Learning Under Algorithmic Conditions
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Learning Under Algorithmic Conditions

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內容簡介

Exploring the influence of AI technologies on theories of reason, cognition, learning, and education

Learning Under Algorithmic Conditions presents twenty-seven concise essays that collectively chart the shifting terrain of learning in the age of artificial intelligence. Providing historical and philosophical context, this innovative volume features prominent scholars from the fields of media studies, philosophy, and education research, who shed light on how learning has become newly envisioned, machinic, and more-than-human. The contributors unravel various histories of machine intelligence and elucidate the current impact of machine learning technologies on practices of knowledge production. Teeming with theoretical and practical insights, Learning Under Algorithmic Conditions is an interdisciplinary guide for those working across the humanities and social sciences as well as anyone interested in understanding our changing social, political, and technical infrastructures.

Contributors: Craig Carson, Adelphi U; Felicity Coleman, U of the Arts London; Ed Dieterle; Shayan Doroudi, U of California, Irvine; David Gauthier, Utrecht U; Cathrine Hasse, Aarhus U; Talha Can İşsevenler, CUNY; Goda Klumbyte; Robb Lindgren, U of Illinois Urbana-Champaign; Michael Madiao; Henry Neim Osman; Luciana Parisi, Duke U; Carolyn Pedwell, Lancaster U; Arkady Plotnitsky, Purdue U; Julian Quiros, U of Pennsylvania; Sina Rismanchian; Warren Sack, U of California, Santa Cruz; R. Joshua Scannell, The New School; Gregory J. Seigworth, Millersville U; Rebecca Uliasz, U of Michigan; David Wagner, U of New Brunswick; Ben Williamson, U of Edinburgh.

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作者簡介

Elizabeth de Freitas is professor at Adelphi University. She is author of Posthuman Social Science and Computational Culture: Essays on Methodology, Theory, and Practice and coauthor of Mathematics and the Body: Material Entanglements in the Classroom.

Matthew X. Curinga is a software developer, associate professor of educational technology and computer science education at Adelphi University, and cofounder of the MIXI Institute for STEM and the Imagination.

Ezekiel J. Dixon-Román is professor of critical race, media, and educational studies and director of the Edmund W. Gordon Institute for Advanced Study at Teachers College, Columbia University. He is author of Inheriting Possibility: Social Reproduction and Quantification in Education (Minnesota, 2017).

P. Taylor Webb is professor in the Department of Educational Studies at the University of British Columbia. He is coauthor of Education Policy and Racial Biopolitics in Multicultural Cities and Algorithms of Education: How Datafication and Artificial Intelligence Shape Policy (Minnesota, 2022).

 

詳細資料

  • ISBN:9781517920043
  • 規格:精裝 / 336頁 / 普通級 / 初版
  • 出版地:美國

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