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      Artificial intelligence and the technological turn of public education privatization: In defence of democratic education

      London Review of Education
      UCL Press

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          Abstract

          This article considers how the development of for-profit artificial intelligence (AI) technologies fosters the privatization of public education and erodes the values and practices of democratic education. The introduction situates the advent of digital technologies in the context of the structural economic and ideological shifts of the past 40 years. Such changes include neo-liberal restructuring, the repressive school and social turn, changes in the use of positivist ideology in schooling, the role of new technologies in social and cultural reproduction and changing imperatives for capital accumulation. The article illustrates different uses of AI as part of the technological turn of public education privatization. Examples include: (1) adaptive learning technology, and transformations to teacher work and conceptions of knowledge and learning; (2) biometric pedagogy and the cultural politics of locating learning in the body; and (3) the convergence of impact investing and digital surveillance technologies. The article considers how changes in the ownership and control over different aspects of public education relate to the cultural politics of knowledge and learning. It also examines how, under the guise of disinterested objectivity and neutrality, particular class and cultural ideologies and interests are promoted through new technologies, with significant pedagogical, cultural, economic and political implications. The article concludes by arguing that AI education is a site of cultural and political contestation and must be comprehended as a form of representational politics. By showing a critical pedagogical AI project, the article suggests that the anti-democratic tendencies of most AI education is hardly inevitable or determined, but rather represents a replication of long-standing ideologies.

          Most cited references42

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          When data is capital: Datafication, accumulation, and extraction

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            Representation: Cultural Representations ad Signifying Practices

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              Automating inequality: How high-tech tools profile, police, and punish the poor

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                London Review of Education
                London Review of Education
                UCL Press
                1474-8460
                July 21 2020
                July 21 2020
                : 18
                : 2
                Article
                10.14324/LRE.18.2.04
                0293d40b-0b5d-451f-a7f9-d8e1b2d1f91e
                © 2020

                http://creativecommons.org/licenses/by/4.0/

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