AI is built by humans and deployed in systems and institutions that have been marked by entrenched discrimination — from the criminal legal system, to housing, to the workplace, to our financial systems. Bias is often baked into the outcomes the AI is asked to predict. Likewise, bias is in the data used to train the AI — data that is often discriminatory or unrepresentative for people of color, women, or other marginalized groups — and can rear its head throughout the AI’s design, development, implementation, and use. The tech industry’s lack of representation of people who understand and can work to address the potential harms of these technologies only exacerbates this problem.