The Thomistic Institute AI and Knowledge of the World I Prof. Jordan Wales
Sep 3, 2025
Jordan Wales, an Associate Professor of Theology at Hillsdale College, dives into the fascinating intersection of artificial intelligence and human understanding. He discusses how AI's statistical models fall short of the rich depth of human conceptual engagement. Wales contrasts divine wisdom with AI’s categorical limitations, drawing on Augustine’s insights. He explores how different worldviews shape perceptions of AI, urging a balanced approach that uses technology for deeper understanding rather than as a definitive solution to life's complexities.
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Why Symbolic AI Broke Down
- Symbolic AI failed because the world resists neat, discrete categories that humans casually use.
- Real-world common sense cannot be exhaustively encoded as propositional rules.
Neural Networks Capture Situations
- Neural networks work by adapting statistically to shifting input patterns rather than applying fixed propositional definitions.
- They treat the world as a statistical blur that can capture situated, intuitive sensibilities.
Creation As Refraction, Not Specimen
- Augustine's account casts creation as a kaleidoscopic refraction of divine wisdom, not fixed species boxes.
- This view helps explain why statistical AI can succeed where symbolic systems fail.
