Draft a datasheet-style documentation fragment that surfaces dataset bias risks.
step-trail before-after try-node A customer-intent classifier will be trained on chat logs, but the team has not documented what the logs represent or omit. Datasheet fragment = motivation + composition + collection + labels + recommended and out-of-scope uses. The common trap is to describe only dataset size. "2.4M rows" sounds robust but says nothing about who appears, who is absent, how labels were made, or whether the data matches the new deployment context. Motivation State why the dataset exists: "Collected to resolve logged-in customer support chats, not to represent all customer support needs." Motivation prevents accidental reuse. A dataset…
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