Mental Health: The Role of AI-Powered Solutions

Yet most mental health professionals have little understanding of AI or the ways in which it will affect efforts to reduce the suffering caused by poor mental health. As history teaches us, that which is poorly understood is feared or denied; but the real danger is that mental health professionals fail to engage in AI’s development, uses and limitations, only to awaken one day to find that the delivery of mental healthcare has permanently changed, seemingly without notice or consultation. In this context, AI-powered solutions have the potential to revolutionise the diagnosis and treatment of mental illness irrespective of workforce capacity and geography. In the world of mental health, diagnoses are made based on a detailed history, physical examination and – critically – the mental state examination. It is perhaps in relation to treatment, rather than diagnosis or early detection, that psychiatrists and psychologists feel they are most immune to the impact of AI. It is no surprise that there are now many apps that deliver talking treatments through ‘virtual’ interactions with therapists rather than face-to-face interactions; a meta-analysis showed that depressive symptoms improved significantly through this medium, particularly when treatments were based on cognitive behavioural therapy (CBT) models. An RCT looking at the use of an AI text-based CBT intervention for substance misuse, W-SUDS (Woebot for Substance Use Disorders), found that those engaging with W-SUDS used substances less than those on the waiting list, and that this reduction in use, unsurprisingly, also improved their general mental health, including anxiety and depression-related symptoms. Science to one side, there are plenty of other issues that need to be considered when it comes to AI in mental health.