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More Than a Glitch: Confronting Race, Gender, and Ability Bias in Tech
Paperback
Technology & EngineeringGeneral Gender StudiesGeneral Racism & Ethnic Studies
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ISBN10: 0262548321
ISBN13: 9780262548328
Publisher: MIT Press
Published: Apr 2 2024
Pages: 248
Weight: 0.70
Height: 0.70 Width: 5.90 Depth: 8.90
Language: English
ISBN13: 9780262548328
Publisher: MIT Press
Published: Apr 2 2024
Pages: 248
Weight: 0.70
Height: 0.70 Width: 5.90 Depth: 8.90
Language: English
Broussard, a researcher and reporter whose work focuses on ethics in AI, is the perfect guide to this moment.--Glamour
Both technical and accessible, this intersectional exploration of algorithmic bias offers real solutions for making technology less harmful, from an expert data scientist. The word glitch implies an incidental error, as easy to patch up as it is to identify. But what if racism, sexism, and ableism aren't just bugs in mostly functional machinery--what if they're coded into the system itself? In the vein of heavy hitters such as Safiya Umoja Noble, Cathy O'Neil, and Ruha Benjamin, Meredith Broussard demonstrates in
Both technical and accessible, this intersectional exploration of algorithmic bias offers real solutions for making technology less harmful, from an expert data scientist. The word glitch implies an incidental error, as easy to patch up as it is to identify. But what if racism, sexism, and ableism aren't just bugs in mostly functional machinery--what if they're coded into the system itself? In the vein of heavy hitters such as Safiya Umoja Noble, Cathy O'Neil, and Ruha Benjamin, Meredith Broussard demonstrates in
More Than a Glitch
how neutrality in tech is a myth and why algorithms need to be held accountable.
Broussard, a data scientist and one of the few Black female researchers in artificial intelligence, masterfully synthesizes concepts from computer science and sociology. She explores a range of examples, such as:
- Facial recognition technology trained only to recognize lighter skin tones
- Mortgage-approval algorithms that encourage discriminatory lending
- The dangerous feedback loops that arise when medical diagnostic algorithms are trained on insufficiently diverse data
- How technologies designed with good intentions by fallible humans develop programs that can result in devastating consequences
Broussard argues that the solution isn't to make omnipresent tech more inclusive, but to root out the algorithms that target certain demographics as other to begin with. With sweeping implications for fields ranging from jurisprudence to medicine, the ground-breaking insights of
More Than a Glitch
are essential reading for anyone invested in building a more equitable future.
how neutrality in tech is a myth and why algorithms need to be held accountable.
Broussard, a data scientist and one of the few Black female researchers in artificial intelligence, masterfully synthesizes concepts from computer science and sociology. She explores a range of examples, such as:
- Facial recognition technology trained only to recognize lighter skin tones
- Mortgage-approval algorithms that encourage discriminatory lending
- The dangerous feedback loops that arise when medical diagnostic algorithms are trained on insufficiently diverse data
- How technologies designed with good intentions by fallible humans develop programs that can result in devastating consequences
Broussard argues that the solution isn't to make omnipresent tech more inclusive, but to root out the algorithms that target certain demographics as other to begin with. With sweeping implications for fields ranging from jurisprudence to medicine, the ground-breaking insights of
More Than a Glitch
are essential reading for anyone invested in building a more equitable future.
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