Schumer’s AI Plan Urges Billions in Spending to Challenge China
The US needs to shield Americans from the risks posed by artificial intelligence while promoting the emerging technology with at least $32 billion in annual government spending to stay ahead of rivals like China, according to a highly anticipated policy blueprint from a bipartisan group of senators.
Congress should craft legislation that mitigates AI's potential harm and funds research to boost US economic and national security, according to the plan released Wednesday by Senate Majority Leader Chuck Schumer. US companies including OpenAI, Alphabet Inc.'s Google, and Meta Platforms Inc. currently hold the global lead, yet China's race to develop highly advanced systems is putting pressure on lawmakers to craft a more lasting approach.
Funding will “keep our companies, our universities, our workers at the cutting-edge and cement America's dominance in AI, including out-competing the Chinese government, which we know is putting lots of dollars into this area already,” Schumer said in unveiling the 30-page document.
The blueprint culminates more than a year's worth of activity on Capitol Hill to familiarize senators with AI, a first step toward eventually writing legislation governing the rapidly evolving technology. The senators last year held a series of closed-door forums featuring labor and tech industry leaders, including OpenAI's Sam Altman, Google's Sundar Pichai, Meta's Mark Zuckerberg and Elon Musk of Tesla Inc., to examine AI's vast implications for everything from national security to jobs to individual privacy.
Rapid developments in AI have fueled concerns that the technology could foment the spread of misinformation and expose consumers' personal data. Executives from Google, Microsoft, IBM and OpenAI have urged more federal oversight to help guarantee safety, and three dozen venture capital firms agreed to abide by voluntary commitments after President Joe Biden in October signed an executive order that set initial safeguards and built on earlier
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