Conservative British Government Is Seizing the Day on AI While the U.S. Dawdles
In the increasingly competitive realm of artificial intelligence, we're seeing other nations step up to the plate.
Last month, the government of the United Kingdom proposed a new £900 million ($1.1 billion) investment in AI. This significant investment will go toward building a top-notch "exascale" computer—on par with the fastest in the world—to advance AI capabilities for public benefit.
The funds will also establish a national research resource that opens up cutting-edge AI R&D to British academia and other institutions, instead of leaving the wherewithal solely in the hands of private industry, as is the current situation in the U.S.
It's a bold move by UK government officials, and absolutely the right one.
Their announcement comes barely two years after staff at the Office of then-Prime Minister Boris Johnson reached out to us at Stanford HAI to learn more about the value of a National AI Research Resource (NAIRR), which we've strongly advocated for domestically.
The speed with which the fiscally conservative, Tory-led government has acted in rolling out these AI investments shows that British officials get it. The U.S. government, however, remains largely on the sidelines.
Beyond investment, the U.S. is also lagging in implementing pro-innovation regulation to foster AI's responsible growth. Here again, the Brits have the edge.
On March 29, the U.K. government followed up their initial AI splash by proposing AI regulation that, among other forward-thinking ideas, creates a regulatory "sandbox", wherein services and products based on innovative tech that fall outside of existing regulation are granted compliance space so appropriate rules can then be dynamically crafted. While not perfect, it is a good start in addressing the big potential and risks that AI poses from a regulatory perspective. Investment and regulation should be complementary to each other; the former needs the latter in order to streamline development while growing public trust.
Lawmakers in Washington should follow the UK’s example in recognizing the enormity of the promise of democratizing access to high-end compute resources, and a willingness to apply some initial regulations.
Washington has taken some initial steps, such as advancing the use of AI with increased funding for AI R&D, supporting the American manufacturing with the CHIPS Act, coordinating AI policy through the National Artificial Intelligence Initiative, and the White House releasing a blueprint for an AI Bill of Rights.
But the funding needed has yet to materialize. A starting point is the final report issued this past January by the National AI Research Resource (NAIRR) Task Force, a federal advisory committee established by the National AI Initiative Act of 2020 and composed of members from government, academia, and private organizations.
The NAIRR Task Force recommended that Congress appropriate $2.6 billion over six years. While we wholly support this recommended appropriation, let's put it in perspective: As a percentage of the United Kingdom's GDP, the British AI investment is actually more than three times the equivalent amount of $2.6 billion as a percentage of United States' GDP.
Meanwhile, Big Tech investment in AI makes these figures look like pocket change. For instance, Microsoft announced an investment of $10 billion over several years to OpenAI, the AI research lab behind ChatGPT, the fastest-growing app of all time.
Private industry will certainly play a significant role in AI; but there are fundamental differences between private and public aspirations.
Simply framed, Big Tech product labs work on short time horizons where making profits and satisfying shareholders is the goal. In contrast, national and academic research laboratories work on long time horizons where big thinking and patience ultimately pay off. It's no wonder that research labs have proven to be unparalleled engines of innovation.
Government-supported, academia-driven research toward basic science has yielded major breakthroughs that have subsequently been commercialized as some of the most profound innovations of the modern age. Examples include the Internet, the Global Positioning System, and CRISPR, the gene-editing breakthrough that's sweeping biotech.
There is historical precedent for lawmakers in Washington to consider in the form of the Human Genome Project. The prospect of mapping all the genes in our bodies led Congress in the late 1980s under the Republican administrations of Presidents Ronald Reagan and George H. W. Bush to appropriate funding for National Institutes of Health and Department of Energy labs to accelerate gene mapping and sequencing technologies. This public effort continued through the 1990s alongside an effort led by Celera, a private company, culminating in 2000 with a joint announcement by President Bill Clinton, British Prime Minister Tony Blair, and Celera's president, Dr. Craig Venter, of a completed initial sequence.
It was a public-private triumph that collectively respected both privacy and open access. Imagine, instead, if the commercial industry alone—like Big Tech today in the U.S. with AI—had been left to decipher the blueprint for human life. Would Big Pharma have trademarked this information and pursued it primarily for profit-driven, short-term gain?
To get the U.S. started down the path to responsible AI development, we encourage creating and fully funding a National AI Research Resource to democratize AI research and get academia back into the game.
To develop the next generation of AI-based applications, we need to democratize access to its essential tools and capabilities at the public level, including universities and nonprofit research organizations. Students need to know and understand AI today in order to deliver on its promise tomorrow.
Right now, the U.K. is rapidly outpacing the U.S. both in terms of AI investment and regulation. It is time for our country to get off the sidelines and into the right type of race–providing AI infrastructure and at a minimum, pro-innovation regulation.
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