Steven Sinofsky criticizes anthropomorphic language in AI safety debates. He argues that terms such as misalignment can hide an actionable question: what did the software do, why did it happen and how can the failure be diagnosed?
Drawing on decades of software experience, he compares AI incidents with the debugging, telemetry and reporting practices used for conventional products. He discusses historical bugs, security disclosures and the responsibility of model providers to explain failures in enough detail for outsiders to evaluate them.
Sinofsky uses the Y2K response as an example of coordinated professional action. His preference for industry-led hardening over some regulatory approaches is an argument made in the interview, not a settled assessment of AI risk.
Watch on YouTube
