CODE@MIT 2023 Plenary Session 2: Martin Tingley and Jean Pouget-Abadie

Martin Tingley - Netflix, “A Tale of Complexity: Report from the Causal Inference and Digital Experimentation Roundtable (CIDER)”
In April 2023, Netflix hosted the Causal Inference and Digital Experimentation Roundtable (CIDER), which brought together practitioners from industry and applied researchers from academia for candid discussions on the current state and next opportunities for experimentation and causal inference at scale. This talk provides an opinionated summary of the discussions, reinforced with specific examples drawn from Netflix. I will first discuss the agricultural roots of digital experimentation, and then propose that a handful of root complexities -scale, time dependence, constraints on treatment delivery, human decision makers- challenge the commodification of experimentation beyond the simple agricultural model.
Jean Pouget-Abadie - Google Research, “Designing Experiments for Marketplaces and other Bipartite Graphs”
When the treatment assignment of one unit affects the outcome of another, we say there is interference. Interference is especially prevalent in marketplaces, where buyer and seller interactions lead to complex dependence structures. As a violation of the stable unit treatment value assumption, the presence of interference can lead to bias of standard estimators under naive randomized designs. In this talk, we will cover a set of design and estimation paradigms used at Google to conduct causal inference research in a bipartite graph setting, inspired from, but not limited to, marketplace experiments, with specific attention paid to clustered randomized designs.