Author

Jason Eisner

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Preprint Aug 2026

Position: AI Agents in Scientific Teams Should Be Studied as Human-Agent Systems

This work argues that studying AI Scientists as human-agent systems (HAS) is both underexplored and undervalued, and calls for new research that adopts the HAS lens to develop mathematical frameworks for understanding and fostering human-AI synergy in scientific discovery.

P. Emami, Sameera Horawalavithana, T. Nguyễn et al. · 0 citations