AI capabilities have been relentlessly improving across a variety of benchmarks. And in November 2022, a new chapter in this story began. ChatGPT became the fastest-growing consumer app of all time. Soon after, a wave of similar AI systems – Claude, Gemini, and Grok – followed, each built in a similar spirit with rapidly improving capabilities. Understandably, a surge of interest – both excitement and alarm – has accompanied this ongoing surge of technological progress.
In this essay, Yoshua Bengio argues that transformative AI creates three new categories of catastrophic risk—destructive chaos from weak actors, concentration of power among strong actors, and the loss of control to rogue AIs. Only if we recognize the global…
AI capabilities have been relentlessly improving across a variety of benchmarks. And in November 2022, a new chapter in this story began. ChatGPT became the fastest-growing consumer app of all time. Soon after, a wave of similar AI systems – Claude, Gemini, and Grok – followed, each built in a similar spirit with rapidly improving capabilities. Understandably, a surge of interest – both excitement and alarm – has accompanied this ongoing surge of technological progress.
In this essay, Yoshua Bengio argues that transformative AI creates three new categories of catastrophic risk—destructive chaos from weak actors, concentration of power among strong actors, and the loss of control to rogue AIs. Only if we recognize the global nature of these risks, he explains, and manage transformative AI as a global public good, will our societies be able to flourish alongside this technology in years to come.
How can we prepare the next generation for work in the age of transformative AI? In this biographical essay, Avital Balwit draws on her experience at a frontier AI company to provide practical career advice to those thinking about the future of work. Our traditional approach to reskilling will not be sufficient—and Balwit sets out what will be required in its place.
Many observers fear that the pursuit of transformative AI or artificial general intelligence (AGI) presents a challenge to the existing global order. Their worry is that the US and China, the two global leaders in AI, are now locked in a destructive race to build the most capable version of the technology, which could lead to unintended consequences and global instability.
TAI would make us collectively more prosperous than ever before. But how will we share that prosperity if our traditional way of doing so, paying people for the work that they do, is less effective than in the past? In this paper, the authors make the case for “universal basic capital,” or UBC, a policy that would foster an ownership stake for all in this increasingly powerful technology.
How can we respond to the impact of transformative AI on the labor market? In this essay, Ioana Marinescu sets out a two-tiered response, recognizing the immense uncertainty about what lies ahead: “adjustment insurance” to help workers who suffer transitory job losses, and a “digital dividend” to support those who might find themselves more permanently without work. Importantly, the latter can be scaled up and down, as we learn more about the challenge we face.
Transformative AI will not only disrupt the labor market, but also the foundations of fiscal stability. As value creation shifts from labor to capital, Anton Korinek and Lee Lockwood explain, traditional tax systems, built on taxing the former, will no longer be fit for purpose. Instead, they set out a framework for an alternative tax system, one that is built for the economy of the future, an age of TAI, rather than the one of the past, an age where human labor sat at the center of economic life.
Transformative AI may make us more collectively prosperous than ever before, yet there is no iron law that says societal well-being must rise along with it. In this essay, Betsey Stevenson argues that a successful transition to a world with TAI requires us to engage with three problems—how ordinary people can seek a better life if human work is devalued or displaced, how valuable resources will be distributed, and where people will get meaning and purpose. If we get the policy response right, we do not need to fear a world with TAI.
Transformative AI will generate a genius supply shock: abundant, cheap, and fast agents that can outperform human beings across many domains. But society is likely to adapt too slowly to this remarkable but unfamiliar new capability. In this essay, the authors explore two policies—regulatory sandboxes and regulatory holidays— that can help companies, regulators, and individuals learn how to use these powerful new tools and put them to effective use.
Transformative AI will transform how society produces and shares information. As Joseph Stiglitz and Màxim Ventura-Bolet argue, it could drive innovation by processing knowledge faster and more efficiently, even generating new questions and insights. Yet it may also erode the supply of reliable information, amplify mis- and disinformation, and leave corrective efforts underprovided. The authors present a framework to understand these informational challenges and outline practical policy responses.
As AI continues its advance, our financial systems stand on the brink of transformation. In this essay, the authors warn that the same technology that promises to enable frictionless trade, real-time modeling, and inclusive ownership could also accelerate inequality, market manipulation, and financial instability. We need to pay more attention, they argue, to how transformative AI will overhaul not only production, but trade and investment as well.
Will transformative AI bring prosperity or disorder? This essay presents a new typology of past technological revolutions—from the Industrial Revolution to the information age—defined by their impact on market structure and labor. Applying this framework to the AI era, the author analyzes four potential futures (Titan’s Dominion, Copilot Empire, Disruption Swarm, and Promethean Fire) and identifies five priorities for steering outcomes toward broad-based prosperity through policies spanning tax, innovation, competition, AI governance, and infrastructure.
Transformative AI has revolutionary potential. But Gabriel Unger argues that whether we can fulfill it, and turn around decades of dissatisfaction, depends on answering three fundamental questions. Can we articulate a compelling shared vision of a future with TAI? Can we settle on a theory of economic growth and AI that allows us to think seriously and carefully about the effect of the latter? And can we redesign education and strengthen social connections in the age of TAI? These are new intellectual opportunities for the economics profession.
A common fear is that transformative AI might concentrate power among a few companies and individuals. Despite its promise, TAI might then leave ordinary people worse off. In this essay, Susan Athey and Fiona Scott Morton explore this problem, noting that while TAI could deliver productivity gains to consumers through lower prices or better products, such outcomes aren’t guaranteed. They propose policy measures, focused on protecting market competition, to ensure TAI’s benefits are broadly shared.
How do we share prosperity in society if work no longer sits at the center of people’s lives? In this essay, Anna Yelizarova explores one provocative possibility: a “global dividend.” If transformative AI shows little respect for national borders, with effects that spill across countries, then we need a global mechanism that is capable of sharing prosperity out across those borders as well. The idea has precedents—but the practical challenge of implementing it would be immense.
How should we govern transformative AI? In this essay, Nick Bostrom argues that an open global investment (OGI) approach—private ventures open to international shareholding and operating within a government‑defined framework—offers advantages over blueprints like the Manhattan Project, CERN, or Intelsat, especially on short timelines. While no model is perfect, OGI appears more inclusive, incentive‑compatible, and practical, and is compatible with further international agreements where feasible.
A global race for transformative AI is underway, defined by intensifying competition between the United States and China. How should we think about these dynamics? In this essay, the authors use game theory to add clarity to the nature of the race and to draw practical policy implications. Competition is not inevitable, they argue, but a shift to cooperation is not automatic, nor easy.
Many observers fear that the pursuit of transformative AI or artificial general intelligence (AGI) presents a challenge to the existing global order. Their worry is that the US and China, the two global leaders in AI, are now locked in a destructive race to build the most capable version of the technology, which could lead to unintended consequences and global instability. But in this essay, the author explores an alternative path for the US and China, one where these countries go “beyond rivalry,” and sets out how this more hopeful, cooperative outcome might be achieved.
The Essays