Accounting for Complexity: Thinking With Idealisations, Models, and Data

Abstract

What does it mean to call something complex? This Review essay describes three recent books which take up complex problems and the problem of complexity: philosopher Angela Potochnik’s Idealization and the Aims of Science (2017); science and technology studies (STS) scholar Nicole Nelson’s Model Behavior: Animal Experiments, Complexity, and the Genetics of Psychiatric Disorders (2018); and historian of science Bruno Strasser’s Collecting Experiments: Making Big Data Biology (2019). Taken together, these works lay out a refreshed analytic vocabulary and set of guiding concerns for thinking about what complexity is and does in medical research, and how complexity mediates public participation in science and medicine.

Keywords

• complexity
• model organisms
• epistemology
• big data