March 27, 2020
AI, society and governance: An introduction
After decades of largely unfulfilled promises, artificial intelligence (AI) has finally—and only recently—begun to demonstrate its massive power to reshape the marketplace, the public sector, the national security arena, and society more broadly. The technical developments that have occurred over the past decade, including new machine learning breakthroughs based on vast improvements in computational power and enormous increases in the quantity of data that can be used to “train” AI systems, have enabled the application of AI to an ever-wider range of sectors and activities. AI’s increasing range of applications are having real-world consequences, both positive and negative. Those consequences, in turn, have animated spirited and at times emotional debates about how governments can craft policies to come to grips with a world increasingly shaped by AI.
With accelerating frequency over the past several years, public authorities, private sector firms, universities, and other organizations around the world have begun to address numerous AI-related policy questions. Within the public sector, AI policymaking is not limited to national governments. Rather, governments at every level—local, state/regional, and national governments in addition to multilateral institutions—have been grappling with AI-related challenges and attempting to craft policies to deal with them.
This newfound level of policymaking activity reflects how AI-driven applications have begun to affect nearly every dimension of human existence. In this arena at least, policy definitely has lagged behind technological advancement. Policymakers are
now rushing to catch up.
The Foresight, Strategy, and Risks Initiative (FSR) provides actionable foresight and innovative strategies to a global community of policymakers, business leaders, and citizens.
As AI policymaking is so new, there is no accepted set of best practices. Experimentation is the order of the day. To illustrate, the first national AI strategy— developed by the Canadian government—did not appear until 2016. Since then, dozens of countries have raced to create their own AI strategies and policies, albeit with widely varying content, goals, mechanisms, and levels of funding.
AI policy, as one commentator puts it, can be defined as “public policies that maximize the benefits of AI, while minimizing its potential costs and risks.” This primer is intended to introduce and clarify AI policy across a wide range of policy domains. Although it is not exhaustive, it is intended to shed some light on the debates that have sprung up across these policy domains. It is intended for the layperson who may not be an AI expert, but who wants to better understand the central questions involved in AI policy debates.
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