Eakinomics: AI Regulation and the Administration

Eakinomics: AI Regulation and the Administration  The buzzword “Artificial Intelligence” (AI) has been tossed around a lot, often in the context of raising fears of massive job displacement and even threats to society. Indeed, the exact fears are often inchoate and difficult to identify. Simultaneously, and perhaps causally, there are calls to regulate AI — notably by figures such as Elon Musk, Bill Gates, Mark Cuban, and the late Stephen Hawking. But what is the right strategy? To begin, it is useful to distinguish between “narrow” AI and “general” AI. Narrow AI are models and mechanisms built upon experience and real-world data to achieve very specific objectives such as translating languages, predicting the weather, and reading medical scans. Narrow AI doesn’t seem to raise any new regulatory issues. If it were desirable to limit or preclude the objective, it would already be regulated; how it gets done doesn’t matter so much. General AI are decision-making systems able to cope with a generalized task in the same way a human does. This seems to be what most people associate with the term AI; a good example is Samantha from the movie Her. How to regulate general AI is an important policy issue. As explained by AAF’s Dan Bosch, the Trump Administration recently released a draft guidance with principles for how federal agencies should regulate AI. This memorandum is only a draft, but after a period of comment it will be finalized. Executive Order (EO) 13,859, “Maintaining American Leadership in Artificial Intelligence” (issued in February 2019), requires that the Office of Management and Budget director issue such a memorandum. The Trump Administration outlines a light-touch approach to regulating AI. That approach seems appropriate given the uncertainties. Its intent, according the EO, is to “sustain and enhance the scientific, technological, and economic leadership” of the United States. To achieve this goal, the administration argues for regulation only when needed, and not as a precaution that might inadvertently cut off innovation.