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Currently Playing: Goals: Are they for LLMs, Cats, and Thermostats?

We often hear that the biggest risk from super-intelligent AI is that their "goals" won't align with human goals. But what if we're asking the wrong question? This video takes philosophical look into the concept of *goals* itself. We move beyond motivational speeches to explore the fundamental question: When we attribute a goal to a thermostat, a chess engine, or an LLM, are we talking about the same thing as a human goal? We analyze prominent definitions of intelligence—like John McCarthy's view that intelligence is goal-directed computation—and use classic philosophical tools to dissect the problem, including: * **Propositional Attitudes** * **Direction of Fit** (Mind-to-World vs. World-to-Mind) * **Value Theory** (Intrinsic vs. Extrinsic Goals, from Aristotle to Mill) By examining goals in everything from hunger and cats to hammers and mushrooms, we develop a better framework for understanding the true nature of AI intelligence. **Do LLMs, Reinforcement Learning Agents, and Chess Engines truly have goals? Or do they have something else entirely?** Find out why the answer to this philosophical question is essential for tackling the biggest risk in modern AI: the Alignment Problem. --- **Topics Covered:** #AIAgnment #PhilosophyOfAI #GoalDirectedness #JohnMcCarthy #LLMs #ArtificialIntelligence #ValueTheory #EthicsOfAI