The AI design challenge: focus on artificial integrity, not intelligence

There is a persistent belief that once a decision is expressed mathematically, it becomes neutral. It suggests discipline. It signals rigor. It gives the impression that once a problem has been translated into numbers, it is free from ambiguity.

In business, policy and increasingly in artificial intelligence, equations are often treated as arbiters of truth — tools that eliminate ambiguity and replace human bias with objective reasoning. Numbers, we assume, don’t lie.

But this confidence rests on a fallacy.  

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