Artificial intelligence (AI) can detect loneliness with 94 per cent accuracy from a person's speech, a new scientific paper reports. Researchers in the US used several AI tools, including IBM Watson, to analyse transcripts of older adults interviewed about feelings of loneliness. By analysing words, phrases, and gaps of silence during the interviews, the AI assessed loneliness symptoms nearly as accurately as self-reports of loneliness and questionnaires completed by the participants themselves, which can be biased. The AI also revealed that lonely individuals tend to have longer responses to direct questions about loneliness, and express more sadness in their answers. 'Most studies use either a direct question of "how often do you feel lonely", which can lead to biased responses due to stigma associated with loneliness,' said senior author Ellen Lee at UC San Diego (UCSD) School of Medicine.

Researchers at the University of California and IBM have used machine learning and natural language ... [ ] processing to predict loneliness in senior citizens in San Diego County, California. Researchers have used artificial intelligence to accurately predict loneliness in residents at a senior housing community in San Diego. Publishing in the American Journal of Psychiatry, the researchers were able to harness natural language processing (NLP) and machine learning to classify the sentiment and emotions of speech. At a time when the coronavirus pandemic is forcing people to remain in social isolation, the study by researchers from the University of California, IBM and elsewhere could prove vital in helping society assess and address widespread loneliness. However, while technology is providing ever-more powerful means of identifying societal problems such as loneliness, it remains questionable as to whether such problems can be solved by tech alone.

Artificial intelligence (AI) can detect loneliness with 94 per cent accuracy from a person's speech, a new scientific paper reports. Researchers in the US used several AI tools, including IBM Watson, to analyse transcripts of older adults interviewed about feelings of loneliness. By analysing words, phrases, and gaps of silence during the interviews, the AI assessed loneliness symptoms nearly as accurately as loneliness questionnaires completed by the participants themselves, which can be biased. It revealed that lonely individuals tend to have longer responses to direct questions about loneliness, and express more sadness in their answers. 'Most studies use either a direct question of "how often do you feel lonely", which can lead to biased responses due to stigma associated with loneliness,' said senior author Ellen Lee at UC San Diego (UCSD) School of Medicine.

Artificial intelligence (AI) can detect loneliness with 94 per cent accuracy from a person's speech, a new scientific paper reports. Researchers in the US used several AI tools, including IBM Watson, to analyse transcripts of older adults interviewed about feelings of loneliness. By analysing words, phrases, and gaps of silence during the interviews, the AI assessed loneliness symptoms nearly as accurately as loneliness questionnaires completed by the participants themselves, which can be biased. It revealed that lonely individuals tend to have longer responses to direct questions about loneliness, and express more sadness in their answers. 'Most studies use either a direct question of "how often do you feel lonely", which can lead to biased responses due to stigma associated with loneliness,' said senior author Ellen Lee at UC San Diego (UCSD) School of Medicine.