Zoom Registration: https://umass-amherst.zoom.us/meeting/register/VWDnTLPlTHGGmEtmUeE_7w#/registration
Abstract:
Artificial intelligence holds promise to transform care for older adults, yet today’s AI systems routinely underperform for this population due to poor data representation, limited validation, and weak alignment with lived experience. Drawing on a six-month collaboration between the SCAN Foundation, CHAI will be synthesizing evidence from literature review, expert interviews, and multi-stakeholder roundtables to surface why AI fails older adults—and what must change. They will outline practical pathways for building equitable AI, including multimodal data integration, standardized validation, local testing, and patient-centered deployment. The talk concludes with a roadmap for developing trustworthy AI that meaningfully improves outcomes for aging populations.
Biography:
- Lucy Orr-Ewing, Head of Policy & Strategy, Coalition for Health AI (CHAI)
- Lucy Orr-Ewing leads Policy and Research for CHAI, where she leads policy engagement at both the state and federal levels and oversees CHAI’s research portfolio, including projects supported by The Scan Foundation and the McGovern Foundation. Prior to CHAI, Lucy was a Harkness Fellow at Stanford Medicine and Chief of Staff of the UK’s National Health Service.