U.S. AI Policy Still Effectively A Closed Box

The ethics of AI deployment are front and center for many organizations advising government at all levels. Julia Stoyanovich, co-founder and director of NYU Tandon's Center for Responsible AI, served on New York City's Automated Decision Systems Task Force, established in 2018 to examine the city government's use of algorithms; in principle, she said, national policy could build off the granular experience local policy experts have gained by crafting relevant policies.

"This gives us a really good sandbox, and not a small sandbox," Stoyanovich said. "New York City is the size of a small- to medium-sized European country. I think it's absolutely imperative for the federal government to work with people who are doing this work locally. Part of the reason is, we are closer to the ground and have a more immediate way to speak with constituents. Another is that we simply don't know how to regulate the use of these technologies; not locally, not globally, not federally. So every example we can use is really crucial."

Stoyanovich said she would be more than happy to speak with federal officials about setting a national course for AI. "Speaking on my own behalf, and on behalf of my colleagues, we would be thrilled to engage with the federal government now that the climate is such where we actually expect there to be positive change, including meaningful useful regulations that actually look to include the interest of many constituencies."

Beyond talking policy with politicians, Stoyanovich said computing professionals need to step up now to educate the public about what AI is, how it works, and how it affects them.

Having served on the task force that wrote the ACM's 2018 Code of Ethics and Professional Conduct, Stoyanovich has spent a lot of time preparing educational materials about AI for non-technologists, including online courses and comic books in a campaign called We Are AI. "The code says it is our responsibility as computing professionals to share our knowledge with people broadly, to make our best effort to explain to anybody who asks 'What's an algorithm?'" she said, "and what it can and can't do."