The Architecture of Ignorance

摘要

This Article develops an approach to environmental law that I refer to as "data-intensive regulation." The origins of data-intensive regulation lie in the public's ability to gather, for the first time, data at spatial and temporal scales of its choosing. This capability, and the knowledge-building efforts it supports, will eclipse the theoretical and computational procedures that guided environmental law's enactment. As environmental law evolves from a data-starved to data-rich enterprise, pollution control and ecosystem management will need to respond in two ways, focusing less on data supply and more on the demands of data users and the data's underlying architecture. Legal scholars neglect these questions, offering proposals to bridge and fill gaps in data. At the same time, environmental law has surrounded itself with supportive structures to accommodate these gaps, which are useful in data-limited contexts. I explore this architecture, and its next phase of evolution, through case studies of citizen monitoring arrays, hazardous substances and microenvironments, and disaster planning and peer-to-peer response. Data-intensive regulation promises to recast debates over regulatory design and federalism. It calls for the coordinated use of previously neglected regulatory tools. And it addresses a wider range of transaction costs, and their influence over responses to environmental harms, than costs related to data supply.