By distinguishing between propositional, procedural, perspectival, and participatory knowing, he reveals why the current paradigm of AI is not equipped to generate consciousness, agency, or true understanding. This lecture also serves as a moral call to action: if we want wise machines, we must first become wiser ourselves.
00:00 Introduction: AI, AGI, and the Nature of Intelligence 02:00 What is General Intelligence? 04:30 LLMs and the Illusion of Generalization 07:00 The Meta-Problems of Intelligence: Anticipation & Relevance Realization 09:00 Relevance Realization: The Hidden Engine of Intelligence 11:30 How We Filter Reality Through Relevance 14:00 The Limits of LLMs: Predicting Text vs. Anticipating Reality 17:00 Four Kinds of Knowing: Propositional, Procedural, Perspectival, Participatory 23:00 Embodiment, Consciousness, and Narrative Identity 27:00 The Role of Attention, Care, and Autopoiesis 31:00 Culture as Niche Construction 34:00 Why AI Can’t Participate in Meaning 37:00 The Missing Dimensions in LLMs 40:00 Rationality vs. Reasonableness 43:00 Self-Deception, Bias, and the Need for Self-Correction 46:00 Caring About How You Care: The Core of Rationality 48:00 Wisdom: Aligning Multiple Selves and Temporal Scales 53:00 The Social Obligation to Cultivate Wisdom 55:00 Alter: Cultivating Wisdom in an AI Future