CL&P Blog

Second Circuit Joins Consensus Holding TCPA Plaintiffs Have Standing Under Spokeo

The Telephone Consumer Protection Act (TCPA) provides people whose cell phones receive unconsented-to, autodialed calls and texts a right to sue. Since the Supreme Court's decision in Spokeo, Inc.  v. Robins, 136 S. Ct. 1540 (2016), which held that statutory violations unaccompanied by "concrete injuries" do not provide a plaintiff with "standing" to sue in a federal court, the question whether receiving calls and texts that violate the TCPA is a "concrete injury" has arisen in a number of cases. TCPA defendants (and in some cases, objectors to TCPA class-action settlements) have asserted that receiving an unwanted call or text is not a real injury for which Congress can provide a judicial remedy. Today, the U.S. Court of Appeals joined the emerging consensus that, under Spokeo, an unwanted call or text that violates the TCPA inflicts an injury that a plaintiff can sue over in a federal court.

Today's decision in Melito v. American Eagle Outfitters holds that the "nuisance and privacy invasion attendant on spam texts" (as well as calls and faxes) are sufficient to provide the "injury-in-fact" necessary for standing to sue in a federal court. The court looked to the two considerations that the Supreme Court said in Spokeo were critical to determining whether a statutory violation inflicts an injury: "history and the judgment of Congress." As to the first, the court found that the nuisance and privacy invasion inherent in unwanted robocalls and spam texts "were the harms Congress identified when enacting the TCPA." As to the second, these injuries "closely relate to traditional claims, including claims for 'invasions of privacy, intrusion upon seclusion, and nuisance.'" Because receiving unwanted communications "is itself the harm" the statute is aimed at, no more is required for a plaintiff to have standing to sue.

The Second Circuit's decision accords with post-Spokeo holdings of the Ninth and Third Circuits. No federal appellate court has yet held otherwise. It seems likely that TCPA plaintiffs will be largely unaffected by Spokeo, though the issue will continue to be raised and decided in other circuits until it has been laid to rest.

Consumer Reports article on barrier to information about defective products

Section 6(b) of the Consumer Product Safety Act generally requires the Consumer Product Safety Commission to get permission from a manufacturer before releasing to the public any information about a defective product that would reveal the identity of the manufacturer. Even when the CPSC announces an alert or recall, companies often can restrict the information that the agency releases.

In the face of some recent recalls of dangerous baby products, Consumer reports writes about the law, its origins, and the risks it poses to public safety. The article is here.

Fourth Circuit Invalidates TCPA’s Government Debt-Collection Exception

In 2015, Congress amended the Telephone Consumer Protection Act (TCPA) to exempt calls made to collect a debt owed to or guaranteed by the federal government from the TCPA’s ban on unwanted robocalls to cell phones. Last week, in a case called American Association of Political Consultants v. FCC, the U.S. Court of Appeals for the Fourth Circuit held that the exception created an unconstitutional content-based restriction on speech in violation of the First Amendment. (Broadly speaking, a law creates a “content-based” restriction when it allows some speech and prohibits other speech depending on what the speaker says.)

Fortunately, the court refused to strike down the TCPA's ban on robocalls to cell phones in its entirety, as the plaintiffs requested, but instead “severed” the government-debt-collection exception from the rest of the statute and invalidated it alone, leaving the rest of the TCPA intact.

Although the court’s First Amendment analysis has some troubling implications for government regulation of commercial activity, no one (except, perhaps, student-loan debt collectors and government budget-hawks) is likely to be too upset by the invalidation of the government-debt-collection exception. Constitutional or not, the provision created an opening for robocalls to student-loan borrowers and others who took out unsustainable government-guaranteed debt. Although the TCPA still prohibits far more unwanted robocalling than it allows, the 2015 exception was probably a bad policy choice, and I won’t be very sorry to see it go as long as that is all the impact that First Amendment challenges have on the TCPA.

The challengers in the Fourth Circuit case, who use robocalling for political purposes, wanted far more than they got from the court. They hoped not just to invalidate the government-debt-collection exception, or to have the TCPA declared unconstitutional as applied to political speech, but to bring down the TCPA’s ban on unwanted robocalls to cell phones in its entirety, leaving consumers vulnerable to unwanted telemarketing.

The challengers included not only business interests (political consultants and pollsters) who make money from political robocalls, but also the Democratic Party of Oregon and the Washington State Democratic Central Committee. It’s sad to see political parties dedicated to progressive values and consumer protection attempting to take down a major consumer-protection law principally aimed at commercial speakers who, left unchecked, would likely besiege our cell phones (and residential landlines, for those like me who still have them) with nonstop robocalls. One hopes that they will think better of pursuing their misguided challenges to the TCPA further.

A case presenting similar arguments against the TCPA, Gallion v. Charter Communication, is currently pending in the Ninth Circuit. There, the challenge is being brought by a company that used unwanted text messages for purely commercial purposes and was sued under the TCPA by a consumer who received one of its marketing texts. The federal government is defending the TCPA in that case, as it did in the Fourth Circuit, and also advocating severance if the court sees a constitutional problem with the government-debt-collection exception. That case was argued earlier this year and will likely be decided sometime in the coming months.

Here’s why recalls are harder than they should be

Vox explains how consumer product recalls work and the need for improvements in the recall system in an article titled "People buy millions of unsafe products every year. Here’s why recalls are harder than they should be," here.

The minimum wage and health

This study published today by the National Bureau of Economic Research finds that a 10% increase in the minimum wage and the Earned Income Tax Credit has a dramatic impact on the number of non-drug-related suicides among men and women without college degrees. Read this article about the study.

Court of appeals rejects payday lender's claim of "tribal sovereign immunity"

The Second Circuit today decided a case involving payday lending and forced arbitration, ruling for the plaintiffs on two important issues.

In Gingras v. Think Finance, Vermont residents who claim that the payday loans violate Vermont usury and consumer protection laws as well as federal laws including the RICO statute sued the operators of an alleged predatory payday lending scheme, in which private investors whose payday lending business had been shut down by the FTC enlisted a native American tribe to set up an entity through which they would make loans over the internet nationwide. The plaintiffs sought monetary and injunctive relief. The defendants include tribal members who are officers of the tribal entity that nominally made the loans.

The tribal defendants claimed tribal sovereign immunity against the plaintiffs’ claims, which are limited to claims for injunctive relief. All the defendants also asserted that the claims are subject to arbitration under arbitration clauses included in the loan agreements. The U.S. District Court for the District of Vermont rejected those and other arguments made by the defendants in support of the dismissal of the actions, and the defendants appealed the rulings denying immunity and denying their motion to compel arbitration.

On appeal, the defendants raised two issues that (1) tribal immunity bars claims for injunctive relief against tribal officers alleged to have violated state laws outside of tribal lands; and (2) the district court erred in not requiring the plaintiffs to arbitrate their claims. The court of appeals rejected both arguments and affirmed the district court on both points. The court held that tribal sovereign immunity does not bar the lawsuit, and that the plaintiffs may sue tribal officers under a theory analogous to Ex parte Young for prospective, injunctive relief based on violations of state and substantive federal law occurring off of tribal lands. The court also held that the arbitration clauses of the loan agreements are unenforceable and unconscionable.

The Second Circuit's decision is here.

Mandatory arbitration at Sterling Jewelers

The New York Times today has a lengthy piece about treatment of female employees at Sterling, Kay, and Jared Jewelers -- stores owned by the same company. The heart of the article is about pay inequity, and pervasive and extreme sexual harassment. But the article also describes the role of the forced arbitration and non-disclosure provisions in the stores' employment contracts in stymying the employees' efforts to hold the company accountable.

all the employees had signed a mandatory arbitration agreement in the flood of paperwork that accompanied their hiring at Sterling — everyone did at the time. Arbitration meant that instead of being heard in a public court, they had to proceed privately in Sterling’s in-house system, called Resolve. The first step of Resolve was an internal investigation. If the employee wasn’t satisfied by the results of that investigation, he or she could ask to be heard by a panel of the employee’s peers and an employment lawyer, all selected by Sterling. If the employee was still dissatisfied, the case was sent to arbitration. Sterling paid the arbitrator. The hearing’s proceedings were carried out with judicial oversight, but they were done in private, and their outcome was sealed. Afterward, if there was a settlement, the employee often had to sign a nondisclosure agreement that prohibited the employee from speaking about the case again.

The full article is here.

How can you protect your privacy online?

How can you protect your privacy online? A New York Times article today suggests that you can't.

People concerned about privacy often try to be “careful” online. They stay off social media, or if they’re on it, they post cautiously. They don’t share information about their religious beliefs, personal life, health status or political views. By doing so, they think they are protecting their privacy.

But they are wrong. Because of technological advances and the sheer amount of data now available about billions of other people, discretion no longer suffices to protect your privacy. Computer algorithms and network analyses can now infer, with a sufficiently high degree of accuracy, a wide range of things about you that you may have never disclosed, including your moods, your political beliefs, your sexual orientation and your health.

There is no longer such a thing as individually “opting out” of our privacy-compromised world.

The full article is here.

Odinet article on student debt, fintech, and discrimination

Christopher K. Odinet of Oklahoma has written The New Data of Student Debt, 92 Southern California Law Review (Forthcoming). Here is the abstract:

Silicon Valley is increasingly setting its sights on student lending. Financial technology (fintech) firms such as SoFi, CommonBond, and Upstart are ever-expanding their online lending activities to help students finance or refinance educational expenses. These online companies are using a wide array of alternative, education-based data points — ranging from applicants’ chosen majors, assessment scores, the college or university they attend, job history, and cohort default rates — to determine creditworthiness. Fintech firms argue that through their low overhead and innovative approaches to lending they are able to widen access to credit for underserved Americans. Indeed, there is much to recommend when it comes to using different kinds of information about young consumers in order assess their financial ability. Student borrowers are notoriously disadvantaged by the extant scoring system that heavily favors having a prior credit history. Yet, there are also downsides to the use of education-based data by private lenders. This Article critiques the use of this kind of borrower information, arguing that while it can have a positive effect in promoting social mobility, it could also have significant downsides. Chief among these are reifying existing credit barriers along income and class lines and further contributing to discriminatory lending practices that harm women, black and Latino Americans, and minority groups. The discrimination issue is particularly difficult because of the novel and opaque underwriting algorithms that facilitate these online loans. This Article concludes by proposing three-pillared regulatory guidelines for fintech credit firms to use in designing, implementing, and monitoring their education-based data underwriting systems.

Prince & Schwarcz article on how AI is a game-changer for proxy discrimination

Anya Prince of Iowa and Daniel Schwarcz of Minnesota have written Proxy Discrimination in the Age of Artificial Intelligence and Big Data, Iowa Law Review, Forthcoming. Here's the abstract:

Big data and Artificial Intelligence (“AI”) are revolutionizing the ways in which firms, governments, and employers classify individuals. Surprisingly, however, one of the most important threats to antidiscrimination regimes posed by this revolution is largely unexplored or misunderstood in the extant literature. This is the risk that modern algorithms will result in “proxy discrimination.” Proxy discrimination is a particularly pernicious subset of disparate impact. Like all forms of disparate impact, it involves a facially-neutral practice that disproportionately harms members of a protected class. But a practice producing a disparate impact only amounts to proxy discrimination when the usefulness to the discriminator of the facially-neutral practice derives, at least in part, from the very fact that it produces a disparate impact. Historically, this occurred when a firm intentionally sought to discriminate against members of a protected class by relying on a proxy for class membership, such as zip code. However, proxy discrimination need not be intentional when membership in a protected class is predictive of a discriminator’s facially-neutral goal, making discrimination “rational.” In these cases, firms may unwittingly proxy discriminate, knowing only that a facially-neutral practice produces desirable outcomes. This Article argues that AI and big data are game changers when it comes to this risk of unintentional, but “rational,” proxy discrimination. AIs armed with big data are inherently structured to engage in proxy discrimination whenever they are deprived of information about membership in a legally-suspect class that is genuinely predictive of a legitimate objective. Simply denying AIs access to the most intuitive proxies for predictive but suspect characteristics does little to thwart this process; instead it simply causes AIs to locate less intuitive proxies. For these reasons, as AIs become even smarter and big data becomes even bigger, proxy discrimination will represent an increasingly fundamental challenge to anti-discrimination regimes that seek to limit “rational discrimination.” This Article offers a menu of potential strategies for combatting this risk of proxy discrimination by AI, including prohibiting the use of non-approved types of discrimination, mandating the collection and disclosure of data about impacted individuals’ membership in legally protected classes, and requiring firms to employ statistical models that isolate only the predictive power of non-suspect variables.