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Data Equals: Democratic Equality and Technological Hierarchy

Contributor(s): Koopman, Colin (Author)

ISBN: 9780226842240

Publisher: University of Chicago Press

Hardcover
$115.00
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Pub Date: September 16, 2025

Dewey: 303.48340973

LCCN: 2025001942

Lexile Code: 0000

Features: Bibliography, Illustrated, Index

Target Age Group: NA to NA

Physical Info: 0.81" H x 9.00" L x 6.00" W ( 1.24 lbs) 296 pages

Descriptions, Reviews, etc.

Description: 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.

Brief description: 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.

Review Quotes: "Data Equals is an urgent, timely, and ambitious call to reconstruct the modern data order, which now suffocates democracies with increasingly powerful technologies of separation that draw our lives further and further apart and leave us unable to encounter one another as equals. With clarity and purpose, Koopman revitalizes the philosophical tradition of pragmatism to remind us of the possibilities for egalitarian politics and how data might finally serve them."--Shannon Vallor, University of Edinburgh

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