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Algorithms of Education: Notes

Algorithms of Education
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table of contents
  1. Cover
  2. Half Title Page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Introduction. Synthetic Governance: Algorithms of Education
  7. 1. Governing: Networks, Artificial Intelligence, and Anticipation
  8. 2. Thought: Acceleration, Automated Thinking, and Uncertainty
  9. 3. Problems: Concept Work, Ethnography, and Policy Mobility
  10. 4. Infrastructure: Interoperability, Datafication, and Extrastatecraft
  11. 5. Patterns: Facial Recognition and the Human in the Loop
  12. 6. Automation: Data Science, Optimization, and New Values
  13. 7. Synthetic Politics: Responding to Algorithms of Education
  14. Acknowledgments
  15. Notes
  16. Image Descriptions
  17. Index
  18. About the Authors

Notes

Introduction

  1. The Turing test is broadly a test to see if a computer can think like, and pass for, a human. See B. J. Copeland, “The Turing Test,” Minds and Machines 10, no. 4 (2000): 519–39.

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  2. A. Ireland, “Black Circuit: Code for the Numbers to Come,” E-Flux Journal no. 80 (March 2017), http://worker01.e-flux.com/pdf/article_100016.pdf., n.p. Another take on Ava is that it personifies a feminist vengeance that is absolutely necessary. In other words, Ava is a technological/AI accelerant for a feminist future.

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  3. N. Selwyn, Should Robots Replace Teachers? (Cambridge: Polity Press, 2019).

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  4. M. A. Boden, AI: Its Nature and Future (Oxford: Oxford University Press, 2016), 1.

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  5. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 3rd ed. (Harlow, Essex: Pearson Education, 2016), 2–3.

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  6. Boden, AI: Its Nature and Future.

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  7. A. Mackenzie, “The Production of Prediction: What Does Machine Learning Want?,” European Journal of Cultural Studies 18, no. 4–5 (2015): 429–45.

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  8. G. Deleuze and F. Guattari, A Thousand Plateaus: Capitalism and Schizophrenia (Minneapolis: University of Minnesota Press, 1987), 219.

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  9. C. Perrotta, K. N. Gulson, B. Williamson, and K. Witzenberger, “Automation, APIs and the Distributed Labour of Platform Pedagogies in Google Classroom,” Critical Studies in Education 62, no. 1 (2021): 97–113.

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  10. Thanks to Colin Symes for this wording.

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  11. B. Williamson, “Digital Education Governance: An Introduction,” European Educational Research Journal 15, no. 1 (2016): 5.

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  12. N. Rose, Powers of Freedom: Reframing Political Thought (Cambridge: Cambridge University Press, 1999), 24.

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  13. A. Barry, T. Osborne, and N. Rose, introduction to Foucault and Political Reason: Liberalism, Neo-Liberalism, and the Rationalities of Government, ed. A. Barry, T. Osborne, and N. Rose (Abingdon, Oxon: Routledge, 1996), 7.

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  14. M. Bevir and R. A. W. Rhodes, “Decentred Theory, Change, and Network Governance,” in Theories of Democratic Network Governance, ed. E. Sørensen and G. Torfing (London: Palgrave Macmillan, 2007).

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  15. Kevin Witzenberger has used the term automated education governance in his PhD thesis (University of New South Wales, Australia). See also K. N. Gulson and K. Witzenberger, “Repackaging Authority: Artificial Intelligence, Automated Governance, and Education Trade Shows,” Journal of Education Policy (2020): 1–16.

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  16. G. Deleuze and F. Guattari, Anti-Oedipus (Minneapolis: University of Minnesota Press, 1983).

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  17. We note here the extensive field of computational thinking and the field of computational rationality (which was the early term for artificial intelligence): S. J. Gershman, E. J. Horvitz, and J. B. Tenenbaum, “Computational Rationality: A Converging Paradigm for Intelligence in Brains, Minds, and Machines,” Science 349, no. 6245 (2015): 273–78. However, we note that we speak broadly to but not from this field. Our interests in computation and thinking come more from the field of feminist technoscience and Science and Technology Studies.

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  18. G. Thompson, “Computer Adaptive Testing, Big Data, and Algorithmic Approaches to Education,” British Journal of Sociology of Education 38, no. 6 (2017): 827–40; E. de Freitas, “The Temporal Fabric of Research Methods: Posthuman Social Science and the Digital Data Deluge,” Research in Education 98, no. 1 (2017): 27–43; A. J. Means, “Hypermodernity, Automated Uncertainty, and Education Policy Trajectories,” Critical Studies in Education 62, no. 3 (2021): 371–86; B. Williamson, “Who Owns Educational Theory? Big Data, Algorithms, and the Expert Power of Education Data Science,” E-Learning and Digital Media 14, no. 3 (2017): 105–22.

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  19. A. L. Feenberg, “Concretizing Simondon and Constructivism: A Recursive Contribution to the Theory of Concretization,” Science, Technology, and Human Values 42, no. 1 (2017): 63.

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  20. Y. Van Den Eede, “Where Is the Human? Beyond the Enhancement Debate,” Science, Technology, and Human Values 40 (2015): 151; J. Ellul, The Technological Society, trans. J. Wilkinson (New York: Vantage Books, 1964); M. Heidegger, The Question concerning Technology and Other Essays, trans. W. Lovitt (New York: HarperPerennial, 1977).

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  21. G. Deleuze, Negotiations: 1972–1990, trans. Martin Joughin (New York: Columbia University Press, 1995), 175.

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  22. A. Mackenzie, “Problematising the Technological: The Object as Event?,” Social Epistemology 19, no. 4 (2005): 397.

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  23. B. G. Peters and J. Pierre, “Governance without Government? Rethinking Public Administration,” Journal of Public Administration Research and Theory 8, no. 2 (1998): 223–43.

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  24. T. Fenwick, E. Mangez, and J. Ozga, “Governing Knowledge: Comparison, Knowledge-Based Technologies, and Expertise in the Regulation of Education,” in Governing Knowledge: Comparison, Knowledge-Based Technologies, and Expertise in the Regulation of Education, ed. T. Fenwick, E. Mangez, and J. Ozga (London: Routledge, 2014), 5.

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  25. A. Wilkins and A. Olmedo, “Introduction: Conceptualizing Education Governance: Framings, Perspectives, and Theories,” in Education Governance and Social Theory: Interdisciplinary Approaches to Research, ed. A. Wilkins and A. Olmedo (London: Bloomsbury, 2019), 2.

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  26. Wilkins and Olmedo, “Introduction,” 5.

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  27. R. A. W. Rhodes, “Understanding Governance: Ten Years On,” Organization Studies 28, no. 8 (2007): 1246.

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  28. D. Cohen, “Market Mobilities/Immobilities: Mutation, Path-Dependency, and the Spread of Charter School Policies in the United States,” Critical Studies in Education 58, no. 2 (2017): 168–86; S. J. Ball and C. Junemann, Networks, New Governance, and Education (Bristol: Policy Press, 2012); F. Rizvi and B. Lingard, Globalizing Educational Policy (London: Routledge, 2010).

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  29. R. A. W. Rhodes, Understanding Governance Policy Networks, Governance, Reflexivity, and Accountability (Buckingham: Open University Press, 1997).

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  30. M. Lawn, “A Systemless System: Designing the Disarticulation of English State Education,” European Educational Research Journal 12, no. 2 (2013): 240.

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  31. Ireland, “Black Circuit.”

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  32. D. Easton, The Political System (New York: Knopf, 1953).

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  33. C. Lury, L. Parisi, and T. Terranova, “Introduction: The Becoming Topological of Culture,” Theory, Culture, and Society 29, no. 4–5 (2012): 28.

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  34. A. Desrosières, The Politics of Large Numbers: A History of Statistical Reasoning (Cambridge, Mass.: Harvard University Press, 2002), 8.

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  35. Ball and Junemann, Networks, New Governance, and Education; Lawn, “Systemless System”; J. Ozga, “Governing Education through Data in England: From Regulation to Self-Evaluation,” Journal of Education Policy 24, no. 2 (2009): 149–62.

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  36. Deleuze and Guattari, Thousand Plateaus.

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  37. J. S. Nye, “Public Diplomacy and Soft Power,” The ANNALS of the American Academy of Political and Social Science 616, no. 1 (2008): 94–109.

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  38. Lee S. Shulman, “Theory, Practice, and the Education of Professionals,” Elementary School Journal 98, no. 5 (1998): 511–26.

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  39. T. Gillespie, “The Relevance of Algorithms,” in Media Technologies, ed. T. Gillespie, P. J. Boczkowski, and K. A. Foot (Cambridge, Mass.: MIT Press, 2014).

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  40. B. Reider, Engines of Order: A Mechanology of Algorithmic Techniques (Amsterdam: Amsterdam University Press, 2020), 16.

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  41. D. Savat, “Introduction: Deleuze and New Technology,” in Deleuze and New Technology, ed. M. Poster and D. Savat (Edinburgh: Edinburgh University Press, 2009), 3.

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  42. D. Beer, Metric Power (London: Palgrave Macmillan, 2016), 111.

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  43. Y. N. Harari, Homo Deus: A Brief History of Tomorrow (London: Harvill Secker, 2015), 345.

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  44. A. Mackenzie, “Machine Learning and Genomic Dimensionality: From Features to Landscapes,” in Postgenomics: Perspectives on Biology after the Genome, ed. S. S. Richardson and H. Stevens (Durham, N.C.: Duke University Press, 2015); H. Stevens, Life out of Sequence: A Data-Driven History of Bioinformatics (Chicago: University of Chicago Press, 2013).

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  45. A. R. Galloway and E. Thacker, The Exploit: A Theory of Networks (Minneapolis: University of Minnesota Press, 2007), 123.

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  46. O. Halpern, “Cybernetic Rationality,” Distinktion: Journal of Social Theory 15, no. 2 (2014): 224.

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  47. Y. Dror, “Prolegomena to Policy Sciences,” Policy Sciences 1, no. 1 (1970): 135–50; E. Rindzevičiūtė, The Power of Systems: How Policy Sciences Opened Up the Cold War World (Ithaca, N.Y.: Cornell University Press, 2016).

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  48. P. Adams, “Education Policy: Explaining, Framing, and Forming,” Journal of Education Policy 31, no. 3 (2016): 293.

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  49. I. Hacking, “Biopower and the Avalanche of Printed Numbers,” in Biopower: Foucault and Beyond, ed. V. W. Cisney and N. Morar (Chicago: University of Chicago Press, 2016): 65–81; Adams, “Education Policy: Explaining, Framing, and Forming”; D. Lerner and H. D. Laswell, The Policy Sciences: Recent Developments in Scope and Method (Stanford: Stanford University Press, 1951).

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  50. M. Simons, M. Olssen, and M. A. Peters, “Re-Reading Education Policies, Part 1: The Critical Policy Orientation,” in Re-Reading Education Policies: A Handbook Studying the Policy Agenda of the 21st Century, ed. M. Simons, M. Olssen, and M. A. Peters (Rotterdam: Sense Publishers, 2009), 15.

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  51. See Centre for Education Statistics and Evaluation, https://www.cese.nsw.gov.au/.

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  52. Williamson, “Who Owns Educational Theory?”

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  53. J. Bridle, New Dark Age: Technology and the End of the Future (London: Verso, 2018), 40.

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  54. N. Cranston, M. Kimber, B. Mulford, A. Reid, and J. Keating, “Politics and School Education in Australia: A Case of Shifting Purposes,” Journal of Educational Administration 48, no. 2 (2010): 182–95.

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  55. M. Power, “The Theory of Audit Explosion,” in The Oxford Handbook of Public Management, ed. E. Ferlie, L. E. Lynn, and C. Pollitt (Oxford: Oxford University Press, 2007).

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  56. B. Anderson, “Preemption, Precaution, Preparedness: Anticipatory Action and Future Geographies,” Progress in Human Geography 34, no. 6 (2010): 777–98.

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  57. S. Zuboff, The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power (New York: Public Affairs, 2019).

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  58. D. H Guston, “Understanding ‘Anticipatory Governance,’” Social Studies of Science 44, no. 2 (2014): 218, original emphasis.

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  59. P. N. Edwards, G. C. Bowker, S. J. Jackson, and R. Williams, “Introduction: An Agenda for Infrastructure Studies,” Journal of the Association for Information Systems 10, no. 5 (2009): 364–74; S. L. Star, “The Ethnography of Infrastructure,” American Behavioral Scientist 43, no. 3 (1999): 377–91.

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  60. L. G. Berlant, “The Commons: Infrastructures for Troubling Times,” Environment and Planning D: Society and Space 34, no. 3 (2016): 393–419; K. Easterling, Extrastatecraft: The Power of Infrastructure Space (New York: Verso Books, 2014); B. Larkin, “The Politics and Poetics of Infrastructure,” Annual Review of Anthropology 42, no. 1 (2013): 327–43; N. Rossiter, Software, Infrastructure, Labor: A Media Theory of Logistical Nightmares (New York: Routledge, 2017).

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  61. Easterling, Extrastatecraft, 80.

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  62. Bridle, New Dark Age, 8.

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  63. Fenwick, Mangez, and Ozga, “Governing Knowledge”; B. Williamson, “New Power Networks in Educational Technology,” Learning, Media, and Technology 44, no. 4 (2019): 395–98.

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  64. D. Roden, Posthuman Life: Philosophy at the Edge of the Human (London: Routledge, 2015).

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  65. Though see recent work: Sam Sellar and David R. Cole, “Accelerationism: A Timely Provocation for the Critical Sociology of Education,” British Journal of Sociology of Education 38, no. 1 (2017): 38–48.

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  66. N. Land and R. Mackay, Fanged Noumena: Collected Writings 1987–2007 (Falmouth, UK: Urbanomic, 2014).

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  67. For critique see B. Noys, Malign Velocities: Accelerationism and Capitalism (Winchester, UK: Zero Books, 2014). And see also Bridle’s (New Dark Age) discussion that asks us to consider whether the accelerationist thesis can escape the disparate framings of contemporary technology, and the idea that inequality is part of this emergence.

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  68. B. Williamson, “Silicon Startup Schools: Technocracy, Algorithmic Imaginaries, and Venture Philanthropy in Corporate Education Reform,” Critical Studies in Education 59, no. 2 (2018): 218–36; Erica Southgate, Artificial Intelligence, Ethics, and Higher Education: A “Beginning-of-the-Discussion” Paper (Perth: National Centre in Student Equity and Higher Education, Curtin University and the University of Newcastle, 2020); A. R. Galloway and E. Thacker, The Exploit: A Theory of Networks (Minneapolis: University of Minnesota Press, 2007).

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  69. L. Parisi, “Automated Thinking and the Limits of Reason,” Cultural Studies ↔ Critical Methodologies 16, no. 5 (2016): 471–81.

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  70. B. Flyvbjerg, Making Social Science Matter: Why Social Inquiry Fails and How It Can Succeed Again (Cambridge: Cambridge University Press, 2001), 167.

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1. Governing

  1. Gibson’s use of the line in the epigraph is multiple. For example, see “Survey: Peering Round the Corner,” The Economist 360, no. 8235 (Oct. 13, 2001): 6.

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  2. For discussion of teacher professionalism and changes, including performativity and policy, see D. Beach and C. Bagley, “Changing Professional Discourses in Teacher Education Policy Back towards a Training Paradigm: A Comparative Study,” European Journal of Teacher Education 36, no. 4 (2013): 379–92; S. J. Ball, M. Maguire, and A. Braun, How Schools Do Policy: Policy Enactments in Secondary Schools (London: Routledge, 2012).

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  3. M. Fourcade and J. Gordon, “Learning Like a State: Statecraft in the Digital Age,” Journal of Law and Political Economy 1, no. 1 (2020): 80.

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  4. A. Wilkins and A. Olmedo, “Introduction: Conceptualizing Education Governance: Framings, Perspectives, and Theories,” in Education Governance and Social Theory: Interdisciplinary Approaches to Research, ed. A. Wilkins and A. Olmedo (London: Bloomsbury, 2019), 9.

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  5. T. Fenwick, E. Mangez, and J. Ozga, “Governing Knowledge: Comparison, Knowledge-Based Technologies, and Expertise in the Regulation of Education,” in Governing Knowledge: Comparison, Knowledge-Based Technologies, and Expertise in the Regulation of Education, ed. T. Fenwick, E. Mangez, and J. Ozga (London: Routledge, 2014), 3.

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  6. I. Hacking, “Biopower and the Avalanche of Printed Numbers,” in Biopower: Foucault and Beyond, ed. V. W. Cisney and N. Morar (Chicago: University of Chicago Press, 2016): 65–81.

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  7. M. Foucault, The History of Sexuality: An Introduction, vol. 1 (New York: Vintage Books, 1990), 141–42.

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  8. T. Lemke, Biopolitics: An Advanced Introduction (New York: New York University Press, 2011), 5.

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  9. Lemke, Biopolitics, 5.

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  10. P. Levine and A. Bashford, “Introduction: Eugenics and the Modern World,” in The Oxford Handbook of the History of Eugenics, ed. A. Bashford and P. Levine (Oxford: Oxford University Press, 2010), 3.

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  11. I. Hunter, “Assembling the School,” in Foucault and Political Reason: Liberalism, Neoliberalism, and Rationalities of Government, ed. T. Osborne, N. Rose, and A. Barry (Abingdon, Oxon: Routledge, 1996), 154.

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  12. M. Lawn, “Introduction: The Rise of Data in Education” in The Rise of Data in Education Systems: Collection, Visualisation, and Use, ed. M. Lawn (Oxford: Symposium, 2013), 7–8.

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  13. Lawn, “The Internationalization of Education Data: Exhibitions, Tests, Standards, and Associations,” in The Rise of Data in Education Systems: Collection, Visualisation and Use, ed. M. Lawn (Oxford: Symposium, 2013), 11.

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  14. S. J. Ball, Foucault, Power, and Education (New York: Routledge, 2013), 74.

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  15. Ball, Foucault, Power, and Education, 74.

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  16. C. Chitty, Eugenics, Race, and Intelligence in Education (London: Continuum, 2007); R. Lowe, “The Educational Impact of the Eugenics Movement,” International Journal of Educational Research 27, no. 8 (1998): 647–60.

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  17. B. Lingard, “Policy as Numbers: Ac/Counting for Educational Research,” Australian Educational Researcher 38, no. 4 (2011): 357; N. Rose, Powers of Freedom: Reframing Political Thought (Cambridge: Cambridge University Press, 1999).

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  18. F. Rizvi and B. Lingard, Globalizing Educational Policy (London: Routledge, 2010); D. Lerner and H. D. Laswell, The Policy Sciences: Recent Developments in Scope and Method (Stanford, Calif.: Stanford University Press, 1951).

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  19. M. Simons, M. Olssen, and M. A. Peters, “Re-Reading Education Policies: Part 1: The Critical Policy Orientation,” in Re-Reading Education Policies: A Handbook Studying the Policy Agenda of the 21st Century, ed. M. Simons, M. Olssen, and M. A. Peters (Rotterdam: Sense Publishers, 2009).

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  20. Rizvi and Lingard, Globalizing Educational Policy, 1.

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  21. While we recognize the wide variety of work that is termed neoliberal, we cite Milton Friedman here, as he had a direct set of proposals that extended his monetary focus into education. M. Friedman, Capitalism and Freedom (Chicago: University of Chicago Press, 1962); M. Freidman, Free to Choose (New York: Harcourt Brace Jovanovich, 1980).

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  22. S. J. Ball, The Education Debate (Bristol: Policy Press, 2008), 12–13.

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  23. G. Biesta, “Education between Accountability and Responsibility,” in Re-Reading Education Policies: A Handbook Studying the Policy Agenda of the 21st Century, ed. M. Simons, M. Olssen, and M. A. Peters (Rotterdam: Sense Publishers, 2009).

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  24. M. Power, “The Theory of Audit Explosion,” in The Oxford Handbook of Public Management. ed. E. Ferlie, L. E. Lynn, and C. Pollitt (Oxford: Oxford University Press, 2007); S. Ranson, “Public Accountability in the Age of Neo-Liberal Governance,” Journal of Education Policy 18, no. 5 (2003): 459–80.

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  25. N. Piattoeva and R. Boden, “Escaping Numbers? The Ambiguities of the Governance of Education through Data,” International Studies in Sociology of Education (2020): 1.

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  26. Rizvi and Lingard, Globalizing Educational Policy, 2.

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  27. Rizvi and Lingard, Globalizing Educational Policy, 2; S. J. Ball, “Intellectuals or Technicians? The Urgent Role of Theory in Education Studies,” British Journal of Educational Studies 43 (1995): 255–71.

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  28. Rose, Powers of Freedom.

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  29. W. Brown, Undoing the Demos: Neoliberalism’s Stealth Revolution (Brooklyn: Zone Books, 2015).

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  30. W. Humes and T. Bryce, “Post-Structuralism and Policy Research in Education,” Journal of Education Policy 18, no. 2 (2003): 175–87.

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  31. B. Williamson, “Who Owns Educational Theory? Big Data, Algorithms, and the Expert Power of Education Data Science,” E-Learning and Digital Media 14, no. 3 (2017): 105–22.

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  32. M-C. Liu and Y-M. Huang, “The Use of Data Science for Education: The Case of Social-Emotional Learning,” Smart Learning Environments 4, no. 1 (2017): 2.

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  33. Liu and Huang, “Use of Data Science for Education,” 2.

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  34. J. D. Kelleher and B. Tierney, Data Science (Cambridge, Mass.: MIT Press, 2018); Williamson, “Who Owns Educational Theory?”

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  35. J. F. Lyotard, The Postmodern Condition: A Report on Knowledge (Minneapolis: University of Minnesota Press, 1984), 4.

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  36. Williamson, “Who Owns Educational Theory?”

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  37. S. J. Ball, “The Teacher’s Soul and the Terrors of Performativity,” Journal of Education Policy 18, no. 2 (2003): 216.

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  38. Y. N. Harari, Homo Deus: A Brief History of Tomorrow (London: Harvill Secker, 2015), 222.

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  39. N. Selwyn, “Data Entry: Towards the Critical Study of Digital Data and Education,” Learning, Media, and Technology 40, no. 1 (2015): 72.

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  40. M. A. Larsen and J. Beech, “Spatial Theorizing in Comparative and International Education Research,” Comparative Education Review 58, no. 2 (2014): 191–214; K. Mundy, “Global Governance, Educational Change,” Comparative Education 43, no. 3 (2007): 339–57; Rizvi and Lingard, Globalizing Educational Policy.

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  41. A. Hartman, Education and the Cold War: The Battle for the American School (New York: Palgrave Macmillan, 2008).

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  42. R. Gorur, “Statistics and Statecraft: Exploring the Potentials, Politics, and Practices of International Educational Assessment,” Critical Studies in Education 58, no. 3 (2017): 262.

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  43. C. Addey et al., “The Rise of International Large-Scale Assessments and Rationales for Participation,” Compare: A Journal of Comparative and International Education 47, no. 3 (2017): 435.

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  44. Addey et al., “Rise of International Large-Scale Assessments,” 436.

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  45. C. Addey and S. Sellar, “Is It Worth It? Rationales for (Non)Participation in Large-Scale Learning Assessments,” in Education Research and Foresight Working Papers Series (Paris: UNESCO, 2019), 3.

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  46. S. Grek, “Governing by Numbers: The Pisa ‘Effect’ in Europe,” Journal of Education Policy 24, no. 1 (2009): 23–37; K. Takayama, “The Politics of International League Tables: Pisa in Japan’s Achievement Crisis Debate,” Comparative Education 44 (2008): 387–407.

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  47. Addey and Sellar, “Is It Worth It?”

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  48. S. Grek, “Expert Moves: International Comparative Testing and the Rise of Expertocracy,” Journal of Education Policy 28, no. 5 (2013): 697.

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  49. S. J. Ball and C. Junemann, Networks, New Governance, and Education (Bristol: Policy Press, 2012), 138.

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  50. R. A. W. Rhodes, Understanding Governance Policy Networks, Governance, Reflexivity, and Accountability (Buckingham: Open University Press, 1997), 15, original emphasis.

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  51. V. August, “Network Concepts in Social Theory: Foucault and Cybernetics,” European Journal of Social Theory (2021): n.p., original emphasis.

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  52. S. J. Ball, Global Education Inc.: New Policy Networks and the Neoliberal Imaginary (London: Routledge, 2012), 9.

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  53. Wilkins and Olmedo, “Introduction: Conceptualizing Education Governance,” 5.

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  54. J. Allen, “Topological Twists: Power’s Shifting Geographies,” Dialogues in Human Geography 1, no. 3 (2011): 284.

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  55. W. Kickert, “Steering at a Distance: A New Paradigm of Public Governance in Dutch Higher Education,” Governance 8, no. 1 (1995): 135–57.

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  56. A. Anagnostopoulos, S. A. Rutledge, and R. Jacobsen, “Mapping the Information Infrastructure of Accountability,” in The Infrastructure of Accountability: Data Use and the Transformation of American Education, ed. A. Anagnostopoulos, S. A. Rutledge, and R. Jacobsen (Cambridge, Mass.: Harvard Education Press, 2013); L. Harris, C. Wyatt-Smith, and L. Adie, “Using Data Walls to Display Assessment Results: A Review of Their Affective Impacts on Teachers and Students,” Teachers and Teaching 26, no. 1 (2020): 50–66.

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  57. R. Crooks, “Representationalism at Work: Dashboards and Data Analytics in Urban Education,” Educational Media International 54, no. 4 (2017): 290.

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  58. Fenwick, Mangez, and Ozga, “Governing Knowledge,” 5.

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  59. S. Hartong, “Towards a Topological Re-Assemblage of Education Policy? Observing the Implementation of Performance Data Infrastructures and ‘Centers of Calculation’ in Germany,” Globalisation, Societies, and Education 16, no. 1 (2018): 134–50.

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  60. G. C. Bowker, K. Baker, F. Millerand, and D. Ribes, “Toward Information Infrastructure Studies: Ways of Knowing in a Networked Environment,” in International Handbook of Internet Research, ed. J. Husinger, L. Klastrup, and M. M. Allen (Dordrecht: Springer, 2010), 97–117.

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  61. Anagnostopoulos et al., “Mapping the Information Infrastructure of Accountability”; A. Kanngieser, B. Neilson, and N. Rossiter, “What Is a Research Platform? Mapping Methods, Mobilities, and Subjectivities,” Media, Culture, and Society 36, no. 3 (2014): 302–18; N. Rossiter, “Coded Vanilla: Logistical Media and the Determination of Action,” South Atlantic Quarterly 114, no. 1 (2015): 135–52; K. Easterling, Extrastatecraft: The Power of Infrastructure Space (New York: Verso Books, 2014); L. Parisi, Contagious Architecture: Computation, Aesthetics, and Space (Cambridge, Mass.: MIT Press, 2013); S. Sellar, “Data Infrastructure: A Review of Expanding Accountability Systems and Large-Scale Assessments in Education,” Discourse: Studies in the Cultural Politics of Education 36, no. 5 (2015): 765–77.

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  62. Hartong, “Towards a Topological Re-Assemblage of Education Policy?,” 135.

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  63. L. Parks and N. Starosielski, introduction to Signal Traffic: Critical Studies of Media Infrastructures, ed. L. Parks and N. Starosielski (Urbana: University of Illinois Press, 2015), 11.

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  64. B. Williamson, “Digital Education Governance: Data Visualization, Predictive Analytics, and ‘Real-Time’ Policy Instruments,” Journal of Education Policy 31, no. 2 (2016): 123.

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  65. “Digital Education Governance: An Introduction,” European Educational Research Journal 15, no. 1 (2016): 5.

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  66. N. Selwyn and J. Fitz, “The Politics of Connectivity: The Role of Big Business in UK Education Technology Policy,” Policy Studies Journal 29, no. 4 (2001): 551–70; P. Burch, Hidden Markets: The New Education Privatization (New York: Routledge, 2009).

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  67. S. J. Ball, Education Plc: Understanding Private Sector Participation in Public Sector Education (New York: Routledge, 2007); Ball, Global Education Inc.

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  68. S. J. Ball and D. Youdell, Hidden Privatisation in Public Education (Brussels: Education International, 2008); H. Roberts-Mahoney, A. J. Means, and M. J. Garrison, “Netflixing Human Capital Development: Personalized Learning Technology and the Corporatization of K-12 Education,” Journal of Education Policy 31, no. 4 (2016): 405–20.

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  69. Fourcade and Gordon, “Learning Like a State,” 95.

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  70. Lawn, “Introduction: The Rise of Data in Education,” 7.

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  71. M. I. Jordan and T. M. Mitchell, “Machine Learning: Trends, Perspectives, and Prospects,” Science 349, no. 6245 (2015): 255–60; P. DeLeon, “Models of Policy Discourse: Insights versus Prediction,” Policy Studies Journal 26, no. 1 (1998): 147–61.

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  72. C. V. Patton, D. S. Sawicki, and J. J. Clark, Basic Methods of Policy Analysis and Planning, 3rd ed. (New York: Routledge, 2016), 23.

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  73. J. Wilsdon, “From Foresight to Hindsight: The Promise of History in Responsible Innovation,” Journal of Responsible Innovation 1, no. 1 (2014): 109–112.

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  74. B. Anderson, “Preemption, Precaution, Preparedness: Anticipatory Action and Future Geographies,” Progress in Human Geography 34, no. 6 (2010): 778.

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  75. S. Amsler and K. Facer, “Contesting Anticipatory Regimes in Education: Exploring Alternative Educational Orientations to the Future,” Futures 94 (2017): 14.

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  76. B. Williamson and R. Eynon, “Historical Threads, Missing Links, and Future Directions in AI in Education,” Learning, Media, and Technology 45, no. 3 (2020): 224.

    Return to note reference.

  77. For example: S. Swauger, “Our Bodies Encoded: Algorithmic Test Proctoring in Higher Education,” Hybrid Pedagogy. April 2, 2020, https://hybridpedagogy.org/our-bodies-encoded-algorithmic-test-proctoring-in-higher-education/.

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  78. B. Williamson, “Meta-Edtech,” Learning, Media, and Technology 46, no. 1 (2021): 1–5.

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  79. M. C. Elish and d. boyd, “Situating Methods in the Magic of Big Data and AI,” Communication Monographs 85, no. 1 (2018): 70.

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  80. E. Alpaydin, Machine Learning (Cambridge, Mass.: MIT Press, 2016), 33.

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  81. Alpaydin, Machine Learning, 39.

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  82. Alpaydin, 111.

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  83. M. Boden, AI: Its Nature and Future (Oxford: Oxford University Press, 2016).

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  84. J. W. Crampton, “Platform Biometrics,” Surveillance and Society 17, no. 1/2 (2019): 58.

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  85. P. N. Edwards, “We Have Been Assimilated: Some Principles for Thinking About Algorithmic Systems,” in Living with Monsters? Social Implications of Algorithmic Phenomena, Hybrid Agency, and the Performativity of Technology (Proceeding of the Working Conference on Information Systems and Organizations 2018), ed. U. Schultze, M. Aanestad, M. Mähring, C. Østerlund, and K. Riemer (Cham: Springer International Publishing, 2018). 21.

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  86. Edwards, “We Have Been Assimilated,” 20–21, original emphasis.

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  87. M. van Otterlo, “The Libraryness of Calculative Devices: Artificially Intelligent Librarians and Their Impact on Information Consumption,” in Algorithmic Life: Calculative Devices in the Age of Big Data, ed. Louise Amoore and V. Piotukh (New York: Routledge, 2016), 37, original emphasis.

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  88. E. Zeide, “The Structural Consequences of Big Data-Driven Education,” Big Data 5, no. 2 (2017): 167.

    Return to note reference.

  89. J. D. Kelleher and B. Tierney, Data Science (Cambridge, Mass.: MIT Press, 2018), 2–3.

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  90. M. Andrejevic, Automated Media (London: Routledge, 2019), 9.

    Return to note reference.

  91. Nigel Gilbert et al., “Computational Modelling of Public Policy: Reflections on Practice,” Journal of Artificial Societies and Social Simulation 21, no. 1 (2018): 1.4.

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  92. Cited by S. J. Ball, “Intellectuals or Technicians? The Urgent Role of Theory in Education Studies,” British Journal of Educational Studies 43 (1995): 259.

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  93. Cited by Ball, “Intellectuals or Technicians?,” 258–59.

    Return to note reference.

  94. M. Andrejevic, Automated Media (London: Routledge, 2019), 9.

    Return to note reference.

  95. N. Rose and J. M. Abi-Rached, Neuro: The New Brain Sciences and the Management of the Mind (Princeton, N.J.: Princeton University Press, 2013), 14.

    Return to note reference.

  96. L. Parisi, “Critical Computation: Digital Automata and General Artificial Thinking,” Theory, Culture, and Society 36, no. 2 (2019): 90.

    Return to note reference.

  97. L. Amoore and V. Piotukh, introduction to Algorithmic Life: Calculative Devices in the Age of Big Data. ed. L. Amoore and V. Piotukh (New York: Routledge, 2016), 7–8.

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  98. E. Kochmar, D. D. Vu, R. Belfer, V. Gupta, I. V. Serban, and J. Pineau, “Automated Personalized Feedback Improves Learning Gains in an Intelligent Tutoring System,” in Artificial Intelligence in Education. ed. I. Bittencourt, M. Cukurova, K. Muldner, R. Luckin, E. Millán. AIED 2020. Lecture Notes in Computer Science, vol. 12164. Springer, Cham. https://doi.org/10.1007/978-3-030-52240-7_26.

    Return to note reference.

  99. For example, see the Center for Data Science and Public Policy at the University of Chicago: http://www.datasciencepublicpolicy.org/projects/education/.

    Return to note reference.

  100. B. Williamson, “Intimate Data Infrastructure: Emerging Comparative Methods of Predictive Analytics and Pycho-Informatics,” in World Yearbook of Education 2019: Comparative Methodology in the Era of Big Data and Global Networks, ed. R. Gorur, S. Sellar, and G. Steiner-Khamsi (London: Routledge, 2019), 72.

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  101. M. Whitehead et al., Neuroliberalism: Behavioural Government in the Twenty-First Century (London: Routledge, 2018); J. Knox, B. Williamson, and S. Bayne, “Machine Behaviourism: Future Visions of ‘Learnification’ and ‘Datafication’ across Humans and Digital Technologies,” Learning, Media, and Technology 45, no. 1 (2020): 31–45.

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  102. Knox, Williamson, and Bayne, “Machine Behaviourism,” 11–12.

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  103. Cited in Fourcade and Gordon, “Learning Like a State,” 82.

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  104. K. N. Gulson and K. Witzenberger, “Repackaging Authority: Artificial Intelligence, Automated Governance, and Education Trade Shows,” Journal of Education Policy (2020): 1–16.

    Return to note reference.

  105. Edwards, “We Have Been Assimilated,” 23.

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  106. A. R. Galloway and E. Thacker, The Exploit: A Theory of Networks (Minneapolis: University of Minnesota Press, 2007), 5.

    Return to note reference.

  107. J. Ozga, “Problematising Policy: The Development of (Critical) Policy Sociology,” Critical Studies in Education 62, no. 3 (2021): 290–305; M. Simons, M. Olssen, and M. A. Peters, “Handbook on Matters of Public Concern: Introduction and Overview,” in Re-Reading Education Policies: A Handbook Studying the Policy Agenda of the 21st Century, ed. M. Simons, M. Olssen, and M. A. Peters (Rotterdam: Sense Publishers, 2009).

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  108. B. Williamson, “Digital Policy Sociology: Software and Science in Data-Intensive Precision Education,” Critical Studies in Education 62, no. 3 (2021): 354–70; A. J. Means, “Hypermodernity, Automated Uncertainty, and Education Policy Trajectories,” Critical Studies in Education 62, no. 3 (2021): 371–86.

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  109. D. Beer and R. Burrows, “Sociology and, of, and in Web 2.0: Some Initial Considerations,” Sociological Research Online 12, no. 5 (2007): 67–79; P. Rabinow, Marking Time: On the Anthropology of the Contemporary (Princeton, N.J.: Princeton University Press, 2008).

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  110. E. de Freitas, E. Dixon-Román, and P. Lather, “Alternative Ontologies of Number: Rethinking the Quantitative in Computational Culture,” Cultural Studies ↔ Critical Methodologies 16, no. 5 (2016): 432.

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2. Thought

  1. S. Ranson, “Public Accountability in the Age of Neo-Liberal Governance,” Journal of Education Policy 18, no. 5 (2003): 459–80; S. J. Ball, “The Teacher’s Soul and the Terrors of Performativity,” Journal of Education Policy 18, no. 2 (2003): 215–28; B. Lingard, “Policy as Numbers: Ac/Counting for Educational Research,” Australian Educational Researcher 38, no. 4 (2011): 355–82.

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  2. J. F. Lyotard, The Postmodern Condition: A Report on Knowledge (Minneapolis: University of Minnesota Press, 1984).

    Return to note reference.

  3. For a historical overview of AI and education that covers these issues, see B. Williamson and R. Eynon, “Historical Threads, Missing Links, and Future Directions in AI in Education,” Learning, Media, and Technology 45, no. 3 (2020): 223–35.

    Return to note reference.

  4. M. Whittaker et al., AI Now Report 2018 (New York: AI Now Institute, 2018).

    Return to note reference.

  5. D. H. Autor, “Why Are There Still So Many Jobs? The History and Future of Workplace Automation,” Journal of Economic Perspectives 29, no. 3 (2015): 3–30.

    Return to note reference.

  6. B. Reider, Engines of Order: A Mechanology of Algorithmic Techniques (Amsterdam: Amsterdam University Press, 2020), 16.

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  7. B. Reider, Engines of Order.

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  8. R. Gorur, “ANT on the PISA Trail: Following the Statistical Pursuit of Certainty,” Educational Philosophy and Theory 43 (2011): 76–93; D. Coole and S. Frost, “Introducing the New Materialisms,” in New Materialisms: Ontology, Agency, and Politics, ed. D. Coole and S. Frost (Durham, N.C.: Duke University Press, 2010), 1–46.

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  9. F. Pasquale, “Professional Judgment in an Era of Artificial Intelligence and Machine Learning,” Boundary 2 46, no. 1 (2019): 73–101.

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  10. A. Mackenzie, Transductions: Bodies and Machines at Speed (London: Continuum, 2002), 5.

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  11. D. Roden, Posthuman Life: Philosophy at the Edge of the Human (London: Routledge, 2015), 165.

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  12. B. Stiegler, Technics and Time (Stanford, Calif.: Stanford University Press, 1998).

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  13. B. Roberts, “Technics, Individuation, and Tertiary Memory: Bernard Stiegler’s Challenge to Media Theory,” New Formations, no. 77 (2012): 12.

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  14. Mackenzie, Transductions, 10.

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  15. Roden, Posthuman Life, 153.

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  16. A. Rouvroy, T. Berns, and E. Libbrecht, “Algorithmic Governmentality and Prospects of Emancipation: Disparateness as a Precondition for Individuation through Relationships?,” Réseaux, no. 1 (2013): x.

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  17. See also J. Knox, B. Williamson, and S. Bayne, “Machine Behaviourism: Future Visions of ‘Learnification’ and ‘Datafication’ across Humans and Digital Technologies,” Learning, Media, and Technology 45, no. 1 (2020): 31–45.

    Return to note reference.

  18. R. Abbinnett, The Thought of Bernard Stiegler: Capitalism, Technology, and the Politics of Spirit (London: Routledge, 2018), 51.

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  19. M. W. McLaughlin, “The Rand Change Agent Study Revisited: Macro Perspectives and Micro Realities” Educational Researcher 19, no. 9 (1990): 11–16.

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  20. Roden, Posthuman Life, 152.

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  21. Roden, 158.

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  22. Roden, 156.

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  23. D. Savat, “Introduction: Deleuze and New Technology,” in Deleuze and New Technology, ed. M. Poster and D. Savat (Edinburgh: Edinburgh University Press, 2009), 3.

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  24. L. Parisi, “The Alien Subject of AI,” Subjectivity 12, no. 1 (2019): 34.

    Return to note reference.

  25. Roden, Posthuman Life, 160.

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  26. P. Crogan, “Bernard Stiegler on Algorithmic Governmentality: A New Regimen of Truth?,” New Formations: A Journal of Culture/Theory/Politics 98, no. 98 (2019): 58.

    Return to note reference.

  27. G. Deleuze, Negotiations: 1972–1990, trans. Martin Joughin (New York: Columbia University Press, 1995), 180, 182.

    Return to note reference.

  28. Roberts, “Technics, Individuation, and Tertiary Memory,” 14.

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  29. J. T. Nealon, “Exteriority and Appropriation: Foucault, Derrida, and the Discipline of Literary Criticism,” Cultural Critique, no. 21 (1992): 97–119.

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  30. N. Land, “A Quick-and-Dirty Introduction to Accelerationism,” Jacobite, May 25, 2017, https://jacobitemag.com/2017/05/25/a-quick-and-dirty-introduction-to-accelerationism/.

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  31. A. Beckett, “Accelerationism: How a Fringe Philosophy Predicted the Future We Live In,” The Guardian. May 11, 2017, https://www.theguardian.com/world/2017/may/11/accelerationism-how-a-fringe-philosophy-predicted-the-future-we-live-in.

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  32. K. E. Bouskill, S. Chonde, and W. Welser IV, Speed and Security: Promises, Perils, and Paradoxes of Accelerating Everything (Santa Monica, Calif.: RAND Corporation, 2018), 1.

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  33. Bouskill et al., Speed and Security, 5.

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  34. V. Garton, “Unconditional Accelerationism as Antipraxis,” 2017, https://cyclonotrope.wordpress.com/2017/06/12/unconditional-accelerationism-as-antipraxis/.

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  35. R. Mackay and A. Avanessian, eds., #Accelerate#: The Accelerationist Reader (Falmouth: Urbanomic, 2014).

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  36. J. F. Sitton, “Speech on Free Trade, with Engels’s Preface of 1888,” in Karl Marx and John F. Sitton, Marx Today: Selected Works and Recent Debates (New York: Palgrave Macmillan, 2010), 88.

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  37. F. Nietzsche, The Will to Power (New York: Vintage, 1968), 477.

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  38. Nietzsche, Will to Power, 478.

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  39. S. Sellar, “Acceleration, Automation, and Pedagogy: How the Prospect of Technological Unemployment Creates New Conditions for Educational Thought,” in Education and Technological Unemployment, ed. M. A. Peters, P. Jandrić, and Alexander J. Means (Singapore: Springer, 2019); B. Noys, Persistence of the Negative: A Critique of Contemporary Continental Theory (Edinburgh: Edinburgh University Press, 2010); S. Sellar and D. R. Cole, “Accelerationism: A Timely Provocation for the Critical Sociology of Education,” British Journal of Sociology of Education 38, no. 1 (2017): 38–48.

    Return to note reference.

  40. F. Berardi, G. Genosko, and N. Thoburn, eds., After the Future (Edinburg: AK Press, 2011).

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  41. G. Deleuze and F. Guattari, Anti-Oedipus (Minneapolis: University of Minnesota Press, 1983), 239–40.

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  42. N. Land, “Teleoplexy: Notes on Acceleration,” in #Accelerate#: The Accelerationist Reader, ed. R MacKay and A. Avanessian (Falmouth: Urbanomic, 2014), 511.

    Return to note reference.

  43. S. Zuboff, The Age of Surveillance Capitalism: The Fight for Human Future at the New Frontier of Power (London: Profile Books, 2019).

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  44. B. Green, “‘Good’ Isn’t Good Enough,” paper presented at the Proceedings of the AI for Social Good workshop at NeurIPS, 2019.

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  45. G. E. Hinton, S. Osindero, and Y. Teh, “A Fast Learning Algorithm for Deep Belief Nets,” Neural Computation 18, no. 7 (2006): 1527–54.

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  46. A. Williams and N. Srnicek, “#Accelerate: Manifesto for an Accelerationist Politics,” in #Accelerate#: The Accelerationist Reader, ed. R. Mackay and A. Avanessian (Falmouth: Urbanomic, 2014), 135–55.

    Return to note reference.

  47. M. E. Gardiner, “Critique of Accelerationism,” Theory, Culture, and Society 34, no. 1 (2017): 35.

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  48. S. Metcalf, “Killing Time/Strife Kolony/Neofuturism,” DI Research Zone 22: Mechanosphereology, November 26, 2018, https://disubunit22.wordpress.com/2018/11/26/steve-metcalf-killing-time-strife-kolony-neofuturism/.

    Return to note reference.

  49. R. Negarestani and R. Mackay, “Reengineering Philosophy,” Urbanomic Document 034, no. 34 (2018): 1–18.

    Return to note reference.

  50. N. K. Hayles, “Cognition Everywhere: The Rise of the Cognitive Nonconscious and the Costs of Consciousness,” New Literary History 45, no. 2 (2014): 199–220.

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  51. Hayles, “Cognition Everywhere,” 201.

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  52. Hayles, 202.

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  53. Hayles, 215.

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  54. Hayles, 212.

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  55. R. S. Bakker, “Crash Space,” Midwest Studies in Philosophy 39, no. 1 (2015): 186–204.

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  56. N. K. Hayles, How We Think: Digital Media and Contemporary Technogenesis (Chicago: University of Chicago Press, 2012), 10, emphasis added. This is a fascinating exploration of the connection between humans, technology, and epigenetics and may provide new insights into how machine/human governance can develop—beyond the remit of this book, but a cognate project.

    Return to note reference.

  57. L. Parisi, “Automated Thinking and the Limits of Reason,” Cultural Studies ↔ Critical Methodologies 16, no. 5 (2016): 480.

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  58. L. Parisi, “Automation and Critique,” Reinventing Horizons Symposium, Prague, March 18–19, 2016, http://www.reinventinghorizons.org/?p=355#more-355, paragraph 9.

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  59. For discussion of these issues, see N. Selwyn, Should Robots Replace Teachers (Cambridge: Polity Press, 2019); A. J. Means, “Hypermodernity, Automated Uncertainty, and Education Policy Trajectories,” Critical Studies in Education 62, no. 3 (2021): 371–86.

    Return to note reference.

  60. Parisi, “Automation and Critique,” paragraph 8.

    Return to note reference.

  61. L. Parisi, “Reprogamming Decisionism,” E-Flux Journal 85 (2017), paragraph 7.

    Return to note reference.

  62. M. A. Boden, AI: Its Nature and Future (Oxford: Oxford University Press, 2016).

    Return to note reference.

  63. K. Hao, “We Analyzed 16,625 Papers to Figure Out Where AI Is Headed Next,” MIT Technology Review (2019), https://www.technologyreview.com/s/612768/we-analyzed-16625-papers-to-figure-out-where-ai-is-headed-next/.

    Return to note reference.

  64. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 3rd ed. (Harlow, Essex: Pearson Education Limited, 2016).

    Return to note reference.

  65. Lyotard, Postmodern Condition.

    Return to note reference.

  66. Parisi, “Reprogamming Decisionism,” paragraph 13.

    Return to note reference.

  67. Parisi, paragraph 13.

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  68. Parisi, paragraph 8.

    Return to note reference.

  69. A. Campalo et al., AI Now 2017 Report (New York: AI Now, 2017).

    Return to note reference.

  70. G. Chatain, “The Limits of Reason,” Scientific American 294, no. 3 (2006): 74–81.

    Return to note reference.

  71. Parisi, “Automated Thinking and the Limits of Reason,” 479.

    Return to note reference.

  72. Parisi, “Reprogamming Decisionism,” paragraph 8, emphasis added.

    Return to note reference.

  73. Parisi, “Reprogramming Decisionism,” paragraph 8.

    Return to note reference.

  74. L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Durham, N.C.: Duke University Press, 2020), 12–13, original emphasis.

    Return to note reference.

  75. J. D. Kelleher, Deep Learning (Cambridge, Mass.: MIT Press, 2019).

    Return to note reference.

  76. L. Amoore, “Doubt and the Algorithm: On the Partial Accounts of Machine Learning,” Theory, Culture, and Society 36, no. 6 (2019): 151.

    Return to note reference.

  77. T. Blakely, J. Lynch, K. Simons, R. Bentley, and S. Rose, “Reflection on Modern Methods: When Worlds Collide—Prediction, Machine Learning, and Causal Inference,” International Journal of Epidemiology 49, no. 6 (2020): 2058–64.

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  78. Amoore, “Doubt and the Algorithm,” 149.

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  79. Amoore, Cloud Ethics, 6.

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  80. Amoore, 5–6.

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  81. N. Weiner, The Human Use of Human Beings: Cybernetics and Society (London: Free Association Books, 1989).

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3. Problems

  1. E. de Freitas, “The Temporal Fabric of Research Methods: Posthuman Social Science and the Digital Data Deluge,” Research in Education 98, no. 1 (2017): 29.

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  2. C. Lury and N. Wakeford, “Introduction: A Perpetual Inventory,” in Inventive Methods: The Happening of the Social, ed. C. Lury and N. Wakeford (New York: Routledge, 2012), 7.

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  3. Australian Research Council Discovery Grant, DP150102098; chief investigators: Bob Lingard, Kalervo Gulson, Sam Sellar, and Keita Takayama, with partner investigators Christopher Lubienski and Taylor Webb. Australian Research Council Future Fellowship, FT180100280; chief investigator: Kalervo Gulson. Canadian Social Sciences and Humanities Research Council Insight Grant Scheme, #435-2018-0102; chief investigator: P. Taylor Webb, with partner investigators Sam Sellar and Kalervo N. Gulson.

    Return to note reference.

  4. P. Rabinow, Marking Time: On the Anthropology of the Contemporary (Princeton, N.J.: Princeton University Press, 2008), 8.

    Return to note reference.

  5. P. Rabinow, “Afterword: Concept Work,” in Biosocialities, Genetics, and the Social Sciences: Making Biologies and Identities. ed. S. Gibbon and C. Novas (New York: Routledge, 2008), 182–92.

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  6. For example, P. Bourdieu, In Other Words: Essays towards a Reflexive Sociology (Palo Alto, Calif.: Stanford University Press, 1990); P. Lather, “2007 Kneller Lecture, Aesa Getting Lost: Social Science and/as Philosophy,” Educational Studies 45, no. 4 (2009): 342–57; P. Rabinow, Anthropos Today: Reflections on Modern Equipment (Princeton, N.J.: Princeton University Press, 2003).

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  7. Rabinow, Marking Time. See also M. MacLure, “Researching without Representation? Language and Materiality in Post-Qualitative Methodology,” International Journal of Qualitative Studies in Education 26, no. 6 (2013): 658–67; E. A. St. Pierre and W. S. Pillow, Working the Ruins: Feminist Poststructural Theory and Methods in Education (New York: Routledge, 2000).

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  8. C. Colebrook and J. Weinstein, “Preface: Postscript on the Posthuman,” in Posthumous Life: Theorizing beyond the Posthuman, ed. J. Weinstein and C. Colebrook (New York: Columbia University Press, 2017), xxii.

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  9. Colebrook and Weinstein, “Preface,” xxvii.

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  10. G. Deleuze and F. Guattari, What Is Philosophy? (London: Verso), 7.

    Return to note reference.

  11. B. Flyvbjerg, Making Social Science Matter: Why Social Inquiry Fails and How It Can Succeed Again (Cambridge: Cambridge University Press, 2001), 167.

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  12. S. Heimans, “Fieldwork in Philosophy, Emancipation, and Researcher Dis-Position: A Post-Qualitative Research Exemplar,” Qualitative Research Journal 16, no. 1 (2016): 2–12.

    Return to note reference.

  13. A. Mol, The Body Multiple: Ontology in Medical Practice (Durham, N.C.: Duke University Press, 2002), 32.

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  14. R. Gorur, S. Sellar, and G. Steiner-Khamsi, “Big Data and Even Bigger Consequences,” in World Yearbook of Education 2019: Comparative Methodology in the Era of Big Data and Global Networks, ed. R. Gorur, S. Sellar, and G. Steiner-Khamsi (London: Routledge, 2019), 5.

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  15. L. Bartlett and F. Vavrus, “Rethinking the Concept of ‘Context’ in Comparative Research,” in World Yearbook of Education 2019: Comparative Methodology in the Era of Big Data and Global Networks, ed. R. Gorur, S. Sellar, and G. Steiner-Khamsi (London: Routledge, 2019), 195.

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  16. M. Sheller and J. Urry, “The New Mobilities Paradigm,” Environment and Planning A 38, no. 2 (2006): 207–26.

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  17. M. Büscher, J. Urry, and K. Witchger, “Introduction: Mobile Methods,” in Mobile Methods, ed. M. Büscher, J. Urry, and K. Witchger (New York: Routledge, 2011), 4.

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  18. Büscher, Urry, and Witchger, “Introduction: Mobile Methods.”

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  19. E. McCann and K. Ward, “Assembling Urbanism: Following Policies and ‘Studying through’ the Sites and Situations of Policy Making,” Environment and Planning A 44, no. 1 (2012): 42–51.

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  20. J. Peck and N. Theodore, Fast Policy: Experimental Statecraft at the Thresholds of Neoliberalism (Minneapolis: University of Minnesota Press, 2015).

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  21. Peck and Theodore, Fast Policy, xxviii.

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  22. Peck and Theodore, 29.

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  23. S. J. Ball, “Following Policy: Networks, Network Ethnography, and Education Policy Mobilities,” Journal of Education Policy 31, no. 5 (2016): 549–66; S. J. Ball, Global Education Inc.: New Policy Networks and the Neoliberal Imaginary (London: Routledge, 2012); Marcia McKenzie, “Affect Theory and Policy Mobility: Challenges and Possibilities for Critical Policy Research,” Critical Studies in Education 58, no. 2 (2017): 187–204; D. Cohen, “Market Mobilities/Immobilities: Mutation, Path-Dependency, and the Spread of Charter School Policies in the United States,” Critical Studies in Education 58, no. 2 (2017): 168–86.

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  24. B. Jessop, N. Brenner, and M. Jones, “Theorizing Sociospatial Relations,” Environment and Planning D: Society and Space 26, no. 3 (2008): 389–401; U. Beck, What Is Globalization? (Cambridge: Polity Press, 2000).

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  25. A. Cochrane and K. Ward, “Guest Editorial—Researching the Geographies of Policy Mobility: Confronting the Methodological Challenges,” Environment and Planning A 44, no. 5–12 (2012): 7.

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  26. Cochrane and Ward, “Guest Editorial.”

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  27. N. Brenner, New State Spaces: Urban Governance and the Rescaling of Statehood (New York: Open University Press, 2004).

    Return to note reference.

  28. Cochrane and Ward, “Guest Editorial,” 5.

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  29. B. Williamson et al., “Education Recoded: Policy Mobilities in the International ‘Learning to Code’ Agenda,” Journal of Education Policy 34, no. 5 (2019): 707.

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  30. S. Hartong, “Towards a Topological Re-Assemblage of Education Policy? Observing the Implementation of Performance Data Infrastructures and ‘Centers of Calculation’ in Germany,” Globalisation, Societies, and Education 16, no. 1 (2018): 134.

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  31. S. J. Ball, C. Junemann, and Diego Santori, Edu.Net: Globalisation and Education Policy Mobility (London: Routledge, 2017), 16. See also E. McCann and K. Ward, “Introduction: Urban Assemblages: Territories, Relations, Practices, and Power,” in Mobile Urbanism: Cities and Policymaking in the Global Age, ed. E. McCann and K. Ward (Minneapolis: University of Minnesota Press, 2011), xiii–xxxv; E. McCann, “Urban Policy Mobilities and Global Circuits of Knowledge: Toward a Research Agenda,” Annals of the Association of American Geographers 101, no. 1 (2010): 107–130.

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  32. Ball, Junemann, and Santori, Edu.Net, 18.

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  33. M. Burawoy, “The Extended Case Method,” Sociological Theory 16, no. 1 (1998): 5; M. Burawoy, “Introduction: Reaching for the Global,” in Global Ethnography: Forces, Connections, and Imaginations in a Postmodern World, ed. M. Burawoy et al. (Berkeley: University of California Press, 2000).

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  34. Peck and Theodore, Fast Policy, 33; J. Peck and N. Theodore, “Follow the Policy: A Distended Case Approach,” Environment and Planning A 44 (2012): 21–30.

    Return to note reference.

  35. B. Williamson, “Silicon Startup Schools: Technocracy, Algorithmic Imaginaries, and Venture Philanthropy in Corporate Education Reform,” Critical Studies in Education 59, no. 2 (2016): 218–36.

    Return to note reference.

  36. S. Sellar, “Data Infrastructure: A Review of Expanding Accountability Systems and Large-Scale Assessments in Education,” Discourse: Studies in the Cultural Politics of Education 36, no. 5 (2015): 765–77.

    Return to note reference.

  37. G. E. Marcus, “Ethnography in/of the World System: The Emergence of Multi-Sited Ethnography,” Annual Review of Anthropology 24, no. 1 (1995): 105.

    Return to note reference.

  38. P. Rabinow et al., Designs for an Anthropology of the Contemporary (Durham, N.C.: Duke University Press, 2008), 78.

    Return to note reference.

  39. P. N. Edwards et al., “Introduction: An Agenda for Infrastructure Studies,” Journal of the Association for Information Systems 10, no. 5 (2009): 364–74; S. L. Star and K. Ruhleder, “Steps toward an Ecology of Infrastructure: Design and Access for Large Information Spaces,” Information Systems Research 7, no. 1 (1996): 111–34.

    Return to note reference.

  40. N. Rossiter, Software, Infrastructure, Labor: A Media Theory of Logistical Nightmares (New York: Routledge, 2017); B. Larkin, “The Politics and Poetics of Infrastructure,” Annual Review of Anthropology 42, no. 1 (2013): 327–43; K. Easterling, Extrastatecraft: The Power of Infrastructure Space (New York: Verso Books, 2014); L. G. Berlant, “The Commons: Infrastructures for Troubling Times,” Environment and Planning D: Society and Space 34, no. 3 (2016): 393–419.

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  41. Larkin, “Politics and Poetics of Infrastructure,” 330.

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  42. E. Levinas, Collected Philosophical Essays (Pittsburgh: Duquesne University Press, 1987), 50.

    Return to note reference.

  43. M. Bevir and R. A. W. Rhodes, Governance Stories (London: Routledge, 2006).

    Return to note reference.

  44. L. Boltanski, On Critique: A Sociology of Emancipation (Cambridge: Polity, 2011), 69.

    Return to note reference.

  45. Rossiter, Software, Infrastructure, Labor, xvii.

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  46. Easterling, Extrastatecraft, 15.

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  47. Easterling, Extrastatecraft, 21.

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  48. Easterling, Extrastatecraft, 73.

    Return to note reference.

  49. Easterling, Extrastatecraft, 21.

    Return to note reference.

  50. F. Jullien, The Propensity of Things: Toward a History of Efficacy in China (New York: Zone Books, 1995), 9.

    Return to note reference.

  51. M. Foucault, Power/Knowledge: Selected Interviews and Other Writings, 1972–1977 (New York: Pantheon Books, 1980).

    Return to note reference.

  52. G. Agamben, What Is an Apparatus? And Other Essays (Redwood City, Calif.: Stanford University Press, 2009), 12.

    Return to note reference.

  53. Rabinow, Anthropos Today, 54.

    Return to note reference.

  54. Foucault, Power/Knowledge.

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  55. P. L. J. Bailey, “The Policy Dispositif: Historical Formation and Method,” Journal of Education Policy 28, no. 6 (2013): 814.

    Return to note reference.

  56. Easterling, Extrastatecraft, 88.

    Return to note reference.

  57. Larkin, “Politics and Poetics of Infrastructure,” 329.

    Return to note reference.

  58. R. Kitchen, The Data Revolution: Big Data, Open Data, Data Infrastructures, and Their Consequences (Thousand Oaks, Calif.: SAGE, 2014), 6.

    Return to note reference.

  59. Bevir and Rhodes, Governance Stories, 3.

    Return to note reference.

  60. M. Savage and R. Burrows, “The Coming Crisis of Empirical Sociology,” Sociology 41, no. 5 (2007): 885–99.

    Return to note reference.

  61. R. Burrows and M. Savage, “After the Crisis? Big Data and the Methodological Challenges of Empirical Sociology,” Big Data and Society 1, no. 1 (2014): 3, original emphasis.

    Return to note reference.

  62. S. L. Star, “Infrastructure and Ethnographic Practice: Working on the Fringes,” Scandinavian Journal of Information Systems 14, no. 2 (2002): 120.

    Return to note reference.

  63. S. L. Star, “The Ethnography of Infrastructure,” American Behavioral Scientist 43, no. 3 (1999): 377.

    Return to note reference.

  64. Star, “Ethnography of Infrastructure.”

    Return to note reference.

  65. L. Parks and N. Starosielski, introduction to Signal Traffic: Critical Studies of Media Infrastructures, ed. L. Parks and N. Starosielski (Urbana: University of Illinois Press, 2015), 13.

    Return to note reference.

  66. B. Williamson and R. Eynon, “Historical Threads, Missing Links, and Future Directions in AI in Education,” Learning, Media, and Technology 45, no. 3 (2020): 231.

    Return to note reference.

  67. N. Seaver, “Algorithms as Culture: Some Tactics for the Ethnography of Algorithmic Systems,” Big Data and Society 4, no. 2 (2017): 5.

    Return to note reference.

  68. L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Durham, N.C.: Duke University Press, 2020), 5.

    Return to note reference.

  69. P. N. Edwards, “We Have Been Assimilated,” 24–25.

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  70. For this type of work, see D. E. Forsythe, Studying Those Who Study Us: An Anthropologist in the World of Artificial Intelligence (Stanford, Calif.: Stanford University Press, 2001); S. G. Hoffman, “Managing Ambiguities at the Edge of Knowledge: Research Strategy and Artificial Intelligence Labs in an Era of Academic Capitalism,” Science, Technology, and Human Values 42, no. 4 (2017): 703–40.

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  71. Rabinow, Marking Time, 51.

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  72. Rabinow et al., Designs for an Anthropology of the Contemporary, 68–69.

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  73. Mol, Body Multiple, 47, original emphasis.

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  74. G. Deleuze and F. Guattari, A Thousand Plateaus: Capitalism and Schizophrenia (Minneapolis: University of Minnesota Press, 1987), 219.

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  75. B. Karsenti, “Imitation: Returning to the Tarde–Durkheim Debate,” in The Social after Gabriel Tarde. ed. M. Candea (London and New York: Routledge, 2015): 121–35.

    Return to note reference.

  76. Gorur, Sellar, and Steiner-Khamsi, “Big Data and Even Bigger Consequences,” 6.

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  77. C. Bacchi, “Why Study Problematizations? Making Politics Visible,” Open Journal of Political Science 2 (2012): 1–8; P. T. Webb, “Policy Problematization,” International Journal of Qualitative Studies in Education 27, no. 3 (2014): 364–76.

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  78. Rabinow, Anthropos Today. 19.

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  79. I. Stengers, “Putting Problematization to the Test of Our Present,” Theory, Culture, and Society 38, no. 2 (2021): 76.

    Return to note reference.

  80. Rabinow, Anthropos Today, 20.

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  81. M. Foucault, “Polemics, Politics, and Problematizations,” in Ethics, Subjectivity, and Truth, ed. P. Rabinow (New York: New Press, 1994), 118.

    Return to note reference.

  82. Stengers, “Putting Problematization to the Test,” 76.

    Return to note reference.

  83. Stengers, 80.

    Return to note reference.

  84. Rabinow, Marking Time, 7.

    Return to note reference.

4. Infrastructure

  1. Midnight Oil, “Gunbarrel Highway,” Diesel and Dust. Sprint/Columbia (1987).

    Return to note reference.

  2. K. Easterling, Extrastatecraft: The Power of Infrastructure Space (New York: Verso Books, 2014), 11.

    Return to note reference.

  3. Easterling, Extrastatecraft, 11.

    Return to note reference.

  4. G. C. Bowker et al., “Toward Information Infrastructure Studies: Ways of Knowing in a Networked Environment,” in International Handbook of Internet Research, ed. J. Husinger, L. Klastrup, and M. M. Allen (Dordrecht: Springer, 2010), 12; S. L. Star and K. Ruhleder, “Steps toward an Ecology of Infrastructure: Design and Access for Large Information Spaces,” Information Systems Research 7, no. 1 (1996): 111–34.

    Return to note reference.

  5. T. R. Gruber, “A Translation Approach to Portable Ontology Specifications,” Knowledge Acquisition 5, no. 2 (1993): 199–220.

    Return to note reference.

  6. See Data Quality Campaign, http://dataqualitycampaign.org; Postsec Data, http://www.ihep.org/postsecdata.

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  7. The Parthenon Group, “Landscape Review: Education Data,” 2007, https://docs.gatesfoundation.org/documents/landscape-review-education-data.pdf.

    Return to note reference.

  8. Microsoft Corporation, “Schools Interoperability Framework Initiative Releases First Working Specification Following Successful School Pilots,” 1999, https://news.microsoft.com/1999/11/10/schools-interoperability-framework-initiative-releases-first-working-specification-following-successful-school-pilots/#sm.

    Return to note reference.

  9. See Access 4 Learning Community (A4L), http://www.a4l.org.

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  10. A4L, “Introducing the Access 4 Learning Community—the Sif Association Matures to Address Not Only Datamanagement but Data Usage for Learning,” (2015), https://www.sifassociation.org/NewsRoom/Press%20Releases/Introducing%20the%20Access%204%20Learning%20Community.pdf.

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  11. A4L, “Introducing the Access 4 Learning Community.”

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  12. See National Schools Interoperability Program—Services and Projects, http://www.nsip.edu.au/services-and-projects.

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  13. This number was accurate in 2016.

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  14. B. Lingard, “Policy Borrowing, Policy Learning: Testing Times in Australian Schooling,” Critical Studies in Education 51, no. 2 (2010).

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  15. SIF AU (SIF Association Australia), “Tri-Borders: Supporting Students across SA, NT and WA,” (n.d.), http://www.nsip.edu.au/sites/nsip.edu.au/files/Pilot%202.1%20Tri-Borders.pdf.

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  16. See National Schools Interoperability Program—Learning Services Architecture, http://www.nsip.edu.au/learning-services-architecture.

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  17. See National Schools Interoperability Program—Learning Services Architecture (flyer), https://www.nsip.edu.au/sites/nsip.edu.au/files/lsa_flyer_v3-0-4.pdf.

    Return to note reference.

  18. M. Bulger, P. McCormick, and M. Pitcan, “The Legacy of inBloom: Working Paper,” Data and Society Research Institute, 2017, 3.

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  19. See National Schools Interoperability Program—Hub Integration Testing Service, https://www.nsip.edu.au/hits-hub-integration-testing-service; accessed May 17, 2017.

    Return to note reference.

  20. M. Callon, “Introduction: The Embeddedness of Economic Markets in Economics,” Sociological Review 46, no. 1, supplement (1998): 50.

    Return to note reference.

  21. C. Shapiro and H. Varian, Information Rules: A Strategic Guide to the Network Economy (Boston: Harvard Business School Press, 1999), 13.

    Return to note reference.

  22. See work on EdTech during the Covid-19 pandemic: https://prospect.org/api/amp/education/ed-tech-cashes-in-on-the-pandemic/?__twitter_impression=true; accessed August 14, 2020.

    Return to note reference.

  23. Shapiro and Varian, Information Rules.

    Return to note reference.

  24. Sam Sellar, “Making Network Markets in Education: The Development of Data Infrastructure in Australian Schooling,” Globalisation, Societies, and Education 15, no. 3 (2017): 341–51.

    Return to note reference.

  25. SIF AU (SIF Association Australia), “Tri-Borders: Supporting Students across SA, NT, and WA,” emphasis added.

    Return to note reference.

  26. See Services and Projects, https://www.nsip.edu.au/services-and-projects; accessed July 20, 2020.

    Return to note reference.

  27. See Hub Integration Testing Service, https://www.nsip.edu.au/hits-hub-integration-testing-service; accessed May 17, 2017.

    Return to note reference.

  28. S. J. Ball, “Beyond Networks? A Brief Response to ‘Which Networks Matter in Education Governance?,’” Political Studies 57, no. 3 (2009): 690.

    Return to note reference.

  29. A. Hogan, S. Sellar, and B. Lingard, “Commercialising Comparison: Pearson Puts the TLC in Soft Capitalism,” Journal of Education Policy 31, no. 3 (2016): 243–58.

    Return to note reference.

  30. Bulger, McCormick, and Pitcan, “Legacy of inBloom,” 3.

    Return to note reference.

  31. Hogan, Sellar, and Lingard, “Commercialising Comparison”; B. Williamson, “Digital Education Governance: An Introduction,” European Educational Research Journal 15, no. 1 (2016): 3–13.

    Return to note reference.

  32. R. Luckin, W. Holmes, M. Griffiths, and L.B. Forcier, Intelligence Unleashed: An Argument for Ai in Education (Pearson, 2016), https://www.pearson.com/content/dam/corporate/global/pearson-dot-com/files/innovation/Intelligence-Unleashed-Publication.pdf.

    Return to note reference.

  33. D. Gonski et al., “Through Growth to Achievement: Report of the Review to Achieve Educational Excellence in Australian Schools,” Department of Education and Training, March 2018, xiii.

    Return to note reference.

  34. See Online Formative Assessment Initiative, https://www.ofai.edu.au/.

    Return to note reference.

  35. Online Formative Assessment Initiative.

    Return to note reference.

  36. NSIP, unpublished and undated presentation to A4L titled “Towards Learning Services Architecture 2.0.”

    Return to note reference.

  37. “Towards Learning Services Architecture 2.0.”

    Return to note reference.

  38. Gonski et al., “Through Growth to Achievement,” 23.

    Return to note reference.

  39. Callon, “Introduction,” 21.

    Return to note reference.

  40. Callon, 17.

    Return to note reference.

  41. K. Çalışkan and M. Callon, “Economization, Part 2: A Research Programme for the Study of Markets,” Economy and Society 39, no. 1 (2010): 7–8.

    Return to note reference.

  42. I. Busch, Standards: Recipes for Reality (Cambridge, Mass.: MIT Press, 2011), 167, original emphasis.

    Return to note reference.

  43. Easterling, Extrastatecraft, 13.

    Return to note reference.

  44. Easterling, 14.

    Return to note reference.

  45. Easterling, 11.

    Return to note reference.

  46. B. Lingard, “The Global Education Industry, Data Infrastructures, and the Restructuring of Government School Systems,” in Researching the Global Education Industry: Commodification, the Market and Business Involvement. edited by M. Parreira do Amaral, G. Steiner-Khamsi, and C. Thompson (New York: Palgrave Macmillan, 2019), 140.

    Return to note reference.

  47. A. Mackenzie, Transductions: Bodies and Machines at Speed (London: Continuum, 2002), x.

    Return to note reference.

5. Patterns

  1. W. Gibson, Zero History (New York: Penguin, 2010), 177.

    Return to note reference.

  2. A. Rouvroy, T. Berns, and E. Libbrecht, “Algorithmic Governmentality and Prospects of Emancipation: Disparateness as a Precondition for Individuation through Relationships?,” Réseaux, no. 1 (2013): x.

    Return to note reference.

  3. E. Alpaydin, Machine Learning (Cambridge, Mass.: MIT Press, 2016), 23–24.

    Return to note reference.

  4. L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Durham, N.C.: Duke University Press, 2020), 70, original emphasis.

    Return to note reference.

  5. M. Andrejevic and N. Selwyn, “Facial Recognition Technology in Schools: Critical Questions and Concerns,” Learning, Media, and Technology 45, no. 2 (2020): 116.

    Return to note reference.

  6. C. Celis Bueno, “The Face Revisited: Using Deleuze and Guattari to Explore the Politics of Algorithmic Face Recognition,” Theory, Culture, and Society 37, no. 1 (2020): 73–91.

    Return to note reference.

  7. Andrejevic and Selwyn, “Facial Recognition Technology in Schools,” 116.

    Return to note reference.

  8. Andrejevic and Selwyn, 119.

    Return to note reference.

  9. C. Perrotta and N. Selwyn, “Deep Learning Goes to School: Toward a Relational Understanding of Ai in Education,” Learning, Media and Technology 45, no. 3 (2020): 251–69.

    Return to note reference.

  10. N. Selwyn, M. Henderson, and S. Chao, “Exploring the Role of Digital Data in Contemporary Schools and Schooling—‘200,000 Lines in an Excel Spreadsheet,’” British Educational Research Journal 41, no. 5 (2015): 767–81.

    Return to note reference.

  11. Andrejevic and Selwyn, “Facial Recognition Technology in Schools,” 120.

    Return to note reference.

  12. For how these cloud services are integrated into school-ready products, see K. N. Gulson and K. Witzenberger, “Repackaging Authority: Artificial Intelligence, Automated Governance, and Education Trade Shows,” Journal of Education Policy (2020): 1–16.

    Return to note reference.

  13. J. W. Crampton, “Platform Biometrics,” Surveillance and Society 17, no. 1/2 (2019): 54–62.

    Return to note reference.

  14. T. Simonite, and G. Barber, “The Delicate Ethics of Using Facial Recognition in Schools,” Wired. October 17, 2019, https://www.wired.com/story/delicate-ethics-facial-recognition-schools/.

    Return to note reference.

  15. J. Goldenfein, “Facial Recognition Is Only the Beginning,” Public Books. January 27, 2020, https://www.publicbooks.org/facial-recognition-is-only-the-beginning/.

    Return to note reference.

  16. For an overview of Chinese AI policy, see J. Knox, “Artificial Intelligence and Education in China,” Learning, Media, and Technology 45, no. 3 (2020): 298–311.

    Return to note reference.

  17. X. Yang, “Accelerated Move for AI Education in China,” ECNU Review of Education 2, no. 3 (2019): 347–52; H. Roberts et al., “The Chinese Approach to Artificial Intelligence: An Analysis of Policy, Ethics, and Regulation,” AI and Society 36, no. 1 (2021): 59–77.

    Return to note reference.

  18. Knox, “Artificial Intelligence and Education in China,” 304.

    Return to note reference.

  19. C. Jee, “IBM Says It Is No Longer Working on Face Recognition Because It’s Used for Racial Profiling,” MIT Technology Review. June 9, 2020, https://www.technologyreview.com/2020/06/09/1002947/ibm-says-it-is-no-longer-working-on-face-recognition-because-its-used-for-racial-profiling/.

    Return to note reference.

  20. Skellefteå Municipality, Anderstorp Gymnasium, and Tieto, Future Classroom-Summary: Do Innovative Technologies Have the Potential to Transform Presence Registration?. Sweden, 2018, http://pages.tieto.com/rs/517-ITT-285/images/SummaryFutureClassroom.pdf.

    Return to note reference.

  21. S. Edvardsen, “How to Interpret Sweden’s First GDPR Fine on Facial Recognition,” IAPP: The Privacy Adviser. August 27, 2019, https://iapp.org/news/a/how-to-interpret-swedens-first-gdpr-fine-on-facial-recognition-in-school/.

    Return to note reference.

  22. Andrejevic and Selwyn, “Facial Recognition Technology in Schools,” 123.

    Return to note reference.

  23. Han Wang—Company Information, https://hanwangt.en.china.cn/about.html.

    Return to note reference.

  24. It is hard to find English language pages on this system. The most extensive was an investigative journalism piece by X. Yujie, “Camera above the Classroom,” SixthTone. March 27, 2019, https://www.sixthtone.com/news/1003759/camera-above-the-classroom.

    Return to note reference.

  25. Crampton, “Platform Biometrics,” 60; Rouvroy, Berns, and Libbrecht, “Algorithmic Governmentality and Prospects of Emancipation.”

    Return to note reference.

  26. J. Pugliese, Biometrics: Bodies, Technologies, Biopolitics (New York: Routledge, 2010), 20.

    Return to note reference.

  27. Andrejevic and Selwyn, “Facial Recognition Technology in Schools,” 116.

    Return to note reference.

  28. McStay, Emotional AI: The Rise of Empathic Media, 45, no. 3 (2020): 66–67.

    Return to note reference.

  29. A. Kachur et al., “Assessing the Big Five Personality Traits Using Real-Life Static Facial Images,” Scientific Reports 10, no. 1 (2020): 84–87.

    Return to note reference.

  30. B. Williamson, “Coding the Biodigital Child: The Biopolitics and Pedagogic Strategies of Educational Data Science,” Pedagogy, Culture, and Society 24, no. 3 (2016): 410.

    Return to note reference.

  31. Celis Bueno, “Face Revisited,” 77.

    Return to note reference.

  32. McStay, Emotional AI, 59.

    Return to note reference.

  33. McStay, 59.

    Return to note reference.

  34. B. Williamson, “Moulding Student Emotions through Computational Psychology: Affective Learning Technologies and Algorithmic Governance,” Educational Media International 54, no. 4 (2017): 267–88.

    Return to note reference.

  35. Amoore, Cloud Ethics, 74.

    Return to note reference.

  36. M. Whittaker et al., AI Now Report 2018 (New York: AI Now Institute, 2018), 25.

    Return to note reference.

  37. We recognize that BIPOC is an imperfect label.

    Return to note reference.

  38. A. Bonnett and B. Carrington, “Fitting into Categories or Falling between Them? Rethinking Ethnic Classification,” British Journal of Sociology of Education 21, no. 4 (2000): 487–500; T. Kukutai and V. Thompson, “‘Inside Out’: The Politics of Enumerating the Nation by Ethnicity,” in Social Statistics and Ethnic Diversity: Cross-National Perspectives in Classifications and Identity Politics, ed. P. Simon, V. Piché, and A. A. Gagnon (Dordrecht: Springer, 2015), 39–61.

    Return to note reference.

  39. I. Hacking, “Why Race Still Matters,” Daedalus 134, no. 1 (2005): 109.

    Return to note reference.

  40. L. Stark, “Facial Recognition is the Plutonium of AI,” XRDS: Crossroads, The ACM Magazine for Students 25, no. 3 (2019): 50–55.

    Return to note reference.

  41. R. Benjamin, Race after Technology: Abolitionist Tools for the New Jim Code (Cambridge: Polity, 2019), 125.

    Return to note reference.

  42. T. Miller, P. Howe, and L. Sonenberg, “Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences,” arXiv preprint arXiv:1712.00547 (2017).

    Return to note reference.

  43. Amoore, Cloud Ethics, 139.

    Return to note reference.

  44. M. L. Gray and S. Suri, Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass (Boston: Houghton Mifflin Harcourt, 2019).

    Return to note reference.

  45. S. U. Noble, Algorithms of Oppression: How Search Engines Reinforce Racism (New York: New York University Press, 2018).

    Return to note reference.

  46. A. Campalo et al., AI Now 2017 Report (New York: AI Now, 2017), 18.

    Return to note reference.

  47. S. M. West, M. Whittaker, and K. Crawford, “Discriminating Systems: Gender, Race, and Power in AI,” AI Now Institute, 2019, 8.

    Return to note reference.

  48. F. Demie, “The Experience of Black Caribbean Pupils in School Exclusion in England,” Educational Review, 73, no. 1 (2021): 55–70; D. Gillborn and D. Youdell, Rationing Education: Policy, Practice, Reform, and Equity (Buckingham: Open University Press, 2000).

    Return to note reference.

  49. C. Katzenbach and U. Lena, “Algorithmic Governance,” Internet Policy Review 8, no. 4 (2019): 6.

    Return to note reference.

  50. Amoore, Cloud Ethics, 66.

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  51. L. Parisi, “The Alien Subject of AI,” Subjectivity 12, no. 1 (2019): 36. Note that Parisi likely uses the male pronoun intentionally in reference to the male subject.

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  52. McStay, Emotional AI, 9.

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  53. Andrejevic and Selwyn, “Facial Recognition Technology in Schools,” 125.

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  54. Celis Bueno, “Face Revisited,” 76.

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  55. Parisi, “Alien Subject of AI.”

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  56. Amoore, Cloud Ethics, 6.

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  57. Amoore, 6.

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6. Automation

  1. DeepMind was acquired by Google in 2014. See Deep Mind—Company Overview, https://deepmind.com/about. Go has simple rules but is very complex strategically. A. Brokaw, “How the Game Go Is Played,” The Verge. March 11, 2016, https://www.theverge.com/2016/3/11/11202542/how-to-play-go-game-google-deepmind-alphago-ai.

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  2. J. D. Kelleher, Deep Learning (Cambridge, Mass.: MIT Press, 2019).

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  3. B. Anderson, “Preemption, Precaution, Preparedness: Anticipatory Action and Future Geographies,” Progress in Human Geography 34, no. 6 (2010): 777–98.

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  4. P. Rabinow, French DNA: Trouble in Purgatory (Chicago: University of Chicago Press, 1999), 150.

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  5. L. Parisi, “Reprogamming Decisionism,” E-Flux Journal 85 (2017): paragraph 7.

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  6. This information is from the Center’s website. The URL is not cited to provide a minimum condition of anonymity.

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  7. Like all research on contemporary political phenomena, especially on organizations, the Center’s policy centrality is likely to change after publication.

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  8. The Center’s “Business Intelligence Report,” 7.

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  9. K. N. Gulson, “Urban Accommodations: Policy, Education, and a Politics of Place,” Journal of Education Policy 23, no. 2 (2008): 153–63.

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  10. R. Crooks, “Representationalism at Work: Dashboards and Data Analytics in Urban Education,” Educational Media International 54, no. 4 (2017): 290.

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  11. R. Kitchin, T. P. Lauriault, and G. McArdle, “Knowing and Governing Cities through Urban Indicators, City Benchmarking, and Real-Time Dashboards,” Regional Studies, Regional Science 2, no. 1 (2015): 11.

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  12. B. Williamson, “Digital Education Governance: Data Visualization, Predictive Analytics, and ‘Real-Time’ Policy Instruments,” Journal of Education Policy 31, no. 2 (2016): 131.

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  13. M.-C. Liu and Y.-M. Huang, “The Use of Data Science for Education: The Case of Social-Emotional Learning,” Smart Learning Environments 4, no. 1 (2017): 2.

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  14. B. Williamson, “Who Owns Educational Theory? Big Data, Algorithms, and the Expert Power of Education Data Science,” E-Learning and Digital Media 14, no. 3 (2017): 119–20.

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  15. I. Lowrie, “Algorithmic Rationality: Epistemology and Efficiency in the Data Sciences,” Big Data and Society 4, no. 1 (2017): 1–2.

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  16. P. Adams, “Education Policy: Explaining, Framing and Forming,” Journal of Education Policy 31, no. 3 (2016): 290–307.

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  17. L. Parisi, “Automated Thinking and the Limits of Reason,” Cultural Studies ↔ Critical Methodologies 16, no. 5 (2016): 478.

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  18. Parisi, “Reprogamming Decisionism,” paragraph 10.

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  19. S. J. Ball, Education Reform: A Critical and Post-Structural Approach (Philadelphia: Open University Press, 1994); P. T. Webb and K. N. Gulson, “Policy Scientificity 3.0: Theory and Policy Analysis in-and-for This World and Other-Worlds,” Critical Studies in Education 56, no. 1 (2015): 161–74. This is not to say that causality is not important in machine learning. There are many attempts to strengthen the causal claims of automated decision-making (e.g., F. Lattimore and D. Rohde, “Causal Inference with Bayes Rule,” Gradient Institute Blog, December 13, 2019, https://medium.com/gradient-institute/causal-inference-with-bayes-rule-eed8ae45fb2e).

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  20. Parisi, “Automated Thinking and the Limits of Reason,” 480.

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  21. Parisi.

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  22. V. Adams, M. Murphy, and A. E. Clarke, “Anticipation: Technoscience, Life, Affect, Temporality,” Subjectivity: International Journal of Critical Psychology 28, no. 1 (2009): 258.

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  23. E. Zeide, “The Structural Consequences of Big Data-Driven Education,” Big Data 5, no. 2 (2017): 167.

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  24. H. Komatsu and J. Rappleye, “A New Global Policy Regime Founded on Invalid Statistics? Hanushek, Woessmann, PISA, and Economic Growth,” Comparative Education 53, no. 2 (2017): 169–91.

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  25. J. Bridle, New Dark Age: Technology and the End of the Future (London: Verso, 2018), 40.

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  26. L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Durham, N.C.: Duke University Press, 2020), 152.

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  27. G. Deleuze, Negotiations: 1972–1990, trans. Martin Joughin (New York: Columbia University Press, 1995).

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  28. F. Rizvi and B. Lingard, “Social Equity and the Assemblage of Values in Australian Higher Education,” Cambridge Journal of Education 41, no. 1 (2011): 9.

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  29. S. U. Noble, Algorithms of Oppression: How Search Engines Reinforce Racism (New York: New York University Press, 2018).

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  30. S. J. Ball, “The Errors of Redemptive Sociology or Giving Up on Hope and Despair,” British Journal of Sociology of Education 41, no. 6 (2020): 871; M. J. Dumas, A. D. Dixson, and E. Mayorga, “Educational Policy and the Cultural Politics of Race: Introduction to the Special Issue,” Educational Policy 30, no. 1 (2016): 3– 12.

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  31. Parisi, “Reprogamming Decisionism,” paragraph 13.

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  32. G. Bateson, “Cybernetic Explanation,” American Behavioral Scientist 10, no. 8 (1967): 29.

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  33. Parisi, “Reprogamming Decisionism.”

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7. Synthetic Politics

  1. See a technical report on the algorithm: https://rpubs.com/JeniT/ofqual-algorithm.

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  2. L. Amoore, “Why ‘Ditch the Algorithm’ Is the Future of Political Protest,” The Guardian. August 19 2020, https://www.theguardian.com/commentisfree/2020/aug/19/ditch-the-algorithm-generation-students-a-levels-politics.

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  3. G. Deleuze, Negotiations: 1972–1990, trans. Martin Joughin (New York: Columbia University Press, 1995), 174.

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  4. D. Savat, Uncoding the Digital: Technology, Subjectivity, and Action in the Control Society (Basingstoke: Palgrave Macmillan UK, 2013); G. Thompson and I. Cook, “The Logic of Data-Sense: Thinking through Learning Personalisation,” Discourse: Studies in the Cultural Politics of Education 38, no. 5 (2017): 740–54; P. T. Webb, “The Evolution of Accountability,” Journal of Education Policy 26, no. 5 (2011): 1–22.

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  5. P. T Webb, and K. N. Gulson. “Policy Scientificity 3.0: Theory and Policy Analysis in-and-for This World and Other-Worlds,” Critical Studies in Education 56, no. 1 (2015): 161–74.

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  6. G. Deleuze and F. Guattari, Anti-Oedipus (Minneapolis: University of Minnesota Press, 1983).

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  7. J. Bridle, New Dark Age: Technology and the End of the Future (London: Verso, 2018), 46.

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  8. L. Winner, “Technologies as Forms of Life,” in Epistemology, Methodology, and the Social Sciences, ed. R. S. Cohen and M. W. Wartofsky (Dordrecht: Springer, 1983), 254.

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  9. J. Ross, “Speculative Method in Digital Education Research,” Learning, Media, and Technology 42, no. 2 (2017): 215.

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  10. I. Stengers, “Putting Problematization to the Test of Our Present,” Theory, Culture, and Society 38, no. 2 (2021): 89.

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  11. Bridle, New Dark Age, 12.

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  12. K. Easterling, Extrastatecraft: The Power of Infrastructure Space (New York: Verso Books, 2014), 15.

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  13. D. Easton, The Political System (New York: Knopf, 1953).

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  14. Edwards, “We Have Been Assimilated,” 23.

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  15. L. Parisi, “After Nature: The Dynamic Automation of Technical Objects,” in Posthumous Life: Theorizing beyond the Posthuman, ed. J. Weinstein and C. Colebrook (New York: Columbia University Press, 2017), 155.

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  16. L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Durham, N.C.: Duke University Press, 2020), 115.

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  17. R. Benjamin, Race after Technology: Abolitionist Tools for the New Jim Code (Cambridge: Polity, 2019).

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  18. F. Pasquale, New Laws of Robotics: Defending Human Expertise in the Age of AI (Cambridge, Mass.: Harvard University Press, 2020).

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  19. S. Zuboff, The Age of Surveillance Capitalism: The Fight for Human Future at the New Frontier of Power (London: Profile Books, 2019).

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  20. While still in draft form, this is, at the time of writing, the most developed regulation concerning AI: https://digital-strategy.ec.europa.eu/en/library/proposal-regulation-laying-down-harmonised-rules-artificial-intelligence-artificial-intelligence.

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  21. Pasquale, “Internet Nondiscrimination Principles Revisited: Working Paper,” 2020, https://ssrn.com/abstract=3634625.

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  22. Zuboff, Age of Surveillance Capitalism, 524.

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  23. S. Leaton Gray, “Artificial Intelligence in Schools: Towards a Democratic Future,” London Review of Education 18, no. 2 (2020): 174.

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  24. J. Sadowski, Too Smart: How Digital Capitalism Is Extracting Data, Controlling Our Lives, and Taking over the World (Cambridge, Mass.: MIT Press, 2020), 177–78.

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  25. A. Campalo et al., AI Now 2017 Report (New York: AI Now, 2017).

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  26. R. Luckin, Machine Learning and Human Intelligence: The Future of Education for the 21st Century (London: UCL Institute of Education Press, 2018), 138.

    Return to note reference.

  27. S. Knight, A. Shibani, S. Abel, A. Gibson, and P. Ryan, “Acawriter: A Learning Analytics Tool for Formative Feedback on Academic Writing,” Journal of Writing Research 12, no. 1 (2020): 141–86; Microsoft has been at the forefront of this kind of incorporation of teachers, academics, and students into the Microsoft ecosystem.

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  28. Zuboff, Age of Surveillance Capitalism.

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  29. L. Parisi, “The Alien Subject of AI,” Subjectivity 12, no. 1 (2019): 34.

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  30. Sadowski, Too Smart, 170.

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  31. A. R. Galloway and E. Thacker, The Exploit: A Theory of Networks (Minneapolis: University of Minnesota Press, 2007), 5.

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  32. T. Walsh, It’s Alive! Artificial Intelligence from the Logic Piano to Killer Robots (Ballarat, Australia: La Trobe University Press, 2017).

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The University of Minnesota Press gratefully acknowledges support for the open-access edition of this book from the University of Sydney, the Australian Research Council, and the Social Sciences and Humanities Research Council (SSHRC) of Canada.

A different version of chapter 2 was previously published as Sam Sellar, “Acceleration, Automation, and Pedagogy: How the Prospect of Technological Unemployment Creates New Conditions for Educational Thought,” in Education and Technological Unemployment, ed. M. A. Peters, P. Jandric, and A. J. Means, 131–44 (Dordrecht: Springer, 2019). A different version of chapter 4 was previously published as Kalervo N. Gulson and Sam Sellar, “Emerging Data Infrastructures and the New Topologies of Education Policy,” Environment and Planning D: Society and Space 37, no. 2 (2019): 350–66; and as Sam Sellar and Kalervo N. Gulson, “Dispositions and Situations of Education Governance: The Example of Data Infrastructure in Australian Schooling,” in Education Governance and Social Theory: Interdisciplinary Approaches to Research, ed. A. Wilkins and A. Olmedo, 63–79 (London: Bloomsbury Academic, 2018); Bloomsbury Academic is an imprint of Bloomsbury Publishing PLC. A different version of chapter 6 was published as Sam Sellar and Kalervo N. Gulson, “Becoming Information Centric: The Emergence of New Cognitive Infrastructures in Education Policy,” Journal of Education Policy 36, no. 3 (2021): 309–26, available at https://www.tandfonline.com.

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