This chapter provides a critical analysis of ‘machine learning’ in education, and its relationship to the discourses of technological unemployment. The promotion of machine learning in education is shown to tend towards a narrative of ‘disruption’; framed as an essential future skill, and accompanied by a prominent public discourse of imminent job replacement, clearly directed towards ‘professional’ and ‘creative’ occupations. These claims are questioned through identifying a distinction between ‘automation’ and ‘autonomy’ in machine learning. Further, educational responses to the discourse of machine learning are examined, suggesting a concerted attempt to re-centre the human being as the authentic site of agency in an era of ‘intelligent machines’. However, this is shown to tend towards a powerful rationale for casting the learner as a ‘creative, problem-solving entrepreneur’, versed in the skills of ‘computational thinking’ that categorise the world into discrete ‘problems’ and ‘solutions’, and aligned with a marketised model of education. The chapter concludes by suggesting that such a framing of the learner should be balanced with notions of critical thinking and citizenship, that provide the capacity to understand, and engage with, the broader social and political conditions within which technologies such as machine learning are developed.
|Title of host publication||Education and Technological Unemployment|
|Editors||Michael A. Peters, Petar Jandrić , Alexander J. Means|
|Number of pages||16|
|Publication status||Published - 30 Apr 2019|