A healthcare software vendor publishes a public model card for its diagnostic-support tool that lists the tool's intended use, known limitations, and the sources of its training data. The vendor also requires a named clinical lead to personally review and sign off on every case the tool flags before the result reaches a treating physician. Which two responsible AI principles does this combination of practices demonstrate? (Select TWO.)
Select all correct answers, then click Submit.
Short Explanation
You're seeing two separate responsible AI moves here. Publishing a model card with intended use, limitations, and training data sources gives people the information they need to trust or question the system, so that's transparency. Naming a clinical lead who personally signs off on every flagged case puts a clear human owner on the outcome, so that's accountability.
Full Explanation
The correct answers are the transparency principle and the accountability principle. Publishing a model card that discloses the tool's intended use, limitations, and training data sources gives users and clinicians the information they need to understand what the system can and cannot do, which is the essence of transparency. Requiring a named clinical lead to personally review and sign off on every flagged case establishes a clear, identifiable point of human responsibility for the tool's outputs, which is the essence of accountability. The inclusiveness principle is incorrect because inclusiveness concerns designing a system so it works well for people with a broad range of abilities, backgrounds, and needs, and nothing in the scenario describes accommodating diverse users. The privacy and security principle is incorrect because privacy and security concerns protecting the confidentiality and integrity of data used by or produced by the system, and the scenario describes documentation and sign-off practices rather than any data protection measure.