Data Accountability
Last updated April 27, 2020
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Over the last few months, the RCRC team has been creating a Data Accountability Guide. We have been steadily adding to it as we observe new issues and face problems head-on. As a result, we have decided to slowly release content to this resource page as a means to create an anthology of content aimed at the ethical alignment of data and human rights practices. Due to the pandemic, we are also operating at a limited capacity to post. As we support crisis relief efforts with research, data, and community organizing, please bear with us as we slowly roll out data accountability content over the next month or so.
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References - last updated April 27, 2020
Bellamy, Jessica. Workshop. Infographics For Social Change: A Graphic Ally Hackathon. 2017-present.
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Community-Based Participatory Research for Health: From Process to Outcomes, second edition, John Wiley & Sons, Publishers, 2008.
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Consentful Project. Building Consentful Tech. Allied Media Projects, Moz://a, and AND ALSO TOO. 2017.
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Data for Democracy. Global Data Ethics Pledge. Data for Democracy partnered with Bloomberg and BrightHive (a collective of 22 contributors) to develop a code of ethics for data scientists, software developers and data analyzers of all types. This code aims to define values and priorities for overall ethical behavior, in order to guide anyone handling data to be a thoughtful, responsible agent of positive change. The code of ethics was developed through a community-driven approach.https://github.com/Data4Democracy/ethics-resources, 2017.
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Eubanks, Virginia. Automating Inequality: How High-Tech Tools Profile, Police, and Punish The Poor. St Martin’s Press, January 2018.
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Ferguson, Andrew. The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement. New York University Press, 2020.
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Lewis, T. Gangadharan, S.P., Saba, M., Petty, T. Digital Defense Playbook: Community Power Tools for Reclaiming Data. Detroit: Our Data Bodies, 2018.
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Noble, Safiya. Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press, 2018.
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Obermeyer, Z. Powers, B. Vogeli, C. Mullainathan, S. Dissecting racial bias in an algorithm used to manage the health of populations. Science 25 Oct 2019: Vol. 366, Issue 6464, pp. 447-453, October 2019.
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O’Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Broadway Books, 2016, 2017.
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Onuoha, Mimi, Mother Cyborg (Diana Nucera). A People’s Guide to AI. Open Society Foundation, August 2018.
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Rightscon.org. RightsCon Data Usage Policy. Last modified February 10, 2016. Retrieved from https://www.rightscon.org/data-usage-policy/
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Sidortsova, Stefanie. “Bias in the Algorithm.” 2019 Michigan Tech Magazine: Issue 1, https://www.mtu.edu/magazine/2019-1/stories/algorithm-bias/, 2019.
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Terms and Conditions May Apply. Hoback, Cullen. Variance Films, July 12, 2013.
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Tisne, Martin. “It’s time for a Bill of Data Rights.” MIT Technology Review, https://www.technologyreview.com/s/612588/its-time-for-a-bill-of-data-rights/, December 14, 2018.