In Japan they call it satori no sedai – the “enlightened generation” — a cohort of young adults emerging from the economic stagnation of the early 2000s who spurn traditional societal expectations around work, careers, family, and consumerism. A less literal translation would be the “resignation generation.”
Other East Asian countries have the same phenomenon with a different name. In South Korea, as noted in a recent piece in The Diplomat, nearly half a million people now fall into the “just resting” category, an entire generation of mainly young people who are neither in nor seeking employment.
In China, poor employment prospects for young people and intense competition for top university places and jobs have spurred the emergence of the “lying flat” generation, who eschew traditional social expectations around work and careers while seeking to reframe the meaning of life success and fulfillment.
This growing sense of detachment undoubtedly has numerous causes: flatlining economic growth, demographic shifts, over-supply of white-collar jobseekers, and broader cultural changes. But one of the most prominent causes is likely to be technological, as ever more powerful AI technologies make inroads into areas of knowledge work traditionally seen as the preserve of humans. Large-language models and AI agents can now carry out tasks as diverse as writing, code generation, marketing, and drug development.
While AI can undoubtedly augment worker skills and increase productivity in some cases, a recent batch of studies points to increased risks of job displacement and reduced earnings in some occupations, sectors, and economies. Such effects are particularly concentrated among younger entry-level professionals and those in higher-paying sectors. According to research by the Bank of Korea, the advent of generative AI has coincided with shrinking youth employment in AI-exposed industries, while more senior jobs have continued to grow.
The response has been a growing debate in South Korea and many other countries about how the fruits of the AI revolution should be divided up. Some prominent suggestions include the creation of sovereign AI funds, a “social solidary wage,” or other ways of distributing the AI profits windfall.
Leaving aside the practicality or desirability of such interventions, a bigger issue is that they would do little to address the loss of meaningful work opportunities that the AI revolution is likely to bring for at least a substantial portion of the workforce.
Put simply, a job is more than just a way of earning a livelihood. For many, perhaps most, people, it is often what gives purpose and structure to their lives. It is wrapped up with their sense of identity. It is no surprise that someone’s line of work is often one of the first questions we get asked upon meeting new people.
And it is this sense of purpose and identity that is most threatened by the blistering speed of AI development. Roles built up over many years of training and experience are suddenly threatened with obsolescence. Economics typically posits re-training for new roles as the solution, but what happens when these new roles are themselves eventually automated? It is notable that software coding, lauded as the career of the future not so long ago, now sits in the eye of the AI automation storm.
Beyond the suggestion of re-training, economics has in fact no real answer to the rootlessness and social dislocations wrought by major technology dislocations. We must turn to sociology instead. In his 1938 classic, “Social Structure and Anomie,” sociologist Robert K. Merton identified the societal strains that ensue when individuals are denied the means to achieve socially required cultural goals, such as a good job and career, to meet society’s expectations of a good citizen.
Individuals who are blocked from achieving such goals, argued Merton, may respond in different ways. One is “retreatism,” similar to the “resignation generation” and “just resting” phenomena noted above, where individuals reject the goals and the means of attaining them. Another is “ritualism,” where individuals persist in their endeavors even while the goals seem ever further out of reach. In South Korea, for example, the proportion of people who see potential for their children to move upward through their own efforts has fallen from 47.7 percent in 2011 to around 30 percent in 2021 – but demand for rigorous tutoring and education remains sky-high nonetheless.
But there is a more positive response to the dislocations identified by Merton: innovation. This is the most fruitful way forward for East Asian countries wrestling with the social dislocation of youth. A starting point would be much greater innovation in educational systems, tilting the focus toward those human skills – critical thinking, creativity, empathy – that are relatively insulated from AI exposure.
However, even greater opportunities lie in the spheres of meaningful work and what occupational psychology researchers call “job crafting,” the extent to which workers are given freedom to shape their work tasks, relations, and overall work context. For example, a warehouse operative might be given scope to suggest changes to floor layouts, or an opportunity to hone selling skills through interactions with customers.
A considerable body of research shows that greater freedom for employees to sculpt work roles is associated with higher levels of engagement, job satisfaction, and performance. In the AI context this could mean workers delegating more routine work to AI so that they can focus on problem-solving or customer relationships, or working alongside AI agents to troubleshoot and reconfigure work processes and operations. Workers could be given an ownership stake in AI agents they work with, reinforcing opportunities for mutual learning over time.
Crucially, higher levels of AI knowledge are likely to amplify effective job crafting, as workers are more likely to understand the strengths and limitations of AI technologies and how they can be integrated into the fabric of work processes. A 2025 study by Chengcheng Sha and Tianlong Chai based on a survey of AI-using workers in China found that existing familiarity with AI tools significantly increased job crafting levels, for example by enabling workers to drop work procedures they find ineffective or re-arrange equipment and the work environment more generally to suit their needs. Of course, such job crafting will be more likely to flourish in environments where companies see AI as a genuine force for long-term worker augmentation, as opposed to a short-term cost-cutting fix.
AI job crafting is likely to appeal significantly to the “resignation generation” and other young people across Asia, who typically are digital natives with high levels of AI awareness, social consciousness, and cultural perceptiveness. Effective job crafting, combined with targeted policy support and business investment, could open up new avenues of meaningful work in sectors such as health and social care, culture, music, fashion, tourism, and many others.
Such an approach will call for substantial changes in organizational cultures, policies and work practices. It means avoiding a headlong rush into AI automation in favor of a harder but more considered route to meaningful AI-infused work. It may involve altering entrenched societal perceptions of worthwhile work and acceptable careers. But that path is likely to yield much greater societal dividends in the long term.
