Nationalize the Data: How the US Can Beat China in AI

Nationalize the Data: How the US Can Beat China in AI

This post is one in a series by students in “Emerging Technologies and the Future of the World,” a new interdisciplinary course on how political, legal and social factors influence technological change.

A member of the class of 2020, Daniel Brennan studies Military History and Political Theory. He is a United States Marine Corps Officer Candidate, a Student Fellow at Penn’s Perry World House, and a rower on the Men’s Varsity Lightweight Crew.

On October 4th, 1957, the Soviet Union launched the first artificial satellite — Sputnik 1 — into space. The United States, which had thought that its technological supremacy was uncontested, was now faced with the prospect of falling behind the Soviets. President Eisenhower and Congress were quick to react. That following year Congress authorized the creation of the Advanced Research Projects Agency — renamed Defense Advanced Research Projects Agency (DARPA) — and passed the National Defense Education Act of 1958. These measures made billions of dollars available to educators and researchers to promote scientific education. America reaped the benefits of this investment for decades to come as American scientists and engineers won the Space Race, developed cutting edge medical treatments, and developed leading research institutions and universities.

With China aspiring to lead the development of artificial intelligence (AI), some American observers have cried “Sputnik” and implored policy makers to pump more money into STEM fields so that the United States does not fall behind. Their concern is valid but their proposed solution is ham-fisted and misguided. The race for artificial intelligence is not the race to the moon. Whereas the moonshot was a narrowly defined government project, leading the AI revolution is a broad and nebulous societal goal.

The transformative nature of artificial intelligence suggests that the best way for the United States to stay at the forefront of AI development is to leverage its current leading position to enable future innovation. The United States should pass legislation requiring the release of privately held data after a period of several years so as to generate a comprehensive public data bank on which nascent AI enterprises can train their algorithms. Creating these data banks would significantly lower the barriers to AI innovation in the United States, draw international talent, and ensure that the US stays at the forefront of technological innovation.

Economist and historian Joel Mokyr contends that the reason the United Kingdom led the world in industrialization was not because of outstanding British inventors such as James Watt, but because Britain had more tinkerers, mechanics, and entrepreneurs than other European countries. As a result Britain was better able to incorporate new industrial technologies into its commercial and civil enterprises once they were developed. The British example suggests that technological revolutions do not simply occur around the best technologists, but where there are many competent technologists who can apply the discoveries of the brilliant few to everyday life.

Continue reading on the course’s Technology, Innovation, and Society blog.