
This article discusses the potential of using multiple AI-based personas to provide mental health advice and diagnose human psychological disorders. The author describes a mini-experiment where they used a language model (LM) to simulate five different personas, each with a specific role in the diagnostic process.
The first persona, Dr. Supposition, identifies draft hypotheses about the patient’s mental health conditions. The second, Dr. Selector, provides tests that could be used to affirm or disconfirm the drafted hypotheses. Dr. Contender serves as a devil’s advocate, questioning the draft hypotheses and proposed tests. Dr. Thoughtful weighs the various factors involved in making a diagnosis, including intrusiveness and cost-effectiveness. Finally, Dr. Double-Checker reviews the diagnosis for consistency and potential pitfalls.
The author asked the LM to perform a mental health analysis of a provided vignette (a fictionalized case study) and compared the results with known answers from the American Board of Psychiatry and Neurology (ABPN). While it’s unclear whether the AI’s performance was due to actual diagnostic capabilities or prior exposure to the case, the results were encouraging.
The author notes that this approach can lead to a “bonus” effect, where the separate personas work together harmoniously to achieve better results. However, they also caution against relying too heavily on these generated explanations, as they may not accurately reflect the internal workings of the AI system.
The author concludes by emphasizing the potential benefits and challenges of using AI personas in mental health analysis and diagnosis.
Source: www.forbes.com