  Human-centered artificial intelligence (AI) posits that machine learning and
AI should be developed and applied in a socially aware way. In this article, we
argue that qualitative analysis (QA) can be a valuable tool in this process,
supplementing, informing, and extending the possibilities of AI models. We show
this by describing how QA can be integrated in the current prediction paradigm
of AI, assisting scientists in the process of selecting data, variables, and
model architectures. Furthermore, we argue that QA can be a part of novel
paradigms towards Human Centered AI. QA can support scientists and
practitioners in practical problem solving and situated model development. It
can also promote participatory design approaches, reveal understudied and
emerging issues in AI systems, and assist policy making.
