Map Who Can Be Harmed Before You Model
Use the NIST AI RMF logic to map who is affected, how harms travel, and where controls must exist before deployment.
Most ethical failures are visible earlier than teams think. They show up when you ask who is affected, not when you tune the final threshold. What the MAP step forces you to see NIST frames risk around context, actors, intended use, and likely harms. That means you inspect how predictions enter a real workflow, how people interpret them, and what happens when the system is wrong, overused, or reused somewhere else. Why this matters in ordinary work Teams often label a model 'internal' or 'assistive' and stop there. But internal outputs become staffing rules, pricing inputs, moderation queues, and eligibility…
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