4. Jay Skelton, Ph.D. and Andrew Leker on AI for mental health
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Description
In this episode I talk with clinical psychologist Jay Skelton, Ph.D. and software engineer Andrew Leker about Willow. Willow is a new, empathetic AI specifically designed to be a mental health tool (and not a replacement for a licensed therapist). We take a deep dive into how Willow was trained, how strict safety guardrails were put in place, how Willow is already being used in mental health clinics, its privacy, and the future of AI for mental health. This podcast came out of a partnership with Bambu AI. Timestamps: (00:00:00) - Trigger warning for mental health discussions(00:01:17) - My interest in Willow AI(00:02:54) - Andrew Leker introduces himself(00:04:05) - Jay Skelton, Ph.D. introduces himself(00:05:32) - Willow's role in mental health(00:06:44) - Discussing Willow's design as an empathetic and curious agent(00:07:34) - Importance of empathic interaction in mental health support(00:09:04) - Willow's non-judgmental approach(00:09:24) - Shaping Willow's empathetic identity(00:12:16) - Real conversations in Willow's training(00:14:04) - Evidence-based practices in Willow's training(00:16:36) - Willow does not diagnose, just assists(00:17:54) - Safety in Willow's interactions(00:19:00) - Technical safety features in Willow(00:24:33) - Handling suicidal ideation cautiously and safely(00:26:59) - Jay's comfort as a clinical psychologist with deploying Willow(00:30:00) - Willow's deployment in mental health clinics(00:33:24) - AI's availability and affordability(00:36:40) - Willow providing emotional support and guidance(00:39:53) - Willow as a mental health tool(00:45:38) - Privacy and security in Willow(00:51:18) - Willow's potential for improvement over time(00:52:10) - Benefits of Willow's feedback for therapists(00:54:43) - Future applications of AI in mental health(00:57:32) - Empathy and theory of mind in AI development(01:00:54) - Importance of Willow's emotional intelligence(01:07:48) - Positive feedback from patients using Willow
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