Healthcare AI and the Limits of Accountability
As artificial intelligence becomes embedded in clinical care and healthcare operations, accountability is increasingly distributed across clinicians, vendors, technology teams, and organizational leadership. When an AI influenced decision causes harm, organizations may struggle to establish who was responsible, what safeguards were in place, and whether those safeguards worked. Drawing on real world cases, this session examines the operational and governance failures that create clinical, regulatory, and legal exposure. Participants explore how to establish clear ownership, strengthen oversight, and maintain the evidence necessary to demonstrate responsible decision making.
Audience
Healthcare executives and boards, physician leaders, legal counsel, compliance and risk management professionals, patient safety leaders, technology executives, and AI governance teams.
Audience takeaways
- Identify accountability gaps throughout the AI lifecycle, including validation, deployment, monitoring, and incident response.
- Establish clearer decision rights and oversight responsibilities across clinical, legal, compliance, technology, and vendor teams.
- Apply a practical AI defensibility assessment to evaluate whether their organization can reconstruct and substantiate an AI influenced decision.
Formats and durations
Keynote (45 to 60 minutes), conference session (60 minutes), executive workshop (90 to 120 minutes), or moderated panel (45 to 60 minutes).
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