Bias Doesn’t End at the Dataset: It Lives in the Deployment

Equity has to be built into the deployment strategy from day one, not treated as a future retrofit. That means prioritizing inclusion not only in the data but in the delivery, and recognizing that inclusive deployment is the foundation for inclusive datasets.

When we talk about bias in healthcare AI, the conversation almost always starts — and ends — with data. We scrutinize training sets, audit algorithms, and develop fairness metrics. But there’s a different kind of bias that flies under the radar: deployment bias. And it’s just as dangerous.

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