1 citations · 2 across the 9 of their papers we have counts for
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Drawing Out Legal Risks: Co-Designing with Lawyers to Predict and Manage Legal Uncertainties of Medical AI Tools
Gennie Mansi, Julia Kim, Michael Rosenbloom +1
While there's optimism around medical AI tools due to their abilities to adapt from user-to-user and across environments, these new abilities complicate how people and organization…
Evaluating Actionability in Explainable AI
Gennie Mansi, Julia Kim, Mark Riedl
A core assumption of Explainable AI (XAI) is that explanations are useful to users -- that is, users will do something with the explanations. Prior work, however, does not clearly…
Understanding the Impact of Physicians' Legal Considerations on XAI Systems
Gennie Mansi, Mark Riedl
Physicians are--and feel--ethically, professionally, and legally responsible for patient outcomes, buffering patients from harmful AI determinations from medical AI systems. Many h…
Implications of Current Litigation on the Design of AI Systems for Healthcare Delivery
Gennie Mansi, Mark Riedl
Many calls for explainable AI (XAI) systems in medicine are tied to a desire for AI accountability--accounting for, mitigating, and ultimately preventing harms from AI systems. Bec…
Legally-Informed Explainable AI
Gennie Mansi, Naveena Karusala, Mark Riedl
Explanations for artificial intelligence (AI) systems are intended to support the people who are impacted by AI systems in high-stakes decision-making environments, such as doctors…
Recognizing Lawyers as AI Creators and Intermediaries in Contestability
Gennie Mansi, Mark Riedl
Laws play a key role in the complex socio-technical system impacting contestability: they create the regulations shaping the way AI systems are designed, evaluated, and used. Despi…