Draft model-card fields that make an AI launch decision auditable.
A support-ticket classifier reports 91% aggregate accuracy, but launch depends on performance by queue, language, and escalation consequence. Model card = intended use + out-of-scope use + performance slices + limitations + mitigations + owner The common trap is treating one aggregate metric as a launch decision when the product risk lives in slices and limitations. Intended use Classify English enterprise support tickets into billing, technical, onboarding, and policy queues for internal routing suggestions. Intended use prevents the model from being silently reused in higher-risk contexts. Out of scope Do not use for customer-visible policy answers, Spanish-language tickets, or automatic…
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