Work in the Next Economy

AI, responsibility, and operational efficiency.

Next:Economy Newsletter Cropped image by BIG ALBERT on Flickr   Do layoffs improve operational efficiency? Ever since the Fed started raising interest rates in early 2022, ending an era of "cheap" money, companies have been focusing more energy on controlling immediate costs, even when doing so may not be in their best interests long term. To wit, here's Bloomberg on a recent trend in earnings calls: Transcript mentions of "operational efficiency" are at the highest ever in the US during this earnings season as companies focus on expense discipline, but also invest in technologies "that can drive future productivity like AI," a team led by Michael Wilson wrote in a note. There is a notable overlap among the industries discussing operational efficiency most prevalently and those that are discussing AI, the strategists said. These groups include software, professional services, health care services, and financial services. Many of these companies are using their quest for "operational efficiency" to justify layoffs—260,000 employees in 2023, with 2024 already off to a bad start. But as Bloomberg columnist Sarah Green Carmichael argues, such "periodic downsizing" is unnecessary—and detrimental to creating long-term value, calling it " a perfect example of a widespread yet deeply corrosive business practice ." Among layoff survivors, morale and engagement sink and turnover increases. Researchers estimate these effects linger for about three years, when another layoff will likely come along. And downsizing rarely has the hoped-for financial effect. Profitability suffers, as do measures of innovation, quality and safety. Although investors may greet layoffs with higher stock prices for a day or two, in the long run, layoffs are associated with flat or declining share prices, particularly when they don't reflect a shift in corporate priorities. Business leaders sometimes have to make tough calls, and that includes overseeing layoffs (hopefully as a last resort). But inefficiencies can be found in all sorts of places. And as Sandra Sucher and Marilyn Morgan Westner note in Harvard Business Review, " Layoffs negatively impact companies in real but hard-to-measure ways ," including by overworking and diminishing the morale of remaining employees, thereby reducing the impetus toward innovation. + The recent flurry of layoffs in the tech industry may be just an "instance of social contagion," as Stanford business professor Jeffrey Pfeffer puts it. But as Matthew Yglesias recently pointed out in his Slow Boring newsletter, "Lots of people lose jobs even in a 'good economy.'" (He also stresses that despite the newsprint devoted to the topic, "the overall volume of layoffs was below average " for 2022 and 2023.) And as Yglesias makes clear, the inevitability of layoffs is proof that we still need a "social safety net" to support those who are unlucky enough to lose their jobs: "The economy is not, in fact, a rising tide that lifts all boats: It's a tide that rises on average, but with a ton of unpredictable individual variation that we can smooth out with public policy." + Bloomberg's reporting above also underscores how intertwined the topics of AI and layoffs have become, even if businesses aren't framing current job cuts as an outcome of AI. + More from Bloomberg: "Employers Want to Fire Workers Without Getting Shamed on TikTok."   What about returning to the office? Operational efficiency may rule the day, but it isn't necessarily improving employees' actual day-to-day. Companies' increasingly insistent demands that employees "return to office" have made this disregard abundantly clear—despite the fact that, according to a recent study by the Federal Reserve Bank of San Francisco, "the Covid-induced shift to remote and hybrid working arrangements has not had any material impact on productivity growth." Another argument in favor of hybrid and remote work: " New research from the Katz Graduate School of Business at the University of Pittsburgh suggests that office mandates may not help companies' financial performances, but they can make workers less satisfied with their jobs and work-life balance." Stanford economist Nick Bloom recently took to X to sum up the results: 1) RTO mandates are more likely in firms with poor recent stock performance, and in those with powerful male CEOs. 2) Glassdoor data finds RTO mandates significantly reduce employee ratings for job satisfaction, work-life balance and senior management. 3) There is no significant impact of RTO mandates on either firm profitability or firm stock-returns. My interpretation is that RTO mandates are often a response to poor recent company performance, perhaps adopted by under-pressure CEOs. These RTO mandates upset employees, but do not appear to yield performance benefits in return. + From the New York Times: "Are We in a Productivity Boom? For Clues, Look to 1994." + More from the Times: "Can America Turn a Productivity Boomlet into a Boom?" + From Bloomberg: "Job Cuts Are Sending a Chill Through the Remote Work World."   Could AI restore the middle class? The current crop of layoffs and demands to return to the office are "solutions" to short-term problems precipitated by the global pandemic. But larger challenges loom. The Economic Innovation Group warns of an "aging U.S. population" in which soon, one out of every five Americans will be senior citizens. Not only will this burden social programs like Social Security and Medicare, but innovation will suffer as the labor force dwindles. And that's not even taking into account the precarious financial circumstances much of the workforce faces: a new Washington Post poll found that only " just over a third of U.S. adults have the financial security to meet [a widely agreed-upon definition of 'middle class']." Many would add AI to this list of urgent concerns—we mentioned above that CEOs expect AI to shrink their workforces, and the IMF cautions that "almost 40 percent of global employment is exposed to AI." But Massachusetts Institute of Technology economics professor David Autor argues that this needn't be the case. The reason is expertise: Expertise is the primary source of labor's value in the U.S. and other industrialized countries. Jobs that require little training or certification, such as restaurant servers, janitors, manual laborers and (even) childcare workers, are typically found at the bottom of the wage ladder. . . . The unique opportunity that AI offers humanity is to push back against the process started by computerization—to extend the relevance, reach and value of human expertise for a larger set of workers. Because artificial intelligence can weave information and rules with acquired experience to support decision-making, it can enable a larger set of workers equipped with necessary foundational training to perform higher-stakes decision-making tasks currently arrogated to elite experts, such as doctors, lawyers, software engineers and college professors. In essence, AI—used well—can assist with restoring the middle-skill, middle-class heart of the U.S. labor market that has been hollowed out by automation and globalization. Autor explores a range of studies and analogies to make the case that "AI could help rebuild the middle class" by increasing productivity and innovation—but doing so by augmenting the capabilities of workers and extending their expertise, not displacing them. But getting there isn't a given, he explains; it will require that we take a different path from the one currently on offer from companies like OpenAI (and, we would argue, from the market forces that animate many of their decisions). "The question," Autor explains, "is not whether we will have jobs—we will—but whether these will be the jobs we want." + As labor critic Hamilton Nolan pointed out in his newsletter, ​​How Things Work, businesses won't "be convinced to do these things via appeals to their better nature": "It doesn't matter how much more productive work forces become," he argues. "Their productivity does not change the logic that says that the greatest benefit for investors can be had by minimizing labor costs while extracting the maximum amount of work." As I've said, we need to rewrite the algorithms that shape our society if we want to create a more human-centered future. (More on creating that future below.) + From Harvard Business Review: "Is GenAI's Impact on Productivity Overblown?" + From CNN: "We May Not Lose Our Jobs to Robots So Quickly, MIT Study Finds."   How will AI affect corporate responsibility? Like every other company, O'Reilly Media has been navigating the tumult of the last few years, but we're trying to ensure we're doing so in a way that doesn't simply maximize short-term value. In a just-published article, "Corporate Responsibility in the Age of AI," O'Reilly president Laura Baldwin and VP of content strategy Mike Loukides ask, "How would corporations behave if their goal were to make life better for all of their stakeholders?"—a task even more crucial as AI comes to dominate the Next Economy: A company has many stakeholders—not just the stockholders, and certainly not just the executives. These stakeholders form a complex ecosystem. Corporate ethics is about treating all of these stakeholders, including employees and customers, responsibly, honestly, and with respect. It's about balancing the needs of each group so that all can prosper, about taking a long-term view that realizes that a company can't survive if it is only focused on short-term returns for stockholders. . . . Our corporate values demand that we do something better, that we keep the needs of all these constituencies in mind and in balance as we move our business forward.   What do Vesuvius and fur trappers have in common? We'll end on a high note, with two projects that illustrate just how AI is already extending expertise to expand our understanding of the world. And interestingly, they both come from the field of history. You may have read about the Vesuvius Challenge, a project dreamed up by investor and former GitHub CEO Nat Friedman to spur the AI community to help decipher the Herculaneum scrolls—which they did to great success. But Wilfrid Laurier University history professor Mark Humphries's work translating 18th-century letters regarding the fur trade probably flew under your radar. Both are compelling examples of how AI will augment workers and make them more productive. And while the results of the Vesuvius Challenge may at first glance appear more monumental (using AI to read burned scrolls without unrolling them is quite impressive), Humphries's project—using AI to better manage information—is more in line with how a great many jobs could use AI to actually improve operational efficiency in the future.   —Tim O’Reilly and Peyton Joyce This message was sent to alexvarboffin.abbb@blogger.com. You are receiving this because you've signed up to receive email from us. Privacy Policy | Unsubscribe From All | Unsubscribe From Next:Economy O'Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA, 95472 (707) 827-7000