Yale NLP/LLM Interest Group Talks

This is an interest group on natural language processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas, present ongoing AI work, and discuss potential collaboration at bi-weekly meetings.

Speaker Bio

Dr. Wang is vice chair of research and assistant professor with a primary appointment in the Department of Health Informatics, and secondary appointments in the Intelligent Systems Program, Department of Biomedical Informatics at the University of Pittsburgh, Clinical and Translational Science Institute, and UPMC Hillman Cancer Center.

He is also the current Chair of the American Medical Informatics Association (AMIA) Natural Language Processing Working Group, and the NLP Lead of the National Center for Advancing Translational Sciences (NCATS) Accrual to Clinical Trails (ACT) Network. His research interest is in artificial intelligence (AI), natural language processing ( NLP), and machine learning methodologies and applications in health care.

Blurb

Generative AI, an emerging technology designed to efficiently generate valuable information, holds great promise in healthcare and medicine. As computing power becomes more accessible and the abundance of health data, such as electronic health records,electrocardiograms, and medical images, increases, it is inevitable that healthcare will be revolutionized by this technology. Recently, generative AI has garnered a lot of attention in the medical research community, leading to debates about its application in the healthcare sector,mainly due to concerns about transparency and related issues. Meanwhile, questions around the potential exacerbation of health disparities due to modeling biases have raised notable ethical concerns regarding the use of this technology in healthcare. However, the ethical principles for generative AI in healthcare have been understudied. As a result, there are no clear solutions to address ethical concerns, and decision-makers often neglect to consider the significance of ethical principles before implementing generative AI in clinical practice. In an attempt to address these issues, we propose the“GREAT PLEA” ethical principles, namely Governability, Reliability, Equity, Accountability, Traceability, Privacy,Lawfulness, Empathy, and Autonomy for generative AI in healthcare. Ultimately, we aim to proactively address the ethical dilemmas and challenges posed by the integration of generative AI into healthcare practice.