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From Money to Data
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Opinions expressed in articles and other materials are those of the authors; they do not necessarily reflect IMF policy.
Viktor Mayer-Schönberger and Thomas Ramge
Reinventing Capitalism in the Age of Big Data
Basic Books, New York, 2018, 288 pp., $28
Smoothly written and provocative, Reinventing Capitalism in the Age of Big Data is one of those rare pop future books that takes fundamental economics seriously. Nobel laureates from Friedrich Hayek to Alvin Roth don’t just make cameo appearances: their insights drive the book’s arguments. Authors Viktor Mayer-Schönberger and Thomas Ramge argue that the data’s rise means money’s decline, that meaningful economic growth overwhelmingly depends on data innovation, and that regulating market competition requires rethinking data access.
Data are not the new oil but a form of capital much like human, social, and intellectual capital. The authors see data becoming the dominant organizing principle for wealth creation. Markets evolve into platforms enabling valuable new genres of data-rich products, services, and experiences. Fintech supersedes traditional finance. Classical market signals like price descend into anachronism.
“In data-rich markets,” they write, “participants no longer use price as the primary conveyor of information...one of the central tasks that money has played in the economy will be gone.” Money’s role will erode to the point where “(r)ather than equating markets with money and the economy with finance capitalism in which money rules supreme, markets will be understood to surge because of rich data flows (not money). Finance capitalism will be as old-fashioned as Flower Power.”
Big data accelerates the creative destruction of capitalism as we now know it. As data assume petabyte proportions and processing powers continue their exponential rise, Nobel Prize–winning research inspires disruptions. For example, reduced transaction and coordination costs—Ronald Coase’s essential insight into enterprise economics—will inexorably lead to new organizational forms. Machine-learned matching and recommendation algorithms embedding Alvin Roth’s intuitions about market design will deliver superior investment and consumption outcomes. And the human limitations of Herbert Simon’s “bounded rationality” and Daniel Kahneman’s behavioral economics will be algorithmically managed by bots nudging people’s actions.
In other words, rich data should lead to richer—and more efficient—societies. The authors’ vision is more upbeat than cautionary: this book was not written to depress.
To be sure, Mayer-Schönberger and Ramge aren’t Pollyannas. Their proposals for regulating data-
dominant oligopolies are thoughtful. How should data be shared to stimulate greater competition, innovation, and entrepreneurship? Can greater transparency be structured to facilitate greater accountability? The world’s Amazons and Googles will increasingly find themselves struggling to answer. If they can’t, regulators and legislators surely will.
That said, the book champions governance over government. Indeed, the authors celebrate markets. “Eliminate the decentralized market and the empowering quality of data vanishes,” they declare. “That is why we call the shift from money to data a revival of the market instead of the rise of artificial intelligence or the advent of Big Data.”
The book’s singular weakness is an overweening Western bias. The Chinese, Indian, and African ontologies receive only perfunctory review. Possible—
even probable—global clashes of big data’s economic and commercial culture are unexplored. These omissions undermine the authors’ optimism and cheat the serious reader. If future wealth, growth, and living standards depend on data-ism, then it will surely be as much a source of rivalry and competition as collaboration and trade.
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