Data Feminism.
Series: Strong ideas seriesPublisher: Cambridge, Massachusetts : The MIT Press, 2023Copyright date: 2020Edition: First MIT Press paperback editionDescription: xii, 314 pages : illustrations (chiefly color), color maps ; 23 cmContent type:- text
- still image
- cartographic image
- unmediated
- volume
- 9780262547185
- 026254718X
- 305.42 23
- HQ1190 .D574 2023
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
BOOK
|
NCAR Library Mesa Lab | HQ1190 .D574 2023 | 1 | Checked out | 09/18/2026 | 50583020031559 |
Includes bibliographical references and indexes.
Introduction: Why data science needs feminism -- Examine power : the power chapter -- Challenge power : collect, analyze, imagine, teach -- Elevate emotion and embodiment : on rational, scientific, objective viewpoints from mythical, imaginary, impossible standpoints -- Rethink binaries and hierarchies : "What gets counted counts" -- Embrace pluralism : unicorns, janitors, ninjas, wizards and rock stars -- Consider context : the numbers don't speak for themselves -- Make labor visible : show your work -- Conclusion: Now let's multiply.
Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. The authors present a new way of thinking about data science and data ethics--one that is informed by intersectional feminist thought.--back cover.