
Insights from recent episode analysis
Audience Interest
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Platform Reach
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
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Total monthly reach
Estimated from 1 chart position in 1 market.
By chart position
- 🇿🇦ZA · Philosophy#189500 to 3K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
250 to 1.5K🎙 Weekly cadence·13 episodes·Last published 3mo ago - Monthly Reach
Unique listeners across all episodes (30 days)
500 to 3K🇿🇦100% - Active Followers
Loyal subscribers who consistently listen
150 to 900
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Reach across major podcast platforms, updated hourly
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
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Recent episodes
Ayn Rand and the Dark Side of AI Efficiency
Mar 16, 2026
16m 15s
Ibn Khaldun’s Warning: When Tools Become Purposes
Dec 22, 2025
12m 01s
Credibility Deficits: Miranda Fricker and the Illusion of AI Literacy
Nov 11, 2025
15m 11s
AI’s Aesthetic Trap: Søren Kierkegaard’s Three Spheres of Existence
Oct 13, 2025
15m 23s
Hannah Arendt and AI’s Collective Thoughtlessness
Sep 8, 2025
12m 57s
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 3/16/26 | ![]() Ayn Rand and the Dark Side of AI Efficiency✨ | Ayn RandAI efficiency+4 | — | Objectivism | — | Ayn RandAI+5 | — | 16m 15s | |
| 12/22/25 | ![]() 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, we examine how AI is being rhetorically elevated to the status of collective purpose. | 12m 01s | ||||||
| 11/11/25 | ![]() 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’t) affect people’s lives. | 15m 11s | ||||||
| 10/13/25 | ![]() 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 fulfillment while preventing genuine growth. | 15m 23s | ||||||
| 9/8/25 | ![]() 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-engagement with consequences. | 12m 57s | ||||||
| 8/4/25 | ![]() 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 technical tasks. | 14m 28s | ||||||
| 7/1/25 | ![]() 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 intermediates,” people who achieve functional competence but never develop true mastery. | 12m 52s | ||||||
| 6/1/25 | ![]() 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. | 14m 23s | ||||||
| 5/1/25 | ![]() 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. | 15m 45s | ||||||
| 4/1/25 | ![]() 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 and govern A.I. | 14m 58s | ||||||
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| 3/2/25 | ![]() 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. | 15m 17s | ||||||
| 2/3/25 | ![]() 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 increasingly adapting ourselves to serve theirs? | 11m 59s | ||||||
| 12/31/24 | ![]() 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. | 12m 15s | ||||||
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Chart Positions
1 placement across 1 market.
Chart Positions
1 placement across 1 market.













