5 Ways that AI is Changing Mental Health Care

Artificial intelligence has been getting a lot of press lately, from traffic jam-inducing, driverless cars in San Francisco to EU legislation proposing a ban on certain AI applications. Meanwhile, the COVID-19 pandemic has led to an explosion of mental health apps, many of which use AI technology.

There have even been headlines about people using Chat GPT as a substitute for therapy. While most experts agree that AI is no substitute for human care, it does have the potential to complement traditional approaches and expand access to support. Here are some ways that AI is changing the field of mental health care:

Screening and assessment:

AI-powered tools are increasingly being used to identify and evaluate mental health conditions. Natural language processing models can analyze patterns in written and spoken language to detect signs of depression, anxiety, or other disorders. In addition, AI is being used to help clinicians with differential diagnoses. Mental health apps like Ginger use AI to guide users to appropriate self-help techniques, match them with therapists, and track progress. Developers hope that these tools will help facilitate early intervention and reduce misdiagnoses, but critics worry they may overlook contextual information and individual nuances crucial to the diagnostic process.

Predictive analytics:

Mental health tech companies are also using AI to identify mental health risk factors, forecast treatment responses, and predict relapse. AI algorithms can analyze large datasets to predict which individuals may be at risk of developing mental health conditions or experiencing an increase in symptoms. AI can also analyze treatment outcome data to suggest the most effective interventions for specific demographics. Finally, predictive analytics can help identify individuals at risk of relapse. For example, wearable devices and smartphone apps can monitor sleep quality, medication adherence, and activity levels and alert patient support systems to deviations from baseline patterns of functioning. There are obvious ethical considerations regarding the disclosure of AI-generated predictive information, in addition to concerns about labeling and stigmatization.

Targeted interventions and support:

Many mental health apps use AI to generate personalized support and interventions. These interventions range from therapist chatbots to evidence-based cognitive-behavioral exercises. Some psychologists say that these apps are effective adjuncts to treatment and that they serve as gateways to more traditional therapy. However, the self-help app space remains woefully unregulated. Psychologist Stephen Schueller notes that many mental health apps lack a plan for long-term support. Schueller’s company One Mind PsyberGuide provides unbiased reviews of mental health technologies.

Virtual reality therapies:

Virtual reality (VR) is being used to provide exposure therapy for PTSD, OCD, and other anxiety disorders. These therapies use computers to generate 3D virtual environments to help patients confront emotional triggers in a safe, controlled environment. Some VR technologies integrate AI via virtual agents who respond dynamically to patients’ behaviors and emotions. AI algorithms can also be used to customize the VR environments in real-time based on patient progress, for example, by altering the intensity of the exposure. Finally, AI can analyze the facial expressions, body language, and vocal cues of patients during sessions, providing useful feedback to both therapist and patient. While these tools show promise, access to VR technology is currently limited beyond select research laboratories.

Digital therapy and counseling

Perhaps the most controversial of AI technologies, AI-based chatbots provide on-demand mental health support, typically within the context of a mobile app like the Stanford-developed Woebot. Chatbots use AI algorithms to understand and respond to user input, simulating human interaction. However, these tools are generally limited to a set number of question-and-answer combinations, much like the voice-activated telephone menus used by insurance companies. If queries get more complex, or if certain “red flag” risk factors are identified, users are routed to human therapists. So while chatbots can’t replace human therapists, they can offer accessible support to individuals in need. In fact, the UK’s National Health Service recommends the chatbot Wysa as a stop-gap for people waiting for traditional therapy.

Conclusion

While AI shows promise in the areas of mental health assessment, treatment planning, and on-demand support, more research is needed to validate and optimize these technologies. In addition, there are ethical concerns that need to be addressed– for example, ensuring confidentiality and informed consent. The self-help app industry should be monitored and regulated to make sure that best practices and ethical standards are being followed. In sum, the effective and responsible use of AI in mental health care requires the very thing that many people fear it will replace: human oversight.