BEER Lab Meeting- Sönke Ehret

We present an experimental design on forecasting the success and failure of social tipping point interventions made in a prior study.  The allure of these interventions lies in their potential to instigate broad changes in collective behaviours through strategic disruptions in coordination dynamics. As such interventions gain technocratic traction, the necessity to accurately predict their outcomes ex-ante becomes paramount.  When can individuals & social planners forecast the impact of such interventions on rapid social change? Specifically, what is the predictive potential of expertise and basic knowledge? Our experimental design utilizes data from earlier lab studies on tipping interventions, with 'social planner' individuals making predictions about the outcomes observed in these studies. The goal of our experiment is to determine whether a well-informed social planner can generate more accurate predictions and to identify which types of information most influence these forecasts. We plan to explore the causal effects of knowledge on pre-intervention preference distributions, the intervention's size, and who it targets. To assess forecast accuracy, we employ incentivized scoring rules and propose a prediction market design. Our study aims to identify what kind of information about interventions helps improve social planners to predict the results of complex social dynamics more accurately.