Drawing on social psychology to detail three ways in which unconscious assumptions can lead to discrimination, this book demonstrates how these dynamics interact in medical care to produce an invisible, self-fulfilling, and self-perpetuating prophecy of racial disparity.

How big data and machine learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition. Machine learning and data analytics thus seek to disrupt the future by making disruption impossible. Chun, who has a background in systems design engineering as well as media studies and cultural theory, explains that although machine learning algorithms may not officially include race as a category, they embed whiteness as a default. Facial recognition technology, for example, relies on the faces of Hollywood celebrities and university undergraduates—groups not famous for their diversity. Homophily emerged as a concept to describe white U.S. resident attitudes to living in biracial yet segregated public housing. Predictive policing technology deploys models trained on studies of predominantly underserved neighborhoods. Trained on selected and often discriminatory or dirty data, these algorithms are only validated if they mirror this data. How can we release ourselves from the vice-like grip of discriminatory data? Chun calls for alternative algorithms, defaults, and interdisciplinary coalitions in order to desegregate networks and foster a more democratic big data.

From everyday apps to complex algorithms, Ruha Benjamin cuts through tech-industry hype to understand how emerging technologies can reinforce White supremacy and deepen social inequity. Benjamin argues that automation, far from being a sinister story of racist programmers scheming on the dark web, has the potential to hide, speed up, and deepen discrimination while appearing neutral and even benevolent when compared to the racism of a previous era. Presenting the concept of the “New Jim Code,” she shows how a range of discriminatory designs encode inequity by explicitly amplifying racial hierarchies; by ignoring but thereby replicating social divisions; or by aiming to fix racial bias but ultimately doing quite the opposite. Moreover, she makes a compelling case for race itself as a kind of technology, designed to stratify and sanctify social injustice in the architecture of everyday life. This illuminating guide provides conceptual tools for decoding tech promises with sociologically informed skepticism. In doing so, it challenges us to question not only the technologies we are sold but also the ones we ourselves manufacture. Visit the book's free Discussion Guide: www.dropbox.com

The #1 New York Times bestseller that sparked international dialogue is now a book for young adults! Based on the adult bestseller by Ibram X. Kendi, and co-authored by bestselling author Nic Stone, How to be a (Young) Antiracist will serve as a guide for teens seeking a way forward in acknowledging, identifying, and dismantling racism and injustice. The New York Times bestseller How to be an Antiracist by Ibram X. Kendi is shaping the way a generation thinks about race and racism. How to be a (Young) Antiracist is a dynamic reframing of the concepts shared in the adult book, with young adulthood front and center. Aimed at readers 12 and up, and co-authored by award-winning children's book author Nic Stone, How to be a (Young) Antiracist empowers teen readers to help create a more just society. Antiracism is a journey--and now young adults will have a map to carve their own path. Kendi and Stone have revised this work to provide anecdotes and data that speaks directly to the experiences and concerns of younger readers, encouraging them to think critically and build a more equitable world in doing so.

The New York Times best-selling book exploring the counterproductive reactions white people have when their assumptions about race are challenged, and how these reactions maintain racial inequality. In this “vital, necessary, and beautiful book” (Michael Eric Dyson), antiracist educator Robin DiAngelo deftly illuminates the phenomenon of white fragility and “allows us to understand racism as a practice not restricted to ‘bad people’ (Claudia Rankine). Referring to the defensive moves that white people make when challenged racially, white fragility is characterized by emotions such as anger, fear, and guilt, and by behaviors including argumentation and silence. These behaviors, in turn, function to reinstate white racial equilibrium and prevent any meaningful cross-racial dialogue. In this in-depth exploration, DiAngelo examines how white fragility develops, how it protects racial inequality, and what we can do to engage more constructively.

First published in 1997, this volume features a wealth of contributions discussing mortgage lending discrimination and the role of the FHA, fair lending enforcement and the Decatur case, along with the future of mortgage discrimination research. This key civil rights debate in the wake of the Fair Housing Act 25 years prior is evaluated and clarified through rigorous review of fair lending research, applied projects and enforcement activities to date. It argues forcefully that the right to take out a mortgage to buy a home should be conditioned only upon one’s credit worthiness and not on one’s race or ethnic group.

Equal treatment in access to credit has long been a fundamental social goal in the United States. However, despite the passage of several laws in the U.S. prohibiting discrimination in the provision of financial services on the basis of race, gender, and marital status, among other factors, questions concerning the existence of racial discrimination in such areas as home mortgage loans and small business credit continue, and confound public policy makers. This book is composed of nine articles and a panel discussion, originally published as a special issue of the Journal of Financial Services Research. These contributions explore the complex issue of discrimination in financial services.