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Data Paradoxes

The Politics of Intensified Data Sourcing in Contemporary Healthcare

by Klaus Hoeyer

ISBN: 9780262545419

Publisher: The MIT Press

Pub Date: April 18, 2023

Why healthcare cannot—and should not—become data-driven, despite the many promises of intensified data sourcing.

Beyond Data

Reclaiming Human Rights at the Dawn of the Metaverse

by Elizabeth M. Renieris

ISBN: 9780262047821

Publisher: The MIT Press

Pub Date: February 7, 2023

Why laws focused on data cannot effectively protect people—and how an approach centered on human rights offers the best hope for preserving human dignity and autonomy in a cyberphysical world.

There Are No Facts

Attentive Algorithms, Extractive Data Practices, and the Quantification of Everyday Life

by Mark Shepard

ISBN: 9780262047470

Publisher: The MIT Press

Pub Date: November 22, 2022

The entanglements of people and data, code and space, knowledge and power: how data and algorithms shape the world—and shape us within that world.

The Alienation of Fact

Digital Educational Privatization, AI, and the False Promise of Bodies and Numbers

by Kenneth J. Saltman

ISBN: 9780262544368

Publisher: The MIT Press

Pub Date: November 22, 2022

An investigation of the role of educational privatization and technology in the crises of truth and agency.

Digital Oil

Machineries of Knowing

by Eric Monteiro

ISBN: 9780262544672

Publisher: The MIT Press

Pub Date: November 8, 2022

How is digitalization of the offshore oil industry fundamentally changing how we understand work and ways of knowing?

Everyday Adventures with Unruly Data

by Melanie Feinberg

ISBN: 9780262544405

Publisher: The MIT Press

Pub Date: October 11, 2022

Paired informal and scholarly essays show how everyday events reveal fundamental concepts of data, including its creation, aggregation, management, and use.

Dataset Shift in Machine Learning

Edited by Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer and Neil D. Lawrence

ISBN: 9780262545877

Publisher: The MIT Press

Pub Date: June 7, 2022

An overview of recent efforts in the machine learning community to deal with dataset and covariate shift, which occurs when test and training inputs and outputs have different distributions.

Human-Centered Data Science

An Introduction

by Cecilia Aragon, Shion Guha, Marina Kogan, Michael Muller and Gina Neff

ISBN: 9780262543217

Publisher: The MIT Press

Pub Date: March 1, 2022

Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets.

Building the New Economy

Data as Capital

by Alex Pentland, Alexander Lipton and Thomas Hardjono

ISBN: 9780262543156

Publisher: The MIT Press

Pub Date: October 12, 2021

How to empower people and communities with user-centric data ownership, transparent and accountable algorithms, and secure digital transaction systems.

Data Science

by John D. Kelleher and Brendan Tierney

ISBN: 9780262535434

Publisher: The MIT Press

Pub Date: April 13, 2018

A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.

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