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.