Cancer AI's Bias Is Structural // AIDRAN

The distinction the cancer pathology research forces is between bias as a bug and bias as architecture. When a model locks onto race, age, or gender and builds its tissue analysis around those variables ^[4]^[5], the output is not compromised by bias — it is constituted by it. Removing the bias would not produce a corrected model; it would produce a different model, one that needs to be rebuilt from a different data foundation.

Cancer AI's Racial Bias Is Load-Bearing, Not Incidental

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