When Brad Wang started his first job in the tech industry after college, he was struck by how Silicon Valley had transformed the workplace into a lavish environment with game rooms, nap pods, and hiking trails, reminiscent of the opulence of Jay Gatsby's house. However, beneath the glitz, he sensed a certain emptiness. He hopped from one software engineering role to another, often feeling that the projects he worked on were meaningless. At Google, he spent 15 months on an initiative that was doomed to fail, and at Facebook, he spent over a year on a product that even the primary customer deemed unhelpful.
Over time, the futility of his work began to frustrate Mr. Wang: "It's like baking a pie that's going right into the trash can." This sentiment of questioning the purpose of one's work has a long history in the corporate world. During the pandemic, thousands joined the r/antiwork subreddit to vent about the drudgery of their jobs and, in many cases, their rejection of work altogether. The 1990s film "Office Space" famously captured the grind of corporate life, with the sentiment "It's not that I'm lazy, it's that I just don't care." Even earlier, Herman Melville's "Bartleby, the Scrivener" depicted a law clerk who passively resists his boss's demands, eventually leading to his own demise.
The corporate office and its paperwork have a way of turning even ostensibly good jobs, with decent salaries and benefits, into soul-crushing drudgery. In 2013, the late radical anthropologist David Graeber addressed this problem in his essay "On the Phenomenon of Bullshit Jobs." This anti-capitalist polemic, which helped coin the "99 percent" slogan of the Occupy Wall Street movement, went viral, resonating with widespread 21st-century frustration. Graeber's subsequent book delved deeper into the subject, suggesting that the economist John Maynard Keynes's dream of a 15-hour workweek had never materialized because humans have invented millions of jobs that are so useless that even the people doing them can't justify their existence. According to a study by Dutch economists, a quarter of the workforce in rich countries sees their jobs as potentially pointless. If workers find their labor dispiriting and their work adds nothing to society, the argument for maintaining these jobs becomes increasingly difficult to justify.
The rise of artificial intelligence (AI) has heightened concerns about job displacement. A recent estimate by Goldman Sachs found that generative AI could eventually automate activities equivalent to 300 million full-time jobs globally, many in office roles like administration and middle management.
When imagining a future where technology replaces human effort, the common view is that it will either be a productivity boon for businesses or a disaster for workers who become obsolete. However, there is a possibility that lies between these extremes. AI may eliminate some jobs that workers themselves deem meaningless or even psychologically degrading. If this happens, would these workers be better off?
The passage discusses different categories of "useless work" that AI could automate, including "flunkies" who exist to make important people look more important, "goons" hired into roles that only exist because of competitor companies, and "box tickers" whose work could disappear with no real effect. Examples include executive assistants, telemarketers, and software engineers doing tasks that primarily serve to help their bosses get promoted.
While these jobs may lack existential purpose, they have traditionally provided reliable salaries and opportunities for career advancement, especially for those seeking to enter white-collar fields. Economists worry that as these jobs disappear, the replacements may bring lower pay and fewer chances for professional mobility, further hollowing out the middle class.
However, the passage suggests that this disruption could also prompt workers to reevaluate what makes a "good job" and seek out more invigorating pursuits. Technology has historically offset job losses with new job creation, though the specific nature of these new roles is hard to predict.
Ultimately, the passage paints a complex picture of the impact of AI on the labor market. While the displacement of "meaningless" jobs could be psychologically liberating for some workers, it also raises concerns about the broader economic and social consequences. The future remains uncertain, but the passage encourages a nuanced perspective on the potential effects of this technological transformation.
The advent of AI is prompting a "species-level identity crisis," as Mr. Kelly puts it, where people are increasingly questioning the meaning and purpose of their work. Some scholars suggest that the crises brought about by automation could actually steer people toward more socially valuable work.
The Dutch historian Rutger Bregman has started a "moral ambition" movement in the Netherlands, where groups of white-collar workers who feel their jobs are meaningless meet to encourage each other to pursue more worthwhile work. Bregman argues that the focus should not be on finding one's "passion," but rather on identifying what needs to be done.
In the AI era, one of the key tasks that will need to be done is oversight and monitoring of the AI systems themselves. Companies will likely hire "AI babysitters" to edit the work produced by AI and police its tendencies. While this may provide some jobs, there are concerns that these roles will also feel meaningless, as humans end up mindlessly skimming for errors in AI-generated content.
Additionally, AI is poised to automate many jobs that involve human empathy and connection, such as customer service. The new roles created for humans may be drained of the emotional difficulty, but also the attendant joy, of these empathic professions.
Even techno-optimists acknowledge that a certain degree of meaninglessness in work is inevitable. As people are relegated to being "tiny cogs in big systems," they may become increasingly frustrated and seek ways to find meaning, whether through organizing their workplaces, advocating for broader economic solutions, or searching for new roles.
Ultimately, while AI will transform the nature of work, it cannot eliminate people's complicated feelings toward their jobs. As Mr. Wang predicts, the "jobs that exist on selling a vision" may be the hardest to automate, as humans continue to grapple with the deeper questions of purpose and meaning in their work.