Using agent-based simulations to anticipate risks and mitigation measures in platform governance

Risk analysis and mitigation in platform governance are constrained by the difficulties of testing changes to platforms’ systems and accessing data. Other fields, ranging from public health to economics, as well as an emerging body of platform research, use agent-based modeling to overcome this obstacle by empowering researchers and regulators to test changes virtually. However, it is still unclear how and under what conditions agent-based modeling can effectively support platform governance. This article aims to reduce this uncertainty in two ways. First, it provides a theoretical framework on the benefits and risks of using agent-based modeling in platform governance, drawing on literature on platform risk assessment, the use of agent-based modeling in other fields, and anticipatory governance and evidence-based policymaking. Second, to validate this framework and clarify the conditions under which regulators can rely on evidence produced by agent-based models, the article reports the results of interviews with 18 regulators. The article finds that agent-based simulations have significant potential to complement other sources of evidence used in platform risk assessment. Their main added value is that they allow researchers and regulators to more easily, ethically, and independently explore the potential impacts of changes to platform design, and provide interactive and visual scenarios that concretize abstract platform dynamics.