Now Stevens artificial intelligence expert K.P. “Suba” Subbalakshmi — working with IBM, the University of California San Diego and China’s Jiangnan University — has developed an AI-based system that predicts loneliness in older adults from personal interviews. The technology may help us better understand the roots of people’s alienation, too.

The team surveyed about 100 residents of a continuing-care senior housing community ranging in age from 66 to 101. Their states of mind were assessed in two ways: through personal interviews with a trained psychiatrist and by using the UCLA Loneliness scale, a self-reporting questionnaire. Next the team transcribed audio of the interviews and fed the transcripts, along with the questionnaire data, into a specially designed AI model that quickly “learned” to tell the linguistic differences in responses between lonely and non-lonely people and then to offer predictions. Presented with interview transcripts and no other context, the AI proved 89% accurate at correctly classifying whether people would report feeling lonely or not.

That’s not all. Certain components of the new AI helped the researchers better understand the nuances of participants’ answers. These layers and portions of the algorithmic system, known as explainable AI (XAI), reported back on which sections of each interview were most important in the AI’s final predictions about whether a person felt lonely or not.

XAI revealed, for instance, that an increased use of emotional adjectives and verbs in verbal responses to the interviewers tended to indicate a person felt lonely — as did increased references to religion, and highly analytical responses. An increased use of personal pronouns also seemed to point to loneliness.

“XAI can play a crucial role not only in identifying individuals at risk of loneliness, but also in understanding the loneliness itself,” says Subbalakshmi.

That’s important, she says, since it’s now believed there are various subtypes of loneliness that require personalized interventions.

“Loneliness caused by actual social isolation might be remedied by building more and stronger social connections,” Subbalakshmi suggests. “But loneliness experienced by a person surrounded by friends and family could stem from a different cause, requiring a different intervention.”

This proof-of-concept study, she continues, indicates XAI can help professionals separate out and elevate the important clues and cues in conversations with older adults in order to better help them recover emotional wellness.

The study, supported by both IBM Research and the National Institutes of Health, was reported in Psychiatry Research.

– Paul Karr