The world urgently needs fresh thinking about political economy. Existing paradigms have largely run their course and failed to address lingering problems. The unprecedented changes since the Industrial Revolution have created serious challenges, even as living standards have improved in societies around the world. Some emerging interdisciplinary projects help address these challenges, but further progress will become harder as societies increasingly struggle to reconcile clashing goals. Scholars and policy-makers will be best positioned to draw actionable inferences from data and history and to make lasting contributions if they focus on the importance of policy experimentation and localized knowledge, systematic thinking about multiple timeframes, responding to the needs of people still living in crushing poverty, and humility about what any single intellectual or policy paradigm can accomplish.
This essay maps the potential, and risks, of artificially intelligent regulation: regulatory arrangements that use a complex computational algorithm or another artificial agent either to define a legal norm or to guide its implementation. The ubiquity of AI systems in modern organizations all but guarantees that regulators or the parties they regulate will make use of learning algorithms or novel techniques to analyze data in the process of defining, implementing, or complying with regulatory requirements. We offer an account of the possible benefits and harms of artificially intelligent regulation. Its mix of costs and rewards, we show, depend primarily on whether AI is deployed in ways aimed merely at shoring up existing hierarchies, or whether AI systems are embedded in and around legal frameworks carefully structured and evaluated to better our lives, environment, and future.