• Decision Making
• Ethics- Medical
• Information Technology
• Mental Disorders

Surrogate decision-making is fraught with speculation. Amid fogs of uncertainty, surrogates must ascertain an incapacitated patient’s wishes. From this, they are entrusted to make life-altering or life-ending decisions based on limited information. This process of guesswork, however, is inevitably shaped by subjective interpretation and personal biases.

In response, artificial intelligence (AI) tools like personalised patient preference predictors (P4) have been proposed as a means to safeguard the accuracy and reliability of surrogate decision-making.1 Yet, whether AI-driven preference predictors can uphold autonomy is a point of moral contention. Proponents like Earp et al. argue that AI tools offer a more systematic, data-driven approach to inferring patient wishes, thereby upholding autonomy by mitigating the human errors of traditional surrogates. Others challenge this assumption. Annoni, for instance, argues that AI-driven preference predictors categorically fail to respect patient autonomy, asserting that autonomy cannot be merely reduced to the satisfaction of patient preferences.2

What follows is an argument for reconsideration. This paper does not contend that AI tools definitively respect autonomy, but instead draws forth novel considerations that challenge the notion of their fundamental incompatibility. To this end, I first examine the case study of AI-powered psychotherapy, in which patients demonstrate a greater willingness to disclose personal information to AI systems. Then, I explore how these insights underscore the promise of …