The Deeper Thinking Podcast

We Modeled the World Before We Understood It - The Deeper Thinking Podcast


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We Modeled the World Before We Understood It

How Generative AI Is Rewriting Science, Reality, and the Meaning of Discovery

The Deeper Thinking Podcast

What if science no longer uncovered reality—but generated it? In an age where AlphaFold predicts faster than biology can observe, where systems like generative AI simulate truth before it's tested, the foundations of knowledge begin to shift. This episode explores the quiet revolution in epistemology catalyzed by models trained not to understand, but to perform—where the output comes before the insight, and the scientific method begins to fade from center stage.

This is not speculation. It is already here. From computational biology to climate modeling, generative systems are rendering futures not yet seen, and versions of nature that were never empirically touched. The result is a strange inversion: where once theory emerged from experience, now experience is shaped by the models we trust. If Kuhn's paradigms were ruptured by anomalies, today's paradigms are replaced by architectures that outperform the need for justification.

But this isn’t just a technical shift. It’s philosophical, ethical, and deeply human. As the observer recedes and the model takes precedence, we must confront what it means to assign value—to curate realities we did not discover, but merely selected. This episode journeys through the conceptual terrain where simulation supersedes observation, and asks: what remains uniquely human when the world is built before it is known?

Why Listen?
  • Understand the shift from empirical science to generative models
  • Explore how AI is reshaping the philosophy of knowledge and discovery
  • Unpack the ethical tensions of systems that create without understanding
  • Reflect on human meaning-making in a versioned, simulated world
  • Further Reading

    As an affiliate, we may earn from qualifying purchases through these links.

    • The Structure of Scientific Revolutions by Thomas Kuhn — A foundational text on how science evolves through paradigm shifts.

      Amazon link

    • How We Became Posthuman by N. Katherine Hayles — A critical look at how computation reshapes identity, embodiment, and knowledge.

      Amazon link

    • The Poetics of Space by Gaston Bachelard — A poetic philosophy of imagined worlds and scientific reverie.

      Amazon link

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        Abstract

        This essay examines the emergence of a post-empirical paradigm in scientific inquiry, driven by the generative capacities of artificial intelligence. As systems like AlphaFold and Gemini surpass human capabilities in prediction and simulation, the traditional epistemology of observation and experimentation begins to erode. Knowledge is no longer extracted from nature—it is synthesized, versioned, and rendered before empirical validation. The essay argues that science is shifting from a mode of discovery to one of architectural performance, where truth is measured by coherence and utility rather than correspondence. In this new landscape, the role of the human transitions from knower to curator, from discoverer to meaning-maker. Drawing on philosophical echoes of Kuhn, Haraway, and Bachelard, the essay articulates a quiet manifesto for navigating a world where reality is not found but generated—and where the responsibility for interpretation, ethics, and selection remains irreducibly human.

         

        Bibliography 

        Epistemology, Philosophy of Science, and Paradigm Shifts
        • Bachelard, Gaston. The New Scientific Spirit. Translated by Arthur Goldhammer. Boston: Beacon Press, 1984.

        • Feyerabend, Paul. Against Method. London: Verso Books, 1975.

        • Hacking, Ian. Representing and Intervening: Introductory Topics in the Philosophy of Natural Science. Cambridge: Cambridge University Press, 1983.

        • Kuhn, Thomas S. The Structure of Scientific Revolutions. 2nd ed. Chicago: University of Chicago Press, 1970.

        • Popper, Karl. The Logic of Scientific Discovery. London: Routledge, 1959.

          Simulation, Models, and Reality
          • Baudrillard, Jean. Simulacra and Simulation. Translated by Sheila Faria Glaser. Ann Arbor: University of Michigan Press, 1994.

          • Floridi, Luciano. The Philosophy of Information. Oxford: Oxford University Press, 2011.

          • Frigg, Roman, and Stephan Hartmann. “Models in Science.” In The Stanford Encyclopedia of Philosophy, edited by Edward N. Zalta. Summer 2022 Edition. https://plato.stanford.edu/entries/models-science/.

          • Vespignani, Alessandro. “Predicting the Behavior of Techno-Social Systems.” Science 325, no. 5939 (2009): 425–28.

          • Winsberg, Eric. Science in the Age of Computer Simulation. Chicago: University of Chicago Press, 2010.

            AI, Generative Systems, and Posthumanism
            • Bridle, James. Ways of Being: Beyond Human Intelligence. New York: Farrar, Straus and Giroux, 2022.

            • Crawford, Kate. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press, 2021.

            • Haraway, Donna. “A Cyborg Manifesto: Science, Technology, and Socialist-Feminism in the Late Twentieth Century.” In Simians, Cyborgs, and Women: The Reinvention of Nature, 149–181. New York: Routledge, 1991.

            • Hayles, N. Katherine. How We Became Posthuman: Virtual Bodies in Cybernetics, Literature, and Informatics. Chicago: University of Chicago Press, 1999.

            • Mitchell, Melanie. Artificial Intelligence: A Guide for Thinking Humans. New York: Farrar, Straus and Giroux, 2019.

              Ethics, Meaning, and Technological Power
              • Arendt, Hannah. The Human Condition. 2nd ed. Chicago: University of Chicago Press, 1998.

              • Jonas, Hans. The Imperative of Responsibility: In Search of an Ethics for the Technological Age. Chicago: University of Chicago Press, 1984.

              • Morozov, Evgeny. To Save Everything, Click Here: The Folly of Technological Solutionism. New York: PublicAffairs, 2013.

              • O’Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown Publishing Group, 2016.

              • Wiener, Norbert. The Human Use of Human Beings: Cybernetics and Society. Boston: Houghton Mifflin, 1950.

                Supplemental Readings (Advanced / Theoretical)
                • Deleuze, Gilles. Difference and Repetition. Translated by Paul Patton. New York: Columbia University Press, 1994.

                • Flusser, Vilém. Towards a Philosophy of Photography. Translated by Anthony Mathews. London: Reaktion Books, 2000.

                • Parisi, Luciana. Contagious Architecture: Computation, Aesthetics, and Space. Cambridge, MA: MIT Press, 2013.

                • Sloterdijk, Peter. Foams: Spheres Volume III: Plural Spherology. Translated by Wieland Hoban. Los Angeles: Semiotext(e), 2016.

                • Tsing, Anna Lowenhaupt. The Mushroom at the End of the World: On the Possibility of Life in Capitalist Ruins. Princeton: Princeton University Press, 2015.

                   

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