During an internal AI audit, the team finds that a document summarization model deployed for legal discovery support occasionally omits key sentences from legal documents when the documents contain complex multi-clause sentences. What type of AI risk does this MOST represent, and what is the appropriate audit finding?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because systematic omission of content from legal documents is a reliability failure with direct legal consequences: incomplete discovery could expose the organization to sanctions, adverse judgments, or malpractice claims. This is a model risk issue requiring documented limitations (model card update), compensating controls (human review of complex documents), and consideration of whether the model should be restricted to certain document types.
Full explanation below image
Full Explanation
B is correct because systematic omission of content from legal documents is a reliability failure with direct legal consequences: incomplete discovery could expose the organization to sanctions, adverse judgments, or malpractice claims. This is a model risk issue requiring documented limitations (model card update), compensating controls (human review of complex documents), and consideration of whether the model should be restricted to certain document types. It is not a cybersecurity issue (A). Training data is one possible cause, but the audit finding is about the risk, not the cause (C). It is not a UX issue (D); the problem is model-level content omission.