CASE STUDY - Please use the following to answer the next question: A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records to a radiologist for secondary review pursuant to agreed-upon criteria (e.g., a confidence score below a threshold). To date, the healthcare network has: Defined its AI ethical principles. Conducted discovery to identify the intended uses and success criteria for the system. Established an AI risk committee. Assembled a cross-functional team with clear roles and responsibilities. Created policies and procedures to document standards, workflows, timelines and risk thresholds during the project. The healthcare network intends to retain a cloud provider to host the solution. It also intends to retain a large consulting firm to supplement its small data science team and help develop the algorithm using the healthcare network’s existing data and de-identified data that is licensed from a large US clinical research partner. In the design phase, which of the following steps is most important in gathering the data from the clinical research partner?
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Reference / correct answer:
Most accepted answer: D. Review the terms of use.
Community votes: D=1
Selected Answer: D D The data is licensed, not owned. Even if it’s de-identified, usage is still constrained by: Purpose limitations (e.g. research vs commercial clinical deployment) Training vs inference rights Sub-licensing to consultants or cloud providers Retention, combination, and downstream use restrictions If you get this wrong, everything else becomes non-compliant, no matter how good your governance setup is. upvoted 1 times