If every event has a cause, then perhaps your next thought was written into the universe long before you were born.

Topics Discussed

 * The American, French, and Latin American Revolutions as products of the Enlightenment
 * Moderate vs. Radical Enlightenment thinkers
 * Three explanations for historical change
 * How the rise of the social sciences transformed explanations of human behavior
 * Laplace's Demon and the idea of causal determinism
 * The distinction between causal determinism and hard determinism
 * Earlier forms of determinism
 * The emergence of social physics
 * Historical and philosophical objections to hard determinism
 * Scientific challenges from non-Euclidean geometry and quantum mechanics
 * Why indeterminism does not automatically establish free will

Lesson 2.3: Laplace's Demon

When an AI tells a joke, writes an essay, or solves a complex programming problem, is it just performing a statistical magic trick—or is there something deeper happening under the hood?

On this episode of The AITEC Philosophy Podcast, Roberto and Sam sit down with computer scientist John McCormick [https://www.dickinson.edu/johnmaccormick], author of Thinking AI: How Artificial Intelligence Emulates Human Understanding [https://press.princeton.edu/books/hardcover/9780691191737/thinking-ai?srsltid=AfmBOopJYY_0axygWMGMBpJ8HkF98UBLTvOtU54DSAMIexSDTxysIZj8] (Princeton University Press).

For over 70 years, we've been asking Alan Turing's classic question: Can a machine think?. John reframes this debate by taking us past the polished, fluent surface of modern Large Language Models to look directly at the underlying code. We discuss whether AI merely mirrors human output or if its internal structures have begun to replicate pockets of human cognition. Despite the existential dread surrounding superintelligence, John shares a surprisingly optimistic perspective: even if we build entities that exceed human intellect, they will never replace the deeply rooted, biological fulfillment of our shared humanity.

Uncover the machinery behind the curtain and join the conversation at ethicscircle.org [https://www.ethicscircle.org/].

#34 John MacCormick: Can Machines Think Like Us?

When the world looks cruel, every defense of God becomes a theory of human nature.

Topics Discussed

 * The problem of evil argument and the two main ways to resist it: reject premise 1 or reject premise 2.
 * Leibniz’s “best of all possible worlds” theodicy, including its psychological promise of consolation and its ethical demand for active striving.
 * Voltaire’s mockery of Leibniz after the Lisbon earthquake, especially the charge that “the best of all possible worlds” sounds absurd in the face of real suffering.
 * Other responses to the problem of evil: deism, the devil, free will, evil as a counterpart to good, the soul-making defense, and skepticism about whether we can prove that unnecessary suffering exists.
 * The connection between theology and moral psychology in Hobbes, Leibniz, and Spinoza: whether people need religion, political authority, or freedom from superstition in order to live well.

Lesson 2.2: The Problem of Evil, Pt. II

Are we trading our critical thinking skills for the sake of digital convenience?In this episode of The AITEC Philosophy Podcast, Roberto Carlos García sits down with Michael Gerlich. Michael is the Head of the Center for Strategic Corporate Foresight and Sustainability, the Head of Executive Education, and a Senior Faculty member at SBS Swiss Business School. Most recently, Michael summarized his research on the interaction between LLMs and humans in The Convenience Trap: What Happens When AI Becomes the Mind Behind Our Lives [https://shop.bookmundo.com/en-NL/book/22063184/the-convenience-trap/EPUB]. In this conversation, Michael shares his interdisciplinary research into how AI is "creeping" into nearly every aspect of our existence. We explore the dangerous phenomenon of "cognitive offloading"—the tendency to let algorithms make our choices, from the music we hear to the news we consume—and how this creates a "convenience trap" that narrows our perspective and weakens our mental "musculature". Michael argues that for AI to be a truly beneficial "sparring partner," we must do the hard work of thinking first before engaging with the machine.

Join the conversation and learn how to keep the power of thought in your own hands at ethicscircle.org [https://www.google.com/search?q=http://ethicscircle.org].

Links:

 * Michael’s book [https://shop.bookmundo.com/en-NL/book/22063184/the-convenience-trap/EPUB]
   
 * One of Michael’s articles on cognitive offloading [https://www.mdpi.com/2075-4698/15/1/6]
   
 * Michael’s article on societal bifurcation [https://www.mdpi.com/2075-4698/16/3/82]
   

#33 Michael Gerlich: How AI is Stealing Your Ability to Think

Have you ever suspected that the technology you use isn't just a tool, but an entirely fake reality replacing the natural world?

On this episode of The AITEC Podcast, Sam Bennett sits down with Israeli philosopher Yochai Ataria to explore the brilliant philosophical undercurrents of Ridley Scott's 1982 classic, Blade Runner. Ataria reveals how the film functions as a profound Heideggerian critique of the modern technological age.

They unpack how the film's protagonist, Rick Deckard, serves as a direct stand-in for René Descartes, undergoing a radical crisis of certainty and identity. The conversation also delves into ancient Greek frameworks, exploring how the replicant Roy Batty mirrors the Oedipus myth and how the rare flashes of lightning in a polluted sky tie back to Zeus. Ultimately, this episode asks whether the representations we rely on—from futuristic photo-analyzers to modern social media algorithms—are actually elaborate lies designed to disconnect us from reality.

#32 Yochai Ataria: Why Blade Runner is Secretly About Fake Realities

Have you ever wondered if AI models actually understand the words they generate, or if they are just really good at faking it?

On this episode of The AITEC Podcast, Roberto García and Sam Bennett are joined by philosopher Jacob Browning (Baruch College, CUNY) to unpack his article, Intentionality All-Stars Redux: Do language models know what they are talking about?

Using a clever baseball diamond metaphor and drawing on the philosophy of Immanuel Kant, Jacob explains why Large Language Models lack the "intentionality" required for genuine comprehension. We cover:

 * First Base (Formal Competence): Why LLMs struggle with basic logic and negation, revealing the absence of an underlying logical engine.
 * Second Base (Rationality): Why true understanding requires purposive behavior, and how LLMs hilariously fail at "intuitive physics" (like trying to inflate a couch to get it onto a roof).
 * Shortstop (Objectivity and World Models): Why genuine understanding requires grasping an objective, mind-independent world that determines whether sentences are true or false. This position explores how LLMs lack a coherent "world model," causing them to fail at tasks that require intuitive physics and planning for counterfactual situations (like predicting where a billiard ball will go or playing simple video games).
 * Third Base (The Unified Self): Why making a claim requires a persistent self that takes responsibility for its beliefs—something a next-token predictor simply cannot do.

Whether you're exploring the intersection of AI, technology, and ethics, or just trying to figure out if your chatbot actually knows what it's saying, this conversation will give you the philosophical toolkit to see through the illusion.

#31: Jacob Browning: Unmasking the Fake Minds of Large Language Models

If God is perfectly good, then this world demands an explanation—or a surrender of belief.

Topics discussed:

 * The relationship between intellectualism and belief in the supernatural
 * A Pyrrhonian-style move: examining both sides of the “religion vs. reason” debate
 * Early Christianity as a countercultural and sometimes anti-intellectual movement
 * Introduction to Baron d’Holbach—an early, explicit defender of atheism
 * The notion of the God of the Gaps
 * The Problem of Evil argument against God’s existence

Lesson 2.1: The Problem of Evil, Part I

Philosopher Andrea Pinotti joins us to discuss At the Threshold of the Image: From Narcissus to Virtual Reality. What begins as a conversation about image theory quickly becomes a sweeping exploration of immersion, identity, and the strange pull of simulated worlds. Why do we long to enter the image? What do we gain—and lose—when the frame disappears? Pinotti guides us from Paleolithic caves to VR headsets, through myths of Narcissus and Pygmalion, to Black Mirror’s digital afterlives. Along the way, we consider how virtual environments blur fiction and reality, evoke religious promises, and reshape what it means to be human.If you've ever wondered why virtual reality feels so real—or so dangerous—this episode is for you.For more, visit ethicscircle.org. 

#30 Andrea Pinotti: Beyond the Frame—Virtual Reality, Narcissus, and the Desire to Enter the Image

If we can’t prove whether God exists, should we treat belief like a gamble—and choose the option with the best payoff?

Topics discussed:

 * The philosophical dilemma of whether belief in God should be based on reason, faith, or skepticism.
 * Major positions on the existence of God: rational theism, fideism, deism, atheism, non-theism, and agnosticism.
 * The life and intellectual background of Blaise Pascal, mathematician, theologian, and pioneer of probability theory.
 * The historical origins of probability theory, including early work by gamblers like Gerolamo Cardano and Pascal’s correspondence with Fermat.
 * The concept of expected utility and how decision theory evaluates rational choices under uncertainty.
 * The structure of Pascal’s Wager, which argues that believing in God maximizes expected value because of the possibility of infinite reward.
 * Mathematical objections to the wager, including the Many Gods objection and the Zero Probability objection.
 * Psychological and ethical objections, including doxastic involuntarism, the moral integrity objection, and the Many Hells objection.

Lesson 1.8: The Ace of Spades

Stop treating AI like a search engine and start using it as a "cognitive architect" to bridge the gap between just having information and actually building expertise.

Topics discussed:

 * The Knowledge Illusion: We often fail to distinguish between knowledge stored in our own heads and information readily available in our environment, leading to a false sense of expertise.
 * Illusion of Explanatory Depth: Instant access to the internet can make us feel more confident in our understanding of a topic than we actually are; forcing ourselves to explain a concept is the best way to break this spell.
 * Setting the Stage: Effective learning begins with isolating core concepts and stripping away non-essential content to reduce cognitive load.
 * Deep Processing: Based on the principle that "memory is the residue of thought," learning happens when we actively think about the meaning and implications of information.
 * AI-Driven Retrieval Practice:
   Free Recall Loop: Using AI to analyze what you remember from memory and identify gaps or misunderstandings.
   Pre-flight Diagnostics: Tasking AI to quiz you on foundational terms to ensure proficiency before moving to complex material.
   Borderline Case Testing: Improving conceptual clarity by asking AI for clear examples, non-examples, and tricky "borderline" cases.
 * The Power of Chunking: Organizing disparate facts into small, meaningful units (like how a chess grandmaster sees patterns rather than individual pieces) to make complex material easier to retain.

Lesson 2: Foundational Fluency with AI

Welcome to AITEC Podcast, where we explore the ethical side of AI and emerging tech.

We call our little group the AI and Technology Ethics Circle (AITEC). Visit ethicscircle.org [https://www.ethicscircle.org/] for more info. 

AITEC Philosophy Podcast

These are PHIL courses taught by R. C. M. García at El Camino College. 

Roberto Carlos

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