Program Schedule

Artificial Intelligence (AI) has the potential to improve healthcare outcomes, yet AI technologies can also present risks. Bias in AI, defined as “unfair systematic error”, or more specifically, “the inclination or prejudice of a decision made by an AI system which is for or against one person or group, especially in a way considered to be unfair” is a topic of vital importance in both the informatics and ethics communities. This workshop will focus on several major facets of mitigating AI risks. A panel discussion will feature presentations from experts from the legal, machine learning, statistics, and medical domains. A poster session with lightning talks will further inform the topic. Subgroup discussions will add attendee input to salient issues of law, policy, clinical practice, data management, and AI transparency. A concluding session will summarize workshop takeaways and chart a path for going forward.