  Domain experts are often engaged in the development of machine learning
systems in a variety of ways, such as in data collection and evaluation of
system performance. At the same time, who counts as an 'expert' and what
constitutes 'expertise' is not always explicitly defined. In this project, we
conduct a systematic literature review of machine learning research to
understand 1) the bases on which expertise is defined and recognized and 2) the
roles experts play in ML development. Our goal is to produce a high-level
taxonomy to highlight limits and opportunities in how experts are identified
and engaged in ML research.
