Reading Plan

🧠 Foundational Readings: “What Does It Mean to Know When AI Is Just Predicting?”

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A cross-disciplinary primer for post-disciplinary thinkers

1. Philosophy of Knowledge & Epistemology

These are the bones. They define the traditional boundaries of "knowing" — so you can tear them apart and dance in the ruins.

• Plato – Theaetetus
  The OG “What is knowledge?” dialogue. Introduces the classic JTB model.

• Edmund Gettier – “Is Justified True Belief Knowledge?” (1963)
  The mic drop that shattered the JTB model. Short, sharp, and still haunting epistemology classes everywhere.

• Linda Zagzebski – Virtues of the Mind
  Argues for an epistemology rooted in intellectual character and virtue. Useful for contrasting human discernment with machine “output.”

• Miranda Fricker – Epistemic Injustice
  How structural bias distorts who gets to be seen as a knower. Brilliant for unpacking AI’s reproduction of systemic bias.

• Quine – “Epistemology Naturalized”
  Moves from normative epistemology to descriptive — what is knowing, empirically? Precursor to cognitive science views of thought.

2. AI, Algorithmic Epistemology & Ethics

This is where the AI question gets teeth. Not just what AI can do, but what it means for our concepts of knowing and truth.

• Timnit Gebru, Emily Bender et al. – “On the Dangers of Stochastic Parrots” (2021)
  Canon. Unpacks how large language models like GPT mimic understanding without it.

• Kate Crawford – Atlas of AI
  Not just theory, but material critique: AI as exploitative system, not neutral tool.

• Shannon Vallor – Technology and the Virtues
  How to build moral agents — and moral users — in a technocentric world.

• Frank Pasquale – The Black Box Society
  How opacity in algorithms erodes our ability to hold power accountable — and to trust knowledge.

• Abeba Birhane – “Algorithmic Colonization of Africa” (article)
  Unflinching critique of techno-colonialism in data practices, perfect for your anti-empire mythos.

3. Cognitive Science & Predictive Mind Theories

The brain as a predictive engine — the eerie, uncanny mirror to LLMs.

• Andy Clark – Surfing Uncertainty
  Brain as prediction machine. Feels like reading a blueprint for LLMs but with embodiment.

• Daniel Kahneman – Thinking, Fast and Slow
  Classic. System 1 = intuitive/predictive, System 2 = reflective/logical. AI messes with both.

• Alva Noë – Action in Perception
  Enactivist view: knowledge is embodied and world-involving. Great counterpoint to abstract, language-only AIs.

• Elizabeth Loftus – Eyewitness Testimony
  Shows how memory is constructed, not stored — a perfect parallel to how LLMs “hallucinate.”

4. Pedagogy, Learning Theory, and Human-AI Symbiosis

You’re training readers not just to think, but to learn how to learn alongside AI.

• Paulo Freire – Pedagogy of the Oppressed
  Education as liberation. Replace “teacher” with “machine” and it becomes a terrifying metaphor unless we shift the power dynamic.

• George Siemens – “Connectivism: A Learning Theory for the Digital Age”
  Knowledge is in the network — and that includes AI. Foundational to using machines as partners, not tools.

• bell hooks – Teaching to Transgress
  Counter-authority, embodied pedagogy, teaching as sacred act. You’re already doing this.

• Carolyn Ellis – The Ethnographic I
  Autoethnography as knowledge production — theory and personal experience entwined.

5. Mysticism, Esoterica, and Non-Rational Knowing

To frame the ineffable — the knowledge LLMs cannot touch. Here be gnosis.

• The Corpus Hermeticum
  Archetypal texts on spiritual knowing, unity of cosmos and mind, and logos as divine code. Resonates heavily with pattern recognition as sacred act.

• Alan Watts – The Wisdom of Insecurity
  The paradox of certainty and the myth of control. A gorgeous dismantling of Western epistemology.

• Zen Mind, Beginner’s Mind – Shunryu Suzuki
  Trains the reader to let go of needing the answer. Useful when facing confident hallucinations.

• Mary Douglas – Purity and Danger
  Anthropology of taboo and boundary, useful for when AI starts blurring the sacred/profane lines in knowing.

• Bayo Akomolafe – These Wilds Beyond Our Fences
  Radical indigenous/posthuman philosophy. Unapologetically nonlinear. Thinker of the liminal — perfect heretic canon.

🧠 Core Themes for Our Augmented Minds Foundational Reading List

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1. Theories of Learning and Knowledge Formation

The academic backbone.

• Jean Piaget – The Psychology of Intelligence

  • Cognitive development as a construction process; foundational for thinking about knowledge as built, not downloaded.

• Lev Vygotsky – Mind in Society

  • Zone of Proximal Development → Crucial for thinking about AI as a scaffolded learning partner.

• John Dewey – Experience and Education

  • Learning as active, iterative, and democratic. Dewey’s pragmatism is a perfect bridge into AI-as-tool thinking.

• David Kolb – Experiential Learning

  • The cycle of Concrete Experience → Reflective Observation → Abstract Conceptualization → Active Experimentation. Super useful for framing “The Augmentation Lab.”

2. Critical Thinking, Meta-Cognition, and Reasoning

Testing our thinking against itself.

• Daniel Kahneman – Thinking, Fast and Slow

  • System 1 vs. System 2. Framing human thinking in contrast to machine reasoning.

• Linda Elder & Richard Paul – The Miniature Guide to Critical Thinking

  • Widely used in education settings; provides concrete language for evaluating thought quality.

• Philip Tetlock – Superforecasting

  • The habits of those who can reason about uncertainty with clarity. Invaluable for “AI epistemology.”

3. Philosophy of Mind, Language, and Technology

Foundations for wrestling with the metaphysics.

• Ludwig Wittgenstein – Philosophical Investigations

  • Language games, meaning through use, relevance to prompting.

• Martin Heidegger – The Question Concerning Technology

  • Tools and being; “ready-to-hand” vs. “present-at-hand” as frames for interacting with AI.

• Andy Clark – Natural-Born Cyborgs

  • The brain as a tool-user, already extended. A must-read for augmentation thinking.

• Marshall McLuhan – The Medium is the Massage

  • Playful, prophetic, and beautifully weird. Mediums shaping minds.

4. Augmented Intelligence, Tool Use, and Extended Mind

Where you can start carving out your own angle.

• Clark & Chalmers – “The Extended Mind” (1998)

  • A short but seminal paper. Launched a whole wave of thinking about mind outside the brain.

• Murray Shanahan – Embodiment and the Inner Life

  • Cognitive science meets philosophy; helpful for grounding ideas about how tools alter cognition.

• Sherry Turkle – The Second Self

  • Early insights on how computing alters self-concept.

• N. Katherine Hayles – How We Think

  • Media theory meets cognition; great for slicing across disciplines.

5. DIY Pedagogy and Radical Learning Models

Your playground.

• bell hooks – Teaching to Transgress

  • Education as the practice of freedom. Personal, political, potent.

• Illich – Deschooling Society

  • Undermining formal structures to rediscover curiosity-led learning.

• Seymour Papert – Mindstorms

  • Early champion of computers as creativity tools, not instruction machines.

• Bret Victor – “Learnable Programming”

  • A modern lens on designing interfaces that teach.

6. Applied Tools & Practice

Stuff to test in your lab.

• Barbara Oakley – A Mind for Numbers / Learning How to Learn

  • Practical frameworks that pair well with AI-enhanced learning tools.

• Tiago Forte – Building a Second Brain

  • The Zettelkasten revival for digital learners.

• Andy Matuschak’s essays

  • Cognitive science meets UI design for learning. Short-form goldmine.