In 2019, tech companies delivered record-breaking earnings that pushed share prices to historical highs. Four companies–Apple, Amazon, Microsoft, and Facebook–accounted for 12% of the S&P 500’s total advances during the first two months of the year. Despite escalating trade tensions with China, widespread fear of a global economic slowdown, and concerns over monetary policy, the share prices of these companies and their peers have increased by 50 percent or more since last December. The fact that four technology companies disproportionately contributed to the stock market’s resurgence in the first half of 2019 is indicative of the unprecedented power that Big Tech wields over the global economy. Their ever-growing profits indicate that the benefits of economic growth are accruing to an increasingly concentrated group of technology companies and individuals. As these companies begin to develop applications for advanced technologies such as AI with the potential for both explosive profits and social disruption, concerns over wealth inequality could boil over into anger and unrest.
These trends are playing out against the backdrop of widespread furor over wealth distribution in the United States. With inequality set to become one of the defining issues of the upcoming presidential election, Democratic candidates vying for their party’s nomination in 2020 have introduced bold new proposals for redistributing wealth. Kamala Harris’ tax policy would provide generous tax credits to the middle class and Elizabeth Warren’s tax on the super-rich could raise $2.75 trillion in revenue over ten years. By promoting a more progressive federal tax system, these policies seek to resolve one of the most visible symptoms of several decades of unequal wage growth. A graph produced by French economist Thomas Piketty in 2014 shows that since 1990, income growth among the wealthiest 10 percent of Americans either outstripped or kept pace with the economy while the rest of the country fell behind. Outsourcing of labor following the liberalization of China’s economy, the regressive tax regime under Reagan, and widespread adoption of advanced technologies have all been identified as reasons for suppressed wage growth.
The accelerating adoption of advanced technologies across all sectors of the economy has the highest potential for future disruption to the labor market. Thanks to unprecedented improvements to computing power and the proliferation of digital services that generate rich data sets, entrepreneurs can now work with innovators to develop specific applications for AI and robotics. According to the consulting firm PwC, these applications will add $15.3 trillion to the global economy by 2030. Some countries will benefit more than others, with China and the US expected to realize 70 percent of these gains. Both China and the US have vibrant venture capital ecosystems, plenty of world-class entrepreneurial and engineering talent, and large headstarts that will enable them to crush competition and compete with one another for global market share. These changes could supercharge global inequality as countries that develop applications for AI pull ahead of countries that don’t.
Pundits have warned us for decades that technology will replace blue-collar work. This is only somewhat true since modern AI’s powers of pattern recognition and prediction excel in both cognitive and physical tasks. Physical tasks that require social interaction or manual dexterity, like waitressing, are much less attractive candidates for AI replacement than cognitive tasks that observe a strict structure, such as accounting. Estimates of the percentage of US jobs at risk of partial or total automation range from 9 percent according to researchers at the OECD (Organization For Economic Co-Development) to 38 percent according to PwC. The PwC estimate, however, draws upon more current assumptions about AI’s capabilities in deep learning, a subset of AI that powers advanced applications such as image and speech recognition. Although PwC acknowledges that regulation and corporate inertia will mitigate actual job losses, such sobering statistics should inform our opinions about the future impact of automation on the US labor market.
Given the current pace of development and the intense interest from both the government and the private sector in AI, these changes will take place faster than workers can adapt. They will accelerate trends unique to modern economics, such as the decoupling of wage growth and economic growth, markets with monopolistic tendencies, and extreme inequality. In a world where machines and the people who either build or own them generate the lion’s share of GDP, the fruits of innovation will increasingly accrue to the wealthiest consumers in society. Although this dystopian scenario would produce extreme inequalities within the US, they would likely be dwarfed by those between the poorest countries and the wealthiest. As large pools of untrained labor shed their economic value, poor countries will find that the labor-intensive manufacturing practices that raised millions of Chinese from poverty are no longer competitive in the new global economy.
Extreme wealth inequality can destabilize society, and unless bold measures to address the impact of automation on workers are introduced, our generation may be the first in American history to be worse off than its predecessor. Various redistribution schemes have been proposed to deal with this issue, and by far the most popular is the universal basic income (UBI). This solution has become the signature proposal of presidential candidate Andrew Yang, a Silicon Valley entrepreneur and philanthropist. This idea is simple: every American adult should receive a regular stipend from the government—no strings attached. Proponents argue that in an age of technological turmoil, a guaranteed income will help society avoid widespread poverty and give people displaced by automation the opportunity to reinvent themselves. The measure would be funded with supersized taxes on the massive profits of both tech giants and the traditional companies that successfully transitioned to AI.
While a UBI may seem like a simple and elegant solution to a daunting challenge, it would do little to solve wage stagnation and unemployment despite commanding a hefty price tag (the bill for Mr. Yang’s UBI of $1,000 a month would be $2.8 trillion per year) since the primary goal of UBI isn’t job creation but poverty reduction. While reducing poverty should be a component of any comprehensive plan to combat structural unemployment, the political response should be proactive rather than reactive by embracing job creation as its aim. Steady work provides us with structure, and for many, it remains a powerful source of identity. As such, a UBI would be a poor substitute for regular work.
We should respond to technological unemployment and income stagnation by creating more public sector jobs that demand those skills that are the most difficult to automate: human interaction and tasks that do not require specific parameters to complete. These jobs will not generate the economic value that their pay would merit, but they will keep people gainfully employed in meaningful work and reassure them of their worth as productive members of society. Kai Fu Lee, yet another Silicon Valley entrepreneur and AI expert, endorses this approach. He recommends using this as an opportunity to hire more teachers and improve our current student to teacher ratio. As algorithms become more accurate at making medical diagnoses, we could expand the number of social workers and nurses that mediate between algorithms and patients by adding a human touch. Finally, social entrepreneurs with ideas to solutions to ecological and social problems could receive a boost in funding. Like the UBI, taxes on the winners of the technological revolution would pay for these programs. Unlike UBI, these solutions are investments that generate immediate value that could offset at least part of the cost of funding them. This solution assumes a rapid shift to AI and recognizes that the private sector cannot absorb the full impact of automation unless the government takes an active role in creating jobs that allow society to transition to a skills-based economy at a more reasonable pace.
Despite trade tensions and fears of a global slowdown that are placing downward pressure on the share prices of tech stocks, Big Tech continues to post record-breaking earnings that point to the increasingly critical role they play in driving economic growth. While claims that robots are coming to take our jobs may seem out of touch with reality in light of the current 3.7 percent unemployment rate, progress in AI has consistently outstripped expectations and many applications for AI remain unrealized. An assessment of AI’s future capabilities and current trends in income inequality reveals vulnerabilities within our labor force that may take years to resolve. However, a proactive and far-reaching government response to automation could turn this challenge into a unique opportunity to reaffirm the contributions people can make to society through their work. Everyone should benefit from the futuristic technology that will make life better, not just those with the deepest pockets.