This morning, my wellness coach reminded me to savor each exciting moment in my day, but to always take time to rest and recharge. It's good advice--good enough that I would believe it came from a human, instead of an artificial intelligence algorithm anthropomorphized as a cartoon panda. Each day, I can use Earkick to describe my mood through writing, voice note, or video. Roughly 20 seconds later, its algorithm has analyzed my statement for signs of anxiety and spit out a personalized, conversational recommendation for how I can feel my best. Earkick is one of a small army of chatbots, Woebot perhaps best-known among them, that promise to use the power of AI to support mental wellness.

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The U.S. is experiencing a chronic shortage of medical professionals. Of course, this includes physicians. But psychiatrists will also be in scant supply. In five years, the U.S.'s supply of psychiatrists will be 15,600 short of the demand from patients, according to a 2017 study from the National Council for Behavioral Health. Although the technology is relatively new, AI applications have already been implemented in medical settings to help diagnose diseases, clarify treatment plans, and study radiology images.

Researchers from the University of Colorado at Boulder are working to apply machine learning to psychiatry, with a speech-based mobile app that can categorize a patient's mental health status as well as or better than a human can. "We are not in any way trying to replace clinicians. But we do believe we can create tools that will allow them to better monitor their patients," Thanks to advances in artificial intelligence, computers can now assist doctors in diagnosing disease and help monitor patient vital signs from hundreds of miles away. Nearly one in five U.S. adults lives with a mental illness, many in remote areas where access to psychiatrists or psychologists is scarce. Others can't afford to see a clinician frequently, don't have time, or can't get in to see one.

Thanks to advances in artificial intelligence, computers can now assist doctors in diagnosing disease and help monitor patient vital signs from hundreds of miles away. Now, CU Boulder researchers are working to apply machine learning to psychiatry, with a speech-based mobile app that can categorize a patient's mental health status as well as or better than a human can. "We are not in any way trying to replace clinicians," says Peter Foltz, a research professor at the Institute of Cognitive Science and co-author of a new paper in Schizophrenia Bulletin that lays out the promise and potential pitfalls of AI in psychiatry. "But we do believe we can create tools that will allow them to better monitor their patients." Nearly one in five U.S. adults lives with a mental illness, many in remote areas where access to psychiatrists or psychologists is scarce.

Five years from now, the U.S.' already overburdened mental health system may be short as many as 15,600 psychiatrists as the growth in demand for their services outpaces supply, according to a 2017 report from the National Council for Behavioral Health. But some proponents say that, by then, an unlikely tool--artificial intelligence--may be ready to help mental health practitioners mitigate the impact of the deficit. Medicine is already a fruitful area for artificial intelligence; it has shown promise in diagnosing disease, interpreting images and zeroing in on treatment plans. Though psychiatry is in many ways a uniquely human field, requiring emotional intelligence and perception that computers can't simulate, even here, experts say, AI could have an impact. The field, they argue, could benefit from artificial intelligence's ability to analyze data and pick up on patterns and warning signs so subtle humans might never notice them.

Five years from now, the U.S.' already overburdened mental health system may be short as many as 15,600 psychiatrists as the growth in demand for their services outpaces supply, according to a 2017 report from the National Council for Behavioral Health. But some proponents say that, by then, an unlikely tool--artificial intelligence--may be ready to help mental health practitioners mitigate the impact of the deficit. Medicine is already a fruitful area for artificial intelligence; it has shown promise in diagnosing disease, interpreting images and zeroing in on treatment plans. Though psychiatry is in many ways a uniquely human field, requiring emotional intelligence and perception that computers can't simulate, even here, experts say, AI could have an impact. The field, they argue, could benefit from artificial intelligence's ability to analyze data and pick up on patterns and warning signs so subtle humans might never notice them.

A team of researchers from the University of Colorado Boulder are working to apply machine learning artificial intelligence (AI) in psychiatry, with a speech-based mobile app that can categorise a patient's mental health status as well as, or better than, a human can. The university research paper has been published in Schizophrenia Bulletin, and lays out the promise and potential pitfalls of AI in psychiatry. Peter Foltz, a research professor at the Institute of Cognitive Science and co-author of the paper, said: "We are not in any way trying to replace clinicians, but we do believe we can create tools that will allow them to better monitor their patients." In Europe, the WHO estimated that 44.3 million people suffer with depression and 37.3 million suffer with anxiety. Diagnosis of mental health disorders are based on an age-old method that can be subjective and unreliable, notes paper co-author Brita Elvevåg, a cognitive neuroscientist at the University of Tromsø, Norway.

Scientists are now working to apply artificial intelligence (AI) to psychiatry, with a speech-based mobile app that can categorise a patient's mental health status as well as or better than a human can. "We are not in any way trying to replace clinicians," said Peter Foltz, research professor at the Institute of Cognitive Science at University of Colorado at Boulder. "But we do believe we can create tools that will allow them to better monitor their patients," he added in a paper published in Schizophrenia Bulletin. Even when a patient does make it in for an occasional visit, therapists base their diagnosis and treatment plan largely on listening to a patient talk – an age-old method that can be subjective and unreliable, notes paper co-author Brita Elvevåg, a cognitive neuroscientist at the University of Tromsø, Norway. They can get distracted and sometimes miss out on subtle speech cues and warning signs.

They've developed an app that could change the way clinicians diagnose mental illness. Whether you're scrolling Facebook or talking to Siri, you're already interacting with artificial intelligence or AI – smart machines that learn through analyzing data. "AI has the potential to learn a lot of things that humans aren't able to learn," said CU graduate student Chelsea Chandler. Chandler is part of a team using AI to tackle a much heavier subject. "We can collect data about their mental state," said CU Research Professor Peter Foltz.