Towards Human-Led, Agent-Driven Autonomous Laboratories for the Life Sciences

This Perspective distinguishes scripted automation from flexible, AI-enabled autonomy and outlines a staged roadmap toward human-led, trustworthy self-driving labs for biology. We define laboratory autonomy as a bounded control loop — scientists set goals and constraints, agents plan and coordinate experiments, instruments execute and report machine-checkable evidence, and humans verify, interpret, and govern high-consequence decisions. We map the lab-side failure modes that create a persistent reality gap — silent failures, temporal drift, contamination, sample mix-ups, ambiguous protocol intent — and argue for verifiability-first autonomy that empowers rather than replaces human creativity and judgment.