Pick Tests That Catch the Mistakes You Care About
Explore how to select and apply specific test methods that identify key failure modes in AI outputs. Learn to match errors with the right checks, document results clearly, and make informed stop or conditional-go decisions to ensure reliability in Department of Defense AI workflows.
Once a team has written down intended use and acceptance criteria, the work can still go wrong at the next step because testing drifts into whatever is easy to run rather than what is likely to fail. That drift is often hidden by fluency. Two outputs can both read like competent incident writing, even when each one fails in a different way that calls for a different check.
Two AI-drafted summaries of the same short incident note make the problem visible. One summary adds a crisp technical detail about a mitigation step that was never in the note, and the other summary keeps every stated fact but drops a key constraint about where the note applies. Both sound ...