Psychological theories continue to expand our understanding of stereotype content and processes. Stereotype content refers to what people think about social groups’ characteristics. Stereotype processes reflect how people integrate information to navigate social interactions. Advances in artificial intelligence introduce innovative analytical tools to revolutionize how psychologists understand stereotypes. Content research builds on theory-driven surveys (e.g. warmth and competence), to data-driven multidimensional scaling (e.g. belief), to large-scale linguistic analysis (e.g. emotion, appearance) to describe a myriad of dimensions people use for social evaluations. Process research starts from an information-processor metaphor (e.g. decoding, encoding), to the predictive brain (e.g. statistical learning, probabilistic modeling), and now to a feedback loop framework (e.g. reinforcement learning, algorithmic bias), paving the way to understand how and why people evaluate others. Understanding stereotypes is a collective enterprise, as evidenced by the scholarly debate that has helped move the field forward.