Before the Silence: Oluwatimileyin Aborisade on Using AI to Identify Social Isolation in later life

Sociologist and Ph.D. researcher Oluwatimileyin Aborisade is developing a new approach to studying social isolation in older adults, which is one of the most invisible but serious public health issues which is more prominent in later life.

In an interview, Aborisade described how his research integrates medical sociology, life course theory, and AI-assisted analysis to detect patterns of social isolation before they lead to severe physical health and mental health outcomes.

According to Aborisade: “Social isolation is not simply a problem of loneliness. It is a quantifiable social phenomenon with serious implications for health, mortality, and quality of life.” “What my research aims to do is shift from responding to isolation only after it has caused harm, to predicting it early enough to act.”

Aborisade, who is completing his Ph.D. in Sociology at Case Western Reserve University, said that his research aims to leverage qualitative research interviews, institutional data, and AI-assisted analysis to monitor for signs of social isolation in the aging population, including decreased social engagement, life course disruption, and the cumulative effects of social disadvantage.

In his view, “AI technologies, when harnessed for good, can aid us in detecting nuanced cues that may have gone unnoticed through conventional means like surveys.” “When older adults report their experiences with daily routines, family life, or community life, AI-assisted qualitative analysis enables us to uncover broader trends from thousands of lived experiences without losing sight of individual voices.”

“Predicting social isolation is not about surveillance; it’s about prevention and care,” he said. “If we can predict it earlier, we can create interventions to support dignity, independence, and social connection rather than crisis management.”

His study is also intended to be policy-focused, according to Aborisade, who cites her experience as an editorial assistant for the ‘Journal of Elder Policies’ and her research on quality of life for seniors. He added that the findings are intended to guide evidence-based interventions and aging-related policy decisions.

He also pointed out that the initial application of her research indicates that the integration of AI-assisted qualitative analysis into the policy framework for aging could greatly enhance the targeting of social services, especially for marginalized and immigrant seniors who are normally not accounted for in traditional data systems.

Asked about the guiding principles behind his work, Aborisade emphasized “Our aim is equity,”. “Aging well should not depend on income, race, immigration status, or family composition. Technology should assist us in identifying who is left behind, not increase existing inequalities.”

“At its best, AI does not substitute for human understanding,” Aborisade said. “It enhances our capacity to listen at scale so that we can design social systems that are more responsive, inclusive, and humane.”

He emphasized that his research is part of a larger trend in the sociology of aging and Life course to move toward mixed-methods, community-based research that seeks to balance innovation with responsibility.

Experts point out that Aborisade’s research is part of an emerging front in the study of aging, one that combines cutting-edge analytical techniques with profound sociological knowledge, which holds out new possibilities for enhancing the quality of life in older age.