On Emotionally Intelligent AI (with Chris Gagne, Hume AI)

(Cross-posted from Fit Check) The mental health field is facing an unexpected disruption: AI is already the largest provider of mental health support in the US, with hundreds of millions using tools like ChatGPT for emotional guidance—whether the technology was designed for it or not. In this AMA, I sit down with Dr. Rachel Wood (licensed counselor with a PhD in cyberpsychology and founder of the AI Mental Health Collective) and Megan Cornish (therapist and community organizer) to take hard questions from mental health professionals about what's actually happening—and what should happen—as AI enters therapeutic spaces. We tackle the uncomfortable questions: Should AI therapy be regulated? What happens in the brain during AI conversations versus human ones? How do we prevent AI from replacing human connection rather than supporting it? And critically—what responsibility do AI companies have when people turn to them who need something AI can't offer? This isn't about whether AI should be used for mental health support. That ship has sailed. This is about understanding the technology, acknowledging the massive access gap in mental healthcare (one therapist for every 1,500+ people in need), and figuring out how to build AI that strengthens human relationships rather than replacing them. We discuss: The neuroscience of attunement and whether AI can replicate therapeutic connection How language models actually work (and why they're more than "just talking") Three core concerns: autonomy, competency, and relatedness Why ChatGPT exemptions in regulation miss the point entirely The difference between AI as replacement versus AI as gateway What accountability could actually look like in this space Whether you're a therapist worried about the impact of AI within your profession, a technologist building in this space, or simply someone trying to understand where we're headed—this conversation matters. For the full discussion and ongoing conversations, check out the Fit Check community.

“Everyone should go to therapy.” It’s a common statement, but much harder to achieve than it looks. There’s only one therapist for every 10K would-be clients, and the gap is only growing every year. That gap is what my latest guest - Dr. Derrick Hull - has spent his career trying to fix. Now serving as the founding Clinical Lead at Slingshot AI, Derrick previously led Clinical R&D at Talkspace, where he was instrumental in popularizing text-message therapy, a previously controversial modality now recognized as critical to increasing accessibility to mental health care. Derrick has had a fascinating career, serving as a practicing psychologist, a clinical advisor and researcher for top startups, and a highly accomplished academic with publications in Nature, the National Academy of Sciences, and Oxford University Press, with his research supported via R01 grants through NIH. It’s been amazing getting to work with Derrick at Slingshot, and I’m so excited to share just a snapshot of the wisdom and insight I collect from him everyday.

Artificial neural networks were designed to emulate the human brain - and their insane performance on a wide range of tasks is pretty good evidence to support the comparison.

Is the AI revolution we're experiencing going to push us into a future we can't imagine? Or will the pace of progress enable us to adjust along the way? Dan Shipper spends his time thinking and writing on these topics (and many others) as the founder and CEO of Every Media, a technology-focused publication trying to understand the future. Dan is also a lifelong coder and entrepreneur with a background in philosophy and its intersection with tech. Dan and I share a ton in common (beyond just our first names!), so I think you all will enjoy our thoughts on... The meaning of the "good life" Whether the study of philosophy evolves over time How cryptocurrency, AI, and the nature of knowledge will accelerate each other The value of philosophy and thinking for thinking's sake What the future holds for engineering, philosophy, and humanity at large If you like this conversation, check out more of Dan's thought at Every.to and on X 'at' @danshipper.

GPT-3 didn't have much of a splash outside of the AI community, but it foreshadowed the AI explosion to come. Is o1 OpenAI's second GPT-3 moment? Machine Learning Researchers Guilherme Freire and Luka Smyth discuss OpenAI o1, it's impact, and it's potential. We discuss early impressions of o1, why inference-time compute and reinforcement learning matter in the LLM story, and the path from o1 to AI beginning to fulfill its potential. 00:00 Introduction and Welcome 00:22 Exploring O1: Initial Impressions 03:44 O1's Reception 06:42 Reasoning and Model Scaling 18:36 The Role of Agents 27:28 Impact on Prompting 28:43 Copilot or Autopilot? 32:17 Reinforcement Learning and Interaction 37:36 Can AI do your taxes yet? 43:37 Investment in AI vs. Crypto 46:56 Future Applications and Proactive AI