We’ve already discussed how AI and mobile devices can be a powerful combination to remotely diagnose and monitor mental health conditions. The emerging digital biomarkers that can detect mood based on voice, activity and interaction with smart devices will be vital for the better diagnosis and management of mental health. It turns out that this same combination can also be effective in treating mental health issues.
The high costs of mental health therapy and the appeal of round-the-clock availability is giving rise to a new era of AI-based mental health bots. Digital therapeutic companies are using AI to diagnose and treat neuropsychiatric disorders. Patient-facing apps provide healthcare providers with real-time tracking of cognition and mood and also offers CBT.
Mental health is a spectrum, with high variability in symptoms and subjectivity in analysis. But our brains are wired to believe we’re interacting with a human when chatting with bots, and this can be powerful when providing the companionship and guidance that the current healthcare system could never offer. This on-demand support for the large number of patients suffering from mental health conditions isn’t possible at present due to resource shortages and a lack of providers.
During a time where healthcare providers face unprecedented demand, internet-based CBT provides accessible, effective, clinically-proven support for people with mild to moderate symptoms. This in turn alleviates wait times, frees up capacity and addresses other potential barriers to care such as stigma and transportation issues. In a randomized controlled trial, published in Nature’s npj Digital Medicine, internet-based CBT programs were both effective and potentially cost-effective in treating depression and anxiety.
Emotional AI is the attempt to use AI to recognize and respond to emotion, and it’s not a new concept. The idea is largely associated with American scholar and inventor Rosalind Picard and her early research on the topic, which is also known as affective computing and is defined as “computing that relates to, arises from or deliberately influences emotions”. Today, the $87 billion global market for affective computing has far-reaching potential, and interest in the space has been gradually building. Machines employing emotional artificial intelligence attempt to interpret human emotion from text, voice patterns, facial expressions and other non-verbal cues. In many cases, they’ll simulate those emotions in response. By tapping into unspoken behaviors and reactions, AI can leverage this “emotional data” to increase gains and better cater to patients. This can be an important aspect of addressing the growing mental health crisis.
