Presentation
Human Factors and Generative AI: Designing for the Next Generation
DescriptionThe rise of generative AI represents a paradigm shift in how we interact with technology. As with many innovations, advancements in consumer technology are beginning to influence health technologies as well, and human factors practitioners need to be ready for this change. Traditional human factors and user research methods, focused on deterministic systems and user interfaces, are insufficient for understanding and shaping usability, safety, and user experiences in the realm of probabilistic models.
Researchers and human factors practitioners can struggle to effectively influence the development of generative AI models because we're accustomed to providing concrete recommendations for design improvements and risk mitigations. However, generative AI requires a different approach. Without a clear understanding of how these models are built and trained, our feedback can be too general or too granular to be actionable for engineers, designers, researchers, or other partners involved in model development. This leads to a disconnect between research findings and model improvements, hindering our ability to advocate for users. This talk addresses this urgent need by providing researchers and practitioners with the tools and knowledge to navigate this new landscape.
This talk aims to bridge this gap by equipping attendees with a foundational understanding of generative AI, its unique challenges and opportunities for human factors, and practical strategies for conducting impactful research. We will explore adapted user research methods, novel evaluation frameworks, and effective communication strategies to ensure that human factors considerations are central to the development and deployment of generative AI in healthcare. By embracing these new tools and perspectives, we can ensure that this transformative technology is harnessed safely and effectively to improve and enhance experiences in health.
Researchers and human factors practitioners can struggle to effectively influence the development of generative AI models because we're accustomed to providing concrete recommendations for design improvements and risk mitigations. However, generative AI requires a different approach. Without a clear understanding of how these models are built and trained, our feedback can be too general or too granular to be actionable for engineers, designers, researchers, or other partners involved in model development. This leads to a disconnect between research findings and model improvements, hindering our ability to advocate for users. This talk addresses this urgent need by providing researchers and practitioners with the tools and knowledge to navigate this new landscape.
This talk aims to bridge this gap by equipping attendees with a foundational understanding of generative AI, its unique challenges and opportunities for human factors, and practical strategies for conducting impactful research. We will explore adapted user research methods, novel evaluation frameworks, and effective communication strategies to ensure that human factors considerations are central to the development and deployment of generative AI in healthcare. By embracing these new tools and perspectives, we can ensure that this transformative technology is harnessed safely and effectively to improve and enhance experiences in health.
Event Type
Oral Presentations
TimeMonday, March 3110:30am - 11:00am EDT
LocationPier 2/3
Digital Health (DH)