Problem
Research questions and friction points this paper is trying to address.
medical AI
legal risk
regulatory uncertainty
AI governance
interdisciplinary collaboration
Drawing Out Legal Risks: Co-Designing with Lawyers to Predict and Manage Legal Uncertainties of Medical AI Tools
🤖 AI Summary
This study addresses the challenge posed by the high adaptability of medical AI systems, which renders legal risks difficult to anticipate, compounded by the general lack of technical understanding among legal professionals despite their legal expertise—limiting their capacity to effectively guide AI development and deployment. To bridge this gap, the project innovatively integrates lawyers into the governance process of medical AI through a two-year interdisciplinary co-design initiative. Combining participatory workshops with customized visualization techniques, the work constructs a practical bridge between legal judgment and AI practice. The resulting outputs include an actionable suite of visualization tools and a systematic risk management framework, significantly enhancing organizations’ ability to identify, anticipate, and respond to legal uncertainties associated with medical AI.
📝 Abstract
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 organizations are able to predict and manage risk based on existing laws and regulations. Lawyers are trained to identify potential legal outcomes, but they lack technical AI knowledge, making it difficult to translate their expertise to creators and users of AI tools. We contribute insights from our co-design process with U.S. lawyers to identify and translate ways to predict and manage risks of medical AI tools. We present the visualizations we developed through two years of cross-disciplinary efforts and thereby illustrate our findings about how legal risks are determined and our strategies for people and organizations to predict and manage these risks. We offer insights about leveraging lawyers' expertise to understand, predict, and manage legal risks.
Innovation
Methods, ideas, or system contributions that make the work stand out.
co-design
legal risk
medical AI
visualization
interdisciplinary collaboration
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