AI, Philosophy, and Human Innovation

After I wrote this piece ‘Will AI Kill Innovation?’, Michael Schrage - A technology, business, and innovation thought leader at MIT - was happy to let me know that my argument was off track :). So take a listen to our conversation that covers AI’s role in human innovation, the debate between free will and determinism, and how philosophy shapes our understanding of intelligence, decision-making, and creativity. We also talk about what Healthcare is getting wrong with Generative AI, and why the future of AI lies in pattern recognition rather than just language. If you have a chance, check out Michael’s article “Philosophy Eats AI” in the MIT Sloan Management Review. Conversation Companion Guide - AppendixIf you are like me and have faded memories of college Philosophy classes, then the below notes may be a helpful guide since we chat about authors, philosophers, and other concepts. Apropos, it was made with the help of an LLM. 📚 Thinkers and Authors Referenced1. Judea Pearl – Causality & AIJudea Pearl is a computer scientist and philosopher best known for his work on causality and Bayesian networks. His book The Book of Why explores how we can move beyond mere correlations to understand cause-and-effect relationships, a key issue in AI and predictive analytics.2. Peter Thiel – Innovation and Zero to OnePeter Thiel is a venture capitalist, entrepreneur, and co-founder of PayPal. His book Zero to One argues that true innovation happens when you create something entirely new, rather than just improving existing ideas.3. Daniel Kahneman & Amos Tversky – Behavioral EconomicsPsychologists Kahneman and Tversky pioneered behavioral economics, studying how human decision-making is often irrational due to cognitive biases. Kahneman’s book Thinking, Fast and Slow explains how our brains use two systems: a fast, intuitive system and a slow, logical system.4. Dan Ariely – Predictably IrrationalA behavioral economist who studies why people make irrational decisions and how emotions, biases, and social influences affect economic choices.5. Albert Einstein – Thought Experiments & RelativityI mention Einstein’s Gedankenexperiment (German for "thought experiment") about riding a beam of light, which led to the development of the Special Theory of Relativity. This highlights how imaginative experiments (not just data-driven analysis) fuel groundbreaking discoveries.6. Stephen Wolfram – A New Kind of ScienceA computer scientist and physicist, Wolfram explores how simple computational rules (like cellular automata) can generate complex behavior, influencing AI and machine learning.7. John von Neumann – AI & Game TheoryA mathematician and physicist, von Neumann contributed to game theory, quantum mechanics, and early computer science, laying the foundation for modern AI.8. Kurt Gödel – Incompleteness TheoremGödel’s Incompleteness Theorem states that in any formal system, there are truths that cannot be proven within the system itself. This challenges AI’s ability to fully understand the world.9. Ludwig Wittgenstein – Language & MeaningWittgenstein explored how meaning is derived from context and usage rather than fixed definitions.10. Sam Harris – Free Will DebateSam Harris is a neuroscientist and philosopher who argues that free will is an illusion, a point Michael Schrage vehemently pushes back against!11. Jean Baudrillard – Simulacra & HyperrealityBaudrillard argued that in today’s world, representations (like media and AI-generated content) can become more "real" than reality itself.12. Nassim Taleb – The Black Swan & RiskA philosopher-statistician who introduced the concept of Black Swan events—rare, unpredictable events that shape history—and argues for "skin in the game", meaning decision-makers should bear the risks of their own choices.13. Michel Foucault – Power & InstitutionsFoucault studied how power and knowledge shape social institutions, including healthcare. Michael pushes back on my “Foucauldian” view, arguing that information asymmetry is a bigger issue than power asymmetry.14. Peter Singer – AI & EthicsA moral philosopher known for utilitarian ethics (the idea that decisions should maximize overall well-being). Singer has an AI trained on his writings -https://www.petersinger.ai/ 📖 Key Concepts Mentioned🔹 Epistemology – The Study of KnowledgeEpistemology is the branch of philosophy concerned with how we acquire, justify, and define knowledge. It explores questions like: What counts as knowledge? Can AI “know” something, or does it merely predict?🔹 Ontology – The Study of Being & ExistenceOntology is the philosophical study of what exists and what it means to “be”. It’s a critical issue in AI, raising questions like: Is an AI that mimics human thought truly intelligent, or just simulating it? Do AI models have any kind of “understanding” or are they just pattern-recognizers?🔹 Teleology – The Study of Purpose & GoalsTeleology examines the purpose or end goal of things. In AI and philosophy, it raises questions like: Does AI have a purpose, or is it just a tool? Should AI systems be built with a specific moral or ethical objective? This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit ankoors.substack.com