Machine learning is fundamentally transforming financial markets. Where trading strategies were once crafted by human experts—executed manually or through pre-coded rules—firms now build models that generate the strategies themselves. These are not just tools but trading automatons: semi-independent systems designed to learn from markets and act on their own. Drawing on over a decade of fieldwork in financial markets, Christian Borch offers a rare inside look at how these systems are built, the risks they pose, and how they challenge our understanding of markets and decision-making. As trading automatons grow more complex and opaque—even to their designers—new sociological questions emerge: What happens when machines become the primary agents in markets? And how should we understand economic action when human judgment is no longer at the center? Trading Beyond Understanding is a powerful investigation of machine agency, market transformation, and the shifting boundaries between technological systems and social life.
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Christian Borch is Professor of Sociology at the University of Copenhagen. He is the author of The Politics of Crowds (2012) and Social Avalanche (2020), and co-editor of The Oxford Handbook of the Sociology of Machine Learning (2025).
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