Exploring how artificial intelligence systematically undermines the conditions necessary for developing human expertise, creating what we might call “permanent intermediates,” people who achieve functional competence but never develop true mastery.

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.

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?

We explore Alisdair MacIntyre’s concept of narrative fragmentation and whether large language models (LLMs) contribute to it through their underlying architecture.