Data Equals

Democratic Equality and Technological Hierarchy

Colin Koopman (Autor)

Buch | Softcover

304 Seiten

2025
University of Chicago Press (Verlag)
978-0-226-84225-7 (ISBN)

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An expansive vision for data equality that goes beyond algorithmic fairness.

When we gave algorithms power over our world, we hoped that the apparent neutrality of machine thinking would create a more egalitarian age. Yet we are more divided than ever, staring down threats to democracy itself. In Data Equals, Colin Koopman argues that data technologies fail us so often because we built them around a deficient notion of equality.

It is not enough, Koopman explains, that algorithms engage everyone’s data with the same measuring stick. The data themselves are all too often structured in ways that obscure and exacerbate stratifying distinctions. Koopman contends that we must also work to ensure that those people subject to computational assessment enter data systems on equal terms. Part philosophical argument, part practical guide (replete with case studies from education technology), Data Equals offers novel methods for realizing democratic equality in a digital age.

Colin Koopman is professor of philosophy and director of new media and culture at the University of Oregon. His books include How We Became Our Data: A Genealogy of the Informational Person, also published by the University of Chicago Press.

Introduction: Reconstructing Democratic Equality in Data Technology from Paper Records to Artificial Intelligence

Part 1: Data Equality
1. Data Hierarchy, Technological Neutrality, and Algorithmic Fairness: Some Obstacles
2. Data Equality in Social Structure: An Opening

Part 2: Equality
3. Structural Equality: A Pragmatist Account of Democratic Equality
4. Equal Treatment: Equitable Entry + Fair Processing

Part 3: Data
5. Structural Data: Formats + Algorithms
6. Format Anatomies: A Methodology for Dissecting Data

Part 4: Democratic Equality in Education Data
7. Artificial Intelligence for Personalized Learning: An Anatomy of Learner-Model Formats
8. Collaboration versus Personalization in Democratic Education: Evaluating Equality in Learner Data

Conclusion: Becoming Data Equals

Acknowledgments
Notes
Bibliography
Index

Erscheinungsdatum	19.08.2025
Zusatzinfo	2 tables
Sprache	englisch
Maße	152 x 229 mm
Gewicht	340 g
Themenwelt	Geisteswissenschaften ► Philosophie ► Ethik
	Mathematik / Informatik ► Informatik
	Sozialwissenschaften
ISBN-10	0-226-84225-8 / 0226842258
ISBN-13	978-0-226-84225-7 / 9780226842257
Zustand	Neuware