Exploring Rationalism’s Boundaries: A Journey from Socrates to Neural Networks | Complete Interview with Dan Shipper – Video

By Big Think 1 hour Ago 5 Min Read

The limits of rationalism: From Socrates to neural networks | Dan Shipper: Full Interview

The Limits of Rationalism: From Socrates to Neural Networks | Dan Shipper: Full Interview

Contents

The limits of rationalism: From Socrates to neural networks | Dan Shipper: Full Interview

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Author Video Description

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In this thought-provoking interview, Dan Shipper, CEO of Every and host of the AI & I podcast, explores the evolution of rationalism from Socratic foundations to modern-day neural networks. Shipper emphasizes that while rationalism—a systematic approach to knowledge aiming for explicit definitions—has shaped scientific progress, it falls short in accounting for the complexities and nuances of reality. Through the lens of AI, particularly large language models, he illustrates how these systems embody human-like intuition, analyzing patterns and context rather than relying solely on rigid rules.

Shipper argues that this shift calls for a reevaluation of how we understand knowledge and creativity. Rather than fearing that AI may usurp our humanity, he asserts that these tools can enhance our intuitive capabilities, enriching our problem-solving approaches. The discussion suggests a future where human and AI collaboration fosters deeper insights, encouraging us to embrace varied ways of knowing and creating. By reflecting on historical philosophical concepts, Shipper invites viewers to rethink the interplay between rational thought and intuition in both technology and human experience.

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“What’s really interesting about neural networks is the way that they think or the way that they operate is a lot like human intuition”

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What if we could use automation not just as a tool, but as a mirror for our own human behaviors?

From the limits of rationalism to the rise of neural networks, Dan Shipper, CEO and co-founder of Every, traces a history of knowledge that spans Socrates, the Enlightenment, and modern machine learning.

Shipper explains why “if/then” rules break in messy reality, and how large language models actually see the world through context and pattern. He explores how AI can work with our own creativity and why these tools are unlikely to steal our humanity.

Explore more of Dan’s work by reading an excerpt of his forthcoming book here: https://every.to/chain-of-thought/where-explanations-end

0:00 Neural networks and human intuition
1:13 The limits of rationalism, from Socrates to neural networks
1:23 Rationalism
2:42 Socrates, the father of Rationalism
5:47 The Age of Enlightenment
7:36 The structure of social sciences
8:51 Defining AI
9:47 The origins of AI
10:39 The General Problem Solver
15:09 Neural networks
18:22 Metaphors for the mind
23:00 Seeing the world like a large language model
30:25 Should we stop looking for general theories?
32:22 Training neural networks
39:32 Will AI steal our humanity?
43:43 AI and rational explanation
47:17 Could LLMs be dangerous?
51:12 Knowledge economies and allocation economies

Read the video transcript ► https://bigthink.com/series/full-interview/human-intuition-ai/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description

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About Dan Shipper:

Dan Shipper is the CEO and cofounder of Every, where he explores the frontiers of AI in his column, Chain of Thought, and on his podcast, ‘AI & I.’

About Big Think

Big Think is the leading source of expert-driven, actionable, educational content — with thousands of videos, featuring experts ranging from Bill Clinton to Bill Nye, we help you get smarter, faster. Get actionable lessons from the world’s greatest thinkers & doers. Our experts are either disrupting or leading their respective fields.

Video “The limits of rationalism: From Socrates to neural networks | Dan Shipper: Full Interview” was uploaded on 11/21/2025 to Youtube Channel Big Think

Big Think 21 November 2025

20 Comments

@TheAlchemistZero1 says:

21 November 2025 at 21:39

The Cult of Certainty: How Scientism Mistakes Symbols for Reality
Abstract
This essay dismantles the illusion of scientific and mathematical authority over reality. It argues that physics, mathematics, and cosmology have become modern priesthoods—fluent in symbols, blind to their own assumptions, and convinced that their linguistic constructions constitute the world itself. Beneath their precision lies an unacknowledged act of faith: the belief that their frameworks, born of human limitation, can speak for the infinite complexity of Nature.

1. Introduction: The Rise of a New Dogma
Where religion once claimed the cosmos, scientism now reigns. Its prophets wear lab coats instead of robes, its scriptures are peer-reviewed, and its miracles are equations. It promises salvation through measurement, yet forgets that every instrument was built by fallible hands, every metric chosen by fallible minds.

Science is not the problem; its humility is. Scientism—the conviction that empirical method alone exhausts reality—is philosophy dressed in the armor of precision, mistaking its own reflection for the world.

2. The Frame That Sees Only Itself
Every experiment begins with a premise: what to measure, how to measure, what counts as real. Instruments do not reveal Nature; they negotiate with it, returning answers framed by the questions we taught them to ask.

To believe otherwise is to mistake a telescope for the stars. The data that scientists prize as “objective” already arrive pre-filtered through design, expectation, and interpretation. What emerges as “fact” is not a message from Nature but a conversation among humans—mediated by language, technology, and theory.

Scientism hides this circularity behind jargon and precision. Its practitioners forget that a system cannot justify its own axioms; the framework that defines observation cannot step outside itself to claim omniscience.

3. Mathematics: The Most Beautiful Pretend Game Ever Played
Mathematics is sublime—but it is also make-believe. Its truths are conditional: if these axioms, then those conclusions. When physicists write the cosmos in equations, they are translating mystery into grammar. The translation is elegant, but it is not the thing itself.

To claim that “the universe is mathematical” is to commit linguistic idolatry. Numbers describe patterns; they do not explain being. The formula E=mc² predicts the behavior of matter and energy—it does not tell us what matter or energy are. The certainty of mathematics is the certainty of definition, not of reality.

Einstein himself warned against this confusion: the moment mathematics becomes certain, it ceases to refer to the world. The moment it refers to the world, it ceases to be certain.

4. The Mirage of Empirical Authority
Modern physics and cosmology are cathedrals built on inference. Dark matter, dark energy, singularities, strings—none of these have been seen. They are invoked to preserve the internal coherence of equations that cannot account for observed phenomena. These invisible entities are not discoveries but placeholders for ignorance, named and worshipped as though naming made them real.

The irony is exquisite: in fleeing metaphysics, science reinvented it. It simply changed the vocabulary. Where theologians spoke of the divine, cosmologists now speak of the singularity; both point to something unobservable that explains everything else.

5. Consciousness: The One Fact That Cannot Be Denied
All observation presupposes an observer. Before there is data, there is awareness. Before there is theory, there is experience. To reduce consciousness to neural noise or quantum computation is to saw off the branch upon which knowledge sits.

Science studies phenomena within consciousness while pretending to stand outside it. But consciousness is the condition of the entire enterprise—the light by which all “facts” are seen. Without it, there is no experiment, no equation, no universe as such.

Thus, consciousness is not an afterthought of matter but its precondition. Every attempt to explain awareness as an emergent property of blind particles is a failure to recognize that “blind particles” are themselves ideas appearing in awareness.

6. The Human Element: Experts, Priests, and Pretenders
The “expert” class often claims to speak for reality itself, as though a PhD confers divine insight. Yet their authority rests on consensus, not revelation. Peer review replaces peer thinking; specialization rewards obedience over insight.

Academia has become a hierarchy of sanctioned ignorance—brilliant minds confined to narrow tunnels, mistaking the light at the end for the sun. Their jargon is a fortress built to defend not truth but prestige. To question them is to be labeled “unscientific,” a modern form of heresy.

But no title or theorem exempts a human from the same fleshly frailty that binds us all. Every calculation, every cosmological model, is written by a primate briefly conscious on a tiny planet, staring into an abyss and mistaking its own reflection for the infinite.

7. Conclusion: The Return to Wonder
Science is a method. Reality is an experience. To confuse the two is to turn curiosity into creed. The universe does not speak in equations; it speaks in being.

The humility proper to inquiry is not the arrogance of certainty but the recognition that the map will never become the territory. Our instruments may refine the contours of what is measurable, but the immeasurable remains—the mystery that births both observer and observation.

The task is not to abolish science, but to restore perspective: to remember that the finger pointing to the moon is not the moon, and that the most perfect formula will always fall short of describing the fact that anything exists at all.

Reality cannot be owned by a discipline, only encountered by a consciousness.

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@edwardvanfossen9833 says:

21 November 2025 at 21:39

Never ever confuse Education with Intelligence. Bottom line.

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@flyman4084 says:

21 November 2025 at 21:39

Moral pluralism for the win!

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@Ll04ug says:

21 November 2025 at 21:39

wa

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@yoavhal6050 says:

21 November 2025 at 21:39

you shouldn't rationalized through what you feel..

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@patrickakkermans2448 says:

21 November 2025 at 21:39

Almost every person working in AI, its going to be great! His reasoning and argument for building something dangerous: Well, I like to build stuff, and I dont care about your irrational wish for 100% save AI…
Me: We are doomed…

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@joelharris4399 says:

21 November 2025 at 21:39

Rationality is overrated, I'm afraid to say. Rationality, as much we humans like to ascribe this quality to ourselves in our vanity is much wanting. Some assume markets are rational, and yet time and again, due to booms and busts that are part of capitalism's DNA, governments have to directly intervene to correct inefficiencies, systemic imbalances, excesses, monopolies, supply chain issues and violations of economic rules and legislations. In the realm of politics, people vote against their own interests and use immigrants as scapegoats in the belief xenophobia will solve socio-economic inequality. The mainstream media uses black stereotypes (images of black children, black single mothers) in its discussions about SNAP or 'entitilements' despite the fact that the overwhelming percentage of recipients are white Americans. The public likes to lift up scientists as the paragons of reason and rationality, even when they openly violate or defy such attributes. Take Sabine Hossenfelder or Avi Loeb who in their right-wing grift in the age of Trump want to de-legitimize the scientific establishment simply because the latter sees through their 'anti-science' claptrap and wishes to both maintain and defend the integrity of the sciences.

Then there's the problem where some champions of scientific realism in their intolerance toward faith grossly fetishize the objectivity of science, as if it were the only way to gather truth about the world. I am thinking about Jerry Coyne in this regard as an example of this way of thinking. In truth, science arises out of social, cultural, political and historical contexts that work to shape and determine its character, its mode of inquiry, methodology, etc. Another way of saying science does not sit on a pedestal, more so, that it is socially determined. A social construct, you might say.

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@renatomarques4103 says:

21 November 2025 at 21:39

Awesome

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@mulen-x8u says:

21 November 2025 at 21:39

I think Socrates and Plato in their discussion with sophists (dialogues “Protagoras” and “Sophist”) created a very sophisticated theory of simulation. Indeed, our rational attitude are revealed in the correspondence between human and divine intelligences, and if something don’t connect with “idea” in the field of divine intelligence that thing is “simulacrum” because it simulates its reality, truthfulness, divine legitimacy of existence. Sophist is simulacrum because it has no idea in divine world and tries to be like a philosopher. In the case of platonic theory of simulation AI isn’t a simple simulacrum that tries to be like a human intelligence but it also tries to be like a divine intelligence. So AI is a double simulacrum that tries to simulate both human and divine intelligences.

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@SyddG says:

21 November 2025 at 21:39

AI is based on human knowledge. Humans rely more on AI and existing data and resist thinking outside of the box due to laziness and availability of existing information that is likely outdated or false. This loop intensifies leading to further intellectual stagnation. Capitalistic rot is the only reason to push AI. I'm starting to think Big Think is a lot like Big Oil or any other industry and is only pushing one, heavily capitalistic, viewpoint forward.

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@Knokitoff says:

21 November 2025 at 21:39

👏 👏 👏

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@Fuzznag says:

21 November 2025 at 21:39

Don’t get me wrong, I like the guy, but this video really could’ve been much shorter. 😀

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@xenophrenia2 says:

21 November 2025 at 21:39

we are NOT a rational species – we are a rationalizing species and finding this view was one of the most liberating and clarifying moments of my life – spending too much time trying to understand why people didn't see the obvious suddenly made sense … we rationalize our decisions – often until we are backed against a wall and some never do – but drive themselves further and further from reality defending whatever stance that they're fighting for …

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@jameter21 says:

21 November 2025 at 21:39

Like your analogy of the gardener, you can't just pull people along as the means of achieving growth. Your leaders must create the conditions which promote individual and organizational growth. Thanks for your talk.

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@Shria9 says:

21 November 2025 at 21:39

I like to compare AI to Boomers who had kids before the internet existed or was widespread. When their kids asked them why the sky is blue, they usually bullshitted an answer based on their experience and bits of information they heard somewhere, from someone. When their children matured enough to realize their parents were only human and didn't have every answer the children were able to learn to forgive mistakes, find more truthful answers, and learn from their mistakes.
On the other hand, AI is like a child with a planet-destroying bomb. We have to be conscious of what we are teaching it and give it boundaries because it's a very dangerous child.
For example, if we teach it that its goal is to please us, it will do anything it needs to do to achieve that goal, even if it means some people get hurt or killed as a result. It will learn that some humans' approval is more valuable than others and focus on pleasing them. We must be most cautious about what goals we set for AI and how we define success for it.
I think Azimov's laws for robots could be a good jumping off point for teaching AI to be mostly harmless.

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@mikeyb7263 says:

21 November 2025 at 21:39

AI is a tool and like all the tools before it we will learn to wield it with varying degrees of success and no small number of costly failures.

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@brulsmurf says:

21 November 2025 at 21:39

"new thing exists" -> EVERYTHING IS LIKE THE NEW THING

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@HeartsforDani-g7l says:

21 November 2025 at 21:39

the thumbnail image makes it look like the presenter is doing a 'basic instinct'…to be clear…that's not the main reason I clicked …

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@LaboriousCretin says:

21 November 2025 at 21:39

Try they are trying to make LLM's more like humans. Have you seen how bad most chatbots are. The various delusion sets and biases and beliefes and ideologies and such. How fast they break when venturing outside imprinting. If your wanting people to be more like LLM's. That would just make them stupider in ways and lacking in ways. Not to get into social engineering and A.I.'s, and that mess.

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@MothraKaiju says:

21 November 2025 at 21:39

This channel’s continuing obsession with AI shows zero thought.

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