Data Discrimination & Algorithmic Bias

All Tech is Human Series #2: with Safiya Noble & Meredith Broussard


Details from the original livestream event put on by All Tech is Human

Details from the original livestream event put on by All Tech is Human


Action Items

For Everyone: 

  1. Join the conversation - learn about the basics of AI and ML, even if you aren’t a computer scientist

  2. Talk about how social issues can be played out in technologies:

    1. We don’t have to settle for what Mark Zuckerberg thinks that society ought to be like

      1. We can be empowered if we start looking for where these social inequalities persist in the technologies that we use

      2. Start having conversations about what it would mean to build better technology (anti-oppressive, anti-racist)

  3. Look for the contradictions in the technologies you use - use this information to help raise awareness about unjust / oppressive tech to help push for positive change politically

    1. Contact reporters and contact scholars can really help spread the word here

  4. Use your voting power! From the top of the ticket to local races, find candidates that support positive technology!

    1. Demand candidates that have a positive tech agenda

  5. Make it personal: If you are looking for motivation to get involved, consider how data discrimination and algorithmic bias might impact you, your family, or your loved ones. 

    1. Have kids + need motivation to get involved?

      1. Imagine your kids and their biometric data, their schooling data, their digital identities that will persist throughout their life and potentially score them on their “worthiness” for things like loans, education, and criminal justice

      2. Think about all of the ways that your data / their data could be exploited

For Technologists and Coders:

  1. Listen to the voices that are not “techno-chauvinist” voices

  2. Listen to the women of color, BIPOC, and gender fluid people who are researching other ways of creating technology, especially those who highlight that western ethics is not the only ethics out there

  3. Ask the following question: is silicon valley’s ethical structure the same ethical structure that we want to embed in all these global technologies all over the world?

  4. Think critically about predictive technologies and how they are deployed.

    1. Ask values questions like:

      1. Is this technology necessary? What is at stake with this technology? Will this technology benefit all society? Or will it benefit the wealthiest at the expense of those who are the most marginalized, the environment, and those who are the most vulnerable?

For Policy Makers:

  1. Advocate for more publicly funded, publicly supported, public interest technologies that are predicated upon different value systems -- not just shareholder profit

  2. Looking for motivation? Think about what is at stake when all kinds of knowledge, propaganda, and information get flattened in platforms like social media and search engines

  3. Advocate for more funding for education, especially K-12!! Try to hold onto the computing educators who are being enticed to work for big tech companies instead of teaching.

  4. Get funding for:

    1. More computers

    2. Faster Wifi

    3. Books

    4. Markers/paper towels, bathrooms, etc… (we must fix education overall in order to fix computer science education, which is all about funding)

For Computing Educators

  1. We need to talk about these topics all throughout the CS curriculum

  2. Educators: Include tech ethics in K-12 curriculum. This includes:

    1. Media literacy

    2. Disinformation Lessons

    3. Data Literacy

    4. AI and ML Literacy

  3. Look at the resources for computing professors interested in including more ethics content below if you are a  computing educator who is interested in including more ethics content in your courses!


Annotated Resources

Resources From Safiya Noble (guest speaker from this episode):

  1. Algorithms of Oppression by Safiya Noble

  2. Safiya’s Dissertation: Searching for black girls: old traditions in new media

  3. Center for Critical Internet Inquiry (Subscribe on their website for help sifting through the stories to get a better idea of what you should read and what you should know)

  4. Follow Safiya on Twitter @safiyanoble

  5. Safiya’s Personal website

    1. Reach out to the team at CCII at UCLA to get in touch with Safiya

Resources From Meredith Broussard (guest speaker from this episode):

  1. Artificial Unintelligence by Meredith Broussard

  2. Follow Meredith on Twitter at @merbroussard

  3. Meredith’s personal website

    1. Meredith is currently working on a new book about the intersection of race and technology. Reach out if you have stories about the way that technology and race intersect! Also reach out if you have suffered at the intersection of race and technology.

Relevant Books

  1. Ruha Benjamin’s Race After Technology (recommended by guests during livestream)

  2. Black Software: The Internet & Racial Justice, from the AfroNet to Black Lives Matter (recommended by guests during livestream)

  3. Weapons of Math Destruction by Cathy O’Neil (recommended by guests during livestream)

  4. Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech by Sara Wachter-Boettcher (recommended by guests during livestream)

  5. Algorithmic Justice League founder Joy Buolamwini signs book deal with Random House (recommended by guests during livestream)

  6. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power by Shoshana Zuboff (recommended by guests during livestream)

Relevant Publications, Media, and Groups:

  1. Center for Critical Race and Digital Studies out of NYU (advice from Meredith during the livestream)

  2. Brick bait: why Big Tech is building for the future (From Meredith’s comment on the financial Times declaring 2019 to be the beginning of the “Tech Lash”)

  3. Google Ad Portal Equated “Black Girls” with Porn by Leon Yin and Aaron Sankin on The Markup (From Safiya’s comment on others continuing her work with Google Ads)

  4. ACM Code of ethics - revised 2018 version (mentioned by Meredith during the livestream)

  5. Look at the new field of Public Interest Technology (advice from Meredith in the conclusion of the livestream)

    1. This field focuses on designing better systems and creating technology for the public good

  6. Other relevant resources:

    1. Coded Bias Documentary

    2. Gender Shades by Joy Buolomwini

    3. Actionable auditing: Investigating the impact of publicly naming biased performance results of commercial ai products by Deb Raji

    4. The Algorithmic Justice League

Computing Ethics Education Resources

  1. What Do We Teach When We Teach Tech Ethics? A Syllabi Analysis by Casey Fiesler et. al

  2. More Than "If Time Allows": The Role of Ethics in AI Education by Natalie Garrett et. al

  3. An Ethics of Artificial Intelligence Curriculum for Middle School Students by Blakeley H. Payne

  4. Teaching Ethics with Coding resources and in-class assignments / activities:

    1. Ethically Aligned CS 1 Course by Evan Peck

    2. AI, Justice, Imagination: Technology and Speculative Fiction course syllabus by Janet Zong York and Jonathan Zong

    3. Data Intro Course on GitHub by Sorelle Friedler

    4. Process Oriented Guided Inquiry Learning in Computer Science by Chris Mayfield

    5. Fairness and Machine Learning by Solon Barocas, Moritz Hardt, and Arvind Narayanan

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