How Big Data Enables Economic Harm to Low-Income Consumers

While this data unquestionably increases the efficiency of the economy in numerous ways, what is in question is whether consumers are ultimately benefitting significantly from those productivity gains or whether that surplus is being largely captured by these "big data platforms."
This post was published on the now-closed HuffPost Contributor platform. Contributors control their own work and posted freely to our site. If you need to flag this entry as abusive, send us an email.

Emerging big data platforms are playing a central role in increasing economic inequality and harming low-income sectors of the population, argues researcher Nathan Newman in public comments (link to FTC workshop page) submitted for a Federal Trade Commission workshop being held today on Big Data: A Tool for Inclusion or Exclusion? The following is a summary of those comments.

Data has been called the "new oil" of the information age, an asset used by corporations to reshape markets and increase their market power and profits. On the Internet, we see the rise of new "big data" platforms such as Google, Amazon, Apple, Facebook and others that accumulate ever-increasing information on consumer behavior, interests and needs. While this data unquestionably increases the efficiency of the economy in numerous ways, what is in question is whether consumers are ultimately benefitting significantly from those productivity gains or whether that surplus is being largely captured by these "big data platforms." Worse, the increasing loss of control of private data by individuals seems to be leaving them vulnerable to economic exploitation by a range of corporate actors.

These big data platforms, what Jaron Lanier calls "siren servers" in his book, Who Will Own the Future?, attract consumers with a variety of services that encourage those users to part with personal data, which in turn is analyzed and combined with private information from other users in massive networks of computers. These companies use that analysis to reshape markets -- "disrupt" in Silicon Valley parlance - and channel an ever greater share of economic wealth into the hands of these big data platforms.

There is a particular concern that "free services" on the Internet use consumer data for the benefit not of those users but for third-party corporate customers of those data platforms, particularly advertisers who drive a large portion of the revenue model of the online Internet economy. While much of that advertising no doubt serves traditional advertising goals of strengthening brand awareness or promoting new products to consumers, the rise of behavioral profiling of consumers using the private data extracted by these big data platforms increases the use of advertising for more exploitative practices.

Big data platforms facilitate advertisers engaging in user profiling that aids those companies in extracting the maximum profit possible from consumers in the overall economy. Advertisers can deliver ads not just to the users most likely to be interested in the product but can tailor prices for individual consumers in ways that can maximize the revenue extracted from each purchaser. Consumers can be profiled and offered higher prices, unaware that other customers are getting better deals, while financially struggling houses are tagged as vulnerable and offered economically exploitative services such as payday and subprime loans.

This ability to charge different prices to different customers for the same good or service, what economists call "price discrimination," is based on the reality that people have different maximum prices they are willing to pay. And profiling consumers helps advertisers identify this "pain point" for each customer and offer a different price to each customer matching that maximum price they are willing to pay without them knowing that other deals are available.

Recent research on online advertising details the consumer loss due price discrimination combined with consumer profiling. Comparing traditional regimes of mass-market advertising to online advertising, researchers Rosa-Branc Esteves and Joana Resende found that average prices with mass advertising were lower than with targeted online advertising. Similarly, Benjamin Reed Shiller found that where advertisers know consumers willingness to pay different prices, companies can use price discrimination to increase profits and raise prices overall, with many consumers paying twice as much as others for the same product.

For less ethical companies, big data gives them the ability to seek out the most vulnerable prospects to exploit and entice them with scams and misleading offers. Such niche scams and economically exploitive relationships can be focused on those most vulnerable to the scam's appeal, while remaining essentially invisible to everyone else, including reporters and researchers trying to evaluate the harms from online advertising methods.

The data broker industry even has a term -- "sucker lists" -- for the poor, old and less educated groups that they compile for such unethical marketers. For example, people who reply to sweepstakes offers are put onto a list by one data broker company and offered to advertisers as an "ideal audience for...subprime credit offers" and other enticements. Other lists include "suffering seniors" who are identified as having Alzheimer's or similar maladies.

Big data lay at the heart of the subprime mortgage and overall financial meltdown the nation suffered at the end of the last decade. Data crunchers were key to manipulating financial markets and securities throughout the financial industry and big data platforms were critical parts of the marketing machine that pushed subprime financial products out to the most vulnerable members of the American public.

In fact, by the mid-2000s, the lion's share of the online advertising economy was being driven by subprime and related mortgage lenders. As Jeff Chester of the Center for Digital Democracy said back in 2007, "Many online companies depend for a disproportionate amount of their income on financial services advertising, with subprime in some cases accounting for a large part of it."

Since the rise of big data has coincided with the stagnation of incomes for average households, policy makers should be raising concerns that, alongside traditional explanations of rising inequality such as deunionization, globalization, and automation of unskilled jobs, the concentration of data into ever fewer corporate hands is helping to drive economic inequality in the broader economy.

In too many data platform services, one company is so dominant that consumers have little leverage to demand greater control of their data and less harmful use of that data. Whether Google in search adverting, Facebook in social networks, Amazon in online retail, Netflix in video streaming, the dynamics of control of user data strengthen concentration in particular sectors.

Part of this are network effects that mean the more people participating on a service, the more valuable it is to other users of that service. Part of the drive to concentration is that as companies collect user data, they gain competitive advantage against any potential challenger who will lack that user data in setting up any rival service. Such data can be redeployed by dominant players not just to strengthen their position in existing services but used in related new services to expand their economic reach. In this way, you see Google, Amazon, Apple and Facebook expanding rapidly into a multiplicity of emerging data-related fields, making it extremely hard for upstart companies to get a toehold except in very specific niches.

The upshot of this dynamic is that the marketplace is doing little to create options for consumers that might alleviate the misuse of consumer data, better protect user privacy or encourage big data platforms to better compensate users who are willing to share their data. As the accumulation of all this data is in increasingly fewer corporate hands with little market pressure on those companies to respect the privacy of users, it is incumbent on federal regulators to take action to prevent those big data platforms from facilitating the use of user data in ways that harm consumers, particularly low-income, minority and other vulnerable members of the population.

While big data can benefit consumers in certain instances, regulators need to take action to address new consumer harms to users from its unregulated use by increasingly centralized data platforms. The Federal Trade Commission has itself highlighted some of these problems in a number of recent reports, as well as litigation against companies engaged in deception in collecting personal data, but it is clear that additional regulation and laws are needed to address the full scope of the harm to consumers.

What is clear is that big data platforms depend on aggressive practices that undermine user control of their data and largely serve third-party interests such as advertisers. Given the size and dominance of many of these data platforms in their particular sectors, equally aggressive and far-reaching action by the federal government is needed to prevent the ongoing harms to consumers, particularly the most vulnerable members of society, detailed in these comments. What is needed is a combination of strengthening individual user control of their data, structural changes in the market to encourage a more accountability to consumers in the marketplace, and public interest regulation of the larger big data platforms to ensure that they are held accountable, particularly in the realm of financial services, in areas where the market will not discipline their actions.

As more of the economy moves online, the importance of data mining and asymmetry of control of information becomes ever more critical in economic markets. Addressing this change calls for far more active regulatory action to reverse the trends undermining user privacy and increasing economic inequality due to that rising information asymmetry. Such action should lead to a greater focus on big data platforms sharing the financial bounty of user information with those users, serving both equity and competition.

Data mining of individual privacy is fundamentally reshaping markets by transferring so much knowledge about user interests, behavior and desires into a few corporate hands. Such information asymmetry is easily converted into economic inequality when one side of every transaction has so much more knowledge about the other during bargaining. The last four decades have seen a steady increase in economic inequality, which is only partially explained by standard explanations centered on the rise of economic returns to education, globalized trade and political changes. The increasing information asymmetry in consumer markets, driven by data mining and facilitated by online services may be an additional significant cause of this overall increase in economic inequality.

Government authorities using regulatory tools can stem at least part of this trend by restoring a degree of control by individuals over what personal data is shared online and the financial terms on which that data is shared. This in turn can eliminate some of the information-based inequality in the modern marketplace that is driving overall economic inequality.

The author's public comments for the FTC workshop are adapted, with some additional research, from two law reviews published this year, the first of which, entitled "The Costs of Lost Privacy: Consumer Harm and Rising Economic Inequality in the Age of Google" and published in the William Mitchell Law Review, highlighted the economic harm to consumers and rising economic inequality stemming from big data. The second, entitled "Search, Antitrust and the Economics of the Control of User Data" and published in the Yale Law Journal on Regulation, detailed the case for antitrust action against Google based on its control of user data and harm to consumers. The author has been writing for twenty years about the impact of technology on society and wrote extensively about big data as a research fellow at the New York University Information Law Institute over the last two years.

Go To Homepage

Popular in the Community