Scaling Mental Health Access through AI with Neil Parikh and Daniel Cahn
Mar 11, 2025
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Neil Parikh and Daniel Cahn, cofounders of Slingshot AI, share their journey of transforming mental health care through artificial intelligence. They discuss the development of AI models designed to enhance therapeutic experiences and how these innovations expand access to subclinical support. The duo contrasts voice and text interactions in therapy, revealing how preferences vary by age. They emphasize empowering patients through data-driven care, envisioning a future where technology enhances the therapist-patient relationship.
Slingshot AI founders emphasize using generative AI to model psychological processes, enabling personalized mental health therapy and support.
They envision AI enhancing mental health care access by assisting therapists with subclinical cases, allowing professionals to focus on serious issues.
Deep dives
The Founding Vision of Slingshot AI
Slingshot AI was founded by Neil Parikh and Daniel Kahn, who aim to enhance access to mental health care using generative AI. Parikh, a med school dropout, realized the limitations of traditional healthcare and sought to innovate within it, while Kahn, driven by his background in AI, shared a vision of modeling the human mind to facilitate mental health support. They both believe this is an opportune moment, fueled by advancements in AI, to create systems that can assist people on their mental health journeys. Their approach seeks to combine personalized therapy with AI capabilities to revolutionize how mental health care is delivered.
Modeling the Mind Through AI
A significant aspect of Slingshot AI's mission is to create a model that can represent psychological processes, as guided by the effectiveness of language models. Parikh and Kahn argue that while traditional therapy involves unpredictability, AI can similarly analyze user experiences and adapt to their needs through probability distributions. This method can help therapists make educated guesses similar to human intuition. They acknowledge the challenge but remain focused on bridging the gap between technology and psychoanalysis to redefine therapy's landscape.
User-Centric Mental Health Metrics
The success of Slingshot AI's approach hinges on a user-defined metric of effective mental health care. Instead of depending on conventional measures, the founders emphasize that the users' perceptions of their experience determine what constitutes 'good therapy.' This user-centric view aligns with their belief in self-determination and the importance of individual autonomy and competency. Their commitment to understanding these subjective experiences will shape the tools and interactions users have with the AI, leading to more meaningful therapeutic outcomes.
The Future Collaboration of AI and Human Therapists
Parikh and Kahn envision a future where AI complements rather than replaces human therapists, focusing on the subclinical population needing support. They argue that AI could relieve therapists by addressing lower-level mental health issues while allowing professionals to dedicate their expertise to more serious cases. The integration of AI in therapy could enhance efficiency and broaden access, providing crucial support to an overburdened healthcare system. Ultimately, they believe that while AI will revolutionize therapy, human insight will always be vital for optimal care.
In this episode, Slingshot AI cofounders Daniel Cahn and Neil Parikh join a16z Bio + Health general partner Julie Yoo to explore how their mission to transform mental health care with AI took shape. Drawing from their unique journeys—Daniel as the son of a psychologist and Neil as a former medical student-turned-entrepreneur—they discuss the challenges and opportunities of building AI models to model psychological processes and how this could expand access for subclinical mental health support.
Listen for candid reflections on Slingshot's innovations, visions for AI's role in preventative care, and a future where technology empowers therapists and patients alike.
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