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Intersections

The Future is Intersectional: Black Women Interrogating Technology

The Spelman College Center of Excellence for Minority Women in STEM in collaboration with the Atlanta University Center Data Science Initiative, UCLA Center for Critical Internet Inquiry and Mozilla Foundation is proud to present a series of discussions highlighting the unique intersectional lens Black women bring to the development and utilization of technology in our society. Talks will cover both the vast contributions of Black women to this field as well as the challenging and demoralizing experiences Black women have in a field where they are highly underrepresented and often undervalued.


Series Resources & Recordings

 

RESOURCES
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Books
Programmed Inequality – Mar Hicks
Algorithms of Oppression: How Search Engines Reinforce Oppression – Safiya Noble
Ghost Work – Mary Gray, Siddharth Suri
Sorting Things Out: Classification and Its Consequences – Geoffrey C. Bowker, Susan Leigh Star
Black Software: The Internet & Racial Justice, from the AfroNet to Black Lives Matter – Charlton D. McIlwain
All of Statistics: A Concise Course in Statistical Inference – Larry Wasserman
Captivating Technology: Race, Carceral Technoscience, and Liberatory Imagination in Everyday Life – Ruha Benjamin (ed)
Race After Technology: Abolitionist Tools for the New Jim Code – Ruha Benjamin
Haben: The Deafblind Woman Who Conquered Harvard Law – Haben Girma
Dark Matters: On the Surveillance of Blackness – Simone Browne
Artificial Un-Intelligence: How Computers Misunderstand the World – Meredith Broussard
The Disordered Cosmos – Chanda Prescod-Weinstein

Articles (Title-Author)
Providing a Good Education in Deep Learning – Rachel Thomas
A Mathematician’s Lament – Paul Lockhart
Understanding Delta-Sigma Data Converters – Richard Schreier; Gabor C. Temes
The hypocrisy in MIT’s moralizing – The Tech Editorial Board
Replacing the "View from Nowhere": A Pragmatist-Feminist Science Classroom – d Sarah Marie Stitzlein
Q&A: Sabelo Mhlambi on what AI can learn from Ubuntu ethics
Providing a Good Education in Deep Learning
– Rachel Thomas
Datasheets for Datasets – Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford
Model Cards for Model Reporting – Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning – Eun Seo Jo, Timnit Gebru
Intersectionality – Kimberle Crenshaw
Diversity and Inclusion Metrics in Subset Selection – Margaret Mitchell, Dylan Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern
Amazon is Pushing for Facial Technology That a Study Says Could Be Biased – Natasha Singer
A.I. Experts Question Amazon’s Facial-Recognition Technology – Cade Metz and Natasha Singer
The Abuse and Misogynoir Playbook – Katlyn Turner, Danielle Wood, Catherine D'Ignazio
Machine Learning that Matters – Kiri Wagstaff
The Moral Character of Cryptographic Work – Phillip Rogaway
Large image datasets: A pyrrhic win for computer vision? – Vinay Uday Prabhu, Adeba Birhane
‘Bias deep inside the code’: the problem with AI ‘ethics’ in Silicon Valley – Sam Levin
Gender Recognition or Gender Reductionism?: The Social Implications of Embedded Gender Recognition Systems – Foad Hamidi, Morgan Klaus Scheuerman, Stacy M. Branham
How Computers See Gender: An Evaluation of Gender Classification in Commercial Facial Analysis Services – Morgan Klaus Scheuerman, Jacob M. Paul, Jed R. Brubaker
Don’t ask if artificial intelligence is good or fair, ask how it shifts power – Pratyusha Kalluri
Ex-Google employee Chelsey Glasson sues over alleged pregnancy discrimination – Pavithra Mohan

Talks/Films/Podcasts
Ruha Benjamin - 2020 Vision: Reimagining the Default Settings of Technology & Society
Ethics and Race in Tech: Ruha Benjamin in Conversation with Meredith Whittaker
Joy Buolamwini - AI, Ain't I A Woman?
Coded Bias
Critical Perspectives on Computer Vision – Emily Denton
Radical AI Podcast


Websites/Miscellaneous
BlackAIR Summer Research Grant Program
AddisCoder
Gender Shades
Statement on the Selection of Jeffrey Ullman for a Turing Award
Measuring Diversity Explorable
Model Cards
Black in AI
Algorithmic Justice League
The Perpetual Lineup Report
William Shockley
El Mahdi El Mhamdi
Cultural Competence in Computing Fellows Program
How to Tell Japs from Chinese – Life Magazine 1941

 

 

 

The New Jim Code? Reimagining the Default Settings of Technology & Society

March 4, 2021

Bibliography
Anna Everett, "Digital Diaspora: A Race for Cyberspace"
Lisa Nakamura and Peter Chow-White, "Race after the Internet"
Lisa Nakamura, "Cybertypes: Race, Ethnicity, and Identity on the Internet"
Alondra Nelson and Thuy Lin Tu (ed.), "Technicolor: Race, Technology, and Everyday Life"
Jessie Daniels, "Cyber Racism"
Simone Browne, "Dark Matters"
*Safiya Noble, "Algorithms of Oppression: How Search Engines Reinforce Racism"
Virginia Eubanks, "Automating Inequality"
Cathy O'Neil, "Weapons of Math Destruction"
Frank Pasquale, "The Black Box Society: The Secret Algorithms that Control Money and Information"
Charlton McIlwain, "Black Software"
Mar Hicks, "Programmed Inequality"
*Meredith Broussard, "Artificial Unintelligence"
Andrew Ferguson, "The Rise of Big Data Policing"
Sarah Roberts, "Behind the Screen"
*Ruha Benjamin ed., "Captivating Technology"
*Ruha Benjamin, "Race After Technology: Abolitionist Tools for the New Jim Code"
Andre Brock Jr., "Distributed Blackness: African American Cybercultures"
Catherine D’Ignazio and Lauren F. Klein, "Data Feminism"
Sasha Costanza-Chock, "Design Justice"
Mary L. Gray and Siddharth Suri, "Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass"
Shoshana Zuboff, "The Age of Surveillance Capitalism"
Sarah J. Jackson, *Moya Bailey, Brooke Foucault-Welles, "Hashtag Activism"
Sarah Brayne, "Predict and Surveil: Data, Discretion, and the Future of Policing"
Sareeta Amrute, "Encoding Race, Encoding Class"

* The Future is Intersectional Speakers