What we commonly refer to as “artificial intelligence” is, in practice, a suite of data-driven systems. These technologies are already transforming nearly every aspect of human life, giving rise to innovative business models and reorganizing entire economies. Over time, they promise to create new jobs, boost productivity and provide tools that expand cognitive capacities, ultimately redefining the very meaning of work.
But alongside these undeniable benefits, the digital revolution and the rapid expansion of data-driven systems are altering labor markets, education and professional training. The consequences are increasingly evident: precarious working conditions determined by algorithm-based platforms, a sustained downward pressure on wages and a structural mismatch between the needs of economies and the training of workers.
“L
a digital revolution and the rapid expansion of data-driven systems are reshaping labor markets, education, and professional training. The consequences are increasingly evident“This raises a crucial question: will the growing use of data-driven systems render paid professional work obsolete? We are often reminded that every technological advance has sparked fears of mass unemployment, and each time those fears have proven unfounded. Yet it is possible that the historical pattern no longer holds.
Past transformative technologies were largely designed to make human work more efficient or physically less demanding. Data-driven systems, by contrast, are often explicitly designed to eliminate humans from the value chain altogether. And, unlike previous technological revolutions, these systems do not limit themselves to routine or low-skilled work. They are expanding into areas once considered exclusive to humans: medical diagnosis and surgery, legal analysis, and cultural production.
The breadth and speed of current data-driven systems call into question the usual claim that technological innovation has always created more jobs than it has destroyed. In fact, no historical law guarantees that technological change must always generate more paid work for people. On the contrary, emerging evidence suggests that data-driven systems are eliminating entire professions faster than new ones can emerge.
Undoubtedly, fewer working hours and more leisure are not inherently bad. A society liberated from excessive work could, in fact, be more humane. The danger does not lie in the loss of work per se, but in what disappears with it: wages, the tax base that sustains public goods, and the non-economic functions that paid employment plays in people’s lives, such as providing a sense of purpose, identity and camaraderie.
“
D⟨as fewer people are needed to generate economic value, policymakers must recognise the impact of data-driven systems on the labor market“As fewer people are needed to generate economic value, policymakers must recognise the impact of data-driven systems on the labor market. What is at stake is nothing less than the long-standing commitment of countries to maximize employment. Urging workers to retrain and upgrade their skills for a job market that may no longer exist places responsibility on people for changes they cannot control, when what is needed is a policy framework that matches the scale of disruption.
In a new book, I propose a concrete framework to seize the ethical opportunities of the current technological transformation and, at the same time, limit its risks. In essence, the SERT model (Society-Entrepreneurship and Time for Research, as abbreviated in English) aims to decouple income from work without making that separation unconditional.
Five Keys for a New Income System
The SERT model rests on five pillars. The first is a tax-financed universal basic income, designed to meet basic physical survival needs while preserving a life of dignity and the respect for human rights.
The second pillar is a conditional decoupling of income from work. In exchange for a basic income, each person would contribute a defined amount of “social time” or socially valuable work. Like the Swiss Civil Service, which has successfully served for nearly three decades as an alternative to military service, people would be free to choose from a broad range of activities. The administration of the SERT model would be predominantly digital, leveraging data-driven systems and, where appropriate, blockchain technology, to document each person’s participation in social time.
“Ensuring dignity for everyone does not depend on merely overcoming scarcity but on distributing resources fairly”
Third, during their social time, people should be able to experience some or all of the non-economic functions provided by paid work, such as social recognition, daily structure and a sense of purpose.
Fourth, the SERT model creates strong incentives for education, research, innovation and entrepreneurship. Commitments in these areas would reduce the required social time or, in some cases, exempt people from it altogether.
Finally, as value creation becomes more efficient and wealth grows, the central question becomes how to share those gains. Ensuring dignity for all does not depend on overcoming scarcity, but on distributing resources fairly. This would require a globally coordinated taxation that shifts the burden from labor to capital by taxing data flows, the volume of data and the use of data-driven systems.
Allowing data-driven systems to replace human workers without a collective response would exacerbate inequality and entrench injustice, risking political instability and undermining social cohesion. If adopted, the SERT model offers a path toward shared prosperity and a more stable, peaceful future.
© Project Syndicate, 2025.
In collaboration with the “la Caixa” Foundation
