AI Governance in the US - so much more than R&D

Looking at existing AI governance measures in the United States and considering the path ahead

This is the second of a series of articles I’ll be writing that look at recent developments in AI policy. The first covered China’s recent AI ethics guidelines, while this one looks at AI strategy and governance measures in the US. 

Intro

A look at the first appearances of Big Tech executives on Capitol Hill (such as Mark Zuckerberg’s still-famous rejoinder to Senator Orrin Hatch’s question about how Facebook remains free: “Senator, we run ads.”) does not inspire much confidence about the US government’s ability to contend with the present state of technology as it defines policy and strategy going forward. Examples of members of Congress displaying an extreme lack of awareness of our digital ecosystem abound. But the picture isn’t entirely bleak--lawmakers made valid points about the inscrutability of recommendation algorithms and platforms’ lack of knowledge about what could be happening on their sites. 

Yet, despite increasing consensus over the need to “reign in” technology giants like Facebook and more discussion of AI in Congressional hearings, next steps and concrete plans from policymakers remain unclear. Among calls for the “responsible” development of AI, bans on technologies like facial recognition, and more democratized access to resources for developing AI systems, it is hard to place a finger on a national strategy for the United States, especially when it comes to regulation. However, there have been efforts to establish official agencies and a clearer desire to establish a national development strategy, as well as examples of legislation at the state level. 

In this piece, we will look at the United States’ national AI plan--how the country intends to support AI development, whether it will consider regulation, and how it will collaborate and compete in the international AI ecosystem--to the extent that there is one, as well as local efforts at AI governance. We will also consider how this national AI plan’s current pieces might come together into something more concrete. In sum, there appears to be little national movement on regulation, while the proliferation of agencies and committees indicate a strong interest in maintaining the US’s advantage in AI. There is little signal from the national government to make regulations seem likely, but groundswells of support for tighter laws around technologies like facial recognition may well prove formative. 

Context

Recent concerns over big tech and the impacts of technologies like facial recognition have drawn significant attention to the prospects for artificial intelligence regulation in the United States. As far as technology policy in the US goes, such regulation of AI would mark a change from past practices: while Europe imposed data privacy regulations with the GDPR, the United States has done little in this vein. Many have called for the United States to take a more proactive approach to regulating AI technologies and not “miss the bus” as it did in contending with data privacy and other unsavory impacts of technology. Regulation advocates are worried about potential adverse impacts due to the adoption of AI technologies, such as unfair criminal sentencing or wrongful arrests due to biased facial recognition systems. 

But not everyone agrees that ex ante regulation--which identifies problems before the fact and seeks to shape incentives--is good or appropriate in the case of rapidly evolving technology. Ben Thompson, for instance, has consistently advocated against a top-down approach to imposing rules for technology development. That is not to say governments should give technology companies free reign to do as they wish. Thompson believes the FTC should not have let Facebook acquire Instagram and that a rule against allowing social networks to merge would be a good one so as not to allow any one network to accrue too much power. But lawmakers should be careful about the unintended consequences of imposing regulatory burdens when they choose to do so and understand that the assumptions they make about the world might quickly cease to be true. 

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