对当代教育政策中数据使用背后原因的批判
虽然人工智能超越人类的科幻故事仍然是非常幻想的，但在《教育算法》中，作者讲述了算法和机器如何改变教育治理的真实故事，对数据及其在教育政策中的作用进行了引人入胜的讨论和评论。
《教育算法》（Algorithms of Education）探讨了对于政策制定者来说，如今不断增长的数据量如何创造出一种幻觉，即对学生的教育未来以及学校领导和教师的工作拥有更大的控制权。作者认为，事实上，随着算法和人工智能进一步将教育经验和远程决策者从教学中抽象出来，教育数据化的增加提供的控制越来越少。专注于教育政策和治理的不断变化的条件，教育算法提出，学校和政府正越来越多地转向“综合治理”——一种治理，在这种治理中，人和机器作为优化教育的战略变得不那么清晰。
探索数据基础设施、面部识别和数据科学在教育中日益广泛使用的案例研究，《教育算法》利用了从批判性理论和媒体研究到科学技术研究和教育政策研究的广泛领域，为教育治理中的数据化和人工智能绘制了政治和方法学方向图。作者认为，我们必须超越人类和机器之间的争论，为教育制定新策略和新政治。
Algorithms of Education: How Datafication and Artificial Intelligence Shape Policy
A critique of what lies behind the use of data in contemporary education policy
While the science fiction tales of artificial intelligence eclipsing humanity are still very much fantasies, in Algorithms of Education the authors tell real stories of how algorithms and machines are transforming education governance, providing a fascinating discussion and critique of data and its role in education policy.
Algorithms of Education explores how, for policy makers, today’s ever-growing amount of data creates the illusion of greater control over the educational futures of students and the work of school leaders and teachers. In fact, the increased datafication of education, the authors argue, offers less and less control, as algorithms and artificial intelligence further abstract the educational experience and distance policy makers from teaching and learning. Focusing on the changing conditions for education policy and governance, Algorithms of Education proposes that schools and governments are increasingly turning to “synthetic governance”—a governance where what is human and machine becomes less clear—as a strategy for optimizing education.
Exploring case studies of data infrastructures, facial recognition, and the growing use of data science in education, Algorithms of Education draws on a wide variety of fields—from critical theory and media studies to science and technology studies and education policy studies—mapping the political and methodological directions for engaging with datafication and artificial intelligence in education governance. According to the authors, we must go beyond the debates that separate humans and machines in order to develop new strategies for, and a new politics of, education.
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