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Using AI in psychotherapy.

How artificial intelligence can be used to battle depression

Artificial intelligence will change the future of psychotherapy, seven researchers write in a work paper. AI can be used in psychotherapy and to battle depression that is a leading cause of disability worldwide. The researchers with backgrounds in psychology and computer science,  Stanford University website reports.

“Large language models (LLMs) such as ChatGPT and GPT-3/4, built on artificial intelligence, hold immense potential to support, augment, or even replace psychotherapy”, they write in their work paper.

“Enthusiasm about such applications is mounting in the field as well as industry. These developments promise to address insufficient mental healthcare system capacity and scale individual access to personalized treatments.” 

“However, clinical psychology is an uncommonly high stakes application domain for AI systems, as responsible and evidence-based therapy requires nuanced expertise.”

The researchers highlight the importance of transparency: Patients must know that they are talking to a bot, and they must be able to opt out if they would like to.  

The paper has  a roadmap for ambitious yet responsible application of clinical LLMs in psychotherapy. It highlights areas of risk given the complex nature of psychotherapy. 

The paper includes recommendations for responsible development including  involving robust interdisciplinary collaboration, and attending to issues like assessment, risk detection, transparency, and bias.

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 “We outline what rigorous and safe evaluation would look like. This really needs to be done responsibly”, the paper’s lead author, Elizabeth Stade, a graduate student at the University of Pennsylvania and an incoming postdoc at Stanford. told the Stanford University website.

“Important parts of the diagnosis and treatment pipeline can be cumbersome for both the therapist and the client, like symptom-tracking questionnaires or progress notes,” Stade says. “Handing these lower-level tasks and processes to automated systems could free up clinicians to do what they do best: careful differential diagnosis, treatment conceptualization, and big-picture insights.”

Given these prospects, and given mental health is a $100 billion market, co-author Johannes Eichstaedt fears companies will rush into this space advertising solutions without due diligence, the website reports. 

He has already been contacted by venture capitalists who want to apply machine learning tools to the world of psychotherapy, who want to, as he put it, “throw an LLM [large language model] at the problem and see if it sticks.”

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