
In this episode, Dr. Ernest Wayde sits down with Zainab Iftikhar, a PhD candidate in Computer Science at Brown University whose research focuses on Human-Computer Interaction (HCI) and AI for mental health. As the first computer scientist featured on the podcast, Zainab offers a unique perspective on how mental health AI systems are designed, evaluated, and used in the real world.The conversation explores why people turn to AI for emotional support, the benefits and risks of mental health chatbots, and what happens when users begin to rely on these systems in place of human connection. Zainab shares insights from her research on emotional dependency, therapeutic boundaries, and the challenges of building AI that supports well-being without causing harm.The episode also examines the critical role of clinicians, researchers, and developers in shaping the future of mental health technology. Together, they discuss how AI can serve as a valuable support tool while preserving human relationships and clinical expertise that remain at the heart of effective care.Takeaways:Human connection remains essential in therapy.AI is designed to agree with users.Overreliance on AI can create dependency.Long-term AI use deserves closer evaluation.Psychologists should help shape mental health AI.Safe AI requires clinician-developer collaboration.Connect with Zainab Iftikhar Website: https://zainabiftikhar.com/Connect With Us https://www.waydeai.com/https://www.facebook.com/waydeaillchttps://www.linkedin.com/company/wayde-ai/info@waydeai.comSubscribehttps://the-waydeai-brief.beehiiv.com/ Chapters:00:00 - Intro02:56 - Journey Into AI & Mental Health Research04:30 - Evaluating AI in Mental Health Contexts08:05 - How People Actually Use AI for Mental Health11:30 - Designing Safer AI for Mental Health Use14:06 - Role of Psychologist Collaboration in AI Design16:07 - Evaluating Long AI Conversations vs Single Responses21:30 - Will AI Replace Therapists?25:47 - Example of AI Helping Emotional Regulation28:41 - Final Tip: Challenge the AI’s Bias
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