Understanding the Impact of Physicians' Legal Considerations on XAI Systems
Gennie Mansi, Mark Riedl

TL;DR
This paper explores how physicians' legal concerns influence the design of explainable AI systems in healthcare, emphasizing the need for contextual information to support legal risk mitigation.
Contribution
It provides insights from physician interviews on legal concerns and proposes design implications for XAI systems to address these issues.
Findings
Physicians anticipate risks and legal concerns with AI in patient care.
Legal risk mitigation strategies may change with new AI systems.
Designs should include contextual information to support legal risk management.
Abstract
Physicians are--and feel--ethically, professionally, and legally responsible for patient outcomes, buffering patients from harmful AI determinations from medical AI systems. Many have called for explainable AI (XAI) systems to help physicians incorporate medical AI recommendations into their workflows in a way that reduces the potential of harms to patients. While prior work has demonstrated how physicians' legal concerns impact their medical decision making, little work has explored how XAI systems should be designed in light of these concerns. In this study, we conducted interviews with 10 physicians to understand where and how they anticipate errors that may occur with a medical AI system and how these anticipated errors connect to their legal concerns. In our study, physicians anticipated risks associated with using an AI system for patient care, but voiced unknowns around how their…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBig Data and Business Intelligence · Electronic Health Records Systems
