Policy Series: Technology in Aging: Artificial Intelligence

Thursday, November 14, 2024

10:00 AM – 11:30 AM PST

Location: Room 211

CE: 1.5

Chair(s)

Angela Perone, PhD, JD, MSW, MA (she/her/hers)

Assistant Professor and Director
School of Social Welfare / Center for Advanced Study of Aging Services
University of California Berkeley
Berkeley, California, United States

Discussant(s)

BL

Brian Lindberg, Master of Management of Human Services (he/him/his)

Public Policy Advisor
Policy & Professional Affairs
Gerontological Society of America
Washington, District of Columbia, United States

Panelist(s)

M. Aaron Guest, PhD, MPH, MSW (he/him/his)

Assistant Professor of Aging
Center for Innovation in Healthy and Resilient Aging
Arizona State University
Phoenix, Arizona, United States
Abigail Stephan, Ph.D., CFLE (she/her/hers)

Research Assistant Professor
Psychology, Institute for Engaged Aging
Clemson University
Clemson, South Carolina, United States
PA

Peter Abadir, MD

Associate Professor of Medicine
Geriatric Medicine and Gerontology
Johns Hopkins University
Baltimore, Maryland, United States
ZH

Zachary Hass, PhD

Associate Professor
Nursing and Industrial Engineering
Purdue University
West Lafayette, Indiana, United States
Bo Xie, PhD, FGSA

Professor
School of Nursing
The University of Texas Austin
Austin, Texas, United States
NB

Nancy Berlinger, PhD (she/her/hers)

Senior Research Scholar
Research
The Hastings Center
Garrison, New York, United States

Artificial Intelligence (AI) is increasingly being used in aging research and gerontological education to analyze vast amounts of data and identify patterns that may offer insights into aging across the life course. By utilizing AI algorithms, researchers, practitioners, and educators can more efficiently study factors such as genetics, lifestyle, and social and environmental influences that contribute to aging. Machine learning techniques may also help predict the onset of age-related diseases and potential interventions. The incorporation of AI in aging research and gerontological education has the potential to revolutionize our understanding of aging and improve the quality of life for older people. Yet, it is not without ethical dilemmas that have sparked increased policy focus in recent months. This interactive session, organized by the GSA Public Policy Advisory Panel, is an interdisciplinary discussion addressing the use of AI in aging research and gerontological education and the related public policy implications. The panelists represent the six sections of GSA: ESPO, BS, BSS, SRPP, HS, and AGHE, along with the Minority Issues in Aging Advisory Panel and the Humanities, Arts, and Culture Gerontology Advisory Panel.

Learning Objectives:

Understand the potential applications of AI in aging research and gerontological education, including its ability to analyze large datasets and identify patterns to enhance understandings of genetics, lifestyle, and social and environmental influences that contribute to aging.
Learn about current challenges and limitations of using AI in aging research and gerontological education within GSA’s sections and academies, such as data privacy and security concerns, issues of equity and representation, and complexities of ongoing validation and interpretation of AI-generated findings.
Explore case studies and real-world examples across the six sections of how AI is being used to advance aging research and gerontological education and discuss the ethical implications and considerations that researchers and educators must keep in mind when utilizing AI technologies in their aging-related fields.