The goal of this study is to craft empirically grounded, practical policy proposals that address tensions between ethical needs for explainability and legitimate commercial needs for trade secrecy raised by AI-based clinical decision software, including diagnostic, treatment, and predictive software. The study will examine both AI-enabled software that is regulated as a medical device by the FDA as well as unregulated software.
Our Grants
Explainability and Trade Secrecy in AI-Enabled Clinical Decision Software
Arti Rai, JD
Duke Law School
Duke Law School
Grant Type
Making a Difference
Grant Cycle
fall 2018
Duration
1 year
Amount
$196,605
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Arti K. Rai, Isha Sharma, and Christina Silcox, Accountability, secrecy, and innovation in AI-enabled clinical decision software, Journal of Law and the Biosciences, Nov 2020
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Christina Silcox et al., Trust, But Verify: Informational Challenges Surrounding AI-Enabled Clinical Decision Software, Duke University Margolis Center for Health Policy White Paper, Sept 2020
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Grant Focus Areas
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