Abstract

As an educator have you recently heard the term or perhaps even been told to be data driven? Inherent in this simple two-word statement is a quagmire of ethical and privacy concerns that educators must confront to reach the goal and realize the expected results. Central to the concept of data-centered collection, interpretation, and prediction is surveillance capitalism from which many of the tools, methods, and ideology used originate. This review of Shoshana Zuboff's work narrows the focus to the implications for education both in the classroom and in research. As an educator, Zuboff describes three central areas of concern for education's adoption of surveillance capitalist methodologies: changes to the division of learning, private money in research, and the impacts on student development. The work presents many quesitons that can be raised at all levels of educaiton to quesiton technological adoption in and for the classroom.

Highlights

  • Under COVID-19 restrictions, the realm of education is changing faster than anyone could have expected

  • Though initially categorized as a branch of information capitalism in which data were collected within any given company to improve its efficiencies (Matthan 2019), Zuboff shows how surveillance capitalism has since moved data collection into all areas of customer social existence

  • Perhaps most Orwellian, these predictions are sold on what’s called a “behavioural futures market” (p. 8) where advertisers and marketing firms pay for the predictions extracted from the dispossessed private data and use the predictions to better target consumers and influence their purchasing behaviour

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Summary

Introduction

Under COVID-19 restrictions, the realm of education is changing faster than anyone could have expected. The work is an easy read that defines, describes, and makes a compelling case against surveillance capitalism and the collection and use of spatial, personal, and digital data to influence behaviour and increase profits for corporate shareholders.

Results
Conclusion

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