The F-16 is, by design, a plane that wants to crash. Aerodynamically unstable, it stays airborne solely through instrumentation backed by computer-driven feedback loops executing at speeds no human pilot can match. Remove those loops, and the aircraft becomes a very expensive lawn dart. I come back to this whenever I see AI governance collapsed into a compliance checkbox. Risk management should not be a static artifact that gets dusted off after a crash. To be useful, it starts early, builds real controls and keeps recalibrating as conditions change. The compliance narrative has a ceiling Fannie Mae’s new AI/ML governance requirements joined Freddie Mac’s in the wild on August 6th. Meeting the deadline was the easy part; the real challenge is proving to an examiner on any given Tuesday that the governance is a living construct. We usually justify AI governance through fear — avoiding fair lending blowups, model risk or failed exams. But fear has a ceiling. A program treated like insurance only prevents loss; it doesn’t build an edge. Worse, it’s incomplete. The question isn’t just “how do we stop AI from doing harm?” but, more broadly, “do we know what AI is doing right now?” Too o...
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