The big promise AI holds for mental health

Artificial intelligence is creeping into mental health services. “How does it make you feel to hear that?” is the question that you might be already discussing with an AI bot. Even more, your AI therapist might be quite successful at helping you overcome any feeling of worry or depression about a direction our future can take with the rise of AI. If looking beyond the scary headlines about Skynet coming true, an increasing use of AI for mental health care is actually great news for many of us. Today, we are experiencing a severe mental health crisis aggravated by the COVID-19 pandemic. Called the plague of modernity, mental health disorders affect one-fifths of people in the US, with 40% of Americans developing symptoms of anxiety or depression or both last year due to the fear of illness, self-isolation, grief, or deepening financial concerns. The landscape around this crisis is no less daunting. Its longtime hallmarks have been the societal stigma around mental illness and an acute shortage of mental health professionals. AI is already disrupting major industries, from healthcare to education, addressing challenges and opening thrilling opportunities. AI for mental health may well be the next hot topic. Thanks to rapid technological advances, AI solutions for healthcare have all the potential to spearhead a positive change in this space that has been long ripe for innovation.

Mental health disorders are among the leading causes of morbidity and mortality, expected to cost the world’s economy some $16 trillion by 2030. They affect at least 10% of the population, with up to 20% of children and adolescents suffering from some type of mental disorder and women more likely than men to be diagnosed with depression. In the US, around 19% of people experienced a mental illness in 2017-18, which was a year-on-year increase of 1.5 million people. The number of the young reporting mental distress is rising more significantly. No one seems to know exactly why depression and anxiety are so common nowadays. Many experts even dismiss any upswing, arguing that what we see is a surge of people actively seeking treatment. Indeed, the number of people applying for help with depression or anxiety in the US has soared, according to the 2021 State of Mental Health in America report. As many as 315,220 people took anxiety tests in January to September 2020, 93% up from the entire 2019. The number of people taking depression screens increased by 62% to 534,784 people. At the same time, only around 40% of US adults with mental illness received treatment in 2019. One of the reasons is a shortage of mental health providers, which the US National Council for Behavioral Health predicts can reach over 15,000 clinicians in the next couple of years. The need for solutions that can scale access to mental health treatment is desperate, while such solutions are already here, thanks to AI.

Unlike medical areas such as radiology or pathology where AI can outperform doctors, mental health care delivery is thought by many as an exclusively human field where emotional intelligence is essential. Most mental health practitioners doubt that artificial intelligence solutions for mental health will ever be able to provide emphatic care. While clinicians may be overwhelmingly skeptical about the use of AI for mental health care, people emotionally connect to technology because they tend to treat robots as living beings, researchers say. We are not talking here about the unsettling intimate bond developed between a lonely man and an AI operating system in the movie Her, but rather about people’s willingness to pour their hearts out anonymously to an AI bot companion, as found out by creators of Eliza, one of the first chatbots designed in the 1960s. Moreover, people do prefer to talk to robots. Only 18% would favor humans over technology to discuss their mental health struggles compared to 68% who would choose robots, according to a recent study conducted by Oracle and Workplace Intelligence. People tend to believe that robots don’t judge, are unbiased, and can provide an instant answer to a health-related question. Just as important, talking to technology helps. Multiple meta-analyses have confirmed that computer-aided cognitive behavioral therapy (CBT) delivered via desktop or mobile apps is equivalent to or even more effective than standard CBT. The National Institute for Health and Clinical Excellence (NICE) in England first recommended computerized CBT packages for depression, panic, and phobias back in 2006 on the grounds of clinical and cost effectiveness.” In the US, the COVID-19 pandemic has prompted the Food and Drug Administration (FDA) to relax policies for a broader use of digital therapeutic tools to treat mental conditions. Particularly important to mental health services are the following AI technologies:

Currently, the applications of artificial intelligence for mental health revolve around:

The current success of artificial intelligence apps and platforms for mental health care can be attributed to the following benefits:

According to a recent report, funding in digital mental health increased from $1,136 million year on year to $1,974 million globally in 2020, with mental health seeing an all-time record number of mentions in the news in March 2021. AI-powered mental health care also sees record levels of venture capital funding. Amid the crisis, researchers have made a few big steps forward in the development of AI for mental health which may be a hint of what lies ahead for us in the very near future. We are likely to see the emergence of more AI therapists like Ellie and new mental health applications driven by AI prediction and detection capabilities. For instance, researchers at Vanderbilt University Medical Center in Tennessee, US, have developed an ML algorithm that uses a person’s hospital admission data, including age, gender, and past medical diagnoses, to make an 80% accurate prediction of whether this individual is likely to take their own life. University of Florida researchers are about to test their new AI platform aimed at making accurate diagnosis in patients with early Parkinson’s disease. Another team of researchers are working on an AI tool to predict schizophrenia based on analysis of brain scans. Research is also underway to develop a tool combining explainable AI and deep learning to prescribe personalized treatment plans for children with schizophrenia. So, it looks like we have the most promising technologies today to overcome the crisis and transform the delivery of mental health care.

AI holds both incredible promises and many next-level complexities, including an array of ethical pitfalls. Like with many healthcare apps, innovators may need to be compliant with the GDPR, HIPAA, and other industry-specific guidelines. But there’s much more to that with artificial intelligence. Creators of AI technology for mental health should be wary of AI challenges, including bias that may come with insufficient and poor quality databases, increased risk to patient privacy and data security, a lack of guidance on the development of AI tools, calls for greater transparency over the use of algorithms and their decision-making logic, complexities with integration into clinical practice, and the need to train mental health professionals in emerging technologies. Scaling access to mental health services is critical, but it should be scaled ethically not to lead to increased risk to patients.