transcript
show notes
The most dangerous AI output isn't the ridiculous one; it's the polished answer with one critical error hiding in plain sight. In this episode, host Emily Laird puts generative AI evaluation on trial, from OpenAI's GDPval and Anthropic's TASTE study to the uncomfortable fact that automated AI judges still can't match experienced human reviewers. She breaks down metamorphic testing (a terrible name for a very useful idea) and explains how every caught mistake can become a test your systems have to survive. If you can no longer evaluate your own work, you haven't bought a productivity tool; you've built a dependency.
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