from the perhaps-AI-can-help-us-deal-with-AI dept
Most people don't understand the nuances of
artificial intelligence (AI), but at some level they comprehend that it'll be
big, transformative and cause disruptions across multiple sectors. And even if AI
proliferation won't lead to a robot uprising, Americans are worried about how AI and automation will
affect their livelihoods.
Recognizing this anxiety, our policymakers
have increasingly turned their attention to the subject. In the 115th Congress,
there have already been more mentions of “artificial intelligence” in proposed legislation and in the Congressional Record than ever before.
While not everyone agrees on how we should
approach AI regulation, one approach that has gained considerable interest is
augmenting the federal government's expertise and capacity to tackle the issue.
In particular, Sen. Brian Schatz has called for a new commission on AI; and Sen.
Maria Cantwell has
introduced legislation setting up a new committee within the Department of
Commerce to study and report on the policy implications of
AI.
This latter bill, the “FUTURE of Artificial Intelligence Act” (S.2217/H.4625), sets forth a bipartisan proposal that
seems to be gaining
some traction. While
the bill's sponsors should be commended for taking a moderate approach in the
face of growing populist anxiety, it's not clear that the proposed advisory
committee would be particularly effective at all it sets out to do.
One problem with the bill is how it sets the
definition of AI as a regulatory subject. For most of us, it's hard to
articulate precisely what we mean when we talk about AI. The term “AI” can describe
a sophisticated program like Apple's Siri, but it can also refer to Microsoft's
Clippy, or pretty much any kind of computer software.
It turns out that AI is a difficult thing to define, even for experts.
Some even argue that it's a meaningless
buzzword. While this is a fine debate to have in the academy, prematurely
enshrining a definition in a statute – as this bill does – is likely to be the
basis for future policy (indeed, another recent bill offers a totally different definition). Down
the road, this could lead to confusion and misapplication of AI regulations. This
provision also seems unnecessary, since the committee is empowered to change
the definition for its own use.
The committee's stated goals are also overly-ambitious.
In the course of a year and a half, it would set out to “study and assess” over
a dozen different technical issues, from economic investment, to worker
displacement, to privacy, to government use and adoption of AI (although,
notably, not defense or cyber issues). These are all important issues. However,
the expertise required to adequately deal with these subjects is likely beyond
the capabilities of 19 voting members of the committee, which includes only
five academics. While the committee could theoretically choose to focus on a
narrower set of topics in its final report, this structure is fundamentally not
geared towards producing the sort of deep analysis that would advance the
debate.
Instead of trying to address every AI-related
policy issue with one entity, a better approach might be to build separate, specialized
advisory committees based in different agencies. For instance, the Department
of Justice might have a committee on using AI for risk assessment, the General
Services Administration might have a committee on using AI to streamline
government services and IT
infrastructure, and the Department of Labor might have a committee on worker displacement
caused by AI and automation or on using AI in employment decisions. While this
approach risks some duplicative work, it would also be much more likely to
produce deep, focused analysis relevant to specific areas of oversight.
Of course, even the best public advisory
committees have limitations, including politicization, resource constraints and
compliance with the Federal Advisory Committee Act. However, not
all advisory bodies have to be within (or funded by) government. Outside
research groups, policy forums and advisory committees exist within the private
sector and can operate beyond the limitations of government bureaucracy while
still effectively informing policymakers. Particularly for those issues not
directly tied to government use of AI, academic centers, philanthropies and other groups
could step in to fill this gap without any need for new public expenditures or
enabling legislation.
If Sen. Cantwell's advisory committee-focused
proposal lacks robustness, Sen. Schatz's call for creating a new “independent federal
commission” with a mission to “ensure that AI is adopted in the best interests
of the public” could go beyond the bounds of political possibility. To his
credit, Sen. Schatz identifies real challenges with government use of AI, such as those posed by criminal justice applications,
and in coordinating between different agencies. These are real issues that
warrant thoughtful solutions. Nonetheless, the creation of a new agency for AI
is likely to run into a great deal of pushback from industry groups and the
political right (like similar proposals in the past), making it a difficult
proposal to move forward.
Beyond creating a new commission or advisory
committees, the challenge of federal expertise in AI could also be
substantially addressed by reviving Congress' Office of Technology Assessment
(which I discuss in a recent paper with
Kevin Kosar). Reviving OTA has a number of advantages: OTA ran
effectively for years and still exists in statute, it isn't a regulatory body,
it is structurally bipartisan and it would have the capacity to produce deep-dive
analysis in a technology-neutral manner. Indeed, there's good reason to
strengthen the First Branch first, since Congress is ultimately responsible for
making the legal frameworks governing AI as well as overseeing government
usage.
Lawmakers are right to characterize AI as a big deal. Indeed, there are trillions of
dollars in potential economic benefits at stake. While
the instincts to build expertise and understanding first make for a commendable
approach, policymakers will need to do it the right way – across multiple
facets of government – to successfully shape the future of AI without hindering
its transformative potential.
Filed Under: ai, artificial intelligence, brian schatz, committees, machine learning, maria cantwell, regulation