Towards Using AI to Augment Human Support in Digital Mental Healthcare

To address the need for more access to, and increase the effectiveness of, mental health treatment, internet-delivered psychotherapy programs such as iCBT are shown to achieve clinical outcomes comparable to face-to-face therapy. While offering ubiquitous access to healthcare, a key concern of digital therapy programs is to sustain users’ engagement with the treatment to attain desired benefits. Research has demonstrated that including a trained ‘human supporter’ to the digital mental health ecosystem can provide useful guidance and motivation to its users, and lead to more effective outcomes than unsupported interventions. Within this context, we describe early research that makes use of machine learning (ML) approaches to better understand how the behaviors of these human supporters may benefit the mental health outcomes of clients; and how such effects could be maximized. We discuss new opportunities for augmenting human support through personalization, and the related ethical challenges.