AI & The Next Economy

ARTIFICIAL INTELLIGENCE can spawn efficiency that will bring down wages and prices, but expect a bumpy ride

Artificial intelligence is boosting the global economy’s efficiency, profitability and productivity, but it’s also exacting a price. It could replace 85 million workers globally by 2025, the World Economic Forum (WEF) projects.

Yet the vast displacement won’t hit hardest among the working- and middle-class employees who’ve borne the brunt of job loss to automation over the last 40 years. Instead, this wave of innovation and adoption will take jobs away from content producers, artists and white-collar workers.

The realization that a group with as many people as the nation of Iran will be jobless within 36 months has quickly altered the debate on social policy, economic theory and political remedies.

Let’s discuss the macroeconomic and socioeconomic realities of all three buckets (without the insight of big data analytics) and then explore the themes that will soon dominate policy debates.

Economic impact

While the WEF report indicates AI could take over the aforementioned 85 million jobs in the next

SINCE 2000, THE WORLD’S GOVERNMENTS HAVE CREATED $185 TRILLION IN NEW DEBT, BUT THE GLOBAL ECONOMY HAS GROWN BY ONLY $46 TRILLION.

couple of years, it also suggests the global economy could create 97 million jobs, thanks to the complementary benefits of AI tech.

Initially, automation will shoulder repetitive, banal or dangerous tasks, freeing workers for more important and interesting roles where they can make better use of their training. As a result, productivity per capita is expected to increase rapidly.

Because it’s a net gain, the number seems promising. The challenge is that the new jobs will require significant upscaling and training.

About 95% of the 1.4 million American workers likely to be replaced by AI will find new specialized jobs with higher pay, the WEF predicts. That said, the cost of retraining global workers could top $34 billion—or an average of $24,000 per displaced worker.

That raises the question of who will pay. A few companies have developed their own training, but taxpayers will finance much of it through new incentives and tax breaks for corporations. And what jobs are we discussing?

Today, AI isn’t flipping burgers at McDonald’s. It’s diagnosing cancer. It’s drafting legal documents with the skill of a third-year law student. It’s

mimicking human speech, writing college-level papers, improving code exponentially, and translating complex language and speech.

In the future, AI will fill additional advanced roles, which will reduce wages and cut costs along supply chains.

So, what policy should address the deflation that technology will drive? Jeffrey Booth, the author of the book Price of Tomorrow, has argued that deflation creates abundance. AI can drive efficiency,

reduce costs and create more with less, he maintains.

In other words, deflation could be a good thing. But with the U.S. economy mired in $31.5 trillion of federal debt, the financial system faces a critical choice—add more debt to service the existing shortfall or use technology to grow the economy radically?

Venture capitalist and co-host of the All-In podcast David Friedberg suggests AI could help move the U.S. economy to hypergrowth that would pull the nation out of debt.

AI COULD ADD $15.7 TRILLION TO THE WORLD ECONOMY IN THE YEAR 2030 ALONE.

“The net benefit of this is economic productivity,” Friedberg says in a February podcast. “The end customers using [these tools] now have a lower cost to run their business. And their total net profits go up. This is what happens with every technology cycle. It always yields greater economic productivity.”

That’s why the economy grows and why technology can be such an important component of

economic growth, not debt, Friedberg notes, adding that “we’ve historically used financial engineering to drive economic growth.”

However, technological adaptation goes against the debt-based economic system. Over the last 25 years, the global economy has benefited from the miracle of deflationary technology like cell phones and extremely fast computers. Yet, central banks have used debt to paper over deflation even with the deteriorating return on investment.

The German news organization Der Spiegel predicted robots would eliminate human workers in 1964, 1978 and 2017. The job losses will soon accelerate as AI’s influence spreads.

Since 2000, the world’s governments have created $185 trillion in new debt. However, the growth return has underperformed. Despite this massive debt load, the global economy has generated only $46 trillion in growth.

Since the expansion of monetary policy in the 1970s, every new dollar of debt has generated less economic growth than the previous dollar. But central banks continue to pump out fiat capital in the face of deflationary outcomes. Expect more of the same and an ever-increasing debt load.

Social impact

Silicon Valley loves artificial intelligence, thanks to the twin benefits of efficiency and profitability. AI could add massive economic growth to the global system by 2030, amounting to $15.7 trillion, according to PwC. The breakdown includes productivity gains of $6.6 trillion on top of $9.1 trillion from “consumption-side effects.”

The economic debate will center on who pockets the gains. The social debate hinges on a basic ques-

tion: Just because AI can be applied to something, should it be?

Take the example of Major League Baseball, which has resisted the temptation to incorporate robotic umpires. The sport would probably benefit in some ways from a system that more accurately calls balls and strikes. But human error is part of the game. What would it be without rhubarbs?

Now consider human error at a larger scale. It’s part of the U.S. economy, and consulting and software businesses derive their very existence from resolving such errors and increasing efficiency. Will AI, big data and advanced analytics remove human error from the equation?

And what will that cost adherents of the broken window fallacy of economics, which states spending on something broken doesn’t lead to economic gain?

AI may resolve social and economic problems created by human error. Some 90% of automobile accidents, for example, are linked to human error, Stanford University noted in 2013. In 2016, IBM estimated that bad data linked largely to human error cost U.S. businesses $3.1 trillion. Plus, 95%

AI COULD HELP MOVE THE U.S. ECONOMY TO HYPERGROWTH.

of cybersecurity events are linked to human error, the World Economic Forum says.

Using AI to improve those situations would have significant societal and financial benefits while displacing existing systems. What’s more, those three examples are among many AI will likely ameliorate.

Naturally, this focus on efficiency, productivity and streamlining will affect consultancies and engineering firms. It’s just a taste of the imminent white-collar revolution.

Until now, automation has been largely a blue-collar challenge that’s pushed down workers’ pay in the last four decades, according to the National Bureau of Economic Research.

Between 50% and 70% of the decline in wages was linked directly to automation, says a 2021 study by Daron Acemoglu and Pascual Restrepo highlighted in the Journal of Economic Perspectives. “The real earnings of men without a high-school degree are now 15% lower than they were in 1980,” they found.

Until recently, observers believed the current wave

of AI automation would follow the same pattern of inflicting pain first on blue-collar workers in factories or behind the wheel of trucks. Then it would come for the lower-skilled white-collar jobs and then the high-skilled ones. Many were convinced it would never take over creative endeavors.

But AI has taken a different course, says OpenAI CEO Sam Altman.

“It’s going in exactly the other direction,” Altman maintains in an event hosted by venture capital firm Greylock Partners. “There’s an interesting reminder in here generally about how hard predictions are, but more specifically about [how] we’re not always very aware, maybe even ourselves, of what skills are hard and easy, what uses most of our brain and doesn’t or how difficult bodies are to control or make.”

The social impact of AI seems undeniable with such major shifts in the workforce. But the changes it’s bringing could go even deeper, shaking the very foundations of society.

It’s not enough to think just about politics and the responses of the central bank. AI could alter the basic nature of the market economy.

End of capitalism?

In 2018, one of China’s top legal scholars, Feng Xiang of Tsinghua University, predicted in a Washington Post op-ed that AI would destroy the capitalist system.

Feng argued that technology billionaires would only increase their stranglehold over the economy— as if this were a U.S.-only phenomenon.

“If AI remains under the control of market forces,” he wrote, “it will inexorably result in a super-rich oligopoly of data billionaires who reap the wealth created by robots that displace human labor, leaving massive unemployment in their wake.”

He uses the article to present a soft endorsement of China’s socialist market economy. The key argument goes that while China has large AI companies with dominant market share, at least the government monitors them.

Perhaps Feng might consider the words of economist John Kenneth Galbraith: “Under capitalism, man exploits man. Under communism, it’s just the opposite.”

Moreover, Marxists have predicted the end of capitalism since 1848. And the German news organization Der Spiegel has forecasted mass unemployment since 1964 because of robotics and mainframes.

The idea of free and voluntary exchange as the central tenant of capitalism doesn’t register with its critics, and perhaps dictionary definitions of “corporatism” or “dirigisme” would better suit Feng because the economy aligns more closely with those ideas.

But OpenAI’s Altman also says he can envision AI’s impact on capitalism, but first he praises the system. “I think capitalism is awesome. I love capitalism,” he notes. “Of all of the bad systems the world has, it’s the best one—or the least bad one we found so far. I hope we find a way better one.”

But as artificial intelligence becomes artificial general intelligence (AGI) operating on the level of human intellect, danger sets in. “I think that if AGI really truly fully happens, I can imagine all these ways that it breaks capitalism,” Altman says.

Perhaps a new system will emerge. Or maybe AI or AGI will break up the centralized control in the economy exercised by players like Alphabet, Amazon and Microsoft. The democratization of AGI would in essence cast aside the criticisms of Feng and other AI political economists.

Other risks move beyond the traditional largescale trends, too. Mark Lippett, CEO of AI chip company XMOS, told Forbes in 2021 he’s concerned about AI invading privacy because it relies on constant data collection.

THE CURRENT WAVE OF AI INNOVATION AND ADOPTION COULD TAKE JOBS AWAY FROM ARTISTS, PROGRAMMERS, CONTENT PRODUCERS AND OTHER WHITECOLLAR WORKERS.

“What we say and do will become increasingly ‘on the record’ unless consumers are educated to make informed decisions about where AI is deployed,” Lippett says.

But protecting data privacy is just one of many shifts that policy makers should address sooner rather than later.

Political impact

A dramatic acceleration in AI adoption through 2025 will clearly make unemployment and job training a major political issue in the elections of 2024 and 2028. But how will the political parties address it?

Do Democrats become Luddites and try to limit the advance of AI? Or will they fight the widening inequality in wages that technology will bring?

Do Republicans become the party of robot owners as income inequality grows? Or will they reevaluate capitalism and embrace the universal basic income (UBI) now under scrutiny in Germany and Chicago?

In fact, UBI could become the subject of heated debate. When Andrew Yang ran for president in 2020, he pushed for a $1,000 monthly payment to every American adult over 18. If AI pushes the American labor force participation rate below 60%, it’s fair to expect a revival of interest in UBI.

AI will also figure into the discussion of the student loan bailout. What happens when AI replaces graduates with engineering, science, mathematics and technology degrees and thus lowers the return on investment for those majors?

Then there’s the issue of AI and big data. “AI is only as good as the data that is used to train it,” says Francois Laborie, president of Cognite, a Norwegian software company. He told Forbes that “this becomes dangerous when a wrong prediction leads to potentially life-threatening events, such as manufacturing accidents or oil spills.”

It would make sense to use AI to engage in analytics, cut fat from government programs and streamline benefit systems. AI can also reduce red tape, slash bureaucracy and optimize welfare. After all, the U.S. falls victim to roughly $60 billion in Medicare fraud annually.

But the problem is that AI can fail when trying to find the sources of such problems.

An example of artificial intelligence gone wrong occurred in 2021 when the Netherlands used AI to examine the authenticity of childcare benefits claims.

The AI erroneously estimated 26,000 parents had filed fraudulent claims. The resulting debacle imposed hardship on working-class families and prompted the resignation of a number of officials.

Imagine thousands of newly minted IRS agents acting on the conclusions of faulty artificial intelligence. The result could be economic paralysis.

Looking ahead

The AI debate will continue as the technology becomes increasingly prevalent in the workplace and at home.

Displacing workers is nothing new, but AI is shifting the burden of change from blue-collar workers to white-collar professionals.

Hence, it makes sense to expect AI to shape up as a major policy issue in the 2024 elections and beyond.

Garrett Baldwin, a commodity and trade economist, serves as Luckbox editor-at-large. He actively trades value and momentum stocks and wagers on sports and prediction markets.