Applying History to Inform Anticipatory AI Governance

How might lessons from previous technologically driven transformations, such as the Industrial Revolution, inform today’s AI governance challenges? These conference proceedings address this question by combining historical analysis with an approach to foresight called backcasting, which examines pathways to hopeful futures. Workshop participants—12 individuals from diverse backgrounds, including business leaders, policymakers, and technologists—were presented with two scenarios, each depicting a different future of AI-enabled human flourishing, and three historical case studies focusing on the societal impacts of general-purpose technologies in the 19th and early 20th centuries. During the workshop, the participants discussed the scenarios in breakout groups to develop their backcasting pathways and then used the historical case studies to refine and rework those pathways.

In terms of policy, workshop participants discussed several potential areas for policy action, including developing more-sophisticated and more-nuanced AI governance models that strike a balance between encouraging innovation and ensuring the public good. In terms of methodology, the organizers found that the workshop demonstrated the potential of historically informed visioning and backcasting. In these conference proceedings, the authors propose that combining the two approaches could help with policy planning for AI governance and other areas in which technology might substantially transform society, and they offer lessons for future efforts.