Who audits the experiment when the experimenter is the model itself?

Autonomous AI systems are being deployed across biology, materials science, and software engineering to design experiments, run them, and write findings with minimal human review per step. A 2026 survey of AI scientist systems found that only 38 percent release the seeds or execution traces needed for a reviewer to reproduce a run, and exactly one of nine fully autonomous systems has been externally validated. There is no mechanism to verify that the steps a model reports match what was actually executed, or that its statistical summaries correctly reflect the underlying data. Human spot-checking does not scale to the volume these systems now produce.