Maja Bak Herrie 
Thinking Through Data [EPUB ebook] 
How Outliers, Aggregates, and Patterns Shape Perception

Apoio

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 distributions—to the systemically overlooked and excluded—this book challenges us to embrace an alternative view of modern data processing.

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Métodos de Pagamento

Tabela de Conteúdo

Acknowledgments
Introduction: Thinking Through Data
1. Outliers
2. Aggregates
3. Patterns
Conclusion: A Data-Saturated World
Notes
Index

Sobre o autor

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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Língua Inglês ● Formato EPUB ● Páginas 166 ● ISBN 9781503642102 ● Tamanho do arquivo 10.7 MB ● Editora Stanford University Press ● Publicado 2025 ● Edição 1 ● Carregável 24 meses ● Moeda EUR ● ID 10104145 ● Proteção contra cópia Adobe DRM
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