Anti-Racism and Anti-Oppression Resources: STEM Resources

In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color. Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance--operating as a source for email, a major vehicle for primary and secondary school learning, and beyond--understanding and reversing these disquieting trends and discriminatory practices is of utmost importance. An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century.

This book is aimed at engineering academics worldwide, who are attempting to bring social justice into their work and practice, or who would like to but don't know where to start.

At a time when popular solutions to the educational plight of poor children of color are imposed from the outside-national standards, high-stakes tests, charismatic individual saviors-the acclaimed Algebra Project and its founder, Robert Moses, offer a vision of school reform based in the power of communities.

Author Diann Jordan took a journey to find out what inspired and daunted black women in their desire to become scientists in America. Letting 18 prominent black women scientists talk for themselves, Sisters in Science becomes an oral history stretching across decades and disciplines and desires.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives--where we go to school, whether we get a car loan, how much we pay for health insurance--are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination.