- Title
- Artificial intelligence and machine learning: A practical and ethical guide for teachers.
- Creator
- Southgate, Erica
- Relation
- Digital disruption in teaching and testing: Assessments, Big Data and the transformation of schooling.
- Relation
- https://doi-org.ezproxy.newcastle.edu.au/10.4324/9781003045793
- Publisher
- Routledge
- Resource Type
- book chapter
- Date
- 2021
- Description
- n February 2020, I was contacted by a journalist seeking comment on the trial of a facial recognition product designed to replace traditional roll call in schools. The product had received a significant amount of commercialization funding from the Australian Government Department of Industry, Science, Energy, and Resources.The published article focused on the lack of Australian regulation related to this type of technology and raised questions about the “convenience of automating rollcall procedures outweigh(ing) the sensitivity of collecting biometric information”(Basford, 2020, para. 7). The article hit several nerves regarding the best use for, and ethico-governance implications of, automation powered by artificial intelligence (AI)in schools (in this case, biometric technology that collects information from the stu-dent’s body). As the article pointed out, the issue is not only how we can use AI“for good,”but for what it is“good for”in educational settings.To have informed conversations about the use of AI in education, teachers and policymakers must negotiate a dense multi/interdisciplinary web of knowledge comprising: technical information about systems and the mathematical and statis-tical methodologies that are used by machines to analyze data; ethical frameworks that do not necessarily provide definitive answers; and a fast-evolving, intricate legal and regulatory landscape. In addition, they must weigh up the potential benefits and risks of AI-powered systems developed (typically independent of educators) by small and large companies in the national and transnational educa-tional technology (EdTech) sector. In response to this complex situation, the aim of this chapter is to introduce educators and policymakers to some foundational knowledge about AI so there can be critical and productive engagement with thetechnology. This chapter is translational research: it is an attempt to bridge the divide, in an accessible way, between the realms of the technical, the pedagogical,and ethico-governance issues associated with AI. I begin the chapter by explain-ing AI and its subfield of machine learning (ML) before proceeding to scope out current and potential uses of AI in educational settings. I then highlight some key ethico-governance challenges for educators and school leaders, policymakers, and industry stakeholders
- Subject
- artificial intelligence; teachers; education; policymakers
- Identifier
- http://hdl.handle.net/1959.13/1448901
- Identifier
- uon:43517
- Identifier
- ISBN:9781003045793
- Language
- eng
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