On July 29, the heads of Amazon, Apple, Facebook and Google testified (virtually) in front of the U.S. House Judiciary Committee’s antitrust subcommittee to defend their dominant market positions in advertising (Facebook and Google), in e-commerce (Amazon) and in applications (Apple).
The hearing was part of the subcommittee’s 13-month investigation of Big Tech’s market power and anti-competitive practices.
Remarkably, the next day, the four companies announced stellar quarterly financial results, beating analysts’ expectations. While the economy tanked because of the pandemic, the four companies reported a combined profit of US$28.6 billion in the second quarter.
As a group, their market value is now around US$5 trillion, making them the most valued companies in the world.
Traditional antitrust measures are not a feasible solution for taming Big Tech’s market power in the data-driven economy. This is because they do not address the source of these firms’ power: data.
An effective way to create a more competitive data-driven economy is to make user data easily accessible to anyone with a legitimate purpose. Data usage may be controlled by a strict regulatory regime modelled on securities regulation that protects the integrity and anonymity of publicly available data.
Bigger, richer, more powerful
The networks these firms provide and the data they collect make them the best at selling access to consumers. If all your friends are on Facebook, you have to be on the platform if you want them to see what you’re doing and thinking and vice versa. If Amazon is where you can find the most products to buy online, that’s where you’re going to shop.
It’s also where merchants are going to want to sell their products to you. You want to search for something on the web, you go to Google, because everyone uses Google.
As the number of people using online products and services grows, companies collect larger amounts of data about them, their preferences and their behaviour. This translates to a more tailored experience to meet people’s specific needs, wishes and interests, which leads to more people joining the network and further data generation.
More people and data mean more money, which means more acquisitions of potential competitors or their technology, thereby adding further people and data to a network.
Taming Big Tech’s power, restoring competition
Traditional antitrust approaches such as breaking up Big Tech firms and preventing potential competitor acquisitions are never-ending processes. Even if you break them up and block their ability to acquire other, smaller tech firms, Big Tech will start growing again because of network effects and their data advantage.
And how do we know when a tech firm is big enough to ensure competitive markets? What are the size or scope thresholds for breaking up firms or blocking mergers and acquisitions?
A small startup acquired for millions of dollars can be worth billions of dollars for a Big Tech acquirer once integrated in its ecosystem. A series of small acquisitions can result in a dominant position in one area of the digital economy. Knowing this, competition/antitrust authorities would potentially have to examine every tech transaction, however small.
Not only would this be administratively costly or burdensome on resources, but it would also be difficult for government officials to assess with some precision (and therefore legitimacy), the likely future economic impact of an acquisition in a rapidly evolving technological environment.
Open data access, level the playing field
Given that mass data collection is at the core of Big Tech’s power as gatekeepers to customers, a key solution is to open up data access for other firms so that they can compete better.
Anonymized data (to protect an individual’s privacy rights) about people’s behaviour, interests, views, etc., should be made available for free to anyone wanting to pursue a commercial or non-commercial endeavour. Data about a firm’s operations or performance would, however, remain private.
Using an analogy from the finance world, Big Tech firms act as insider traders. Stock market insiders often possess insider (or private) information about companies that the public does not have. Such individuals then have an incentive to profit by buying or selling shares in those companies before the public becomes aware of the information.
Big Tech’s incentives are no different than stock market insiders. They trade on exclusively available private information (data) to generate extraordinary profits.
Continuing the finance analogy, financial securities regulators forbid the use of inside or non-publicly available information for personal benefit. Individuals found to illegally use such information are punished with jail time and fines.
They also require companies to publicly report relevant information that affects or could significantly affect their performance. Finally, they oblige insiders to publicly report when they buy and sell shares in a company in which they have access to privileged information.
Transposing stock market insider trading regulation to Big Tech implies that data access and use should be monitored under an independent regulatory body — call it a Data Market Authority. Such a body would be responsible for setting and enforcing principles, rules and standards of behaviour among individuals and organizations in the data-driven economy.
For example, a Data Market Authority would require firms to publicly report how they acquire and use personal data. It would prohibit personal data hoarding by ensuring that data is easily portable from one platform, network or marketplace to another. It would also prohibit the buying and selling of personal data as well as protect individuals’ privacy by imposing penalties on firms and individuals in cases of non-compliance.
Data openly and freely available under a strict regulatory environment would likely be a better way to tame Big Tech’s power than breaking them up and having antitrust authorities approving every acquisition that they wish to make.
This article was originally published on The Conversation. Read the original article.