Fives moves to fix AI governance now
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AI governance frameworks built for single models are failing at scale. Drawing on historical failures like JPMorgan's London Whale and Zillow's home-buying algorithm collapse, five concrete fixes are proposed: formally defining model boundaries, versioning every output-affecting component, measuring version sensitivity before deployment, mapping risk propagation through pipelines, and establishing governance for routing layers in agentic systems. These moves are framed against the EU AI Act's August 2026 deadline and grounded in a formal academic framework defining models as versioned typed operators.
Table of contents
The same failure, twiceWhat the EU AI Act requires and where it leaves gapsWhy this is getting harder, not easierFive moves to make to fix AI governance before the August 2026 deadlineThe formal foundation exists todayMoving forwardSort: