What if we could cure loneliness? Philosophy, dopamine, and more with Mark Ungless
Feb 26, 2025
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Mark Ungless, a neuroscientist and Director of AI at Mental Health Innovations, shares his insights on the biological roots of loneliness and the interplay between neuroscience and AI. He discusses how dopamine impacts human behavior and its parallels with reinforcement learning in AI. The conversation also dives into the philosophical implications of free will amidst evolving technology. Furthermore, Ungless explores innovative AI solutions for mental health, highlighting the potential for technology to enhance social interactions and support well-being.
Mark Ungless emphasizes the complex nature of loneliness, revealing that it has biological roots that can inform mental health interventions.
The podcast explores the limitations of AI in replicating the intricacies of human neural networks, stressing that true understanding of our brains remains unmatched.
Mark discusses the evolving perspective on depression, advocating for a multidimensional approach that goes beyond the simplistic serotonin theory.
Deep dives
Mark Unglis's Background and Expertise
Mark Unglis has over 20 years of experience in psychology and neuroscience, contributing significantly to the field with a PhD in experimental psychology. His groundbreaking research includes studies that reveal how even a single exposure to addictive drugs can lead to lasting changes in the brain's reward circuitry. He has identified two types of dopamine systems—one for rewards and another for aversive signals. His work also extends to social isolation, where he collaborated with MIT to investigate a particular type of dopamine neuron related to the experience of loneliness.
The Experience Machine and Its Implications
The discussion introduces the thought experiment of the 'experience machine,' a hypothetical device that creates pleasurable experiences by directly stimulating the brain. While Mark suggests that true technological feasibility is a long way off, he acknowledges the concept's relevance in exploring dopamine’s role in experience and pleasure. The conversation hints at the idea that substances like opioids might serve as a primitive version of this machine, artificially elevating dopamine levels to induce pleasure. This raises ethical questions about the nature of pleasure and whether technology could replicate genuine human experience.
Neural Complexity and the Nature of Intelligence
Mark emphasizes that the human brain's complexity, with approximately 80 billion neurons, leads to intricate neural circuits that are not fully understood. This complexity contrasts with AI neural networks, which while inspired by brain functions, may lack the dynamic and multifaceted nature of biological processes. The discussion explores the limitations of AI in replicating human-like learning, such as the quick acquisition of language skills, highlighting a fundamental difference between artificial and biological intelligence. Therefore, while AI may mimic certain aspects of human behavior, the deep intricacies of human neural networks remain unmatched.
The Debate on the Serotonin Theory of Depression
Mark delves into the serotonin theory of depression, questioning the simplistic understanding that low serotonin levels are the sole cause of the condition. He references a recent systematic review indicating that direct evidence linking serotonin levels to depression is weak, suggesting a need for deeper understanding of mental health disorders. Despite the popularity of SSRIs as a treatment, he cautions against viewing depression solely as a brain disease, emphasizing the continuum of mood variability among individuals. The complexities of diagnosing and understanding depression underline the necessity for advancements in neuroscience to develop more effective interventions.
AI's Potential in Mental Health Support
The potential for AI in mental health care is highlighted through the example of the 'Shout' service, which provides 24/7 support via trained volunteers. Mark discusses the advantage of utilizing AI to assist in these conversations, especially in managing high demand for mental health services. AI could serve as a supplement, increasing access for those who otherwise might wait long periods for human assistance, while ensuring the quality and safety of such interactions remain a priority. This blend of technology and human support presents a promising pathway to enhance mental health care accessibility and effectiveness.
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.
Well, it's a bit more complicated than that, at least according to my guest Mark Ungless, former neuroscience lecturer at Imperial and Oxford and current Director of AI at the UK's Mental Health Innovations. Mark and I have collaborated on research for 5+ years, and I've long enjoyed his thoughts on the biology of the brain, the philosophy of the mind, and how AI is changing (and being changed) by our understanding of both. In our latest conversation, we touch on...
His groundbreaking research on the biological root of loneliness
How understanding neuroscience helps you understand humans
How well neural networks represent our own minds (and whether it matters at all!)
AI’s ability to do therapy
What it means to have free will in a world where we understand more about our brains every day
For more conversations like this, be sure to follow our Youtube channel (@ThinkingMachinesPodcast) and subscribe to our show in your favorite podcast player.
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