Implicit Bias Guide

This report illustrates some of the shortcomings of algorithmic decision making, identifies key themes around the problem of algorithmic errors and bias, and examines some approaches for combating these problems.

Data is fundamental to the modern world. From economic development, to healthcare, to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this bias in time, money, and sometimes with their lives. Celebrated feminist advocate Caroline Criado Perez investigates the shocking root cause of gender inequality and research in Invisible Women, diving into women's lives at home, the workplace, the public square, the doctor's office, and more.

As Pokémon Go reshaped our neighborhood geographies and the human flows of our cities, mapping the virtual onto lived realities, so too has gaming and game theory played a role in our contemporary understanding of race and racial formation in the United States.

This book provides current research on misperceptions, perspectives, and the role of social media on stereotypes and stereotyping.

Tobias Baer helps you understand where algorithmic bias comes from, how to manage it as a business user or regulator, and how data science can prevent bias from entering statistical algorithms.