Can artificial intelligence replace human therapists?
Websites, smartphone apps and social-media sites are dispensing mental-health advice, often using artificial intelligence. Meanwhile, clinicians and researchers are looking to AI to help define mental illness more objectively, identify high-risk people and ensure quality of care.
Some experts believe AI can make treatment more accessible and affordable. There has long been a severe shortage of mental-health professionals, and since the Covid pandemic, the need for support is greater than ever. For instance, users can have conversations with AI-powered chatbots, allowing then to get help anytime, anywhere, often for less money than traditional therapy.
The algorithms underpinning these endeavors learn by combing through large amounts of data generated from social-media posts, smartphone data, electronic health records, therapy-session transcripts, brain scans and other sources to identify patterns that are difficult for humans to discern.
Despite the promise, there are some big concerns. The efficacy of some products is questionable, a problem only made worse by the fact that private companies don’t always share information about how their AI works. Problems about accuracy raise concerns about amplifying bad advice to people who may be vulnerable or incapable of critical thinking, as well as fears of perpetuating racial or cultural biases. Concerns also persist about private information being shared in unexpected ways or with unintended parties.
The Wall Street Journal hosted a conversation via email and Google Doc about these issues with John Torous, director of the digital-psychiatry division at Beth Israel Deaconess Medical Center and assistant professor at Harvard Medical School; Adam Miner, an instructor at the Stanford School of Medicine; and Zac Imel, professor and director of clinical training at the University of Utah and co-founder of LYSSN.io, a company using AI to evaluate psychotherapy. Here’s an edited transcript of the discussion.
WSJ:What is the most exciting way AI and machine learning are being used to diagnose mental disorders and improve treatments?
DR. MINER: AI can speed up access to appropriate services, like crisis response. The current Covid pandemic is a strong example where we see both the potential for AI to help facilitate access and triage, while also bringing up privacy and misinformation risks. This challenge—deciding which interventions and information to champion—is an issue in both pandemics and in mental-health care, where we have many different treatments for many different problems.
DR. IMEL: In the near term, I am most excited about using AI to augment or guide therapists, such as giving feedback after the session or even providing tools to support self-reflection. Passive phone-sensing apps [that run in the background on users’ phones and attempt to monitor users’ moods] could be exciting if they predict later changes in depression and suggest interventions to do something early. Also, research on remote sensing in addiction, using tools to detect when a person might be at risk of relapse and suggesting an intervention or coping skills, is exciting.
DR. TOROUS: On a research front, AI can help us unlock some of the complexities of the brain and work toward understanding these illnesses better, which can help us offer new, effective treatment. We can generate a vast amount of data about the brain from genetics, neuroimaging, cognitive assessments and now even smartphone signals. We can utilize AI to find patterns that may help us unlock why people develop mental illness, who responds best to certain treatments and who may need help immediately. Using new data combined with AI will likely help us unlock the potential of creating new personalized and even preventive treatments.
WSJ:Do you think automated programs that use AI-driven chatbots are an alternative to therapy?
