Abstract
Twenty years ago, legal scholars and regulators alike were convinced that information-forcing regulations heralded a new era in environmental law. Coming off the success of the Toxics Release Inventory (TRI), which seemed to decrease toxic chemical pollution solely by forcing industry to disclose if they released certain chemicals, many called information regulation the third wave of environmental law. New information disclosure policies were enacted and old policies reinvigorated, leading to a plethora of informationbased regulations throughout environmental law. Now, twenty years later, the emergence of big data and artificial intelligence (AI) approaches to environmental analysis have only further increased the belief in the benefits of information-forcing approaches. In this time, the central premise that information regulation works to change behavior and improve environmental outcomes has been largely unquestioned. Despite the widespread enthusiasm, after decades of implementation it is increasingly clear that information regulation largely fails to achieve its environmental goals. This Article makes two main contributions. By drawing on quantitative and qualitative case studies of information-forcing regulations, it first answers the question of whether this approach to environmental regulation is effective. It evaluates the success of information-forcing policies, finding that these policies often fail both to change behavior towards improving environmental conditions and to achieve other stated goals. This Article then analyzes the mechanisms behind information forcing in conjunction with these case studies to propose characteristics that determine the success, or failure, of information regulation. It finds that contrary to popular belief, persuasive and economic mechanisms not drive environmental behavior change. Instead, information- forcing regulations with legal mechanisms of action show the most promise and efficacy. Moving beyond sweeping promises of efficiency and transparency to understand the specific characteristics that make these programs successful is essential moving forward into an era of big environmental data.