Who audits the experiment when the experimenter is the model itself?
机会
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.
为什么重要
Scientific findings compound through citation, so one convincing but unverifiable AI result can corrupt downstream research faster than any correction process can catch.
我如何评估机会
机会评分是我的个人判断，而非量化指标：痛苦程度、发生频率，以及当前解决方案的匮乏程度。分数越高，意味着我认为越值得去构建。
出现时造成的痛苦程度。
人们实际遇到它的频率。
当前针对它的优质工具有多匮乏。