How to Treat the Data Economy Like a Utility | 7wData

How to Treat the Data Economy Like a Utility | 7wData

The rise of the “data economy” rightly makes people nervous. From political propaganda to scandals involving personal data, companies like Google, Apple, Facebook and Amazon have not exactly covered themselves with glory. Politicians and others have grown more and more concerned about how the data economy is becoming monopolistic and exploiting workers, and several Democratic presidential candidates have proposed using the tools of monopoly regulation to break up the Silicon Valley giants. These efforts are commendable but ironically may not be ambitious enough.

Regulating the digital economy will mean not only assuring competition, but also actively incentivizing ways it serves the common good. New data-intensive firms have tremendous potential to transform the economy. But so far, their effect has been negligible. American productivity is slowing and whatever benefits productivity brings has not returned to workers. To fully realize the potential benefits that this industry may bring, we need to treat it like what it most resembles — a utility. The utility approach to regulating data firms opens a vista of possibilities to create a new economic ecosystem that serves the public good while assuring economic growth.

At first glance, the challenges of regulating data-intensive industries might seem unprecedented and daunting. Data, unlike many other commodities, has huge network effects and returns to scale. Our individual information is valuable but not as valuable as the aggregated information of many users. “Big data” allows developers to sharpen predictive and analytic tools and could eventually be the fuel upon which giant leaps in artificial intelligence is developed.

There are harms that come with this segmented platform ecosystem. First, developers are reliant on one or another platform for inputs restricting the interoperability of systems. As a result, large platform companies can then either acquire or compete with their customers. This is common enough that developers have termed it “the kill zone.” Indeed, despite tales of Silicon Valley entrepreneurship, new business creation is down and many technology startups are sold to major firms.

While these arrangements are good for some individual entrepreneurs who are well compensated for selling their firms, it is bad for competition and the larger economy. This might be the answer to the infamous “productivity puzzle” — the question of why, despite massive technological advances, productivity has slowed. Instead of diffusing productive advances across industries, platforms with large network effects force other firms to rely on their standards and environments to deploy technology.

We are faced with a dilemma. On one hand, big data requires scale and uniformity that fits a large network better than many small silos. However, this same effect is also responsible for an inequitable, politically opaque and ultimately inefficient structure for a vital new industry. The good news is that we’ve been here before, and we have the tools to solve these issues. The creation of utilities, or publicly authorized and specially regulated monopolies, is a cornerstone of American anti-trust law seen by the original progressives as a powerful tool with which to combat rent-seeking but “natural” monopolies.

The progressive era also offers us an example of a general-purpose technology that mirrors data and AI: electricity.

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