AI is going to eliminate way more jobs than anyone realizes

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Prepare for the Oncoming Tsunami of Change: AI’s Unpredictable Impact on the Global Economy

Brace yourself for the impending deluge set to cascade upon the world economy.

The ascent of artificial intelligence has held captive our imaginations for decades, both in fanciful films and scholarly texts. Despite these musings, the emergence of accessible and user-friendly AI tools in recent times has jolted us, as if the future arrived well ahead of schedule. Now, this long-anticipated, abrupt technological revolution stands poised to upend the economic landscape.

A March report from Goldman Sachs unearthed a potential disturbance of over 300 million jobs globally, thanks to AI, while the prominent consulting firm McKinsey approximated that around 12 million Americans could pivot to different vocations by 2030. A “tempest of inventive destruction,” akin to the concept espoused by economist Joseph Schumpeter, appears poised to sweep away countless enterprises, simultaneously breathing life into novel industries. It’s not all bleak: Projections suggest that both non-generative and generative AI may contribute anywhere from $17 trillion to $26 trillion to the global economy over the forthcoming decades. What’s paramount is that many lost jobs will find replacement in novel endeavors.

Behold the Archetypal Great Resigner: A Gen Z enthusiast inhabiting the realm of leisure and hospitality, adroitly switching roles in pursuit of superior remuneration and occupational security.

The surge of participants in the Great Resignation shows no sign of subsiding.

While a reduced number of Americans switch vocations compared to a year past — when departures peaked to levels unparalleled since the inception of Bureau of Labor Statistics records over two decades ago — the trend of job-hopping persists more prominently than before the pandemic’s onset.

Given that job vacancies continue to exceed pre-pandemic levels, the Great Resignation may extend its presence in the months ahead. According to a March survey by YouGov, commissioned by Bankrate and involving over 2,400 Americans, 56% of the workforce intends to hunt for new occupations within the next year. This marks an increase from 51% in 2022.

Aspects of the current participants in the Great Resignation, as well as the rewards reaped by joining its ranks, remain unchanged over recent years. However, the landscape has witnessed substantial alterations.

From age demographics to industries of engagement and salary augmentation, the profile of a quintessential Great Resigner has undergone reformation.

The crescendo of this technological surge surges forth, and we stand at the nascent stages of an upheaval that will ripple through labor markets and the global economy. A transformation as influential as the industrial revolution and the advent of the internet appears imminent. While these shifts could elevate living standards, bolster productivity, and accelerate economic opportunities, the rosy prognosis is far from assured. Unless governments, CEOs, and workers engage with a sense of urgency to prepare for this impending upheaval, the AI revolution may herald a tumultuous era.

The advent of AI may catch us off guard, much like the unsuspected onset of the internet.

Predicting the adoption of groundbreaking technologies proves challenging. Take the example of the internet: In 1995, Newsweek published an article titled “Why the Web Won’t Be Nirvana,” arguing against the likelihood of purchasing books and airline tickets online. In the same year, Bill Gates, when questioned by a skeptical David Letterman, fielded the query, “What about this internet thing?” Even three years later, as adoption expanded, economist Paul Krugman audaciously asserted that the influence of the internet would scarcely surpass that of the fax machine. In retrospect, it’s evident that the internet’s repercussions were drastically underestimated.

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Initial skepticism stemmed from the internet’s uneven and gradual impact, which later surged as a broader populace grasped its functioning. As Erik Brynjolfsson, a Stanford University economist specializing in innovation, asserted, “The rule for exponential curves is that they change the world slowly at first, and then suddenly.”

The arrival of AI introduces analogous uncertainties, yet the trajectory of growth manifests with accelerated clarity. In 2017, McKinsey foresaw the advent of robust large language models like GPT-4 by 2027. Yet, they have already come into existence. Overnight, OpenAI’s generative AI became an integral facet of Microsoft’s offerings. In a span of mere months, corporate behemoths such as Amazon, AT&T, Salesforce, and Cisco eagerly integrated enterprise-grade AI tools. McKinsey’s recent report projects that approximately half of today’s work tasks could undergo automation between 2030 and 2060. Their best-guess timeline for this transformation, previously set for 2045, has been hastened by almost a decade. A whirlwind of change is upon us. As adoption escalates, so shall the downstream ramifications of this technology. The World Economic Forum posits that over the next five years, AI could render 83 million jobs obsolete while simultaneously generating 69 million new positions — leaving 14 million jobs in limbo. Even those retaining their positions will grapple with a substantial shift in how they execute their tasks; the World Economic Forum anticipates that 44% of core worker competencies will undergo transformation within the next five years.

Mass unemployment seems unlikely. However, mass disruption is plausible, asserts Stanford economist Erik Brynjolfsson.

Prior automation waves primarily impacted low-skilled laborers. With generative AI, however, even educated and highly skilled workers, hitherto immune to automation’s influence, confront vulnerability. According to the International Labor Organization, the global cohort of knowledge workers, ranging from 644 million to 997 million, constitutes 20% to 30% of total global employment. In the United States, this knowledgeable workforce encompasses nearly 100 million individuals — a staggering one out of every three Americans. Occupations spanning diverse domains such as marketing, software engineering, research and development, accounting, financial consultation, and writing teeter on the brink of automation or metamorphosis.

This does not entail a surge of unemployed individuals desperately seeking employment. AI will ultimately lead to net job creation, with some seemingly imperiled roles experiencing growth in demand. Case in point: ATMs expanded the horizons of bank teller employment.

“I do not think we’ll see mass unemployment,” opines Brynjolfsson, who envisions AI disseminating at a pace swifter than other ubiquitous technologies. “But I do think we’ll see mass disruption, where wages for certain roles dwindle while others surge. The landscape will shift, heralding demand for distinct skill sets. A comprehensive reallocation of labor and reskilling awaits.”

This transition shall be so monumental that the vanishing of several roles may pass unnoticed. Just as the industrial revolution rendered the role of human alarm clocks obsolete, AI’s advance will consign certain positions to historical oblivion.

Although protracted mass unemployment remains unlikely, the short-term transition promises turbulence. Should a quarter of tasks across diverse U.S. vocations succumb to AI automation, and one-third of worker responsibilities witness replacement, a mere fragment of the expansive white-collar workforce experiencing job loss or transition could precipitate dire consequences for the broader economy. This monumental reshuffling underscores the necessity for governmental and corporate preparedness. The Organization for Economic Co-operation and Development, in its most recent employment outlook, asserts that proactive measures are indispensable to navigate this AI revolution.

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The Enigma of Productivity Surge

In 1987, economist Robert Solow famously quipped, “You can see the computer age everywhere but in the productivity statistics.” Solow’s “productivity paradox” spotlighted a confounding aspect of the nascent computer age. Despite substantial investments in information technology and computing power, ostensibly aimed at heightening worker efficiency, official data indicated a lack of increased output per hour.

Robert Gordon, a macroeconomist and self-proclaimed “prophet of pessimism,” provocatively posited that unimpressive productivity figures evidenced contemporary technology’s relatively modest radicality, implying that advanced economies had hit a point of stagnation. The most pivotal technological marvels — think the car or the toilet — have already graced our existence, Gordon contended, while subsequent advancements only marginally improved productivity. A similar argument postulates that the rate of innovation is dwindling.

While these viewpoints may appear compelling, the case for AI’s potential to yield rapid productivity gains is strong. The mass adoption of the internet necessitated software, network protocols, infrastructure, and devices, resulting in a gradual proliferation of computers and internet access.

In the case of AI, the adoption trajectory stands to accelerate given the preexisting technological foundation. Furthermore, unlike the hyped cycles surrounding crypto or the metaverse, AI approaches maturity. User experience remains uncomplicated, practical applications already exist, and millions have seamlessly integrated the technology into their daily workflows. Corporations are progressively embracing this evolution.

AI’s transformative potential is magnified when layered upon existing technology. Just as the convergence of the internet, GPS, and smartphones revolutionized the world, AI married to preexisting tech can unlock exponential progress. Laser weeders empowered by AI, GPS, and tractor technology are now capable of scanning fields to eradicate weeds, obviating the need for herbicides or labor-intensive weeding teams. AI embedded within advanced imaging tools holds the promise of revolutionizing cancer diagnosis and treatment.

If the internet flattened the world, AI propels it into high-speed mode. A recent study headed by Brynjolfsson assessed the productivity of over 5,000 customer-service agents employing generative AI. Encouragingly, call-center operatives exhibited a 14% surge in productivity, while novices experienced up to a 30% spike. MIT research revealed that generative-code-completion software expedited software developers’ tasks by 56%, and yet another study affirmed that generative AI facilitated professional-document writing by 40%.

Cumulative small and substantial increments in productivity across myriad industries form the crux of AI’s growth trajectory. Goldman Sachs speculates that generative AI’s influence over a decade could elevate annual U.S. labor-productivity growth by nearly 1.5 percentage points — akin to the boost prompted by prior transformative technologies like electric motors and personal computers. Such an upswing could yield an annual 7% surge in global GDP, contributing $2.6 trillion to $4.4 trillion to the worldwide economy, a sum commensurate with the UK’s economy.

Brynjolfsson, a “mindful optimist,” exudes confidence in the cumulative nature of these productivity gains, asserting that they will be discernible in official statistics. He wagers with pessimist Gordon that productivity growth will surpass the Congressional Budget Office’s projected 1.4% annual increment. “I think it’s going to be closer to double that,” he ventures.

While productivity projections illuminate heightened efficiency within firms, they also assume the reemployment of displaced workers. As productivity escalates, economic output and GDP are bound to rise, ushering in a virtuous cycle where companies expand operations to meet augmented demand, consequently spurring job creation. Moreover, augmented labor-productivity growth correlates with enhanced real incomes, a boon for workers and households alike. In essence, technological innovation, despite displacement, ultimately benefits workers in the long term. Economist David Autor and his collaborators cite that 60% of contemporary occupations did not exist 80 years ago, demonstrating an 85% employment growth engendered by technological innovation.

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Charting a Future-Proof Course: Swift and Intelligent Adaptation

While these prospects are heartening, the upheaval accompanying the AI revolution cannot be ignored. The rapid stride of AI advancement and integration distinguishes this transition from prior industrial revolutions. The scenario is not as straightforward as textile laborers yielding to mechanized looms; workforce reconfigurations span diverse occupations and degrees of intensity. This pace of transformation is poised to outstrip any adjustments in education and workforce readiness.

America’s antiquated workforce education system is ill-equipped to address the exigencies of modern workers, let alone contend with the impending AI revolution. Maria Flynn, CEO of the think tank Jobs for the Future, decries the U.S.’s disjointed assortment of programs, which lack cohesion. A mere 43 federal employment-training initiatives, with a collective budget of $20 billion, represent less than 0.1% of the $25 trillion GDP and the workforce comprising over 150 million individuals.

To mitigate the labor-market disruption’s impact, the U.S. must promptly invest more in its workforce. One potential approach involves emulating Denmark’s “flexicurity” model of job security and retraining, a system designed to stave off structural unemployment by enabling employers to release workers, coupled with robust support for those laid off. This program provides up to two years of unemployment benefits, reaching as high as $2,860 per month, in tandem with personalized job counseling and retraining opportunities. This approach has significantly curtailed unemployment duration for Danish workers compared to peers in similar economies.

The U.S. once instituted a comparable program, the Trade Adjustment Assistance program, launched in 1974 and overseen by the Department of Labor, aimed at workers impacted by foreign trade and production shifts. Flynn highlights the program’s entitlement nature, ensuring that qualifying workers displaced due to trade shifts received income and retraining support. An expansive, well-funded initiative tailored to the AI labor-market transformation could help alleviate workforce turbulence. Such an initiative could offer relocation grants and wage insurance to bridge income gaps for individuals transitioning to lower-paying positions.

The U.S. could take inspiration from Singapore for retraining in an AI-driven economy. In Singapore, individuals above the age of 25 receive $500 in credits to access a diverse range of courses spanning data science to business. Additionally, a collaborative public-private retraining initiative ensures that skills training aligns with employers’ job classifications. Annually, over 660,000 people tap into Singapore’s national retraining program. For those concerned about lagging productivity, these large-scale education and training enhancements hold promise in mitigating workforce transition gaps. Thanks to Singapore’s efforts, the nation has propelled its annual labor-productivity growth rate to a commendable 3%.

However, public-sector policies necessitate parallel private-sector investment in retraining. An MIT survey of workers indicates that 50% of respondents have received formal skills training from their employers. Encouraging retraining through tax credits, similar to programs in New York and Georgia, could incentivize employers to act and ensure a workforce adequately prepared for the AI revolution.

Technology cannot be uninvented — disruptive catalysts such as AI demand proactive adaptation. Safeguarding workers against significant shocks requires acknowledgment that this technological wave might temporarily displace a significant proportion of the workforce or, alternatively, facilitate a smoother transition into calmer waters.