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Written by economist Michael Spence for the IMF's Finance & Development magazine, this piece offers a mainstream macroeconomic perspective on AI's growth implications, relevant for understanding governance and policy debates around AI deployment at a global scale.
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Importance: 42/100opinion pieceanalysis
Summary
Nobel laureate Michael Spence examines AI's potential to accelerate global economic growth, arguing that AI could boost productivity and help developing economies close development gaps. The piece addresses both the transformative opportunities and the distributional risks AI poses across different income levels and sectors.
Key Points
- •AI could significantly accelerate productivity growth by automating cognitive tasks and augmenting human decision-making across sectors.
- •Developing economies face both opportunities (leapfrogging) and risks (being left behind) depending on access to AI infrastructure and talent.
- •Labor market disruption is a central concern, particularly for middle-skill workers whose tasks are most susceptible to automation.
- •Policy frameworks and international coordination are needed to ensure AI's benefits are broadly shared rather than concentrated among advanced economies.
- •Investment in human capital, digital infrastructure, and governance institutions is critical to realizing AI's positive economic potential.
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AI’s Promise for the Global Economy Loading component...
F&D Magazine
AI’s Promise for the Global Economy
MICHAEL SPENCE
September 2024
Credit: CFOTO/Future Publishing via Getty Images
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If properly used, it could significantly accelerate economic growth and help productivity growth rebound
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MICHAEL SPENCE is a senior fellow at the Hoover Institution and Philip H. Knight Professor and dean, emeritus, at Stanford Graduate School of Business. In 2001, he was awarded the Nobel Memorial Prize in Economic Sciences.
Opinions expressed in articles and other materials are those of the authors; they do not necessarily reflect IMF policy.
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English русский العربية 中文 français español The postpandemic global economy is beset by slower growth, the most persistent inflation in decades, limited progress on sustainability, and high borrowing costs weighing on investment, including the massive investments needed for the energy transition. Perhaps the strongest headwind, though, is sluggish productivity growth since the global financial crisis.
AI is our best chance at relaxing the supply-side constraints that have contributed to slowing growth, new inflationary pressures, rising costs of capital, fiscal distress and declining fiscal space, and challenges in meeting sustainability goals. And the reason is that AI has the potential not only to reverse the downward productivity trend, but over time to produce a major sustained surge in productivity.
Of course it will take time. Roy Amara’s law applies here as in past episodes of technological transformation: we tend to overestimate the short-run impacts and underestimate the longer-term ones. My best guess (and it is just a guess, based on current patterns of investment) is that we may start to see meaningful impacts in labor productivity by the end of this decade.
All these things result from the collision of three powerful forces.
The first is shocks, including war, pandemic, climate change, geopolitical tensions, resurgent nationalism, and growing focus on national security in the conduct of international economic policy. These increasingly severe and frequent disruptions are shifting global supply networks toward greater diversification and resilience. But that is an expensive pressure and a contributor to inflationary pressures.
For example, Apple is steering more manufacturing to India, which now produces 15 percent of iPhones. Meanwhile, only South Korea and Taiwan Province of China make (as opposed to design) the most advanced semiconductors, an unsustainable arrangement from a national security perspective.
Diversification of sourcing is reinforced by policy initiatives aimed at bringing important supply cha
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