Machines & Meaning

John Rawls and the Right to Meaningful Work

Using John Rawls’s theory of justice as fairness, we examine whether a society that willfully eliminates the conditions for meaningful work can be considered just, regard

Ayn Rand and the Dark Side of AI Efficiency

Using Ayn Rand’s philosophy of Objectivism, we examine how AI’s efficiency gains are made possible by ignoring the quiet awareness of claiming skills we don’t fully posse

Ibn Khaldun’s Warning: When Tools Become Purposes

Episode Description: Using Ibn Khaldun’s concept of asabiyyah (ah-sa-BEE-yah), a word derived from Arabic that roughly translates to tribal solidarity or social cohesion,

Credibility Deficits: Miranda Fricker and the Illusion of AI Literacy

Using Miranda Fricker’s concept of testimonial injustice, we examine how AI creates new hierarchies of who gets taken seriously and how the credibility we assign (or don’

AI’s Aesthetic Trap: Søren Kierkegaard’s Three Spheres of Existence

Exploring how Kierkegaard’s three spheres of existence reveal why AI might be creating the most sophisticated trap for authentic human development by appearing to create

Hannah Arendt and AI’s Collective Thoughtlessness

Exploring how Hannah Arendt’s concept of “thoughtlessness” reveals why AI systems create the perfect conditions for systematic harm that emerge from widespread non-engage

Aristotle’s Phronesis and the Wisdom to Judge Ourselves

Exploring how Aristotle’s concept of practical wisdom reveals the meta-cognitive skills professionals will need to remain valuable in an age when AI can perform most tech

Permanent Intermediates: Martin Heidegger and AI’s Erosion of Mastery

Exploring how artificial intelligence systematically undermines the conditions necessary for developing human expertise, creating what we might call “permanent intermedia

The Accountability Threshold: Thomas Aquinas’ Doctrine of Double Effect.

Exploring how Thomas Aquinas’ Doctrine of Double Effect helps us understand our complex relationship with AI’s unintended consequences. 

Universal Laws: Kant’s Categorical Imperative and AI’s Immutable Rules

Exploring how Immanuel Kant’s concept of the categorical imperative parallels our current challenge of creating immutable ethical rules for artificial intelligence.

The Detriment of Constructs: Simone de Beauvoir and Our AI Categories

Using Simone de Beauvoir’s philosophical framework on categorization, we examine how rigid binary thinking and over-compartmentalization limit our ability to understand a

The Calculation Default: What René Descartes Teaches Us About Reasoning Models

Using Descartes’ framework for how we acquire knowledge, we examine what happens when AI reasoning models confront problems where mathematical certainty isn’t enough.

Who’s Adapting to Whom? Lewis Mumford’s Warning for Technics.

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 increasing

The Narrative Machine: LLMs Through the Eyes of Alasdair MacIntyre

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