The hard problem of AI therapy

The Best of Science Blogging The hard problem of AI therapy Why even 'perfect' AI therapy may be structurally doomed (author: Josh Lipson) Seeds of Science Oct 28, 2026 17 1 4 Share Josh Lipson, PhD, is a clinical psychologist, psychedelic researcher, and multidisciplinary scholar, completing a postdoctoral fellowship at the Emory Center for Psychedelics and Spirituality. His recently launched psychotherapy practice can be found at drjoshlipson.com, and he writes on a variety of topics at Whitmanic. Things have an end, but feeling is infinite: we’re changing, but it’s alright, and everything is finite. — David Byrne One of the hats I wear is that of psychotherapist, so naturally, these days I’m thinking a good deal about the ways “AI” (in the narrow sense of the commercially available, ubiquitous phenomenon of LLM-based chatbots) has the power to help or hurt mental health at the scale of hundreds of millions. It’s a conversation I have almost every day with my colleagues and friends. I’m not interested in rehashing the discourse on people using ChatGPT or Claude as ersatz therapist, or recapping the myriad stories of LLM-driven psychosis. Not because probing people’s entirely homespun ways of relating to superintelligent chatbots isn’t interesting—I’m involved in a study of exactly this—but rather, because it’s hard to make a novel point when so much has already been documented and shared. My only aim here is to stand athwart the flow of takes and assert one very simple structural point about the use of easy LLM applications for psychotherapeutic purposes, and why I think they’re doomed not to work well at scale, no matter how popular this use case gets. Whether or not it puts me out of a job. As a sometimes-therapist, I have every psychic and material incentive to reject the idea of the AI therapist. But it’s my duty to be honest with myself and with you, and to level. I can’t tell you with any certainty that AI therapists won’t be able to match and eventually best us in every capacity—at this point, I see no reason to doubt that AI may one day outmatch everyone at everything. If this is the case, why should I gate-keep good medicine and hope for ineffective technology? Of course, there are many valid reasons for a more skeptical take (and one better for my long-term career prospects, even if not necessarily for the greater good). There’s a genuine chance that the attunement of one embodied, feeling human to another embodied, feeling human’s experience is simply unbeatable. Add to this, LLM chatbots’ sycophancy problem—the tendency to validate to the point of telling us exactly what we want to hear, when one of the fundamental tasks of therapy is to unsettle your sense of “normal”. You could argue that ChatGPT and Claude are too domain-general, that their architecture forbids a healthy compartmentalization of therapy away from non-therapeutic activities. You could argue that the way liability is parsed in our legal system, there is no way an AI-dominated therapy ecosystem could work. Ultimately, though, I’m not convinced that any of these are long-term barriers to mass adoption, like it or not. For all I know, fine-tuned AI therapy will have all but replaced human-mediated psychotherapy at scale by the end of this decade. But what I am quite confident of, is that however widely AI is adopted for therapy and therapy-adjacent activities, and no matter satisfied people are with it, it will run into serious problems, and perhaps even stir up new ones at scale—for structural reasons more basic than anything I named above. The frame is the medicine Here’s the crux of it: the main problem with AI therapy is that it’s too available. Too cheap to meter. Let me put this in clearer terms: psychotherapy, in all its well-known guises, is something you engage in within a limited, time-bound frame. In today’s paradigm, whatever your therapist’s orientation, that tends to mean one 45- or 50-minute session a week; for the infinitesimally small minority of therapy patients in classical psychoanalysis, this can amount to 3, even 5, hours a week. And then at a much smaller scale population-wide, people in intensive outpatient and residential treatment programs may spend one or two dozen hours a week in therapy—albeit, mostly of the group variety. I can think of other exotic cases, like some DBT therapists’ willingness to offer on-demand coaching calls during crisis situations—with the crucial exception that in these situations, therapists are holding the frame zealously, jealous of their own time and mindful of the risks of letting patients get too reliant. So even under the most ideal of conditions, in which an LLM-based chatbot outmatches the best human therapists—attunes beautifully, offers the sense of being witnessed by a human with embodied experience, avoids sycophancy, and draws clear boundaries between therapeutic and non-therapeutic activities—there’s still a glaring, fundamental difference: that it’s functionally unlimited and unbounded. The current consumer model for access to mass-market LLMs is an extraordinarily generous one (designed to create a sense of indispensability, probably). In the case of ChatGPT, $20/month earns you access to unlimited text queries. In other words, for all intents and purposes, people have access to an unlimited monthly volume of something approximating therapy for the price of one lunch out. To be clear, for many who previously lacked access to therapy due to financial, social, or other structural constraints, LLM-based therapy may represent a marginal improvement over the base case of no therapy at all. But all else equal: does infinite, on-demand therapy—even assuming the highest quality per unit of therapeutic interaction—sound like a good idea to you? I can tell you, to me it does not. First of all, despite detractors’ claims to the contrary, the basic idea of therapy is not to make you dependent for life—but rather, to equip you to live m