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Unveiling Disparities: A Data-Driven Exploration of African-American Health Experiences

April 2 @ 2:00 pm 3:00 pm

Part of the Planning Workshop #1

Jamell Dacon, Ph.D.
Assistant Professor, Dept. of Computer Science
Morgan State University

Abstract:  In the United States, African-Americans exhibit disproportionately higher incidence of, and mortality from, pervasive health disparities including but not limited to hypertension, di- abetes, cardiovascular disease (CVD), Cerebrovascular accident (CVA) compared to other racial and ethnic groups. In this proposal, we propose to substantiate key drivers of health dis- parities among African-Americans. To do so, we will (1) investigate healthcare assumptions including misdiagnoses and late diagnoses, and incidence of, and mortality rates, (2) exam- ine (i) environmental risks, (ii) racial attitudes, (iii) health insurance coverage, (iv) geographic agents and (v) underlying conditions, and (3) determine multifaceted (i.e., systemic, environ- mental, and socio-cultural) factors exacerbating health inequities. By leveraging both cutting-edge AI-related and data analysis tools, and methodologies our research aims to identify trends and patterns to provide a nuanced understanding of these pervasive health disparities and in- form evidence-based interventions and policies. We hope our contributions can provide actionable insights for emerging researchers, policymakers, healthcare professionals, non-profit organizations and communities, and lead to improved health outcomes for the African-American community. 

Bio: Dr. Jamell Dacon (he/him) is an Assistant Professor in the Department of Computer Science at Morgan State University as of September 2023, the Principal Investigator of the Machine Intelligence and Data Science Lab and founder of a non-profit organization called the Institute of Interdisciplinary Data Science Research (soon to be launched). Dr. Dacon is also a Research Affiliate Faculty member of both the Center for Equitable Artificial Intelligence and Machine Learning Systems (CEAMLS) and Trustworthy AI in Law & Society (TRAILS) Institute, where he recently was awarded an ONR Summer Faculty Research Program (SFRP) Award. He earned his Ph.D. degree in Computer Science from Michigan State University (MSU) in 2023, where he was supported by both an MSU University Enrichment Fellowship (UEF) and an NSF GRFP. His current research spans the areas of Trustworthy AI, Natural Language Processing, Computational Social Science, and Interdisciplinary Data Science. Specifically, he focuses on implementing empirical methods to conceptualize, examine, and mitigate socioethical implications (e.g., bias, stereotypes, and representational harms) of innovative AI technology by highlighting its negative social impacts.