Primer Readings

Primer Readings


Bias on the Web

This is an article detailing the multitude of spaces that Web bias impacts. Author, Ricardo Baeza-Yates discusses activity bias, data bias, algorithmic bias, and bias on user interaction. 

Baeza-Yates, R. (2018, June 01). Bias on the Web. 

Design, Justice, A.I., and Escape from the Matrix of Domination

This is a three part essay from esteemed scholar and Associate Professor of Civic Media at MIT, Sasha Costanza-Chock. They discuss the alarming erasure of trans identities in millimeter wave scanning, the consequences of A.I. falling into the matrix of domination, and the opportunity to design decolonized A.I. and inclusive, healing, and sustainable technology.

Costanza-Chock, S. (2019). Design Justice, A.I., and Escape from the Matrix of Domination. Journal of Design and Science. 

Discriminating Systems: Gender, Race, and Power in AI

This article summarizes the diversity crisis in the A.I. The authors address the discrimination feedback loop occurring in the development of A.I. and the various strategies there are to address it. Their research includes a list of recommendations to hault bias and discrimination in the data science community. 

West, S.M., Whittaker, M. and Crawford, K. (2019). Discriminating Systems: Gender, Race and Power in AI. AI Now Institute. 

LGBT Data Collection – Center for American Progress Community Catalyst 

This article provides a discussion of the importance of LGBTQ+ data collection as it relates to health disparities. It includes numerous resources detailing the prior work being done to use data to positively impact sexual and gender minority groups that may also intersect with other various identities such as race, immigration status, or ethnicity. 

LGBT Data Collection. Center for American Progress. Prepared for Southern Health Partners Convening: June, 2015. 

#MoreThanCode: Practitioners reimagine the landscape of technology for justice and equity.

A summary of the findings surrounding the experiences of technology practitioners whose work is focused on social justice. Includes five recommendations for improving the tech community in terms of inclusion, bias, and discrimination towards marginalized groups. 

Sasha Costanza-Chock, Maya Wagoner, Berhan Taye, Caroline Rivas, Chris Schweidler, Georgia Bullen, & the T4SJ Project, 2018. #MoreThanCode: Practitioners reimagine the landscape of technology for justice and equity. Research Action Design & Open Technology Institute. 

Race, Technology, and Algorithmic Bias, Vision and Justice, Radcliffe University. 

This is a video of a conversation moderated by Darren Walker, president of the Ford Foundation, between Joy Buolamwini and Latanya Sweeney. Buolamwini is the founder of the Algorithmic Justice League and Sweeney is a professor of government and technology  residence at Harvard University. This captivating talk outlines the limitations and algorithmic bias that both of these women, and many other people of color, have faced in their interactions with technology. Beyond the limitations, they discuss the role of the arts in restoring racial justice to the world of technology. 

University, H. (2019, May 07). Race, Technology, and Algorithmic Bias.