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Learning Under Algorithmic Conditions
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Notes

table of contents
  1. Cover
  2. Half Title Page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Introduction
  7. Part 1. Imitation, Thought, and Reason
    1. 1. Technics and Text: Guided by Gilbert Simondon
    2. 2. Deviation Games: Desire and the Pedagogy of Thought
    3. 3. Number Sense in Large Language Models
  8. Part 2. Bodies, Brains, and Common Sense
    1. 4. Neuro-symbolic Algorithms and the Infant Mind
    2. 5. The Problem of Algorithmic Commonsense Learning
    3. 6. Learning on the Neuromorphic Circuit
  9. Part 3. Curriculum, Control, and Computation
    1. 7. Who Controls the Curriculum for AI? The Limits of Participatory Design for Educational AI
    2. 8. Learning to Program
    3. 9. Computational Thinking and Software Studies
  10. Part 4. Mysticism, Robots, and Genetic Algorithms
    1. 10. Machine Learning Ecologies and Self-Organization
    2. 11. Meaningful Robot Learning
    3. 12. Bioinformatic Algorithms and Educational Genomics
  11. Part 5. Viral Affect and School Interfaces
    1. 13. The Urban Public School as Cybernetic Apparatus
    2. 14. Algorithms and Immediacy
    3. 15. Responsible AI and Learning to Language
  12. Part 6. The Onto-Epistemology of Colonial Instrumental Reason
    1. 16. Machining Coloniality and Learning Otherwise
    2. 17. Noisy Compression and Colonial Violence
    3. 18. Instrumentalizing Colonial Reason
  13. Part 7. Life and the Limits of Computation
    1. 19. Learning in the New Dispersed Prime Time
    2. 20. Machine Learning and the Digital Archiving of Death
    3. 21. Thinking Softly with Incomputability
  14. Part 8. Multimodal Learning with Unruly Tools
    1. 22. Learning by Co-constructing with Stupid (but Useful) Generative AI
    2. 23. Digital Technologies and Perceptual Curation
    3. 24. Technosocial Scotomas in the Algorithmic Age
  15. Part 9. The Disruptive Technical Being of Generative AI
    1. 25. Prompt Battles and the Conundrums of Logos
    2. 26. Machine Learning and Its Operational Diagrams
    3. 27. Algorithmic Creativity, Deception, and Delirium
  16. Acknowledgments
  17. Contributors

Contents

  1. Introduction

    Elizabeth de Freitas, Matthew X. Curinga, Ezekiel J. Dixon-Román, and P. Taylor Webb

  2. Part 1. Imitation, Thought, and Reason

    1. Technics and Text: Guided by Gilbert Simondon

      Elizabeth de Freitas

    2. Deviation Games: Desire and the Pedagogy of Thought

      Arkady Plotnitsky

    3. Number Sense in Large Language Models

      Julian Quiros

  3. Part 2. Bodies, Brains, and Common Sense

    1. Neuro-symbolic Algorithms and the Infant Mind

      Elizabeth de Freitas

    2. The Problem of Algorithmic Commonsense Learning

      Carolyn Pedwell

    3. Learning on the Neuromorphic Circuit

      Henry Neim Osman

  4. Part 3. Curriculum, Control, and Computation

    1. Who Controls the Curriculum for AI? The Limits of Participatory Design for Educational AI

      Michael Madaio

    2. Learning to Program

      Warren Sack

    3. Computational Thinking and Software Studies

      Matthew X. Curinga

  5. Part 4. Mysticism, Robots, and Genetic Algorithms

    1. Machine Learning Ecologies and Self-Organization

      Craig Carson

    2. Meaningful Robot Learning

      Cathrine Hasse

    3. Bioinformatic Algorithms and Educational Genomics

      Ben Williamson

  6. Part 5. Viral Affect and School Interfaces

    1. The Urban Public School as Cybernetic Apparatus

      Rebecca Uliasz

    2. Algorithms and Immediacy

      Gregory J. Seigworth

    3. Responsible AI and Learning to Language

      David Wagner

  7. Part 6. The Onto-Epistemology of Colonial Instrumental Reason

    1. Machining Coloniality and Learning Otherwise

      R. Joshua Scannell

    2. Noisy Compression and Colonial Violence

      Luciana Parisi

    3. Instrumentalizing Colonial Reason

      Ezekiel Dixon-Román

  8. Part 7. Life and the Limits of Computation

    1. Learning in the New Dispersed Prime Time

      Talha Can İşsevenler

    2. Machine Learning and the Digital Archiving of Death

      Felicity Colman

    3. Thinking Softly with Incomputability

      P. Taylor Webb

  9. Part 8. Multimodal Learning with Unruly Tools

    1. Learning by Co-constructing with Stupid (but Useful) Generative AI

      Sina Rismanchian and Shayan Doroudi

    2. Digital Technologies and Perceptual Curation

      Robb Lindgren

    3. Technosocial Scotomas in the Algorithmic Age

      Edward Dieterle

  10. Part 9. The Disruptive Technical Being of Generative AI

    1. Prompt Battles and the Conundrums of Logos

      David Gauthier

    2. Machine Learning and Its Operational Diagrams

      Goda Klumbytė

    3. Algorithmic Creativity, Deception, and Delirium

      Elizabeth de Freitas

  11. Acknowledgments
  12. Contributors

Annotate

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The University of Minnesota Press gratefully acknowledges the generous assistance provided for the publication of this book by the University of British Columbia, Columbia University, and Adelphi University.

Chapter 1 contains portions previously published, in modified form, from Elizabeth de Freitas, “Fragile Books and Machine Readers: Trans/in/dividual Reading Tactics in a Complex Technical Milieu,” International Journal of Qualitative Studies in Education 37, no. 6 (2024): 1655–65; reprinted by permission of the publisher (Taylor & Francis Ltd, https://www.tandfonline.com). Portions of chapter 5 were previously published in a different form in Carolyn Pedwell, “The Intuitive and the Counter-intuitive: AI and the Affective Ideologies of Common Sense,” New Formations 112 (2024): 70–93.

Copyright 2026 by the Regents of the University of Minnesota

Learning Under Algorithmic Conditions is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), https://creativecommons.org/licenses/by-nc-nd/4.0/.
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