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This chapter reviews ways in which machine learning is being deployed in environmental science, policy, and management and considers their sociological implications. The chapter first reviews how machine learning is used to collect and classify data, to harmonize diverse datasets, and to intervene at various phases of the environmental policy cycle. Second, drawing on research and frameworks from science and technology studies, the chapter explores machine learning’s role as environmental infrastructure that is embedded in physical systems and social institutions. Third, drawing on political economic perspectives, the chapter locates the sociology of machine learning and the environment in the context of the analysis of global capitalism and its relationship to environmental, political, and economic inequality. The chapter concludes by outlining several areas for further research in the sociology of machine …