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Figures walk toward a glowing doorway of devices while one figure raises a hand in refusal and another waits in shadow.
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Research · Policy & Ethics

Refusing Educational Technology: Artificial Intelligence, Inequity, and the Problem of Critical Optimism

Source: Educational Researcher, . Summarized by Human Learning Review.

Summary

This essay asks what positions educators and other stakeholders take toward educational technology, and whether refusing a technology counts as a legitimate choice. It reports no empirical results. The authors use generative AI as a case and draw on science and technology studies to map the range of stances people adopt toward technology in education.

  • The authors argue that optimism is education's default position toward new technology.
  • They contend this optimism holds even among critics who see technology as capable of amplifying inequity, a stance the title calls critical optimism.
  • According to the essay, refusal is rarely treated as a legitimate response to educational technology.
  • The authors argue that unproven tools such as generative AI carry potential for harm at scale, so the most rational stance is strong caution paired with a readiness to refuse.
  • They propose specific forms of refusal that educational stakeholders could consider.

The essay closes by setting out what refusal could look like in practice. The authors describe curricular refusal and bureaucratic refusal, and add a third, administrative form, as options for people working in education. Their argument starts from the observation that AI, like earlier technologies, arrives with both hope and worry about what it means for schooling. They hold that the risk of widespread harm from tools whose benefits are unproven justifies a cautious default, with refusal kept open as a real choice.

Main findings

  • The authors argue that optimism is education's default stance toward technology, even among critics who worry it can widen inequity.
  • The essay contends that refusing a technology is rarely accepted in education as a legitimate response.
  • Because unproven tools like generative AI could cause harm at scale, the authors argue that strong caution with a readiness to refuse is the most rational position.
  • The authors outline curricular and bureaucratic forms of refusal, along with an administrative one, for educational stakeholders to consider.

This page is a short summary of a research paper. The full piece belongs to Educational Researcher, and preprints may not have been peer reviewed.

Read the original at Educational Researcher
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