The three challenges of AI regulation
June 15, 2023
The drumbeat of artificial intelligence (AI) corporate chieftains calling for government regulation of their activities is mounting. As Senate Judiciary Committee Chairman Richard Durbin (D-IL) observed, it is “historic” to have “people representing large corporations… come before us and plead with us to regulate them.” There are three challenges for AI oversight: dealing with the velocity of AI developments, parsing the components of what to regulate, and determining who regulates and how:
- Challenge #1 - Velocity (AKA The Red Queen Problem): In Lewis Carroll’s 1871 surrealistic classic Through the Looking Glass, the Red Queen tells Alice: “Now here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run twice as fast as that!” It is an appropriate admonition for oversight in the fast-paced AI era. Keeping the corporate AI race from becoming reckless requires the establishment and development of rules and the enforcement of legal guardrails. Dealing with the velocity of AI-driven change, however, can outstrip the federal government’s existing expertise and authority.
- Challenge #2 - What to Regulate: Because AI is a multi-faceted capability, “one-size-fits-all” regulation will over-regulate in some instances and under-regulate in others. The use of AI in a video game, for instance, has a different effect—and should be treated differently—from AI that could threaten the security of critical infrastructure or endanger human beings. AI regulation, thus, must be risk-based and targeted.
- Challenge #3 - Who Regulates and How: Thus far in the digital age in the US, it is the innovators who have made the rules. This is in large part because the American government has failed to do so. OpenAI’s Sam Altman endorsed the idea of a federal agency dedicated to AI oversight; as well as Microsoft’s Brad Smith and Meta’s Mark Zuckerberg. The challenge facing the US Congress is to be as expansive and creative in their thinking about a new agency and its operations as the innovators of the digital revolution have been in the doping the creations necessitating such a body. Methods to regulate AI may include licensing, risk-based agility, or emulating management practices from digital companies.
The three challenges of AI regulation