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Congress probes how AI will impact U.S. economic recovery

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AI has the potential to improve human lives and a company’s bottom line, but it can also accelerate inequality and eliminate jobs during the worst U.S. recession on record since the Great Depression. It’s that dual promise and peril that led members of the House Budget Committee to hold a hearing today in Congress to discuss the impact of AI on economic recovery, the future of work, and the federal budget.

Expert witnesses recommended approaches today ranging from giving people lifelong learner accounts for upskilling to creating regional investment districts or portable benefits.

Daron Acemoglu warned the committee about the dangers of excessive automation. The MIT professor and economist recently found that every robot replaces 3.3 human jobs in the U.S. In a working paper published by the National Bureau of Economic Research, Acemoglu detailed how excessive automation looks for ways to replace workers with machines or algorithms but produces few new jobs. Companies are currently incentivized by a U.S. tax code that taxes capital at a lower rate than human labor, policy he said incentivizes companies to replace humans with automation. In practice, this can be an action as simple as replacing a McDonald’s worker with a touchscreen. He argues automation has been a drag on the U.S. economy, potentially slowed market productivity, and has failed to lead to higher wages for low- and middle-class workers.

“AI is a broad technological platform with great promise. It can be used for helping human productivity and creating new human tasks, but it could exacerbate the same trends if we use it just for automation,” he said. “Excessive automation is not an inexorable development. It is a result of choices, and we can make different choices.”

Also shaping the nature of automation in the economy are Big Tech companies with business models that focus on replacing human labor with algorithms, and priorities enshrined in U.S. government funding. Acemoglu said Congress must also consider factors unseen in data such as the loss of self-worth suffered by a person without a job or how employment impacts the likelihood a person becomes involved in their community.

Rep. Bill Flores (R-TX) cautioned against changes to how the government treats capital and labor, saying “I think we as policymakers need to be very careful about trying to get into adjusting the mix of capital versus labor, because as you said early on chairman Yarmouth the government moves slowly, and I think we as policymakers could end up being well behind where the economy is if we’re not careful with that.”

It’s unclear whether testimony delivered today could influence any particular upcoming piece of legislation but it could impact how members of Congress shape policy related to funding in areas like research and development, national defense, and job retraining.

The McKinsey Global Institute predicts AI will drive GDP growth around the world in the decades ahead, but studies also find that automation in the workplace is expected to particularly impact Black or Latinx people, who make up a larger percentage of the service economy than other groups. Certain cities, states, and regions are also expected to be disproportionately impacted by the proliferation of AI. About one in three jobs in the U.S. may require some form of retraining due to automation, according to the OECD. On the business side, KPMG report released last year urged company executives to take AI-driven job loss seriously and consider ways to retrain or reskill workers.

High-speed broadband access received bipartisan support in the hearing as a way to close the digital divide and ensure widespread access to education, job training, and remote job opportunities. A bill with nearly $80 billion in broadband funding was approved by the House of Representatives in July, but the Senate has not yet taken up the legislation.

Helping workers find job or skill training will be an important part of addressing the instability and job loss brought on by AI, said Stanford Human-Centered Artificial Intelligence (HAI) associate director Susan Athey, but historically the United States hasn’t done a great job of helping displaced workers impacted by automation. Athey is currently working with the Rhode Island state government on using AI to help people find work. Making people feel comfortable and confident in upskilling recommendations will be an important part of helping people fulfill job training programs and acquire new skills.

“They need to have confidence that if they do make that effort and take that scarce time and money, they will be able to use that to get a new job,” she said. “I’m optimistic about the future, but we have to be intentional about it, and we actually have to execute and follow through on promises.”

Stanford HAI is only a little over a year old, but the organization led by former Google Cloud chief scientists and ImageNet creator Dr. Fei-Fei Li has made multiple policy proposals to Congress. Last fall, Stanford HAI urged the federal government to invest $120 billion in the U.S. AI ecosystem over the next decade with $2 billion in funding for entrepreneurs and innovation, $7 billion for AI research, and $3 billion for education. In June, Stanford HAI joined companies like AWS, Google, and Microsoft to urge the federal government to create a national AI research cloud bill.

As is standard in congressional hearings about artificial intelligence, competition between China and the U.S. came up on multiple occasions. Jason Matheny is director of the Center for Security and Emerging Technology (CSET) at Georgetown University and serves on the National Security Commission on Artificial Intelligence (NSCAI), a temporary body formed to provide Congress with military and national security policy recommendations. The group asserts that AI dominance by the United States is vital to U.S. national security

Matheny said immigration of highly skilled workers was key to the U.S. winning World War II and the Cold War and that the U.S. maintains an asymmetrical advantage over China today because more AI research talent wants to live and work in the U.S. than they want to live and work in China. National Science Foundation (NSF) data shows that more than half of Masters and Ph.D. level computer scientists in the U.S. today were born abroad. He also named immigration an important part of addressing worker shortages brought on by Baby Boomers leaving the workforce.

Matheny named the United States’ lead in the semiconductor hardware used to accelerate AI a key advantage over China.

“It will be very difficult for China to match us if we play our cards right,” Matheny said. “We shouldn’t rest on our laurels, but if we pursue policies that strengthen our semiconductor industry while also placing the appropriate controls on the manufacturing equipment that China doesn’t have and that China currently doesn’t have the ability to produce itself, and is probably a decade away from being able to produce itself, we’ll be in a very strong position.”

He continued to say in the hearing that the U.S. is still too reliant on semiconductor hardware from abroad and called Intel potentially working with Taiwan Semiconductor Manufacturing Company on advanced manufacturing advanced semiconductors outside the United States “extremely worrying.”

As part of securing the semiconductor supply chain, Matheny also encouraged strengthening alliances with other nations. In June, the U.S. and more than a dozen other nations joined the Global Partnership on AI (GPAI). The group holds its first annual meeting in December.

The NSCAI first recommended that Congress invest in public-private partnerships to bring more semiconductor hardware back to the United States earlier this year. On the subject of AI talent or retraining, earlier this summer, the NSCAI recommended creating a government university to produce more trained AI talent that works in the federal government. The NSCAI will issue a final list of recommendations to Congress in spring 2021.

For markedly different reasons, members of Congress voiced some criticisms at the hearing today. In her questioning, Rep. Sheila Jackson-Lee (D-TX) said “We’re all speaking to haves because the have nots are not in the room,” she said in reference to the fact that the witness list did not include the voices of people impacted by job dislocation or inequality. Last fall, for example, the Federal Trade Commission received a complaint about AI-powered hiring tool HireVue alleging unfair practices and intrusive collection of biometric data.

In response to a question from Jackson-Lee, Brookings Institution director of governance studies Darrell West said investment in broadband, telemedicine, and education could help address inequities in tech.

“We’re almost in a situation where technology is helping to fuel the inequality in the sense that the haves are doing better and getting tax breaks and have programs that support them, and people at the lower end aren’t even in the game. They don’t have access to the digital economy,” he said.

In his critique, ranking member Steve Womack (R-AK) called the hearing focused on AI interesting and important but said the budget committee would be better served by focusing on how to reduce the U.S. federal budget deficit. Updated projections released by the Congressional Budget Office Wednesday found that the deficit now stands at $3.3 trillion, more than triple what it was in fiscal year 2019 and the highest percentage of debt compared to GDP since 1945.

When asked by Rep. Womack how the federal government should prioritize research and development funding, Matheny suggested a focus on areas where private businesses may be likely to underinvest. This includes basic research carried out by groups like DARPA and the National Science Foundation, and testing and evaluation by agencies like the National institute of Standards and Technology (NIST).

Numerous witnesses testifying before the committee today said the government can use AI to improve government efficiency.

“I do believe it is a good time to start thinking about modernizing federal government infrastructure,” Athey said, adding that cybersecurity, fraud protection, and administrative services are ways the federal government can deliver services. A joint NYU-Stanford study examining federal government use of AI found that only 15% of federal agencies currently use advanced forms of artificial intelligence today. Some government use of AI might result in job loss, but Athey said that job loss could lead to better allocation of human resources for society.

“While that loses a piece of employment for the worker sitting behind the counter, maybe there’s other things your government could be doing: More childcare, more eldercare, there are other services that are underprovided where the human workers can be better deployed if we use technology to do things where the human is kind of getting wasted on both sides of the table,” she said.

In other recent government regulation and AI news, the Portland City Council passed the strictest facial recognition ban in the United States Wednesday. Businesses and government agencies who fail to comply can face fines of $1,000 per day for each violation of the law.



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