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Post 1: The Compliance Trap

When we design AI systems to meet minimum legal requirements, we get systems optimized for minimums.


Compliance frameworks define *floors*, not ceilings. A training dataset balanced to meet WCAG 2.1 AA standards doesn't inherently serve users whose needs exceed those thresholds. An algorithmic fairness audit that passes regulatory scrutiny may still systematically exclude edge-case populations.


The structural trap: AI learns the floor, not the ceiling.


Genuine inclusion requires moving beyond compliance. It requires asking: "What would it take to genuinely serve the people excluded by minimum standards?"


 
 
 

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