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. 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.0Algorithms 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.0Exploring 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 Education, Digital Culture, Science and Technology Studies Cover Page 1 Title Page 4 Copyright Page 5 Contents 6 Introduction: Synthetic Governance: Algorithms of Education 8 Chapter 1: Governing: Networks, Artificial Intelligence, and Anticipation 24 Chapter 2: Thought: Acceleration, Automated Thinking, and Uncertainty 42 Chapter 3: Problems: Concept Work, Ethnography, and Policy Mobility 62 Chapter 4: Infrastructure: Interoperability, Datafication, and Extrastatecraft 78 Chapter 5: Patterns: Facial Recognition and the Human in the Loop 102 Chapter 6: Automation: Data Science, Optimization, and New Values 118 Chapter 7: Synthetic Politics: Responding to Algorithms of Education 138 Acknowledgments 152 Notes 154 Index 186 About the Author 198 "Exploring case studies of data infrastructures, facial recognition, and the use of data science in education, Algorithms of Education maps the political and methodological directions for engaging with datafication and artificial intelligence in education governance. According to the authors, we must go beyond debates that separate humans and machines to develop new strategies for, and a new politics of, education"-- Provided by publisher
