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The federal government is set to award more than $42 billion in new grants to state governments this summer, with the goal of expanding high-speed internet access in areas that currently lack it.

But as this new Broadband Equity, Access, and Deployment program ramps up, it is crucial that states spend the money wisely.

Read the full piece here.

As the U.S. House Energy and Commerce Subcommittee on Oversight and Investigations convenes this morning for a hearing on overseeing federal funds for broadband deployment, it bears mention that one of the largest U.S. broadband-subsidy programs is actually likely run out of money within the next year. Writing in Forbes, Roslyn Layton observes of the Affordable Connectivity Program (ACP) that it has enrolled more than 14 million households, concluding that it “may be the most effective broadband benefit program to date with its direct to consumer model.”

Read the full piece here.

I.        Introduction

On behalf of the International Center for Law & Economics (ICLE), we thank the Federal Communications Commission (FCC or the Commission) for the opportunity to comment on this Notice of Proposed Rulemaking in the Matter of Implementing the Infrastructure, Investment, and Jobs Act: Prevention and Elimination of Digital Discrimination (NPRM).[1]

The Commission is contemplating creating a definition of “digital discrimination of access” under Section 60506 as “(1) policies or practices, not justified by genuine issues of technical or economic feasibility, that differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin” and/or (2) “policies or practices, not justified by genuine issues of technical or economic feasibility, that are intended to differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin.”[2]

Finding ways to increase deployment to those Americans who have been persistently difficult to connect is a laudable goal, but there are better and worse ways to proceed. Section 60506 is about making sure that broadband is deployed fairly, given existing technological and economic constraints. It is not a radical prescription from Congress, but a request that the FCC ensure that impermissible discrimination doesn’t affect broadband deployment.

This requires accounting for the current state of deployment, the economic realities that constrain deployment decisions, and the existing legal framework that constrains the manner in which the Commission can interpret Section 60506.

A.     The State of Deployment

As a baseline, it’s important to recognize that broadband providers have, by and large, done an excellent job of deploying to most households, while the data the FCC is currently gathering to assemble new broadband maps will enhance our ability to identify those problem areas that remain. Some of the comments in the record illustrate this baseline well. For example, NCTA observes in its comments that more than 98% of homes across income levels have access to fiber connections with speeds of at least one gigabit per second,[3] and that more than “97% of all homes and businesses in cable provider service areas have gigabit access regardless of race.”[4] As the FCC interprets Section 60506, the goal should be to work with this track record of success and not erect roadblocks that could prevent building on this base.

Moreover, broadband providers have been actively courting low-income consumers, particularly since Congress enacted successful programs such as the $14.2 billion Affordable Connectivity Program (ACP). By actively participating in these programs and offering tailored low-cost options, broadband providers are working to bridge the digital divide and reach unserved consumers. For example, Comcast’s “Internet Essentials” and “Internet Essentials Plus” programs offer affordable high-speed Internet service to eligible low-income households,[5] while AT&T’s “Access” program provides low-cost broadband plans to qualifying families.[6] Additionally, providers such as Charter Communications, through their “Spectrum Internet Assist” initiative, extend discounted Internet services to qualifying individuals and families.[7]

B.     The Economic Constraints of Section 60506 and Deployment

Section 60506 directs the FCC to prevent discrimination in broadband access based on income level. It also instructs the Commission to consider issues of technical and economic feasibility. A fundamental challenge presented by the intersection of these two directives is that a prospective broadband territory’s income level is related, albeit indirectly, to the economic feasibility of deployment projects to serve that territory. Economic feasibility is driven largely by population density and anticipated broadband adoption and retention. Broadband adoption and retention are, in turn, driven by income, willingness-to-pay, and many other factors. This present an “income conundrum,” in that it is nearly impossible to completely disentangle a given customer base’s anticipated rates of broadband adoption and retention from their income level.

It is well known and widely accepted that income is correlated with many factors that are not identified in Section 60506, including population density, age, educational attainment, home-ownership status, home-computer ownership and usage, and rates of broadband adoption and un-adoption. Because each of these additional factors is correlated with income level, many effects-based statistical tests of broadband adoption are likely to produce false positives, concluding the presence of digital discrimination even where explicit efforts are made to avoid such discrimination.

This problem is exacerbated if providers are not allowed to point to the relative profitability of prospective deployment investments. Like all firms, broadband providers have limited resources to invest. While profitability is a necessary precondition for investment, not all profitable investments can be undertaken. At any given time, firms must choose from numerous potentially profitable projects, some more apparently profitable than others. Firms must be allowed to choose the mix of profitable investments that they believe will best advance long-term deployment without fear of having to defend claims of income discrimination.

While the NPRM[8] and several commenters[9] suggest the statute can be read to give the FCC broad authority to redress the disparate impact of deployment decisions based on income and race (among other impermissible deployment factors), principles of statutory interpretation preclude that reading. Supreme Court precedent on antidiscrimination statutes makes clear how Congress can write disparate-impact law.[10] It also makes clear that many provisions of antidiscrimination statutes apply only to intentional discrimination.[11] The difference turns on the language of the operative text and the statutory purpose, as illustrated by things like the overall structure of the legislation and the stated policy objective (including legislative intent, if it can be known).[12] Applying this rubric to Section 60506, we find that it lacks requisite “results-oriented language” that would make it into an effects-oriented statute. Thus, the prohibition against digital discrimination “based on income level, race, ethnicity, color, religion, or national origin” would apply only in cases of intentional discrimination in deployment decisions. Mere statistical correlation between deployment and protected characteristics is insufficient to support a finding of discrimination.

As to the overall structure of the Act, while the Infrastructure, Investment, and Jobs Act (IIJA) incorporates some of its provisions into the Communications Act, Section 60506 is not among them. The IIJA is concerned chiefly with promoting broadband buildout through the use of subsidies. As to the policy objective, the scant congressional record on Section 60506 fails to illuminate the text, leaving us to consider the plain meaning of the statute. The “statement of policy” in subsection (a) holds that subscribers “should” benefit from equal access to broadband and that the Commission “should” take steps to ensure such equal access.[13] This “precatory”[14] section tells us the goal of the operative text: to make sure the Commission takes steps to promote broadband buildout. The mandate to create rules that facilitate equal access to broadband service—including by “preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin”—grants the Commission authority to set up a regulatory structure that would prevent intentional discrimination in deployment decisions, using language akin to those antidiscrimination provisions that speak only to intent.[15] This limited authority doesn’t allow for disparate-impact analysis, nor does it create a private right of action to enforce against any broadband provider. Instead, it empowers the Commission (and the Office of the Attorney General) to ensure federal policies promote equal access by prohibiting such deployment discrimination.[16]

Broadband buildout is big business, in the sense that a lot of money is invested by providers and governments (in the form of subsidies) alike. How these providers are regulated is a “major question” of “vast economic [and] political significance.”[17] To allow the Commission to exercise broad authority to ameliorate disparate impact, as suggested by some commenters, would be to find the proverbial “elephants in mouseholes”[18] in this statute, which the U.S. Supreme Court has not permitted.

In Part II, we review specific questions in the NPRM, the economics underlying deployment decisions, and how these relate to potential digital discrimination.

In Part III, we review some of the legal implications of attempting to regulate “digital discrimination” under both an intent-based and effects-based approach.

In Part IV, we consider the need for safe harbors and other procedural protections.

In Part V, we conclude and offer some thoughts on how to give best effect to Section 60506.

II.      Using Income as a Measure of Digital Discrimination

Section 60506 directs the FCC to prevent discrimination in broadband access based on income level, race, ethnicity, color, religion, or national origin, while also directing the Commission to consider issues of technical and economic feasibility.

We assert that the FCC should adopt an intent-based discriminatory-treatment standard, rather than one that opens the doors to disparate-impact claims. The high risk of false positives under a disparate-impact standard would stifle broadband deployment through additional costs, delays, and risk of litigation. Similarly, FCC rules should articulate a presumption of nondiscrimination in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision.

It is clear that population density and anticipated broadband adoption are the key factors affecting the economic feasibility of broadband-deployment investments. Affordability and willingness to pay are the primary drivers of broadband adoption where it is available. Indeed, Congress has recognized this reality in its recent legislation. The IIJA’s Broadband Equity and Access program provides more than $42 billion in grants to state programs to help them support providers and give assistance directly to users.[19] The Affordable Connectivity Program provided another $14 billion in funding to help users pay for devices and broadband connections.[20]

If the Commission has good evidence of intentional discrimination in the deployment of broadband, it has a role to play in preventing it. But attempts to use the regulatory process to root out digital discrimination will do little to shrink the digital divide without substantial resources to increase adoption and retention of broadband services.

A.      The Indirect Relationship Between Income and Economic Feasibility

The NPRM asks “how does a consumer’s income level, or the average income level of a geographical area, relate to economic feasibility in the deployment and provision of broadband internet access services?”[21]

The short answer is that income level is only indirectly related to economic feasibility. When evaluating the economic feasibility of a potential investment, broadband providers consider that territory’s anticipated adoption rate.[22] There is evidence that income, willingness to pay, and many other factors affect consumers’ adoption and retention decisions. Thus, it can be said that income level is related to deployment decisions only through a daisy chain linking anticipated adoption and retention rates to consumers’ willingness to pay, with willingness to pay loosely correlated with income level.

Population density is widely acknowledged to be the most important factor driving broadband-deployment decisions. For example, the U.S. Government Accountability Office (GAO) reports that population density is the “most frequently cited cost factor” and “a critical determinant of companies’ deployment decisions.”[23] Academic research supports the GAO’s conclusions. Brian Whitacre & Roberto Gallardo describe population density as one of “the main determinants of Internet availability.”[24] Similarly, Tonny Oyana, citing earlier research, concluded that “[l]imited broadband access is common in rural communities because of geographic remoteness and low population density.”[25]

Several other factors also affect the profitability of broadband-deployment investments, including:

• Terrain: The GAO notes that “it is more costly to serve areas with low population density and rugged terrain with terrestrial facilities than it is to serve areas that are densely populated and have flat terrain.”[26]
• Backhaul: That is, the cost of routing Internet traffic from rural areas to larger cities in order to connect to a major Internet-backbone provider. The GAO also reports that the cost of backhaul can affect broadband deployment to rural areas.[27]
• State-level broadband-funding programs: Whitacre & Gallardo find such programs are associated with a modest increase (1.2–2.0 percentage points) in broadband availability.[28]

Juan Schneir & Yupeng Xiong note that firms are more likely to deploy broadband in urban and suburban areas, rather than rural areas, due to both cost and demand factors. They conclude this is “because of the high density of users willing to pay for high-speed broadband services and the relatively low network rollout costs in urban and suburban areas.”[29] Consistent with Schneir & Xiong’s conclusion, the GAO also finds that population density is an important factor on the demand side of deployment decisions. In particular, the GAO concludes that it is more difficult to “aggregate sufficient demand” to pay for broadband service in low-density rural areas.[30]

But broadband access alone also may not be sufficient to drive greater rates of broadband adoption. For example, Brian Whitacre and his co-authors found that while the reduced levels of broadband access in rural areas explained 38% of the rural-urban broadband-adoption gap in 2011, differences in other general characteristics—such as income and education—explain “roughly half of the gap.”[31] Another GAO report concluded that “even where broadband service is available … an adoption gap may persist due to the affordability of broadband and lack of digital skills.”[32] The report further notes that nearly one-third of those with access to broadband do not subscribe to it and that “lower-income households have lower rates of home broadband subscriptions.”[33]

The price of broadband services is another significant factor that affects adoption. A National Telecommunications and Information Administration (NTIA) survey of Internet use identified “affordability as a driving factor around why some households continue to remain offline, confirming that cost of service is an essential part of increasing Internet adoption.”[34] The survey reported that the average price that offline households wanted to pay for Internet access was approximately $10 per month, and about 75% of households gave $0 or “none” as their answer. Kenneth Flamm & Anindya Chaudhuri’s empirical research finds that broadband price is a “statistically significant driver” of broadband demand.[35] They conclude that broadband-price declines in the early 2000s explain “some portion” of increased broadband adoption.[36] Victor Glass & Stela Stefanova’s empirical study found that higher prices “depress” demand for broadband.[37]

Price sensitivity is linked to income. Christopher Reddick and his co-authors concluded that “[i]ncome is a major factor that is likely to influence broadband adoption especially where technology is available.”[38] Glass & Stefanova find broadband service to be a normal good, which means that increased incomes are associated with increased broadband adoption—a finding consistent with previous research.[39] Similarly, the GAO reports: “A recent nationally representative survey by Consumer Reports reported that nearly a third of respondents who lack a broadband subscription said it was because it costs too much, while about a quarter of respondents who do have broadband said they find it difficult to afford.”[40] Alison Powell and her co-authors report that a significant number of low-income Americans engage in a cycle of broadband adoption and “un-adoption,” in which they adopt broadband and then drop it for financial or other reasons, and then re-adopt when circumstances improve for them.[41]

In addition to price and income guiding a household’s broadband-adoption decisions, other factors are also relevant. Oyana’s empirical research concludes that income, the share of a population who are senior citizens, and the share with some college education are the “three most important demand-side factors” affecting both access and adoption.[42] On the demand side, the GAO reports that “demand will be greater in areas where potential customers are familiar with computers and broadband.”[43] The GAO reports that “[o]ther barriers include lack of digital skills,” citing a 2016 Pew Research Center report finding that “about half of American adults were hesitant when it comes to new technologies and building their digital skills.”[44]

It can be argued that the gap between rates of broadband access and broadband adoption may present the real digital divide. That is, large numbers of American who have access to broadband do not adopt it, and some who do may “un-adopt” it. While income is a key factor in a household’s adoption choice, it is only one of several important factors, which also include age, educational attainment, and home-computer ownership and usage—each of which is, in turn, also correlated with income.

If firms do not expect sufficient levels of adoption, then deployment may be unprofitable. It would be a mistake to infer that income discrimination in deployment causes low rates of broadband adoption in low-income communities when low income itself—and other factors correlated with income—may be a primary cause of low rates of broadband adoption, even where broadband access is available.

B.      Profitability, Return on Investment, and Economic Feasibility

The NPRM asks, “should a provider be permitted to defend a claim of income-based intentional discrimination by offering projections showing that deploying to a particular community would likely produce a lower-than-normal rate of return on investment?”[45]

Section 60506 requires the Commission to take account of “issues of technical and economic feasibility.” There is broad understanding that “economic feasibility” here refers to profitability.[46] More precisely, a project is economically feasible if it provides an adequate return on investment (ROI). Like all firms, broadband providers have limited resources with which to make their investments. While profitability is a necessary precondition for investment, not all profitable investments can be undertaken. Among the universe of potentially profitable projects, firms are likely to give priority to those that promise greater returns on investment relative to those with lower ROI.[47] Thus, any evaluation of potential digital discrimination must examine not only whether a given deployment is likely to be profitable, but also how its expected returns compare to other investment opportunities.

This concept—opportunity cost—is fundamental not just to economics, but to our daily lives. Indeed, we all live in a world of endless wants, but only limited resources (e.g., money, time, natural resources) to satisfy them. As a result, we must make choices about how best to use those resources to satisfy our wants. By choosing to pursue one activity, we must forgo another. The value of what we have foregone is our opportunity cost.[48] A worker contemplating quitting their job to start a business is certain to consider the income they would be giving up as an opportunity cost of entrepreneurship.

Similarly, a broadband provider who invests in region A recognizes that it is giving up the opportunity to invest in region B. But the provider faces another factor the would-be entrepreneur does not. If the provider regularly chooses low-ROI investments over higher ROI investments, then its shareholders may choose to replace management with a team that can provide better returns. The opportunity-cost calculus is unavoidable.

Thus, it is surprising to see comments to this proceeding that suggest the FCC should ignore opportunity cost in evaluating economic feasibility.[49] Section 60506 specifically calls on the FCC to consider economic feasibility—not financial feasibility or accounting feasibility. There is no evidence that this was an accident or mistake. Because opportunity cost is a cornerstone of economic analysis, it would be reasonable to conclude that the law’s mandate to consider economic feasibility was meant to rely on economic analysis and, in turn, to consider the opportunity costs of foregone deployment investments. We strongly encourage the Commission to include opportunity costs that providers face whenever it evaluates alleged digital discrimination in deployment.

C.      Demonstrating Discrimination: The Income Conundrum

The NPRM asks, “[S]hould a provider be permitted to defend a claim of income-based intentional discrimination by offering projections showing that deploying to a particular community would likely produce a lower-than-normal rate of return on investment? How are we to determine whether a proffered economic justification, such as rate of return, is a pretext for income-based discrimination?”[50] The NPRM reports that some have argued a sub-normal profit margin should not be considered sufficient reason to claim economic infeasibility and that the Commission should rarely excuse discrimination on such grounds.[51]

A provider should be permitted to defend a claim of income-based intentional discrimination by demonstrating that deploying to a particular community would likely produce a lower return on investment relative to other likely alternatives investments. Thus, a provider should be able to defend a claim of income-based intentional discrimination even if deploying to a particular community would likely produce a higher than “normal” ROI—so long as other deployment alternatives produce anticipated ROIs that are greater still. As noted above, a positive ROI is a necessary precondition for investment, but not all profitable investments can be undertaken. Evaluations of potential digital discrimination must examine not only whether a given deployment is likely to be profitable, but also how its expected returns compare to other investment opportunities.

It would be near-impossible to evaluate demographic, economic, and financial data to determine whether profitability, ROI, or other economic reasons constitute a pretext for a pattern of so-called income-based discrimination. Our research indicates that such an approach would likely lead to a huge number of “false positives”—finding discrimination where no discrimination is intended or, indeed, where it was explicitly avoided. This presents what we call the “income conundrum,” because it is virtually impossible to disentangle the factors affecting economic feasibility from factors correlated with membership in certain income and other protected classes.[52]As such, alleged patterns of income-based discrimination provide very little (if any) information, and certainly not enough information to sufficiently prove a violation of Section 60506.

Former FCC Chief Economist Glenn Woroch combined recent census-block-level wireline-broadband deployment data from the Commission’s Form 477 reports with demographic and income data published by the U.S. Census Bureau to evaluate broadband availability rates for wireline 100/20 Mbps service (1) between census-based “white” and “non-white” households and (2) between households above and below the Federal Poverty Guidelines.[53] His statistical analysis indicates broadband availability rates are about 5 percentage points higher for non-white households than for white households, and that broadband availability rates are nearly identical for households above and below the Federal Poverty Guidelines.

Woroch’s results are consistent with the statistical analysis published by Randolph Beard & George Ford.[54] Their data indicate that U.S. Census blocks with higher population densities are associated with a higher share of minority residents and lower average incomes. Beard & Ford also report that blocks with a higher share of minority residents have lower fixed-broadband adoption rates and a higher share of mobile-only broadband use. Their empirical model includes four demand factors for each Census block: fixed-broadband adoption rate, mobile-broadband adoption rate, the share of persons with a tertiary education, and the share of homes with a computer. The model also includes five cost factors: population density, the share of rural blocks within the Census-block group, and three cost categories from CostQuest. Using this information, they evaluate: (1) fiber deployment by race, (2) fiber deployment by income level, (3) download speeds by race, and (4) download speeds by income level. Beard & Ford conclude from their statistical analysis that there is “no meaningful evidence of digital discrimination in either race or income for fiber deployments or for download speeds.”

It is well-known and widely accepted that income is correlated with many factors that are not identified in Section 60506, including population density, age, educational attainment, home-ownership status, home-computer ownership and usage, and broadband adoption and un-adoption. But because each of these other factors is, in turn, correlated with income level, applying an effects-based statistical analysis is likely to produce false positives that conclude the presence of digital discrimination, even if there was an explicit effort to avoid such discrimination. This is a version of Nobel laureate Ronald Coase’s well-known quote: “If you torture the data long enough, it will confess.”^[55]

Indeed, as the Competitive Enterprise Institute (CEI) notes, even if the Commission were to adopt a disparate-impact standard (discussed infra), it would be exceedingly difficult, if not impossible, to prove income discrimination through a series of correlated proxies under existing Supreme Court precedent:

Thus, as Hazen demonstrates that as long as the motivating factor for digital discrimination of access is analytically distinct from the protected characteristic (even if one is correlated with the other, like age when set against years of service), the person who is wholly motivated by other factors wouldn’t be discriminating based on protected characteristics. [56]

Thus, even if correlational evidence is introduced, it will be of such little probative value as to contribute very little information to a proceeding. For example, even if statistical analysis indicated a relationship between income and some other non-protected characteristic (e.g., education), under 1993’s Hazen Paper Co. v. Biggins decision, that information could not be used to demonstrate income discrimination. The only way that a prohibition on income-based discrimination would make sense at all would be if Section 60506 were construed as prohibiting intentional discrimination. In this sense, claims would have to be brought on the basis that a provider intentionally discriminated against a low-income household, or against a territory for being low-income, with all else being equal. That is, if a particular opportunity would otherwise have been included in a provider’s deployment plans, discrimination could be found if that provider refrained from deploying based on an intent not to serve low-income households in the area.

III.    Section 60506 Empowers the Commission to Facilitate Equal Access to Broadband by Prohibiting Intentional Discrimination

Congress did not, with Section 60506, turn the FCC into a general-purpose civil-rights agency. It did, however, give the Commission a set of tools to identify and remedy particular acts of discrimination.

In the NPRM, the Commission proposes:

to define “digital discrimination of access,” for purposes of this proceeding, as one or a combination of the following: (1) “policies or practices, not justified by genuine issues of technical or economic feasibility, that differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin”; and/or (2) “policies or practices, not justified by genuine issues of technical or economic feasibility, that are intended to differentially impact consumers’ access to broadband internet access service based on their income level, race, ethnicity, color, religion, or national origin.”[57]

Although some commenters have called for the FCC to employ an effects-based “disparate impact” analysis under Section 60506,[58] we continue to believe this would be a mistake under both the structure of Section 60506 and the Supreme Court’s established jurisprudence on disparate-impact analysis. A more reasonable approach for the Commission would be to construe Section 60506 as directing an analysis of intentional discrimination in deployment.

Statutes that define impermissible discrimination, such as the Civil Rights Act of 1964, can be analyzed legally either as addressed toward explicit discriminatory intent, referred to as “discriminatory treatment,” or toward behavior inferred from discriminatory effects, such as the “disparate impact” that the challenged behavior or policy has on a protected class.[59] A case involving discriminatory treatment is somewhat more straightforward,[60] insofar as it demands evidence demonstrating that decisions adversely affecting some protected class were made based on bias toward members of that class. In this context, where deployment decisions are made on the basis of discriminatory intent, the Commission is on much firmer legal ground to pursue them.

By contrast, were the Commission to adopt a “disparate impact” assessment as part of Section 60506, it would face a steep uphill legal climb. Among the primary justifications for disparate-impact analysis is to remedy those historical patterns of de jure segregation that left an indelible mark on minority communities.[61] While racial discrimination has not been purged from society, broadband only became prominent in the United States well after all forms of de jure segregation were made illegal, and after Congress and the courts had invested decades in rooting out impermissible de facto discrimination. Any policy intended to tackle disparate impact in broadband deployment needs to take this history into account.

Commenters like Public Knowledge point to Section 60506’s stated policy objective to make the case that the statute encompasses disparate-impact analysis.[62] They also situate the IIJA as a part of the universal service regime of the Communications Act.[63] However, Section 60506 was not incorporated into the Communications Act, unlike other parts of the IIJA. In other words, the FCC’s general enforcement authority doesn’t apply to the regulatory scheme of Section 60506. The FCC must rely on the statute alone for that authority. Moreover, the statement of policy in Section 60506(a) is exactly that: a statement of policy. Courts have long held that sections using words like “should”[64] are “precatory.”[65] While this helps to illuminate the goal of the provision at issue, it does not actually expand the remit of FCC authority. The goal of the statute is clear: to make sure the Commission takes steps to promote broadband buildout. It empowers the Commission (and the Office of the U.S. Attorney General) to ensure that federal policies promote equal access by prohibiting such deployment discrimination.[66]

There is little evidence that IIJA’s drafters intended the law to be read so broadly. The legislative record on Section 60506 is exceedingly sparse, containing almost no discussion of the provision beyond assurances that “broadband ought to be available to all Americans,”[67] and also that the provision was not to be used as a basis for the “regulation of internet rates.”[68] Given that sparse textual basis, reading Section 60506 as granting the Commission expansive powers to serve as a broadband civil-rights czar could also run afoul of the “major questions” doctrine.[69] That doctrine requires Congress “to speak clearly if it wishes to assign to an agency decisions of vast ‘economic and political significance.’”[70] To allow the Commission to exercise the type of broad authority to ameliorate disparate impact, as suggested by some commenters, would be to find the proverbial “elephants in mouseholes”[71] in this statute that the Supreme Court has not allowed.

More specifically, it does not appear that Section 60506 can be reasonably construed as authorizing disparate-impact analysis. While the Supreme Court continues to uphold disparate-impact analysis in the context of civil-rights law, it has recently imposed some important limitations. For example, in Texas Department of Housing & Community Affairs v. The Inclusive Communities Project Inc., the Court upheld the disparate-impact doctrine, but noted that disparate-impact claims arise under statutes explicitly directed “to the consequences of an action rather than the actor’s intent.”[72] For example, in the Fair Housing Act, Congress made it unlawful:

To refuse to sell or rent after the making of a bona fide offer, or to refuse to negotiate for the sale or rental of, or otherwise make unavailable or deny, a dwelling to any person because of race, color, religion, sex, familial status, or national origin.[73] [Emphasis added.]

The Court noted that the presence of language like “otherwise make unavailable” is critical to construing a statute as demanding an effects-based analysis.[74] Such phrases, the Court found, “refer[] to the consequences of an action rather than the actor’s intent.”[75] Further, the structure of a statute’s language matters:

The relevant statutory phrases… play an identical role in the structure common to all three statutes: Located at the end of lengthy sentences that begin with prohibitions on disparate treatment, they serve as catchall phrases looking to consequences, not intent. And all [of these] statutes use the word “otherwise” to introduce the results-oriented phrase. “Otherwise” means “in a different way or manner,” thus signaling a shift in emphasis from an actor’s intent to the consequences of his actions.[76]

Previous Court opinions help to parse the distinction between statutes limited to intentional-discrimination claims and those that allow for disparate-impact claims. Particularly relevant here, in Alexander v. Sandoval, the Court emphasized that it was “beyond dispute—and no party disagrees—that § 601 prohibits only intentional discrimination.”[77] The relevant statutory language stated that “No person in the United States shall, on the ground of race, color, or national origin, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving Federal financial assistance.”[78]

Thus, when Public Knowledge argues that “assertion that the phrase ‘based on’ limits the Commission to disparate intent is based on the dissent not the majority opinion of Inclusive Communities. The majority’s opinion states the exact opposite… The phrase at issue in Inclusive Communities was ‘because of,’ which is equivalent to ‘based on’ contained in section 1754…”[79], it gets both Inclusive Communities and previous precedents wrong. First, Inclusive Communities primarily based its opinion on the “otherwise make unavailable” language and not on the “because of” language on its own. Second, the closest analogy for “based on” is the “grounded on” language of Title VI, which does not include the “otherwise” language found to be so important in Inclusive Communities. If the Court has found “grounded on” means only intentional discrimination, then it is hard to see how “based on” wouldn’t lead to the same conclusion.

Further, even where disparate-impact analysis is appropriate, the Court held in Inclusive Communities that it is significantly constrained by the need to ensure that the free-enterprise system continues to function:

[Supreme Court precedent] also teach[es] that disparate-impact liability must be limited so… regulated entities are able to make the practical business choices and profit-related decisions that sustain a vibrant and dynamic free-enterprise system. And before rejecting a business justification…a court must determine that a plaintiff has shown that there is “an available alternative … practice that has less disparate impact and serves the [entity’s] legitimate needs.”[80] [Emphasis added.]

In practice, this means that lower courts are free to probe a disparate-impact claim rigorously in order to avoid such claims becoming a club to wield against regulated entities.[81] It also suggests that, in a context such as Section 60506’s proscriptions against digital discrimination, they may not be so broad as to render it impossible for broadband providers to make effective decisions about which deployment projects are economically feasible.

More to the point, as Section 60506 was drafted without “results-oriented language”[82] and instead frames the prohibition against digital discrimination as “based on income level, race, ethnicity, color, religion, or national origin,”[83] this would put the rule squarely within the realm of prohibitions on intentional discrimination.[84] That is, to be discriminatory, the decision to deploy or not to deploy must have been intentionally made based on or grounded on the protected characteristic. Mere statistical correlation between deployment and protected characteristics is insufficient.

In enacting the IIJA, Congress was undoubtedly aware of the Court’s history with disparate-impact analysis. Had it chosen to do so, it could have made the requirements of Section 60506 align with the requirements of that precedent. But it chose not to do so, thereby reinforcing that it intended the FCC to have some discretion, but to err on the side of caution when declaring certain practices an impermissible form of discrimination.

This is not to say that Section 60506 has no effect. As mentioned above, it can be reasonably read to encompass intentional discrimination, given appropriate evidence. Further, the means available to the FCC to remedy undesirable patterns of deployment are manifold. The only options rendered off the table would be requirements that are technologically or economically infeasible, such as an unfunded mandate that providers deploy at maximum speeds to all households simultaneously.

Moreover, as NCTA noted in its comments, the “intentional discrimination” standard provides ample room for the Commission to act upon instances of impermissible discrimination:

[I]t is NCTA’s position that discriminatory intent need not be proven with a “smoking gun,” such as documentary evidence overtly acknowledging or demonstrating discrimination, but can instead be sufficiently pled and shown with evidence including a combination of impact elements and facts such as: statistics demonstrating a pattern of discriminatory intent, the sequence of events leading to the decision, departures from normal procedures, and a consistent pattern of actions imposing much greater harm on the protected class that is unexplainable on grounds other than discriminatory ones.[85]

Indeed, in Vill. of Arlington Heights v. Metro. Hous. Dev. Corp.,[86] the Supreme Court established a legal test for determining intentional discrimination. The test requires a plaintiff to demonstrate that a discriminatory intent was a motivating factor behind the challenged action or decision.[87] To prove intentional discrimination, the Court identified several factors that can serve as evidence.  Under this test, “[d]etermining whether invidious discriminatory purpose was a motivating factor demands a sensitive inquiry into such circumstantial and direct evidence of intent as may be available.”[88] Such an analysis can include circumstantial evidence of:

• A history of discriminatory practices or a pattern of decisions that have consistently disadvantaged a protected class;[89]
• Significant departures from standard procedures, substantive norms, or established practices can indicate discriminatory intent, especially if they seem designed to disadvantage a specific group;[90]
• Statements or actions by decisionmakers during the decision-making process that reveal prejudice or bias against a protected group;[91]
• Evidence of differential treatment or disparate outcomes for similarly situated individuals from different protected groups; or[92]
• Unjustified or pretextual explanations that are implausible, inconsistent, or unsupported by facts.[93]

As the DOJ observes, while statistical evidence of patterns of discrimination cannot themselves be used as proof of discriminatory intent, they can be used as supporting evidence in such claims.[94] Critically, as noted in the section above, when dealing with claims of income-based discrimination, this means that challenges to deployment decisions must be made on the basis of bias regarding consumers at a particular income level, and cannot be divined through statistical inferences in the myriad factors that are merely correlated with income (such as education, computer ownership, adoption levels, and willingness to pay).

In sum, Section 60506 is an intentional-discrimination statute and the Commission’s rules should reflect that fact. To create a disparate impact regime would be to invite a drawn-out legal battle that would likely result in the rules being struck down.

IV.    The Commission Should Adopt Sufficient Procedural Protections

The Commission asks whether it should adopt safe harbors, rely on case-by-case inquiry into “technical or economic” feasibility issues, or both.[95] We believe that the FCC needs to establish clear and robust safe harbors and affirmative defenses to discrimination complaints. Without such safe harbors, the administration of Section 60506 would become unwieldy, as the Commission wades through what is likely to be many false positives. There are a few situations that provide prima facie evidence that a broadband provider is not impermissibly discriminating against low-income consumers, or consumers in an otherwise protected class.[96]

For instance, in areas where a provider deploys service that is adhering to obligations under federal or state subsidy programs, a provider is obviously trying to reach underserved communities. Any shortcomings in deployment in such an area are almost certainly going to be the result of technical or economic realities. Similarly, where a provider is constrained by federal or state laws regarding permitting or access to rights of way, it would be fruitless to investigate; only once a provider is actually able to deploy legally should it be subject to scrutiny under Section 60506.

Similarly, there are constrains implicit in particular technologies that would make it difficult to accurately assess discrimination in some cases.[97] For example, when examining deployment of wireless providers, spectrum availability is a major issue that can constrain a provider’s ability to deploy in certain areas. Relatedly, the nature of a particular geographic area may limit how signals propagate. Even if a wireless provider fully deploys in such areas, building density or, inversely, sparsely populated areas might appear to be underperforming. In such cases, the Commission should adopt a technological safe harbor that assumes best efforts in certain cases imply good-faith compliance with Section 60506.

Thus, not only do all providers need some form of safe harbor, given the limitations of technology, but the Commission should also employ tailored safe harbors that incorporate the unique features of both wireless and wired providers.

Moreover, safe harbors do more than merely safeguard against an unfair or inefficient process, but may become a virtual necessity if the Commission attempts to rely on a “disparate impact” standard. As USTelecom noted in its comments, related civil-rights laws invariably include safe harbors in the context of fact-dependent, complicated proceedings.[98] These well-established legal proceedings create a formal burden-shifting framework that attempts to capture the economic and business realities underlying challenged practices.[99]

The Commission has also asked whether it would be appropriate to rely on its informal consumer-complaint process as part of its enforcement of Section 60506.[100] An informal complaint process that invites input from individuals directly affected by deployment decisions can make sense in some cases, while in others, a more formal complaint process will be necessary. Even if the Commission can appropriately delineate these cases, certain procedural protections should be in place to ensure the process is not abused.

First, there should be some form of standing requirement, such that a complainant actually is in a position to obtain broadband service, but is unable to do so (or do so at “comparable speeds, capacities, latency, and other quality of service metrics in a given area, for comparable terms and conditions”[101]). Given how large the national deployment footprint is, without an injury-in-fact requirement, opening the process to third parties who lack direct interest would be unmanageable. It would burden both the Commission and providers, who we otherwise want to spend their scarce resources on further deployment. Moreover, private parties with adequate standing who believe they have valid complaints can file through an informal process that could theoretically be handled much more quickly and efficiently.

The Commission also asks whether it should adopt a private right of action or permit state and local government enforcement against broadband providers.[102] Both options are likely to prove unworkable for a number of reasons. First, states and localities are often in a position of both granting access to necessary facilities as well as granting permission for providers to deploy. A right of action for states and localities—or even a process by which states and localities can source complaints in their jurisdiction and try those complaints—would create an imbalance in the bargaining process between providers and state authorities. Those authorities could use the complaint process as a leverage tool to extract inappropriate concessions from providers as they negotiate franchising agreements and other permissions necessary for deployment in particular jurisdictions.[103] Giving them a dual role in this respect—as both a complainant that can use legal process to intervene in providers’ deployment decisions as well as a party seeking to conduct an arm’s length negotiation with providers—threatens to seriously distort deployment incentives.

Moreover, providers are responsible for managing deployment decisions in a way that inherently crosses jurisdictional barriers, particularly for large providers that cross state lines. A given locality could be in a position to complain about a provider’s deployment decision, even if that decision makes technical and economic sense across jurisdictional boundaries. A state or locality is not well-positioned to adjudicate this problem, while the FCC is extremely well-positioned to do so.

Ostensibly in the interests of completeness, the NPRM asks whether it has authority to retroactively pursue claims for digital discrimination.[104] We believe it should go without saying that this procedure should be forward looking. Nothing in Section 60506 suggests that Congress intended to give the FCC authority to pursue providers for previous deployment decisions.

V.      Conclusion

It is evident that, while the Commission possesses considerable authority to remedy intentional discrimination under Section 60506, its discretion is not without boundaries. Moreover, it should create safeguards to ensure that the complaint process does not excessively burden Commission staff or erect administrative barriers to providers’ efforts to deploy broadband.

Although “income level” is included as a protected category under Section 60506, income can be correlated with such a wide array of variables, which themselves better explain deployment and adoption, that the Commission needs to take care. Trying to construe discrimination on the basis of “income” too broadly will surely generate a large number of false positives, and will lead the Commission astray.

Moreover, Section 60506 employs language directly related to case law centered on “intentional discrimination” and further includes crucial provisions directing the Commission to consider technical and economic feasibility. This legislative framework exists against the backdrop of the Supreme Court’s expanding “major questions” doctrine. With the law and the economics taken together, it is clear that the Commission should not adopt a “disparate impact” test under Section 60506. Moreover, it is crucial to remember that “income” remains a slippery metric to judge, and attempts to use correlational proxies in a discrimination analysis are fraught. As such, claims based on income discrimination should be rooted in bias regarding particular income levels, all else equal. It is critical that Section 60506 not be used as a cudgel against providers as they attempt to balance the opportunity costs of competing deployment opportunities.

The FCC rules should also articulate a presumption of nondiscrimination in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision. This presumption should furthermore be coupled with adequate safe harbors that allow that Commission to consider defenses based on “technical and economic” feasibility in an expedited manner. Otherwise, given the economic realities discussed above, there is an unacceptably high chance that every one of a provider’s decisions will be subject to challenge, wasting the resources of both the Commission and the providers.

The largest takeaway is that adoption matters quite a bit. Indeed, one of the biggest issues affecting economic feasibility is consumers’ ability and willingness to pay. Moreover, Congress has recognized this reality in its recent legislation. The IIJA’s Broadband Equity and Access program provides more than $42 billion in grants to state programs to help them support providers and give assistance directly to users.[105] The Affordable Connectivity Program provided another $14 billion in funding to help users pay for devices and broadband connections.[106] In our estimation, the Commission stands to do the most good by championing and shepherding programs like these.

If the Commission has good evidence of intentional discrimination in the deployment of broadband, it has a role to play in preventing it. But without strong, compelling evidence of intentional discrimination, the FCC will waste scarce resources chasing bogeymen.

 

[1] Notice of Proposed Rulemaking, Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (Dec. 22, 2022) [hereinafter “NPRM”].

[2] Id. at ¶ 12.

[3] Comments of NCTA, GN Docket No. 22-69 (Feb. 21, 2023), at 4 [hereinafter “NCTA”].

[4] Id. at 6.

[5] Apply for Internet Essentials or Internet Essentials Plus From Comcast, Comcast, https://www.xfinity.com/support/articles/comcast-broadband-opportunity-program (last visited Apr. 19, 2023).

[6] Affordable Connectivity Program, AT&T, https://www.att.com/help/affordable-connectivity-program (last visited Apr. 19, 2023).

[7] Spectrum Internet for Low Income Households, Spectrum, https://www.spectrum.com/internet/spectrum-internet-assist (last visited Apr. 19, 2023).

[8] NPRM, supra note 1 at ¶ 12

[9] See, e.g., Comments of Public Knowledge, Benton Institute for Broadband and Society, and Electronic Privacy Information Center, GN Docket No. 22-69 (Feb. 21, 2023), at 52 (“Congress has again centered the focus of the Commission’s actions on getting all people access, regardless of any discriminatory treatment or intent of the provider.”) [hereinafter “Public Knowledge”]; Letter from David Brody, Lawyers’ Committee for Civil Rights Under Law, to Marlene H. Dortch, Implementing the Infrastructure and Jobs Act: Prevention and Elimination of Digital Discrimination, WC Docket No. 22-69 (Dec. 12, 2022) [hereinafter “Brody”].

[10] See, e.g., Tex. Dep’t of Hous. & Cmty. Affs. v. Inclusive Cmtys. Project Inc., 576 U.S. 519 (2015) [hereinafter “Inclusive Communities”].

[11] See, e.g., Alexander v. Sandoval, 532 U. S. 275, 280 (2001) (“[I]t is… beyond dispute—and no party disagrees—that § 601 prohibits only intentional discrimination.”).

[12] See, e.g., Inclusive Communities, supra note 10 at 533- 34 (“[A]ntidiscrimination laws must be construed to encompass disparate-impact claims when their text refers to the consequences of actions and not just to the mindset of actors, and where that interpretation is consistent with statutory purpose.”); Board of Ed. of City School Dist. of New York v. Harris, 444 U. S. 130 –141 (1979) (considering the context of a statute’s text, history, purpose, and structure in determining whether a statute encompasses disparate impact analysis).

[13] See Section 60506(a)(1), (a)(3).

[14] See, Emergency Coal. to Def. Educ. Travel v. U.S. Dep’t of Treasury, 498 F. Supp. 2d 150, 165 (D.D.C. 2007) (“Courts have repeatedly held that such ‘sense of Congress’ language is merely precatory and non-binding.”), aff’d, 545 F.3d 4 (D.C. Cir. 2008).

[15] Compare 42 U.S. Code § 2000d (“No person in the United States shall, on the ground of race, color, or national origin, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving Federal financial assistance.”) with Section 60506(b)(1) (empowering the Commission to create rules taking into account “preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin”) (emphasis added).

[16] See Section 60506(c) (“The Commission and the Attorney General shall ensure that Federal policies promote equal access to robust broadband internet access service by prohibiting deployment discrimination…”).

[17] West Virginia v. EPA, 142 S. Ct. 2587, 2607–2608 (2022); Util. Air Regul. Grp. (UARG) v. EPA, 573 U.S. 302, 324 (2014).

[18] Whitman v. Am. Trucking Ass’ns, 531 U.S. 457, 468 (2001).

[19] Broadband Equity, Access, and Deployment Program, BroadbandUSA, https://broadbandusa.ntia.doc.gov/resources/grant-programs/broadband-equity-access-and-deployment-bead-program (last visited Oct. 23, 2022).

[20] Affordable Connectivity Program, Federal Communications Commission, https://www.fcc.gov/acp (last visited Oct. 23, 2022).

[21] NPRM, supra note 1 at ¶24.

[22] NOI Reply Comments of AT&T, GN Docket No. 22-69 (Jun. 30, 2022), (“In particular, like all companies operating in a competitive marketplace, broadband providers must and do take expected demand into account, and the ‘economic feasibility’ qualifier protects their right to do so.”)

[23] Telecommunications: Broadband Deployment Is Extensive Throughout the United States, but It Is Difficult to Assess the Extent of Deployment Gaps in Rural Areas, U.S. Gov’t Accountability Off., GAO-06-426 (May 2006), https://www.gao.gov/assets/gao-06-426.pdf. [hereinafter “GAO-06-426”].

[24] Brian Whitacre & Roberto Gallardo, State Broadband Policy: Impacts on Availability, 44 Telecomm. Pol’y. 102025 (2020).

[25] Tonny J. Oyana, Exploring Geographic Disparities in Broadband Access and Use in Rural Southern Illinois: Who’s Being Left Behind?, 28 Gov’t. Info. Q. 252 (2011).

[26] GAO-06-426, supra note 23.

[27] Id.

[28] Whitacre & Gallardo, supra note 24.

[29] Juan Rendon Schneir & Yupeng Xiong, A Cost Study of Fixed Broadband Access Networks for Rural Areas, 40 Telecomm. Pol’y. 755 (2016).

[30] GAO-06-426, supra note 23.

[31] Brian Whitacre, Sharon Strover, & Roberto Gallardo, How Much Does Broadband Infrastructure Matter? Decomposing the Metro–Non-Metro Adoption Gap with the Help of the National Broadband Map, 32 Gov’t Info. Q. 261 (2015).

[32] Broadband: National Strategy Needed to Guide Federal Efforts to Reduce Digital Divide, U.S. Gov’t Accountability Off., GAO-22-104611 (May 31, 2022) [hereinafter “GAO-22-104611”].

[33] Id. See also, How Do Speed, Infrastructure, Access, and Adoption Inform Broadband Policy?, Pew Research Center (Jul. 7, 2022), https://www.pewtrusts.org/en/research-and-analysis/fact-sheets/2022/07/how-do-speed-infrastructure-access-and-adoption-inform-broadband-policy (“nearly 1 in 4 Americans do not subscribe to a home broadband connection, even where one is available”).

[34] Michelle Cao & Rafi Goldberg, New Analysis Shows Offline Households Are Willing to Pay $10-a-Month on Average for Home Internet Service, Though Three in Four Say Any Cost is Too Much, National Telecommunications and Information Administration (Oct. 6, 2022), https://www.ntia.doc.gov/blog/2022/new-analysis-shows-offline-households-are-willing-pay-10-month-average-home-internet.

[35] Kenneth Flamm & Anindya Chaudhuri, An Analysis of the Determinants of Broadband Access, 31 Telecomm. Pol’y. 312 (2007).

[36] Id.

[37] Victor Glass & Stela K. Stefanova, An Empirical Study of Broadband Diffusion in Rural America, 38 J. Reg. Econ. 70 (Jun. 2010).

[38] Christopher G. Reddick, Roger Enriquez, Richard J. Harris, & Bonita Sharma, Determinants of Broadband Access and Affordability: An Analysis of a Community Survey on the Digital Divide, 106 Cities 102904 (2020).

[39] Glass & Stefanova, supra note 37 at 70.

[40] GAO-22-104611, supra note 32.

[41] Alison Powell, Amelia Bryne, & Dharma Dailey, The Essential Internet: Digital Exclusion in Low-Income American Communities, 2 Pol’y & Internet 161 (2010).

[42] Oyana, supra note 25.

[43] GAO-06-426, supra note 23.

[44] GAO-22-104611, supra note 32.

[45] NPRM, supra note 1 at ¶ 66.

[46] See, e.g., Notice of Inquiry, Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (2022) (“If underlying cost or geographic hurdles exist in conjunction with demand in an area that makes it unprofitable, how should the Commission address such a situation?”).

[47] Public Knowledge, supra note 9 at 45 (“In many cases, a provider has the choice to build out and provide service in one area, or another. It will likely choose to build out in the more profitable area, even if it could break even or turn a profit serving the other, as well.”)

[48] See, e.g., N. Gregory Mankiw, Principles of Microeconomics, 9^th ed. (2021) (“The opportunity cost of an item is what you give up to get that item. When making any decision, decision makers should take into account the opportunity costs of each possible action.”).

[49] Public Knowledge, supra note 9 at 45 (“determinations of economic feasibility also cannot take into account opportunity costs”).

[50] NPRM, supra note 1 at ¶ 66.

[51] Id.

[52] Eric Fruits & Kristian Stout, The Income Conundrum: Intent and Effects Analysis of Digital Discrimination, Int’l Ctr. for L. & Econ. (Nov. 14, 2022), available at https://laweconcenter.org/wp-content/uploads/2022/11/The-Income-Conundrum-Intent-and-Effects-Analysis-of-Digital-Discrimination.pdf.

[53] Declaration for Glenn Woroch, NOI Reply Comments of AT&T, supra note 22.

[54] T. Randolph Beard & George S. Ford, Digital Discrimination: Fiber Availability and Speeds, by Race and Income, Phoenix Ctr. for Advanced Legal & Econ. Pol’y Stud., Phoenix Ctr. Pol’y Paper No. 58 (Sep. 2022), https://phoenix-center.org/pcpp/PCPP58Final.pdf.

[55] Garson O’Toole, If You Torture the Data Long Enough, It Will Confess, Quote Investigator (Jan. 18, 2021), https://quoteinvestigator.com/2021/01/18/confess.

[56] Comments of CEI, GN Docket No. 22-69 (Feb. 21, 2023), at 8.

[57] NPRM, supra note 1 at ¶ 12.

[58] Public Knowledge, supra note 9 at 52 (“Congress has again centered the focus of the Commission’s actions on getting all people access, regardless of any discriminatory treatment or intent of the provider.”); see also, Brody, supra note 9.

[59] Ricci v. DeStefano, 557 U.S. 557, 577 (2009) [hereinafter “Ricci”].

[60] Id. (Intentional discrimination cases “present the most easily understood type of discrimination…[that] occur[s] where [a party[ has treated [a] particular person less favorably than others because of a protected trait.”).

[61] Inclusive Communities, supra note 10 at 528–29.

[62] See Public Knowledge, supra note 9 at 50-53.

[63] Id. at 5-40.

[64] See Section 60506(a)(1), (a)(3).

[65] See, Emergency Coal. to Def. Educ. Travel v. U.S. Dep’t of Treasury, 498 F. Supp. 2d 150, 165 (D.D.C. 2007) (“Courts have repeatedly held that such ‘sense of Congress’ language is merely precatory and non-binding.”), aff’d, 545 F.3d 4 (D.C. Cir. 2008).

[66] See Section 60506(c) (“The Commission and the Attorney General shall ensure that Federal policies promote equal access to robust broadband internet access service by prohibiting deployment discrimination…”).

[67] 167 Cong. Rec. 6046 (2021).

[68] 167 Cong. Rec. 6053 (2021).

[69] See, e.g., West Virginia v. EPA, 142 S. Ct. 2587 (2022); Util. Air Regul. Grp. (UARG) v. EPA, 573 U.S. 302 (2014).

[70] West Virginia v. EPA, 142 S. Ct. at 2607–2608; UARG, 573 U.S. at 324.

[71] Whitman v. Am. Trucking Ass’ns, 531 U.S. 457, 468 (2001).

[72] Inclusive Communities, supra note 10 at 534.

[73] 42 U.S.C. § 3604(a) (emphasis added).

[74] Inclusive Communities, supra note 10 at 534.

[75] Id.

[76] Id. at 534-35.

[77] Alexander v. Sandoval, 532 U.S. 275, 280 (2001).

[78] 42 U.S.C. §2000d (emphasis added).

[79] Public Knowledge, supra note 9 at 54.

[80] Inclusive Communities, supra note 10 at 533 (emphasis added).

[81] Id. at 521–22 (“Courts should avoid interpreting disparate-impact liability to be so expansive as to inject racial considerations into every housing decision. These limitations are also necessary to protect defendants against abusive disparate-impact claims.”).

[82] Id.

[83] Section 60506 (emphasis added).

[84] Ricci, supra note 59 at 557.

[85] NCTA, supra note 3 at 21.

[86] 429 U.S. 252, 266-67 (1977).

[87] Id. at 265 (“Proof of racially discriminatory intent or purpose is required to show a violation of the Equal Protection Clause.”).

[88] Id. at 266.

[89] Id. at 266-67.

[90] Id. at 267.

[91] Id. at 268.

[92] See, Texas Dep’t of Cmty. Affs. v. Burdine, 450 U.S. 248, 258–59 (1981). Note that the last two factors listed in this and the subsequent footnote are part of the McDonnell Douglas framework, McDonnell Douglas Corp. v. Green, 411 U.S. 792, 798, 93 S. Ct. 1817, 1822, 36 L. Ed. 2d 668 (1973). Technically, the Arlington factors are generally used when analyzing group discrimination and the McDonnell Douglas factors are used when analyzing discrimination against individuals. Section 60506 might, however, be plausibly read as permitting either approach to intentional discrimination in deployment decisions.

[93] See, Reeves v. Sanderson Plumbing Prod. Inc., 530 U.S. 133, 143–44 (2000).

[94] US Dep. of Justice, Title VI Legal Manual: Proving Discrimination – Intentional Discrimination, https://www.justice.gov/crt/fcs/T6Manual6 (“While statistical evidence is not required to demonstrate intentional discrimination, plaintiffs often successfully use statistics to support, along with other types of evidence, a claim of intentional discrimination.”).

[95] NPRM, supra note 1 at ¶ 35-36.

[96] Indeed, as NCTA notes in its comments, a safe harbor of this kind would give effect to Congress’ requirement that the FCC acknowledge constraints on deployment relating to “technical or economic feasibility.” NCTA, supra note 3 at 25-30.

[97] See, e.g., Comments of T-Mobile, GN Docket No. 22-69 (Feb. 21, 2023), at 30-31.

[98] Comments of USTelecom, GN Docket No. 22-69, (Feb. 21, 2023), at 33-34.

[99] Id.

[100] NPRM, supra note 1 at ¶ 52.

[101] Section 60506(a)(2).

[102] NPRM, supra note 1 at ¶ 76.

[103] These possibilities open the door for what public-choice economists call “rent extraction,” whereby public officials use the ability to control entry into a market for their own benefit. See Fred McChesney, Money for Nothing: Politicians, Rent Extraction, and Political Extortion (1997). See also, ICLE Ex Parte on Sec. 621, MB Docket No. 05-311 (Jul. 18, 2019), available at https://laweconcenter.org/wp-content/uploads/2019/07/ICLE-Comments-on-Implementation-of-Section-621a1-of-the-Cable-Communications-Policy-Act-of-1984.pdf (arguing that local and state franchising authorities often abuse their authority to get in-kind contributions from cable providers far beyond the 5% cost limit).

[104] NPRM, supra note 1 at ¶ 92.

[105] Broadband Equity, Access, and Deployment Program, BroadbandUSA, https://broadbandusa.ntia.doc.gov/resources/grant-programs/broadband-equity-access-and-deployment-bead-program (last visited Oct. 23, 2022).

[106] Affordable Connectivity Program, Federal Communications Commission, https://www.fcc.gov/acp (last visited Oct. 23, 2022).

 

 

ICLE Director of Innovation Policy Kristian Stout was interviewed by RFD-TV for a story item about the challenges involved in connecting rural areas to broadband internet.

 

 

One of the threats that could affect the efficacy of this program could be different state authorities not necessarily focusing on people who have traditionally been very difficult to connect to the internet but looking at lower hanging fruit that it’s easier to connect, like people who

might have slower than extremely fast but are faster than what we consider nonexistent broadband service. There are a number of hurdles that have just traditionally existed everywhere in the United States for broadband deployment. These include things like municipal permitting, getting rights of way, and then one of the largest drivers cost is access to utility poles across the United States. There are some more complicated problems that go into accessing these poles around whether they’re privately-owned or whether they’re owned by municipalities and co-ops, which can easily explode costs for a particular deployment and make it so that the money that the federal government is directing to reach these remote areas is not being fully-used to reach these people but is instead being wasted.

The infrastructure bill that President Joe Biden signed in November 2021 included a provision requiring the Federal Communications Commission to prevent discrimination in access to broadband internet based on race, ethnicity, color, religion, or national origin.

Read the full piece here.

Executive Summary

Section 60506 of the Infrastructure Investment and Jobs Act (“IIJA”)—signed by President Joe Biden on Nov. 15, 2021—requires the Federal Communications Commission (“FCC”) to adopt final rules facilitating equal access to broadband Internet. More specifically, the statutory text directs the FCC to prevent discrimination in broadband access based on income level, race, ethnicity, color, religion, or national origin, while also directing the Commission to consider issues of technical and economic feasibility.

Evaluating digital discrimination based on race, ethnicity, color, religion, or national origin should be relatively straightforward. But Section 60506 adds income level as a protected class. This presents what we call the “income conundrum.” It is virtually impossible to disentangle the factors affecting economic feasibility from factors correlated with membership in this particular protected class.

In this issue brief, we focus on the tension between the goals of preventing discrimination based on income level and ensuring that broadband-deployment projects are economically feasible, as well as the relevant distinctions between the application of intent-based or effects-based tests of discrimination. We find that some tests of so-called “digital discrimination” on the basis of income level—particularly in the context of effects-based “disparate impact” tests—can be misleading, and their application could be counterproductive.

First, it is important to note that Section 60506 refers to discrimination in the provision of broadband access and not to levels or rates of broadband adoption. While access is a necessary precondition to adopt broadband services, policymakers should be cautious not to infer that lack of adoption is necessarily caused by lack of access. Research finds that consumer income and the affordability of broadband services are key factors influencing whether those who enjoy broadband access will ultimately adopt broadband service. Other factors broadly correlated with income—such as age, educational attainment, and home-computer ownership and usage—similarly affect broadband-adoption decisions.

Thus, the use of income as a heuristic to determine whether providers’ deployment decisions are discriminatory is inherently fraught. Income level will influence consumer decisions to adopt broadband, which in turn affects providers’ ability to deploy to a given area. Therefore, while correlations between income and broadband adoption certainly can be found, research to date does not find evidence that—all else being equal—broadband providers intentionally discriminate against similarly situated groups on the basis of income, race, or other protected characteristics when it comes to broadband access.

Further, it is broadly agreed that Section 60506’s reference to “economic feasibility” refers to profitability—e.g., to whether broadband providers can earn a competitive return from their investments in deployment. Because broadband providers’ investment decisions are always constrained by their limited resources, they must prioritize deployment projects. As a consequence, they must decide not only whether a given project is likely to be profitable, but also how profitable it is likely to be relative to all other potential projects.

The expected profitability of any given broadband-deployment decision depends on a range of cost and demand factors. On the cost side, providers must consider a given territory’s population density and terrain, as well as such factors as state and local rules and taxes. On the demand side, the propensity of consumers who would be served by the deployment to both adopt and purchase broadband are key factors. Thus, the general willingness within a given territory to adopt broadband factors into deployment decisions. Where there is insufficient willingness to purchase broadband service, deployment may not be profitable.

Population density is generally acknowledged as the most important cost factor driving broadband-deployment decisions. The U.S. Government Accountability Office reports that population density is the cost factor most cited as “a critical determinant of companies’ deployment decisions,” a conclusion supported by academic research. Population density also figures into the demand side of the equation, as the GAO notes that low-density rural areas often struggle to “aggregate sufficient demand” to purchase broadband service. Because population density also can be correlated with demographic factors like income, race, age, educational attainment, and home-computer use, however, there may be a temptation for policymakers to infer digital discrimination in deployment decisions that were, in fact, based on population density or other permitted cost and demand considerations.

Further complicating the evaluation of digital-discrimination claims based on income is that, not only is income a key factor influencing whether a given consumer will adopt broadband, but it is also highly correlated with race, ethnicity, national origin, age, education level, and home-computer ownership and usage. Any rules promulgated under Section 60506 that fail to recognize this “income conundrum” will invite costly and time-consuming litigation based on allegations of digital discrimination either where it does not exist or where it is excused by economic-feasibility considerations. Moreover, this threat of litigation could hinder, rather than foster, further broadband deployment.

The U.S. Supreme Court has established tests governing when it is appropriate to conduct an effects-based “disparate impact” analysis in the context of discrimination law. Applying this rubric to Section 60506, we find that it lacks “results-oriented language.” The prohibition against digital discrimination “based on income level, race, ethnicity, color, religion, or national origin” would therefore apply only in cases of intentional discrimination in deployment decisions.  Mere statistical correlation between deployment and protected characteristics is insufficient to support a finding of discrimination.

Finally, to close the so-called “digital divide,” it would be wise to avoid creating inefficient bureaucratic processes through which broadband providers would be forced to defend economically justified deployment decisions. For this reason, FCC rules should articulate a presumption of non-discrimination, in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision. Direct user support—such as that offered by the Affordable Connectivity Program and programs operated under the Universal Service Fund—is a much more direct and economically efficient way to help close the “adoption gap” component of the digital divide.

I. Introduction

As part of 2021’s Infrastructure Investment and Jobs Act (“IIJA”), Congress tasked the Federal Communications Commission (“FCC”)  with investigating and remedying “digital discrimination” in broadband deployment.[1] The law directs the Commission to adopt rules that “facilitate equal access to broadband internet access service,” which is defined as “preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin.”[2]  To this end, the Commission issued a Notice of Inquiry (“NOI”)[3] as a first step toward an ultimate rulemaking.[4]

The NOI states that “one of the Commission’s foremost goals is to ensure that every person in the United States has equal access to high-quality, affordable broadband internet access service… Every person across our Nation deserves—and must have—equal access to this crucial technology in the increasingly digital world; a person’s zip code should not determine their destiny.”^[5]

But Section 60506 of the IIJA[6] creates a tension between the goals of encouraging greater broadband deployment and remedying alleged discrimination; indeed, some efforts to address the latter concern could result in slower investment in buildout. Importantly, the NOI does not focus on extending broadband deployment to the truly unserved—i.e., to those who lack any broadband Internet options at all.^[7] In fact, the word “unserved” does not appear in the NOI at all, while the NOI instead declares that its target is the “underserved.”^[8] But rather than define “underserved” consumers by reference to their relative inability to access broadband Internet service, the NOI defines the set as those who are members of categories that “have been historically underserved, marginalized, or adversely affected by persistent poverty or inequality” because of their income level, race, color, religion, or national origin.^[9] The NOI therefore includes in the ranks of the “underserved” individuals who do have the ability to access broadband service, although potentially at slower speeds than some of their neighbors, or who have otherwise opted not to adopt broadband service.

Getting faster Internet to those who live where broadband service already exists, or assisting them in paying for access to the service that already exists, are fundamentally different problems than that faced by Americans who lack Internet access because they live in geographic areas without broadband infrastructure. Moreover, onerous or poorly implemented requirements that seek to curtail “digital discrimination” may be more likely to generally slow further broadband deployment than to speed it. An overly broad enforcement regime—one that sought to apply effects-based “disparate impact” tests or that operated from a presumption of discrimination—could force providers to constantly justify everything from decisions around actual deployment to decisions regarding whether to bid on particular deployment programs offered by governments.

Indeed, were the Commission to pursue economically ill-considered rules to curtail alleged “digital discrimination,” it could lead to intractable litigation. As we discuss below, the U.S. Supreme Court has in the recent past imposed limits on how “disparate impact” tests may be imposed by legislation.[10] These limits apply even to sectors with a demonstrated history of discriminatory redlining, such as housing.

It is undoubtedly important to examine patterns of deployment to discover how best to connect underserved communities. But if we are to overcome impediments that stand in the way of reaching every potential broadband consumer, it is essential that the FCC carefully consider how and why investment decisions are made in broadband markets.^[11]

In short, we generally question the NOI’s framing of broadband-connectivity issues as being primarily or even substantially a matter of “discrimination.” Indeed, the IIJA’s project to eliminate “digital discrimination of access based on income level”^[12] may not usefully forward efforts to connect the underserved at all. While there remains much work to be done to achieve the goal of universal connectivity, the FCC is already well-aware of the technical, economic, regulatory, and geographical issues that can impede deployment. The Commission should continue the important work it is already doing to address those issues and should ensure that its implementation of Section 60506 is focused on remedying cases where there is strong evidence of intentional discrimination against consumers based on protected characteristics.

In Part II, we analyze the relevant legal concerns for the Commission, should it seek to undertake a “disparate impact” rulemaking. In Part III, we discuss the theoretical and practical challenges that attend treating “income level” as a protected category. We address the economics of “access vs. adoption” and how, if not treated carefully, the issue would substantially skew any effects-based analysis of broadband-deployment patterns. We also discuss the economics of broadband deployment, including the factors that best explain deployment patterns. Part IV concludes with a brief set of policy recommendations.

II. Disparate Impact & Digital Discrimination: A Legal Analysis

Section 60506 requires that:

[T]he Commission shall adopt final rules to facilitate equal access to broadband internet access service, taking into account the issues of technical and economic feasibility presented by that objective, including… preventing digital discrimination of access based on income level, race, ethnicity, color, religion, or national origin; and… identifying necessary steps for the Commissions to take to eliminate discrimination… .[13]

Pursuant to this, the FCC asks in its NOI for:

… comment on how we should understand when digital discrimination is “based on” one of the listed characteristics. Does the term “based on” require discriminatory intent? If so, how would we determine the presence or absence of discriminatory intent? Would such an approach be practicably difficult to enforce? Alternatively or in addition, should we establish a “discriminatory effects” or disparate impact test? [14]

Advocates who support greater FCC authority to pursue alleged digital discrimination argue that the use of impermissible factors has contributed to underinvestment in minority communities and that “digital redlining has left unserved and underserved neighborhoods on the wrong side of the digital divide.”[15] Thus, a number of comments submitted to the record have called for the FCC to employ an effects-based “disparate impact” analysis under Section 60506.[16] As we discuss below, however, both the structure of Section 60506 and the Supreme Court’s established jurisprudence on disparate-impact analysis suggest that it would be much more reasonable for the Commission to construe Section 60506 as directing an analysis of intentional discrimination in deployment.

Statutes that define impermissible discrimination, such as the Civil Rights Act of 1964, can be analyzed legally either as addressed toward explicit discriminatory intent, referred to as “discriminatory treatment,” or toward behavior inferred from discriminatory effects, such as the “disparate impact” that the challenged behavior or policy has on a protected class.[17] A case involving discriminatory treatment is somewhat more straightforward,[18] insofar as it demands evidence demonstrating that decisions adversely affecting some protected class were made because of bias toward members of that class. In this context, where deployment decisions are made on the basis of discriminatory intent, the Commission is on much firmer legal ground to pursue them.

By contrast, were the Commission to adopt a “disparate impact” assessment as part of Section 60506, it would face an uphill legal climb. Among the primary justifications for disparate-impact analysis is to remedy those historical patterns of de jure segregation that left an indelible mark on minority communities.[19] While racial discrimination has not been purged from society, broadband only became prominent in the United States well after all forms of de jure segregation were made illegal, and after Congress and the courts had invested decades in rooting out impermissible de facto discrimination. Any policy intended to tackle disparate impact in broadband deployment needs to take this history into account.

Moreover, there is little evidence that IIJA’s drafters intended the law to be read so broadly. The legislative record on Section 60506 is exceedingly sparse, containing almost no discussion of the provision beyond assurances that “broadband ought to be available to all Americans,”[20] and also that the provision was not to be used as a basis for the “regulation of internet rates.”[21] Given that sparse textual basis, reading Section 60506 as granting the Commission expansive powers to serve as a broadband civil-rights czar could also run afoul of the “major questions” doctrine.[22] That doctrine requires Congress “to speak clearly if it wishes to assign to an agency decisions of vast ‘economic and political significance.’”[23]

More specifically, it does not appear that Section 60506 can be reasonably construed as authorizing disparate-impact analysis. While the Supreme Court continues to uphold disparate-impact analysis in the context of civil-rights law, it has recently imposed some important limitations. For example, in Texas Department of Housing & Community Affairs v. The Inclusive Communities Project, Inc., the Court upheld the disparate-impact doctrine, but noted that disparate-impact claims arise under statutes explicitly directed “to the consequences of an action rather than the actor’s intent.”[24] For example, in the Fair Housing Act, Congress made it unlawful:

To refuse to sell or rent after the making of a bona fide offer, or to refuse to negotiate for the sale or rental of, or otherwise make unavailable or deny, a dwelling to any person because of race, color, religion, sex, familial status, or national origin.[25] [Emphasis added.]

The Court noted that the presence of language like “otherwise make unavailable” is critical to construing a statute as demanding an effects-based analysis.[26] Such phrases, the Court found, “refer[] to the consequences of an action rather than the actor’s intent.”[27] Further, the structure of a statute’s language matters:

The relevant statutory phrases… play an identical role in the structure common to all three statutes: Located at the end of lengthy sentences that begin with prohibitions on disparate treatment, they serve as catchall phrases looking to consequences, not intent. And all [of these] statutes use the word “otherwise” to introduce the results-oriented phrase. “Otherwise” means “in a different way or manner,” thus signaling a shift in emphasis from an actor’s intent to the consequences of his actions.[28]

The Court reached this holding after reviewing a number of its previous decisions developing the distinction between effects-based and intent-based interpretations of a law. Particularly relevant here, in Univ. of Texas Sw. Med. Ctr. v. Nassar, the Court considered statutory language that prohibited discrimination “because of … age” and found that it only prevented intentional discrimination.[29] The Court also noted that, in previous cases, it had construed “because of” to mean “‘based on’ and that ‘based on’ indicates a but-for causal relationship.”[30]

Further, even where disparate analysis is appropriate, the Court held that it is significantly constrained by the need to ensure that the free-enterprise system continues to function:

[Supreme Court precedent] also teach[es] that disparate-impact liability must be limited so… regulated entities are able to make the practical business choices and profit-related decisions that sustain a vibrant and dynamic free-enterprise system. And before rejecting a business justification…a court must determine that a plaintiff has shown that there is “an available alternative … practice that has less disparate impact and serves the [entity’s] legitimate needs.”[31] [Emphasis added.]

In practice, this means that lower courts are free to probe a disparate-impact claim rigorously in order to avoid such claims becoming a club to wield against regulated entities.[32] It also suggests that, in a context such as Section 60506’s proscriptions against digital discrimination, they may not be so broad as to render it impossible for broadband providers to make effective decisions about which deployment projects are economically feasible.

Thus, as Section 60506 was drafted without “results-oriented language”[33] and instead frames the prohibition against digital discrimination as “based on income level, race, ethnicity, color, religion, or national origin,”[34] this would put the rule squarely within the realm of prohibitions on intentional discrimination.[35] That is, to be discriminatory, the decision to deploy or not to deploy must have been intentionally made because of the protected characteristic. Mere statistical correlation between deployment and protected characteristics is insufficient.

In enacting the IIJA, Congress was undoubtedly aware of the Court’s history with disparate-impact analysis. Had it chosen to do so, it could have made the requirements of Section 60506 align with the requirements of that precedent. But it chose not to do so, thereby reinforcing that it intended the FCC to have some discretion, but to err on the side caution when declaring practices an impermissible form of discrimination.

This is not to say that Section 60506 has no effect. As mentioned above, it can be reasonably read to encompass intentional discrimination, given appropriate evidence. Further, the means available to the FCC to remedy undesirable patterns of deployment are manifold. The only options rendered off the table would be requirements that are technologically or economically infeasible, such as an unfunded mandate that providers deploy at maximum speeds to all households simultaneously. As discussed further below, the FCC also has broad authority over various funding programs that it could use to generate both user subsidies and provider incentives to deployment, which could go a long way toward closing the digital divide.

III. Using Income as a Measure of Digital Discrimination

Evaluating digital discrimination based on race, ethnicity, color, religion, or national origin should be relatively straightforward. But Section 60506 adds income level as a protected class. This presents what we call the “income conundrum.” It is virtually impossible to disentangle the factors affecting economic feasibility from factors correlated with membership in this particular protected class.

The expected profitability of any given broadband-deployment decision will hinge on a range of cost and demand factors. On the cost side, providers must consider a given territory’s population density and terrain, as well as such factors as state and local rules and taxes. On the demand side, the propensity of consumers who would be served by the deployment to both adopt and purchase broadband are key factors. Thus, the general willingness within a given territory to adopt broadband weighs heavily in providers’ deployment decisions. Where there is insufficient willingness to purchase broadband service, deployment may not be profitable.

As we explain below, economic feasibility is essentially synonymous with return on investment. While income may be correlated with some factors that drive decisions to deploy, animus against potential customers with protected characteristics is almost certainly not an important factor in deployment decisions. Thus, even if the Commission engages in an intent-based analysis under Section 60506, there are many economic-feasibility factors it needs to take into consideration, which we set forth below.

A.   Access vs. adoption

The text of Section 60506 refers to discrimination in the provision of broadband access and not to levels or rates of broadband adoption. While access is a necessary precondition to adopt broadband services, policymakers should be cautious not to infer that lack of adoption is necessarily caused by lack of access. Research finds that consumer income and the affordability of broadband services are key factors influencing whether those who enjoy broadband access will ultimately adopt broadband service. Other factors that may be broadly correlated with income—such as age, educational attainment, and home-computer ownership and usage—similarly influence broadband-adoption decisions. Thus, comparing relative levels of income in territories that are, or are not, chosen for broadband deployment is a poor heuristic to determine whether providers’ deployment decisions are discriminatory. Local income will influence consumer decisions to adopt broadband, which in turn affects whether it will be economically feasible for providers’ to deploy to a given area.

The Commission therefore should not summarily conclude that deployment patterns correlated with income are a form of impermissible discrimination. As explained above, in order to run afoul of Section 60506, the Commission should insist that challenged deployment decisions are directly attributable to an intentional choice not to serve consumers who are members of a protected category. To apply analysis that ignores intent and instead looks at whether members of such categories are impacted disparately by deployment decisions would threaten to create an unmanageable and open-ended legal standard that ultimately slows deployment overall.

Broadband access alone also may not be sufficient to drive greater rates of broadband adoption. For example, Brian Whitacre and his co-authors found that, while the reduced levels of broadband access in rural areas explained 38% of the rural-urban broadband-adoption gap in 2011, differences in other general characteristics—such as income and education—explain “roughly half of the gap.”[36] A report by the U.S. Government Accountability Office concluded that “even where broadband service is available … an adoption gap may persist due to the affordability of broadband and lack of digital skills.”[37] The GAO report notes that nearly one-third of those with access to broadband do not subscribe to it and that “lower-income households have lower rates of home broadband subscriptions.”[38]

The price of broadband services is another significant factor that affects adoption. A National Telecommunications and Information Administration survey of Internet use identified “affordability as a driving factor around why some households continue to remain offline, confirming that cost of service is an essential part of increasing Internet adoption.”[39] The survey reported that the average price that offline households wanted to pay for Internet access was approximately $10 per month, and about 75% of households gave $0 or “none” as their answer. Kenneth Flamm and Anindya Chaudhuri’s empirical research finds that broadband price is a “statistically significant driver” of broadband demand.[40] They conclude that broadband-price declines in the early 2000s explain “some portion” of increased broadband adoption.[41] Victor Glass and Stela Stefanova’s empirical study indicates that higher prices “depress” demand for broadband.[42]

Price sensitivity is closely tied to income. Christopher Reddick and his co-authors concluded that “[i]ncome is a major factor that is likely to influence broadband adoption especially where technology is available.”[43] Glass and Stefanova find broadband service to be a normal good, which means that increased incomes are associated with increased broadband adoption—a finding consistent with previous research.[44] Similarly, the GAO reports: “A recent nationally representative survey by Consumer Reports reported that nearly a third of respondents who lack a broadband subscription said it was because it costs too much, while about a quarter of respondents who do have broadband said they find it difficult to afford.”[45] Alison Powell and her co-authors report that a significant number of low-income Americans engage in a cycle of broadband adoption and “un-adoption,” in which they adopt broadband and then drop it for financial or other reasons, and then re-adopt when circumstances improve for them.[46]

In addition to price and income guiding a household’s broadband-adoption decisions, other factors are also relevant. Tonny Oyana’s empirical research concludes that income, the share of a population who are senior citizens, and the share with some college education are the “three most important demand-side factors” affecting both access and adoption.[47] The GAO reports that “[o]ther barriers include lack of digital skills,” citing a 2016 Pew Research Center report finding that “about half of American adults were hesitant when it comes to new technologies and building their digital skills.”[48]

It can be argued that the gap between broadband access and adoption may present the real digital divide. That is, large numbers of American who have access to broadband do not adopt it, and some who do may “un-adopt” it. While income is a key factor in a household’s adoption choice, it is only one of several important factors, which also include age, educational attainment, and home-computer ownership and usage—each of which is, in turn, also correlated with income. As discussed below, deployment decisions are based on many factors, including a territory’s projected broadband adoption. If firms do not expect sufficient levels of adoption, then deployment may be unprofitable. It would be a mistake to infer that income discrimination in deployment causes low rates of broadband adoption in low-income communities when low income itself—and other factors correlated with income—may be a primary cause of low rates of broadband adoption.

B.   Equal access and economic feasibility

Section 60506 requires the Commission to take account of “issues of technical and economic feasibility.” There is broad consensus that “economic feasibility” here refers to profitability.[49] More precisely, a project is economically feasible if it provides an adequate return on investment (ROI). Like all firms, broadband providers have limited resources with which to make their investments. While profitability is a necessary precondition for investment, not all profitable investments can be undertaken. Among the universe of potentially profitable projects, firms are likely to give priority to those that promise greater returns on investment relative to those with lower ROI. Thus, any evaluation of potential digital discrimination must examine not only whether a given deployment is likely to be profitable, but also how its expected returns compare to other investment opportunities.

Returns on investment in broadband depend on several factors. As noted earlier, population density, terrain, regulations, and taxes are all important cost factors, while a given consumer population’s willingness to adopt and pay for broadband are key demand-related factors.

In addition to these cost and demand factors, the timing of both investment and adoption affect the ROI of a deployment investment. Consider two hypothetical investments, shown in Table I below. Both Deployment A and Deployment B require the same initial investment of $100 million and both ultimately generate the same income of $44 million a year. However, Deployment B has a slower adoption rate. Not only does Deployment B generate lower income over the hypothetical 20-year life of the investment, but its ROI is less than half that of deployment A. While both deployments are profitable and both eventually generate the same annual income, relative to deployment A, deployment B is unprofitable.

Table 1: How Timing Affects ROI in Hypothetical Deployments A and B

Source: Authors

Because the timing of investment returns is critical in a firm’s deployment decisions, local regulations that slow broadband buildout can have significant effects on a deployment investment’s ROI.

C.   Density in broadband deployment

By far, population density is widely acknowledged to be the most important cost factor driving broadband-deployment decisions. For example, the GAO reports that population density is the “most frequently cited cost factor” and “a critical determinant of companies’ deployment decisions.”[50]

Academic research supports the GAO’s conclusions. For example, Brian Whitacre and Roberto Gallardo describe population density as one of “the main determinants of Internet availability.”[51] Similarly, Oyana—citing earlier research—concludes that “[l]imited broadband access is common in rural communities because of geographic remoteness and low population density.”[52] Juan Schneir and Yupeng Xiong identify that firms are more likely to deploy broadband in urban and suburban areas, rather than rural areas, due to both cost and demand factors. They note this is “because of the high density of users willing to pay for high-speed broadband services and the relatively low network rollout costs in urban and suburban areas.”[53] Consistent with Schneir & Xiong’s conclusion, the GAO also finds that population density is an important factor on the demand side of deployment decisions. In particular, the GAO concludes that it is more difficult to “aggregate sufficient demand” to pay for broadband service in low-density rural areas.[54]

Several other factors also affect the profitability of broadband-deployment investments. The GAO identifies terrain as an important factor, concluding that “it is more costly to serve areas with low population density and rugged terrain with terrestrial facilities than it is to serve areas that are densely populated and have flat terrain.”[55] The GAO also reports that the cost of “backhaul” can affect broadband deployment to rural areas. “Backhaul” is the cost of routing Internet traffic from rural areas to larger cities in order to connect to a major Internet backbone provider.[56] Whitacre & Gallardo find that state-level broadband-funding programs are associated with a modest increase (1.2–2.0 percentage points) in broadband availability.[57] On the demand side, the GAO reports that “demand will be greater in areas where potential customers are familiar with computers and broadband.”[58]

Population density is also correlated to varying degrees with such demographic factors as income, race, age, educational attainment, and home-computer use. Thus, one should be cautious about inferring digital discrimination based on such factors from deployment decisions that are likely to be based on population density.

D.   The income conundrum

As noted above, the evaluation of digital-discrimination claims based on income level is complicated by the fact that income is a key factor—and perhaps the key factor—affecting broadband adoption. Moreover, it is also correlated with race, ethnicity, national origin, age, education level, and home-computer ownership and usage. Adoption of Section 60506 rules that do not recognize this “income conundrum” will invite costly and time-consuming disparate-impact litigation alleging digital discrimination, both where no such discrimination exists and where it is excused by economic-feasibility considerations. The threat of litigation from injudicious rulemaking also may hinder, rather than foster, further broadband deployment.

Randolph Beard and George Ford report:[59]

Survey evidence and empirical research on broadband adoption show that income has a demonstrable effect on demand. Also, empirical research and survey evidence show that some racial minorities—in particular, Hispanic, Black, and Native Americans—are less likely to adopt fixed-service broadband services in the home. Moreover, income is correlated with many factors that affect demand including, among other things, employment, education levels, and housing stability, which makes the determination of “income discrimination” extremely difficult since it is the discriminatory treatment of low-income households, and not these other correlated factors, that is mentioned in the statute. Minority population shares and income levels are also correlated with population density, which affects the cost of network deployment and upgrades. Quantifying “digital discrimination” is, therefore, an extremely challenging endeavor.

In addition to the factors identified by Beard & Ford, income is correlated with several factors associated with broadband adoption. For example, Pew reports that, among lower-income adults:[60]

• 41% do not have a desktop or laptop computer and a majority are not tablet owners. Pew indicates that each of these technologies is “nearly ubiquitous” among adults in households earning more than $100,000 annually.
• 13% of adults with annual household incomes below $30,000 do not have access to any of these technologies at home (e., home-broadband services, a smartphone, a desktop or laptop computer, or a tablet); by contrast, only 1% of adults from households making more than $100,000 a year report a similar lack of access.
• 27% of adults living in households earning less than $30,000 annually are smartphone-only Internet users, meaning they own a smartphone but do not have broadband Internet at home.

Some argue that broadband has become more of a necessity over time,[61] akin to utilities for home heating, cooling, and cooking.[62] According to Ryan Finnigan and Kelsey Meagher, low-income households spend approximately half their monthly income on housing and another 10-20% on utilities.[63] The incidence of utility disconnections can provide an indication of ability or willingness to pay for broadband. If a household is more likely to experience a utility disconnection, the household is likely to have a lower ability to pay for a broadband connection. In this sense, broadband disconnections for non-payment can be seen as an extreme form of “un-adoption,” as described by Powell, et al. Diana Hernández and Jennifer Laird’s empirical research on utility disconnections finds that disconnections are correlated with income, education, and home-ownership status, as well as race:[64]

Disconnections are disproportionately high among households with low incomes, a Black head of household, a head who does not have a high school diploma, mobile homes, older homes, poorly insulated homes, rentals, rural homes, and homes in the Northeast. Among those households with an income less than $20,000, nearly 8% have experienced a disconnection—a rate about 2.5 times as high as those with incomes between $20,000 and $59,999.

If a broadband provider determines a given territory is likely to have a low adoption rate or a high “un-adoption” rate, it is likely to conclude that deployment to that locality is less economically feasible than other territories. Empirical evidence suggests that race and income are among the factors associated with broadband adoption and un-adoption. Other factors like population density, education, age, familiarity with computers, and computer ownership are also known to be correlated with race and income and, indeed, race and income are widely known to be correlated with each other. For example, Beard & Ford show that U.S. Census blocks with higher population densities are associated with a higher share of minority residents and lower average incomes. They also report that blocks with a higher share of minority residents have lower fixed-broadband adoption rates and a higher share of mobile-only broadband use.[65]

Beard & Ford attempt to statistically untangle the income conundrum.[66] Their empirical model includes four demand factors for each Census block: fixed-broadband adoption rate, mobile-broadband adoption rate, the share of persons with a tertiary education, and the share of homes with a computer. The model also includes five cost factors: population density, the share of rural blocks within the Census-block group, and three cost categories from CostQuest. Using this information, they evaluate: (1) fiber deployment by race, (2) fiber deployment by income level, (3) download speeds by race, and (4) download speeds by income level. Beard & Ford conclude from their statistical analysis that there is “no meaningful evidence of digital discrimination in either race or income for fiber deployments or for download speeds.” But Beard & Ford is just a single study looking at the possibility of nationwide discrimination. While their approach is rigorous and provides compelling results, it would be challenging to “scale down” the approach to evaluate digital discrimination by firms or locality.

Consider a hypothetical FCC rule mandating that broadband providers must completely exclude income level, race, ethnicity, color, religion, and national origin from their deployment calculus. Instead, firms must rely on their estimates of deployment costs—including population density, terrain, local regulations, and local taxes—and non-protected demand factors, such as population density, education, age, utility-disconnection rates, and rates of computer ownership and usage. This would be one plausible implementation of an intent-based test of digital discrimination under Section 60506. So long as providers’ deployment decisions are not made “because of” any of the protected characteristics, then they would not be found to be practicing digital discrimination. Whether these other factors—education, age, population density, computer usage—are sufficient on their own to determine the economic feasibility of a deployment project is a separate empirical question beyond the scope of this brief.

But because each of these other factors are correlated with income level—and with other protected characteristics—applying an effects-based statistical analysis is likely to produce a false positive concluding the presence of digital discrimination, even when there was an explicit effort to avoid such discrimination. This is a version of Nobel laureate Ronald Coase’s well-known quote: “If you torture the data long enough, it will confess.”[67]

IV. Conclusion

The economics discussed above underscore that the FCC must be particularly cautious when promulgating rules under Section 60506. In particular, the Commission should adopt an intent-based discriminatory-treatment standard, rather than one that opens the doors to disparate-impact claims. The high risk of false positives under a disparate-impact standard would stifle broadband deployment through additional costs, delays, and risk of litigation. Similarly, FCC rules should articulate a presumption of non-discrimination in which allegations of digital discrimination must be demonstrated, rather than a presumption of discrimination that must be rebutted for each deployment decision. Otherwise, given the economic realities discussed above, there is an unacceptably high chance that every one of a provider’s decisions will be subject to challenge, wasting the resources of both the Commission and the providers.

The largest takeaway is that adoption matters quite a bit. Indeed, one of the biggest issues affecting economic feasibility is consumers’ willingness to pay. Moreover, Congress has recognized this reality in its recent legislation. The IIJA’s Broadband Equity and Access program provides more than $42 billion in grants to state programs to help them support providers and give assistance directly to users.[68] The Affordable Connectivity Program provided another $14 billion in funding to help users pay for devices and broadband connections.[69]

If the Commission has good evidence of intentional discrimination in the deployment of broadband, it has a role to play in preventing it. But without strong, compelling evidence of intentional discrimination, the FCC will waste scarce resources chasing bogeymen.

[1] H.R. 3684, 117th Cong. (2021).

[2] 47 U.S.C. § 1754(b).

[3] Notice of Inquiry, In the Matter of Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (Feb. 23, 2022), at para. 1 [hereinafter “NOI”].

[4] This issue brief supplements and extends the comments we submitted to the Commission as part of the NOI: Comments in the Matter of Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69, International Center for Law & Economics (2022), accessed at: https://laweconcenter.org/resource/icle-comments-to-the-fcc-on-prevention-and-elimination-of-digital-discrimination.

[5] NOI, supra note 4, at para. 1.

[6] 47 U.S.C. § 1754 [hereinafter “Section 60506”]

[7] Currently defined by the FCC as 25/3 Mbps for terrestrial fixed broadband and 10/1 for mobile broadband. See Fourteenth Broadband Deployment Report, In the Matter of Inquiry Concerning Deployment of Advanced Telecommunications Capability to All Americans in a Reasonable and Timely Fashion, GN Docket No. 20-269 (Jan. 19, 2021), at para. 12 (defining terrestrial fixed broadband), para. 15 (defining mobile broadband) [hereinafter “Fourteenth Broadband Deployment Report”].

[8] NOI, supra note 4, at para. 2 (quoting 47 U.S.C. § 1754(b)(1)).

[9] Id. at para. 3, n. 5; id. at para. 40 (both quoting Executive Order 13985).

[10] Texas Dept. of Housing & Community Affairs v. The Inclusive Communities Project, 576 U.S. 519, (2015).

[11] See, Geoffrey A. Manne, Kristian Stout, & Ben Sperry, A Dynamic Analysis of Broadband Competition: What Concentration Numbers Fail to Capture, ICLE White Paper (June 2021), available at https://laweconcenter.org/wp-content/uploads/2021/06/A-Dynamic-Analysis-of-Broadband-Competition.pdf [hereinafter “ICLE Broadband Competition Paper”].

[12] NOI, supra note 4, at para. 2.

[13] Section 60506, supra note 6, at (b)(1)-(b)(2).

[14] NOI, supra note 4, at para. 22.

[15] Comments of the Joint Advocates on Digital Discrimination, GN Docket No. 22-69 (May 16, 2022).

[16] See Comments of Public Knowledge, GN Docket No. 22-69 (May 16, 2022), pp 7-10; see also, Comments of the Multicultural Media Telecom and Internet Council, GN Docket No. 22-69 (May 16, 2022); Reply Comments of the National Digital Inclusion Alliance, GN Docket No. 22-69 (June 30, 2022).

[17] Ricci v. DeStefano, 557 U.S. 557, 577, (2009).

[18] See, id. (Intentional discrimination cases “present the most easily understood type of discrimination…[that] occur[s] where [a party[ has treated [a] particular person less favorably than others because of a protected trait.”).

[19] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 528–29.

[20] 167 Cong. Rec. 6046 (2021).

[21] 167 Cong. Rec. 6053 (2021).

[22] See, e.g., West Virginia v. EPA, 142 S. Ct. 420, (2021).

[23] Util. Air Regulatory Group v. EPA, 573 U.S. 302, (2014) quoting FDA v. Brown & Williamson Tobacco Corp., 529 U.S. 120, (1999); see also, West Virginia v. EPA, 142 S. Ct. 420.

[24] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 534.

[25] 42 U.S.C. § 3604(a) (emphasis added).

[26] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 534.

[27] Id.

[28] Id. at 534-35.

[29] Univ. of Texas Southwestern Med. Ctr. v. Nassar, 570 U.S. 338, 350, (2013) (citing Gross v. FBL Fin. Servs., Inc., 557 U.S. 167, 176, (2009)).

[30] Id. (citing Safeco Ins. Co. of America v. Burr, 551 U.S. 47, 63–64; n. 14, (2007)).

[31] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 533 (emphasis added).

[32] Texas Dep’t of Hous. & Cmty. Affs., 576 U.S. at 521–22 (“Courts should avoid interpreting disparate-impact liability to be so expansive as to inject racial considerations into every housing decision. These limitations are also necessary to protect defendants against abusive disparate-impact claims.”).

[33] Id.

[34] Section 60506, supra note 6 (emphasis added).

[35] See, e.g., Ricci, 557 U.S. 557.

[36] Brian Whitacre, Sharon Strover & Roberto Gallardo, How Much Does Broadband Infrastructure Matter? Decomposing the Metro–Non-Metro Adoption Gap with the Help of the National Broadband Map, 32 Gov’t Info. Q. 261 (2015).

[37] U.S. Gov’t Accountability Off., GAO-22-104611, Broadband: National Strategy Needed to Guide Federal Efforts to Reduce Digital Divide (May 31, 2022) [hereinafter “GAO-22-104611”].

[38] Id. See also, How Do Speed, Infrastructure, Access, and Adoption Inform Broadband Policy?, Pew Research Center (Jul. 7, 2022), https://www.pewtrusts.org/en/research-and-analysis/fact-sheets/2022/07/how-do-speed-infrastructure-access-and-adoption-inform-broadband-policy (“nearly 1 in 4 Americans do not subscribe to a home broadband connection, even where one is available”).

[39] Michelle Cao & Rafi Goldberg, New Analysis Shows Offline Households Are Willing to Pay $10-a-Month on Average for Home Internet Service, Though Three in Four Say Any Cost is Too Much, National Telecommunications and Information Administration (Oct. 6, 2022), https://www.ntia.doc.gov/blog/2022/new-analysis-shows-offline-households-are-willing-pay-10-month-average-home-internet.

[40] Kenneth Flamm & Anindya Chaudhuri, An Analysis of the Determinants of Broadband Access, 31 Telecomm. Pol’y. 312 (2007).

[41] Id.

[42] Victor Glass & Stela K. Stefanova, An Empirical Study of Broadband Diffusion in Rural America, 38 J. Reg. Econ. 70 (Jun. 2010).

[43] Christopher G. Reddick, Roger Enriquez, Richard J. Harris & Bonita Sharma, Determinants of Broadband Access and Affordability: An Analysis of a Community Survey on the Digital Divide, 106 Cities 102904 (2020).

[44] Victor Glass & Stela K. Stefanova, supra, note 43 at 70.

[45] GAO-22-104611, supra note 37.

[46] Alison Powell, Amelia Bryne & Dharma Dailey, The Essential Internet: Digital Exclusion in Low-Income American Communities, 2 Pol’y & Internet 161 (2010).

[47] Tonny J. Oyana, Exploring Geographic Disparities in Broadband Access and Use in Rural Southern Illinois: Who’s Being Left Behind?, 28 Gov’t. Info. Q. 252 (2011).

[48] GAO-22-104611, supra note 37.

[49] Notice of Inquiry, Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (2022) (“If underlying cost or geographic hurdles exist in conjunction with demand in an area that makes it unprofitable, how should the Commission address such a situation?”).

[50] U.S. Gov’t Accountability Off., GAO-06-426, Telecommunications: Broadband Deployment Is Extensive Throughout the United States, but It Is Difficult to Assess the Extent of Deployment Gaps in Rural Areas (May 2006), https://www.gao.gov/assets/gao-06-426.pdf. [hereinafter “GAO-06-426”].

[51] Brian Whitacre & Roberto Gallardo, State Broadband Policy: Impacts on Availability, 44 Telecomm. Pol’y. 102025 (2020).

[52] Tonny J. Oyana, supra note 47 at 252.

[53] Juan Rendon Schneir & Yupeng Xiong, A Cost Study of Fixed Broadband Access Networks for Rural Areas, 40 Telecomm. Pol’y. 755 (2016).

[54] GAO-06-426, supra note 50.

[55] Id.

[56] Id.

[57] Brian Whitacre & Roberto Gallardo, State Broadband Policy: Impacts on Availability, 44 Telecomm. Pol’y. 102025 (Oct. 2020).

[58] GAO-06-426, supra note 50.

[59] T. Randolph Beard & George S. Ford, Digital Discrimination: Fiber Availability and Speeds, by Race and Income, Phoenix Ctr. for Advanced Legal & Econ. Pol’y Stud., Phoenix Ctr. Pol’y Paper No. 58 (September 2022).

[60] Emily A. Vogels, State Broadband Policy: Impacts on Availability, Pew Research Center (Jun. 22, 2021), https://www.pewresearch.org/fact-tank/2021/06/22/digital-divide-persists-even-as-americans-with-lower-incomes-make-gains-in-tech-adoption.

[61] Victor Glass & Stela K. Stefanova, An Empirical Study of Broadband Diffusion in Rural America, 38 J. Reg. Econ. 70 (2010) (“The low price elasticity found in the 2009 study indicates that broadband access has become more of a necessity than it used to be in 2005.”).

[62] Meredith Whipple & Aden Hizkias, We Already Knew Broadband Should Be a Public Utility. The Pandemic Made It Obvious, Public Knowledge (Mar. 15, 2021), https://publicknowledge.org/we-already-knew-broadband-should-be-a-public-utility-the-pandemic-made-it-obvious.

[63] Ryan Finnigan & Kelsey D. Meagher, Past Due: Combinations of Utility and Housing Hardship in the United States, 62 Sociological Persp. 91 (2018).

[64] Diana Hernández & Jennifer Laird, Surviving a Shut-Off: U.S. Households at Greatest Risk of Utility Disconnections and How They Cope, 66 Am. Behav. Sci. 856 (2022).

[65] T. Randolph Beard & George S. Ford, Digital Discrimination: Fiber Availability and Speeds, by Race and Income, Phoenix Ctr. for Advanced Legal & Econ. Pol’y Stud., Phoenix Ctr. Pol’y Paper No. 58 (2022).

[66] Id.

[67] Garson O’Toole, If You Torture the Data Long Enough, It Will Confess, Quote Investigator (Jan. 18, 2021), https://quoteinvestigator.com/2021/01/18/confess.

[68] Broadband Equity, Access, and Deployment Program, BroadbandUSA, https://broadbandusa.ntia.doc.gov/resources/grant-programs/broadband-equity-access-and-deployment-bead-program (last visited Oct. 23, 2022).

[69] Affordable Connectivity Program, Federal Communications Commission, https://www.fcc.gov/acp (last visited Oct. 23, 2022).

Introduction

We thank the Federal Communications Commission (FCC) for the opportunity to offer these reply comments on the Further Notice of Proposed Rulemaking (FNPRM) in the Matter of Accelerating Wireline Broadband Deployment by Removing Barriers to Infrastructure Investment.

Ensuring that broadband connectivity is deployed effectively and efficiently to all Americans is among the FCC’s most important priorities. As Chair Rosenworcel has observed:

We are about to invest billions in high-speed infrastructure nationwide. It’s essential that we have policies in place that make sure these dollars are used in a cost-effective way and that pole attachment policies facilitate, rather than impede, broadband buildout.[1]

The Infrastructure Investment and Jobs Act (IIJA) allocated $65 billion to help the Commission and the National Telecommunications and Information Administration (NTIA) facilitate further deployment and adoption.[2] Private investment in broadband networks also continues to grow, with $2 trillion spent since 1996, including $86 billion in 2021 alone.[3]

This attention and funding could be wasted, however, due to roadblocks that stand in the way of deployment and threaten to reduce the efficacy of federal investment. Inflation remains at very high levels, which diminishes the practical reach of IIJA funds. Moreover, NTIA has signaled its interest in promoting policy goals that may divert some funding away from targeting the needs of the unserved.[4] Given this backdrop, it is crucial that the Commission exercise its authority to remove barriers to deployment.

In this proceeding, we believe that means seeking reform and clarification of inefficient pole-attachment rules that lead to cost overruns and deployment delays.[5] The docket includes numerous comments that document various ways utility-pole owners sometimes shift costs onto attachers.[6] What’s more, several different types of pole owners are subject to FCC jurisdiction in this area, multiplying the problems across many different bargaining parties, including providers such as incumbent local exchange carriers, privately owned public-utility providers, and investor-owned poles.[7]

The aim of pole-attachment rules should be to equitably assess costs in a way that ensures the attachment process does not inefficiently serve to extract rents.  As the Commission notes, the Wireline Bureau focused on these potential inefficiencies when it “clarif[ied] that it is unreasonable and inconsistent with Section 224 of the Communications Act, the Commission’s rules, and past Commission precedent, for utilities to impose the entire cost of a pole replacement on a requesting attacher when the attacher is not the sole cause of a pole replacement.”[8] In short, a rule that unilaterally imposes replacement costs on a given attacher—while potentially expedient from an administrative perspective—is unlikely to provide an economically optimal outcome. At the same time, depending on the condition of the pole, shifting all or most costs onto the pole owner may also be inadvisable.

With that in mind, a strict “sole cause” standard for determining the resolution of pole replacements is likely inefficient. As we discuss below, such standards can lead to hold-up and hold-out problems that negatively affect broadband deployment. We believe the current formula can be refined to ensure that deployment funds aren’t unjustifiably captured as rents. As others in the docket have maintained,[9] the formula should be adjusted to ensure that the allocation of pole-replacement costs more closely reflects the incremental costs and benefits to each of the parties.

In particular, the allocation should account for the depreciated value of the pole being replaced, as well as the incremental costs and benefits of larger and newer poles to pole owners, incumbent attachers, and anticipated future attachers, as well as the incremental costs to pole owners of early replacement. The remainder of this comment summarizes these considerations and offers some broad recommendations.

Before discussing our view of how to amend the pole-replacement-cost formula, we would like to express again our support for the idea commonly voiced in the docket that pole-replacement disputes should be placed on the Accelerated Docket. As many commenters note in the record, delays in resolving pole disputes can seriously delay or entirely jeopardize some deployment projects.[10]Fundamentally, the focus of this proceeding—as well as most of the federal funding that has been devoted toward expanding broadband—regards how best to connect locations that are far out on the cost curve. Delays are very costly and reduce the number of households served. Encouraging disputes to be settled in a timely fashion can only help to close the digital divide.

Download the full comments here.

[1] Accelerating Wireline Broadband Deployment by Removing Barriers to Infrastructure Investment (“FNMRPM”), FCC 22-20 (Mar. 16, 2022) https://docs.fcc.gov/public/attachments/FCC-22-20A2.docx.

[2] Drew Clark, Commerce Department’s NTIA Releases Details for Funds Distributed Under IIJA, BroadbandBreakfast (May 13, 2022) https://broadbandbreakfast.com/2022/05/commerce-departments-ntia-releases-details-for-funds-distributed-under-iija.

[3] 2021 Broadband Capex Report, USTelecom (Jul. 18, 2011) https://ustelecom.org/research/2021-broadband-capex-report.

[4] Kristian Stout, To Close the Digital Divide, Broadband Infrastructure Funds Must Be Spent Efficiently, Truth on the Market, (May 27, 2022) https://truthonthemarket.com/2022/05/27/to-close-the-digital-divide-broadband-infrastructure-funds-must-be-spent-efficiently.

[5] NCTA notes in its petition that, in hard-to-connect rural areas, as much as 25% of a project’s cost could be attributable to pole-attachment disputes. Petition of NCTA for Expedited Declaratory Ruling, In the Matter of Accelerating Wireline Broadband Deployment by Removing Barriers to Infrastructure Investment, WC Docket No. 17-84 (Jul. 16, 2020), at 5-9, available at https://www.ncta.com/sites/default/files/2020-07/071620_17-84_NCTA_Petition_for_Declaratory_Ruling.pdf. Pole owners dispute this number. For example, AT&T says that only 0.35% of requests it received resulted in the need for replacement. Robert Vitanza, David Chozempa, & David Lawson, Comments of AT&T (Corrected), AT&T (“AT&T Comments”) at 7-8 (Jun. 29, 2022) https://www.fcc.gov/ecfs/search/search-filings/filing/ NCTA, on the other hand, says about 8% of requests might need pole replacement. Ultimately, this is an empirical question the Commission needs to resolve. That said, the IIJA and BEAD programs are overwhelmingly focused on those households that are underserved and who are, by definition, more expensive to connect. Thus, it can be possible both for AT&T to be correct generally that pole-attachment disputes are rare, as well as for NCTA to be correct specifically about the extent of the problem in rural areas when pole replacements are needed.

[6] See, e.g., Thomas Cohen, Re: Ex Parte Filing of the American Cable Association on Accelerating Wireline Broadband Deployment by Removing Barriers to Infrastructure Investment, WC Docket No. 17-84, Kelley Drye & Warren LLP (Mar. 26, 2018) https://www.fcc.gov/ecfs/file/download/ACA%20Poles%20Ex%20Parte%203-26-18%20(FINAL).pdf?folder=1032633296362 (“…utilities often fail to provide any explanation for the significant increases in project costs on the final bill and do not provide the information necessary to challenge the reasonableness of the make-ready charges. Mr. Shawn Beqaj (Armstrong) provided examples where a utility charged a new attacher for the correction of preexisting safety violations caused by others or for overdue improvements designed to bring poles into compliance with utility regulations”); Kris Anne Monteith, Declaratory Ruling By the Chief, Wireline Competition Bureau, Federal Communications Commission, (Jan. 19, 2021) https://www.fcc.gov/ecfs/search/search-filings/filing/106282945908521 (“A California fiber ISP whose mission is to bring fiber broadband networks to rural and remote areas experienced serious time delays and a large increase in project expenses when an investor-owned utility revealed that hundreds of its poles in some very rural and remote areas did not have test and treat survey inspections in a decade or more. This caused substantial delays in bringing broadband service to unserved communities during the COVID-19 pandemic. Further, this high pole failure meant that the project expense forecasts were too low, and so the return on investment went from 7-9 years upward to a level that made the project almost uneconomical.”); Matthew M. Polka, Thomas Cohen, & Ross J. Lieberman, Comments of the American Cable Association on the Notices of Proposed Rulemaking, American Cable Association (Jun. 15, 2017) https://www.fcc.gov/ecfs/file/download/ACA%20Infrastructure%20NPRM%20Comments%20(FINAL).pdf?folder=1061666240361 (“…an investor-owned utility in Minnesota charged Mediacom to fix violations on poles to which Mediacom had been attached for 20 years caused by the utility moving its equipment during pre-make-ready inspections for a new attacher.”); Rick Chessen, Neal M. Goldberg, Steven F. Morris, & Maria Browne, Petition for Expedited Declaratory Ruling, NCTA – The Internet & Television Association (Jul. 16, 2020) https://www.ncta.com/sites/default/files/2020-07/071620_17-84_NCTA_Petition_for_Declaratory_Ruling.pdf (“ComEd refused to permit Crown Castle to attach to poles that had been ‘red tagged’ by ComEd until Crown Castle first pays to replace or reinforce those red tagged poles, even though the conditions that caused the red tag status existed prior to and are unrelated to Crown Castle’s proposed attachment.”); Christopher L. Shipley & Andrew Mincheff, Comments of INCOMPAS, INCOMPAS (Jun. 27, 2022) https://www.fcc.gov/ecfs/search/search-filings/filing/10629168805842(“INCOMPAS’ member IdeaTek, which operates in rural Kansas…has been allocated 100 percent of the replacement costs on applications that require make-ready and pole replacement, with no consideration given to the enrichment and benefit this confers to the utility or the current value or condition of the pole.”)

[7] See Public Notice: States that Have Certified that They Regulate Pole Attachments, Federal Communications Commission (Mar. 19, 2020) https://docs.fcc.gov/public/attachments/DA-20-302A1_Rcd.pdf. Note that this only applies across the 23 states that have not certified that they regulate pole attachments. Id.

[8] FNMPRM ¶ 2

[9] See, e.g., Re: WC Docket No. 17-84 – Accelerating Wireline and Wireless Broadband Deployment by Removing Barriers to Infrastructure Investment, Connect the Future Coalition (Jun. 27, 2022) https://files.fcc.gov/ecfs/download/e595c759-afb8-4e7d-a10f-35373238e59f?orig=true&pk=cb77b2ec-1a58-dbc6-139b-ad192cfd5d9b; Elizabeth Andrion & Maureen O’Connell, Comments of Charter Communications Inc., Charter Communications (Jun. 27, 2022) https://files.fcc.gov/ecfs/download/355be4d0-4729-48d4-807a-640c5645c3e9?orig=true&pk=cb77b2ec-1a58-dbc6-139b-ad192cfd5d9b; James E. Dunstan, Comments of TechFreedom, TechFreedom (Jun. 27, 2022) https://files.fcc.gov/ecfs/download/4a3c5f41-de6e-4da5-a973-fd18d2ef9f39?orig=true&pk=cb77b2ec-1a58-dbc6-139b-ad192cfd5d9b.

[10] See, e.g., Ross J. Lieberman, Brian Hurley, Thomas Cohen, & Edward A. Yorkgitis Jr., Comments of ACA Connects on Second Further Notice of Proposed Rulemaking, ACA Connects (Jun. 27, 2022) https://files.fcc.gov/ecfs/download/085b9a94-c9a3-41a0-975e-dbdd4bc7969f?orig=true&pk=cb77b2ec-1a58-dbc6-139b-ad192cfd5d9b; Randolph J. May, Seth L. Cooper, & Andrew K. Magloughlin, Comments of the Free State Foundation, Free State Foundation (Jun. 27, 2022) https://freestatefoundation.org/wp-content/uploads/2022/06/FSF-Comments-%E2%80%93-Accelerating-Wireline-Broadband-Deployment-by-Removing-Barriers-to-Infrastructure-Investment-062722.pdf; Steven Morris, Victoria Goldberg, Maria Browne, & David M. Gossett, Comments of NCTA – The Internet & Television Association, NCTA (Jun. 27, 2022) https://files.fcc.gov/ecfs/download/9391ec57-88c4-43c1-8f5c-b8af2b23a626?orig=true&pk=cb77b2ec-1a58-dbc6-139b-ad192cfd5d9b; Matthew M. Polka, Ross J. Lieberman, Thomas Cohen, Edward A. Yorkgitis Jr., & J. Bradford Currier, Comments of the American Cable Association on the Notices of Proposed Rulemaking, American Cable Association (Jun. 15, 2017) https://www.fcc.gov/ecfs/file/download/ACA%20Infrastructure%20NPRM%20Comments%20(FINAL).pdf?folder=1061666240361 (“MetroNet…has been waiting more than a year for approval of applications for 160 pole attachments because the one employee responsible for reviewing applications was out on extended medical leave.”)

Introduction

On behalf of the International Center for Law & Economics (ICLE), we thank the Commission for the opportunity to comment on this Notice of Inquiry in the Matter of Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination (“NOI”). The NOI states that “one of the Commission’s foremost goals is to ensure that every person in the United States has equal access to high-quality, affordable broadband internet access service… Every person across our Nation deserves—and must have—equal access to this crucial technology in the increasingly digital world; a person’s zip code should not determine their destiny.”[1]

Despite this high-minded rhetoric, the NOI does not focus on extending broadband deployment to those who are actually unserved—i.e., to those who lack any broadband Internet options at all.[2] In fact, the word “unserved” does not appear in the NOI at all. The notice instead focuses on eliminating “digital discrimination of access based on income level, race, color, religion, or national origin.”[3] This group is deemed to be the “underserved,” a designation the NOI defines not by reference to their relative inability to access broadband Internet service, but by their membership in categories that “have been historically underserved, marginalized, or adversely affected by persistent poverty or inequality.”[4] Thus, the NOI includes in the ranks of the “underserved” individuals who do have the ability to access broadband service, although potentially at slower speeds than some of their neighbors.

Getting faster Internet to those who live where broadband service already exists—or assisting them in paying for access to that service which already exists—is a fundamentally different problem than that faced by Americans who lack Internet access because they live in geographic areas without broadband infrastructure. We thus caution the Commission that this rulemaking may distract from the pressing need, demonstrated by the FCC’s own broadband-deployment data, to build out broadband networks in those hardest-to-reach areas.

The Commission asks whether broadband-deployment decisions are being made based on impermissible “income discrimination.” But as we explain in greater detail below, differences in the levels of broadband service available to the richest and poorest census blocks are insignificant relative to the differences in availability between lowest population-density census blocks and even the next- lowest population-density census blocks.[5] Indeed, the issues raised in NOI largely do not speak to the need to alleviate the significant deficit of broadband infrastructure in the most rural areas of this country. While the NOI presumes that discrimination is to blame for differences in the availability of higher-speed tiers of broadband service, the data and the underlying economics tell a different tale.

Underpinning the stark differences in broadband availability between urban and rural areas is the underlying cost of deployment. Population density serves as a supply-side constraint on buildout decisions because it is cost-prohibitive to build a network to serve only a very few potential subscribers. Similarly, those differences that can be observed in the deployment of the highest-speed tiers in urban centers—which are far less pronounced, in comparison to the urban-rural divide—are similarly the result of providers’ judgment about the likelihood to recoup their investments, not willful decisions to discriminate on the basis of income or protected racial or religious characteristics.

It is undoubtedly important to examine patterns of deployment to discover how best to connect underserved communities. But if we are to overcome those obstacles that have impeded reaching every potential broadband consumer, it is essential that the FCC carefully consider how and why investment decisions are made in broadband markets. ICLE has researched these questions extensively and we offer, in addition to these comments, that commissioners and FCC staff may wish to read the more fulsome analysis offered in our 2021 paper, “A Dynamic Analysis of Broadband Competition: What Concentration Numbers Fail to Capture.”[6]

In short, we question the NOI’s framing of broadband-connectivity issues as a matter of “discrimination.” We would assert that the project to eliminate “digital discrimination of access based on income level”[7] does not usefully forward efforts to connect the underserved. While there remains much work to be done to connect the underserved, the FCC is already well aware of the technical, economic, regulatory, and geographical issues that can impede deployment and has for years been doing important work on these issues. The Commission should continue this important work and should avoid the unhelpful framing of “discrimination.”

In Part II, we detail some of the important factors that guide broadband providers’ investment decisions and that drive competition in specific markets. There is no reasonable model (nor data) that would suggest broadband companies have engaged in discrimination against racial, ethnic, or religious minorities—or even against lower-income consumers—as that would imply that they have systematically sacrificed profits due to animus.

In Part III, we offer an approach to implement Section 60506 of the Infrastructure Investment and Jobs Act that applies insights from the law & economics of broadband buildout. It is not accurate to categorize the process firms undertake to evaluate the likelihood of recoupment as “discrimination” on the basis of “income level, race, ethnicity, color, religion, or national origin.”[8]

Thus, rules to proscribe “digital discrimination” ought to focus on cases where explicit and demonstrable discriminatory intent played a role in broadband providers’ investment decisions.

In Part IV, we counsel the FCC that it is economically infeasible to require equivalent broadband infrastructure across all territories irrespective of the likelihood that providers will be able to recoup their investment. Mandates that providers make unprofitable deployment decisions in some areas would necessarily require either that they raise prices in other areas or that they be subsidized directly by the government. The former (i.e., cross-subsidization) is generally infeasible, as higher-income territories tend to have more competitive markets. Thus, we recommend that the FCC and the federal government consider user subsidies (e.g., connectivity vouchers) to encourage more options for lower-income consumers.

Read the full comments here.

[1] Notice of Inquiry, In the Matter of Implementing the Infrastructure Investment and Jobs Act: Prevention and Elimination of Digital Discrimination, GN Docket No. 22-69 (Feb. 23, 2022), at para. 1 [hereinafter “NOI”].

[2] Currently defined by the FCC as 25/3 Mbps for terrestrial fixed broadband and 10/1 for mobile broadband. See Fourteenth Broadband Deployment Report, In the Matter of Inquiry Concerning Deployment of Advanced Telecommunications Capability to All Americans in a Reasonable and Timely Fashion, GN Docket No. 20-269 (Jan. 19, 2021), at para. 12 (defining terrestrial fixed broadband), para. 15 (defining mobile broadband) [hereinafter “Fourteenth Broadband Deployment Report”].

[3] NOI, supra note 1, at para. 2 (quoting 47 U.S.C. § 1754(b)(1).

[4] Id. at para. 3, n.5; para. 40 (both quoting Executive Order 13985).

[5] See Part II.B below.

[6] Geoffrey A. Manne, Kristian Stout, & Ben Sperry, A Dynamic Analysis of Broadband Competition: What Concentration Numbers Fail to Capture (ICLE White Paper, Jun. 2021), available at https://laweconcenter.org/wp-content/uploads/2021/06/A- Dynamic-Analysis-of-Broadband-Competition.pdf [hereinafter “ICLE Broadband Competition Paper”].

[7] NOI, supra note 1, at para. 2

[8] 47 U.S.C. § 1754.

 

ICLE Director of Law & Economics Programs Gus Hurwitz joined the Cardinal Institute’s podcast Forgotten America to discuss the logistical, political, and philosophical questions surrounding broadband in rural America. The full episode can be found here.