Advancing Healthcare Equity through AI/ML Innovation: Duke hosts FAIR HEALTH Workshop on Algorithmic Bias in Healthcare
Monday, January 8, 2024: Duke University recently hosted the Fostering AI/ML Research for Health Equity and Learning Transformation (FAIR HEALTH) Workshop at the Kirby Horton Hall in the scenic Sarah P. Duke Gardens in Durham, NC. This inclusive event was designed for individuals passionate about advancing healthcare through innovation while emphasizing equity and fairness in clinical algorithms. Attendees, including faculty, staff, and students, comprised a diverse audience committed to shaping the future of healthcare technology.
The FAIR HEALTH Workshop focused on the pressing issue of algorithmic bias in clinical decision-making, offering participants valuable insights and strategies to identify, evaluate, and mitigate biases in healthcare algorithms. With AI and machine learning playing increasingly pivotal roles, the imperative was to ensure these technologies don’t inadvertently perpetuate biases, promoting unequal treatment.
A distinguished panel of experts, featuring Duke AI Health’s Michael Cary, PhD, RN, Sophia Bessias, MPH, MSA, and Ben Goldstein, PhD, and Duke-Margolis Center for Health Policy’s Christina Silcox, PhD, led discussions into the legal and ethical dimensions surrounding the implementation of clinical algorithms. The panelists offered practical strategies applicable across the entire development lifecycle. Their aim extended beyond raising awareness about the challenges posed by algorithmic bias; they sought to equip attendees with the tools needed to effectively address these challenges.
The workshop’s contributions were pivotal, illuminating a path for advancing healthcare equity through innovative AI and machine learning solutions that enhance patient care while minimizing bias and prioritizing equity.
Another distinctive element of the FAIR HEALTH Workshop was its interactive nature. Organizers seamlessly integrated a combination of lectures and an engaging case study discussion to foster active participation. The case study honed in on a clinical prediction algorithm deployed at Duke Health, allowing participants to apply their bias-probing skills in a real-world scenario.
The panelists underscored the importance of considering legal and ethical implications in the development and deployment of clinical algorithms. The complex regulations surrounding AI in healthcare were demystified, providing clear guidance to participants. This knowledge is pivotal in navigating the evolving landscape of healthcare technology, ensuring that ethical considerations stand at the forefront of AI integration.
Attendee feedback underscored the success of the workshop, receiving a stellar rating of over 4.5 out of 5. The interactive discussions and practical examples emerged as key components that significantly enhanced the understanding of how biases can infiltrate clinical AI tools. Participants expressed gratitude for the opportunity to hone their skills in assessing data reliability and reducing bias, crucial elements for preventing AI systems from inadvertently favoring certain patient groups.
The FAIR HEALTH Workshop at Duke University marked a substantial stride in ongoing efforts to ensure fairness in AI used in patient care. The event successfully brought together a diverse group of professionals, fostering collaboration across disciplines, including clinicians, clinician scientists, social scientists, and technical experts. As AI integration in healthcare continues to burgeon, the commitment to its ethical application extends beyond professional boundaries, becoming a community responsibility.