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El. knyga: Thinking Through Data: How Outliers, Aggregates, and Patterns Shape Perception

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Thinking Through Data: How Outliers, Aggregates, and Patterns Shape PerceptionDidesnis paveikslėlis
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We encounter digital data processing on a range of platforms and in a multitude of contexts today: in the predictive algorithms of the financial sector, in drones, insurance, and risk management, in smart cities, biometrics, medicine, and more. This fascinating book explores the historical context of the current data-driven paradigm and explains how elusive yet crucial statistical concepts such as outliers, aggregates, and patterns form how we sense and make sense of data. From the sixteenth century's embodied measurements of the foot, through the blurred facial features of L'Homme Moyen, to the image aggregates of today's security systems, the examples collected in this book illustrate the central role of aesthetics throughout the history of statistical knowledge production. Taking its point of departure in analyses and discussions of contemporary artistic experiments by Rossella Biscotti, Stéphanie Solinas, and Adam Broomberg and Oliver Chanarin, the book broadens our understanding of the structures of knowledge and methods in statistical computation beyond optimistic narratives of calculative power. Venturing out into the tails of the distributionsto the systemically overlooked and excludedthis book challenges us to embrace an alternative view of modern data processing.

Recenzijos

"Anyone who wants to understand the fundamentals of contemporary data processing and data sciences can turn to this study, which is both original and coherently structured and whose epistemic questions are always in close contact with the digital arts." Sybille Krämer, Freie Universität Berlin "How do we think with data? From aggregates to patterns, from numbering to classifying and ordering, thinking has become driven by data. In this book, the digital object affords a new dimension of meaning exposing unattended possibilities of critical thinking."

Luciana Parisi, Duke University

Acknowledgments
Introduction: Thinking Through Data
1. Outliers
2. Aggregates
3. Patterns
Conclusion: A Data-Saturated World
Notes
Index
Maja Bak Herrie, postdoc at The School of Communication and Culture at Aarhus University, works within the fields of aesthetics, media theory, and the philosophy of science on topics such as computational technologies of vision, scientific imaging, photography, and artistic research. She is co-editor The Nordic Journal of Aesthetics.
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Pastovi nuoroda: https://www.kriso.lt/db/97815036421026e.html
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