Policy Brief - Toward Responsible Development and Evaluation of LLMs in Psychotherapy

Policy Brief | Toward Responsible Development and Evaluation of LLMs in Psychotherapy
 

Executive Summary

There is growing enthusiasm about the potential of OpenAI’s GPT-4, Google’s Gemini, Anthropic’s Claude, and other large language models (LLMs) to support, augment, and even fully automate psychotherapy. By serving as conversational agents, LLMs could help address the shortage of mental healthcare services, problems with individual access to care, and other challenges. In fact, behavioral healthcare specialists are beginning to use LLMs for tasks such as note-taking, while consumers are already conversing with LLM-powered therapy chatbots.

However, psychotherapy is a uniquely complex, high-stakes domain. Responsible and evidence-based therapy requires nuanced expertise. While the stakes involved with using an LLM for productivity purposes may be failing to maximize efficiency, in behavioral healthcare, the stakes may include the improper handling of suicide risk.

Our paper, “Large Language Models Could Change the Future of Behavioral Healthcare,” provides a road map for the responsible application of clinical LLMs in psychotherapy. We provide an overview of the current landscape of clinical LLM applications and analyze the different stages of integration into psychotherapy. We discuss the risks of these LLM applications and offer recommendations for guiding their responsible development.

In a more recent paper, “Readiness for AI Deployment and Implementation (READI): A Proposed Framework for the Evaluation of AI-Mental Health Applications,” we build on our prior work and propose a new framework for evaluating whether AI mental health applications are ready for clinical deployment.

This work underscores the need for policymakers to understand the nuances of how LLMs are already, or could soon be, integrated in psychotherapy environments as researchers and industry race to develop AI mental health applications. Policymakers have the opportunity and responsibility to ensure that the field evaluates these innovations carefully, taking into consideration their potential limitations, ethical considerations, and risks.