Predicting who is likely to attempt suicide is difficult even for the most highly trained human experts, says Dr. Jordan Smoller, co-director of Mass General Brigham and Harvard University’s Center for Suicide Research and Prevention. There are risk factors that clinicians know to look for in their patients—certain psychiatric diagnoses, going through a traumatic event, losing a loved one to suicide—but suicide is “very complex and heterogeneous,” Smoller says. “There’s a lot of variability in what leads up to self-harm,” and there’s almost never a single trigger.
The hope is that AI, with its ability to sift through massive amounts of data, could pick up on trends in speech and writing that humans would never notice, Smoller says. And there is science to back up that hope.
Read more HERE about how researchers hope to use big data and AT to identify those most at risk for suicide. This will be one of the central projects of the newly formed Center for Suicide Research and Prevention.
AI Is Turning Social Media Into the Next Frontier for Suicide Prevention (TIME)
