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There Is No Reward Function for Meaning

The article argues that meaning in life cannot be optimized like a reward function in AI, because meaning is inherently subjective, context-dependent, and resistant to any single metric or goal-based framework.

Background

- The article argues that "meaning" in life cannot be captured by a reward function (a mathematical objective used in AI training), contrasting with how reinforcement learning systems optimize for clear goals. - Aaron Ang is a writer and technologist who explores intersections of philosophy, AI, and human purpose. - This matters because as AI systems become more capable, there's growing pressure to define human values in computational terms — but the author insists meaning is fundamentally irreducible to optimization.

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