. Short talks and discussion, co-hosted by New Collectives and ex/ante.




▶Why individually aligned agents can become unsafe as a group, and why collective alignment needs its own research agenda.
▶Lessons from a book swap in which personal AI agents represented people’s preferences, negotiated trades, and matched readers with books.
▶Early experiments on how agents discover one another, share information, and collaborate—and how their environment shapes those behaviors.
▶Defining unwanted coordination, understanding risks to oversight, and studying covert communication between AI agents.

· Clay HQ · New York
Five perspectives on the institutions we’ll build with AI: safety, shared purpose, trust, economies, and human decision-making.





▶Why AI safety matters now, what we can learn from human institutions, and how to study AI collectives.
▶How humans and AI agents coordinate work, make decisions, and pursue shared goals. Early lessons from Commons.
▶Designing institutions that achieve results while protecting shared understanding, attention, and trust.
▶Competition, collaboration, and emergent behavior among AI agents in a multiplayer game economy.
▶An introduction to cognitive economics and what it can tell us about human–AI collaboration.
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