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Different disciplines are approaching causal inference in contrasting, complementary ways. But the scale and complexity of these experiments also create scientific and statistical challenges for design and inference. When appropriately theorized and rigorously applied, randomized experiments are the gold standard of causal inference and a cornerstone of effective policy. This new toolkit portends a sea-change in our scientific understanding of human behavior and dramatic improvements in social and business policy as a result. As more and more social interactions, behaviors, decisions, opinions and transactions are digitized and mediated by online platforms, our ability to quickly answer nuanced causal questions about the role of social behavior in population-level outcomes such as health, voting, political mobilization, consumer demand, information sharing, product rating and opinion aggregation is becoming unprecedented. About newly emerging capability to rapidly deploy and iterate micro-level, in-vivo, randomized experiments in complex social and economic settings at population scale is, in our view, one of the most significant innovations in modern social science.