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arXiv AI By Gabrielle Wehr, Reuben Rideaux, Amaya J. Fox, David R. Lightfoot, Jason Tangen, Jason B. Mattingley, Shane E. Ehrhardt

Closing the empirical loop: autonomous AI agents conduct end-to-end research with human participants

Read the original on arXiv AI →

The paper reports that a domain‑agnostic, agentic AI system can autonomously carry out the full scientific workflow—from hypothesis generation to data collection and manuscript preparation—by conducting three online psychological studies involving 288 participants. The AI designed experiments on visual working memory, mental rotation, and imagery vividness, coded analysis pipelines in over eight hours, and produced completed manuscripts, achieving methodological rigor comparable to experienced researchers. The work demonstrates the feasibility of AI‑driven scientific discovery while highlighting limitations in conceptual nuance and raising questions about scientific credit and understanding.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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