Relationship-Centered Care: Relatedness and Responsible Design for Human Connections in Mental-Health Care
This addresses a critical issue for mental health care by shifting AI design from simulating to scaffolding human relationships, though it is incremental as it builds on existing frameworks like Self-Determination Theory and Responsible AI.
The paper tackles the problem that AI-powered conversational agents in mental health care, designed to optimize therapeutic alliance, may create an 'appearance of connection' that undermines human relatedness and long-term recovery. It proposes a model using Self-Determination Theory and Responsible AI to design AI that scaffolds rather than simulates relationships, aiming to strengthen patients' connections with therapists, caregivers, family, and peers.
There has been a growing research interest in Digital Therapeutic Alliance (DTA) as the field of AI-powered conversational agents are being deployed in mental health care, particularly those delivering CBT (Cognitive Behaviour Therapy). Our proposition argues that the current design paradigm which seeks to optimize the bond between a patient in need of support and an AI agent contains a subtle but consequential trap: it risks producing an "appearance of connection" that unintentionally disrupts the fundamental human need for relatedness, which potentially displaces the authentic human relationships upon which long-term psychological recovery depends. We propose a reorientation from designing artificial intelligence tools that simulate relationships to designing AI that scaffolds them. To operationalize our argument, we propose an interdisciplinary model that translates the Responsible AI Six Sphere Framework through the lens of Self-Determination Theory (SDT), with a specific focus on the basic psychological need for relatedness. The resulting model offers the technical and often clinical communities a set of relationship-centered design guidelines and relevant provocations for building AI systems that function not just as companions, but as a catalyst for strengthening a patient's entire relational ecology; their connections with therapists, caregivers, family, and peers. In doing so, we discuss a model towards a more sustainable ecosystem of relationship-centered AI in mental health care.