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Using Descartes’ framework for how we acquire knowledge, we examine what happens when AI reasoning models confront problems where mathematical certainty isn’t enough.
We explore Lewis Mumford’s concept of ‘technics’ to answer an essential question in AI: are we creating technologies that adapt to serve human needs, or are we increasingly adapting ourselves to serve theirs?
Exploring how Thomas Aquinas’ Doctrine of Double Effect helps us understand our complex relationship with AI’s unintended consequences. 
Exploring how Immanuel Kant’s concept of the categorical imperative parallels our current challenge of creating immutable ethical rules for artificial intelligence.
Using Simone de Beauvoir’s philosophical framework on categorization, we examine how rigid binary thinking and over-compartmentalization limit our ability to understand and govern A.I.
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