Artificial Intelligence Policy: A Primer and Roadmap
This paper provides a roadmap (not the road) to the major policy questions presented by AI today. The goal of the essay is to give sufficient detail to describe the challenge of AI without providing the policy outcome. It discusses the contemporary policy environment around AI and the key challenges it presents including: justice and equality; use of force; safety and certification; privacy and power; and taxation and displacement of labor. As it relates to privacy in particular, the author posits that the acceleration of artificial intelligence, which is intimately tied to the availability of data, will play a significant role in this evolving conversation in at least two ways: (1) the problem of pattern recognition and (2) the problem of data parity.
Talk of artificial intelligence is everywhere. People marvel at the capacity of machines to translate any language and master any game. Others condemn the use of secret algorithms to sentence criminal defendants or recoil at the prospect of machines gunning for blue, pink, and white-collar jobs. Some worry aloud that artificial intelligence will be humankind’s “final invention.”
This essay, prepared in connection with UC Davis Law Review’s 50th anniversary symposium, explains why AI is suddenly on everyone’s mind and provides a roadmap to the major policy questions AI raises. The essay is designed to help policymakers, investors, technologists, scholars, and students understand the contemporary policy environment around AI at least well enough to initiate their own exploration.
Topics covered include: Justice and equity; Use of force; Safety and certification; Privacy (including data parity); and Taxation and displacement of labor. In addition to these topics, the essay will touch briefly on a selection of broader systemic questions: Institutional configuration and expertise; Investment and procurement; Removing hurdles to accountability; and Correcting mental models of AI.