In this commentary, invited for the 100th anniversary of the Journal, we discuss the addition of randomized experiments, along with natural experiments that emulate randomized trials using observational data, as designs in the social epidemiologist's toolbox. These approaches transform the way we define and ask questions about social exposures. They compel us to ask questions about how well-defined interventions change a social exposure that might lead to changes in health. As such, experiments are of unique public health and policy significance. We argue that they are a powerful approach to advance our understanding of how well-defined changes in social exposures impact health, and how credible social policy reforms may be instrumental to address health inequalities. We focus on two research designs. The first is a "pure" randomized controlled trial (RCT) in which the investigator defines and randomly assigns the intervention. The second is a natural experiment, which exploits the fact that policies or interventions in the real world often involve an element of random assignment, emulating an RCT. To give the reader our bottom line: While acknowledging their limits, we continue to be very excited about the promise of RCTs and natural experiments to advance social epidemiology.