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AI Algorithms to Prevent Suicide Gain Traction

Posted on Wednesday, 13th December 2017 @ 09:03 PM by Text Size A | A | A

A growing number of researchers and tech companies are beginning to mine social media for warning signs of suicidal thoughts. Their efforts build on emerging evidence that the language patterns of a person’s social-media posts, as well as the subconscious ways they interact with their smartphone can hint at psychiatric trouble.

Businesses are just starting to test programs to automatically detect such signals. Mindstrong, for instance, an app developer in Palo Alto, California, is developing and testing machine-learning algorithms to correlate the language that people use and their behaviour—such as scrolling speed on smartphones—with symptoms of depression and other mental disorders. Next year, the company will expand its research to focus on behaviour associated with suicidal thoughts, which could eventually help health-care providers detect patients’ intentions to harm themselves more quickly. And in late November, Facebook announced that in much of the world, it was rolling out its own automated suicide-prevention tools. Tech giants Apple and Google are pursuing similar ventures.

Some mental-health professionals hope such tools could help reduce the number of people who attempt suicide, which is rising in the United States, where it is the second leading cause of death among people between the ages of 15 and 34. And young people are more likely to reach out for help on social media than to see a therapist or call a crisis hotline, according to social-work researcher Scottye Cash at Ohio State University in Columbus.

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