AI Might Not Diminish Critical Thinking, But Vested Interests Often Do

One sometimes hear it argued that fewer homes will "get internet" because of changes to Broadband Equity, Access, and Deployment Program rule changes. One also hears arguments that increased use of artificial intelligence will reduce critical thinking skills. 

Sometimes those arguments are highly questionable. There are other reasons why reality, truthfulness or factuality can be challenged, and it has nothing to do with human critical thinking or using AI. Instead, the issue is vested economic interest. 

Advocates for local or state government, for example, have a vested interest in increasing the share of federal resources they can deploy to solve problems. And sometimes they have vested interests in particular ways of solving problems. 

Consider arguments for how to bring better home broadband services to rural areas. For decades, the preference has been for a particular solution, namely optical fiber to the home, with opposition to using other arguably more-affordable and immediately-deployable solutions including satellite service and using mobile networks rather than cabled networks. 

Nobody disagrees that optical fiber to the home is the most “future proof” solution, providing it is economically feasible. The problem is that feasibility often is precisely the issue. 

FTTH Deployment Environment	Typical Homes Passed per Mile	Cost per Mile (All-In)*	Cost per Location (Homes Passed)	Key Cost Drivers
Urban (High Density)	80 – 150+	$50,000 – $100,000	$500 – $1,200	Shorter drops, existing duct/conduit, shared trenching, many users per mile
Suburban (Moderate Density)	30 – 70	$40,000 – $80,000	$1,200 – $2,500	Mix of aerial and buried, moderate trenching cost, fewer homes per mile
Rural (Low Density)	5 – 20	$25,000 – $60,000	$3,000 – $10,000+	Long distances, expensive trenching, new poles/conduit, very few users per mile

Very-rural areas might require investment so high no payback is possible. 

That is the reason a rational argument can be made that FTTH should not be built “everywhere,” and that feasible solutions must include satellite or mobile network access. The argument that “work from home” is not possible unless FTTH is deployed is almost always false. 

I have “worked from home, full time” on connections including symmetrical gigabit per second broadband and on connections offering less than 100 Mbps downstream and single digits upstream. My work has never been adversely affected. 

To be sure, my work does not routinely involve upgrading large files on a sustained basis. But most of us do not require a home-based server role, do not create long-form 4K video content all day and need to upload those files continually. 

So if it is said that changes to BEAD rules mean “fewer households will get high speed internet,” the statement is misleading or false. Fewer households might get internet access using FTTH, but that does not mean they will not get internet. And whether such access is “high speed” or not depends on the definitions we choose to use. 

Beyond that, “high speed” might not actually provide any user-perceivable advantage beyond a few hundred megabits per second in the downstream direction. Whether it makes any difference in the upstream direction might be a more-relevant issue, but even there, actual users might not find their work from home impeded. 

We sometimes forget that society has any number of pressing problems to be solved, and internet access is just one of those problems. Investments we make in any area have opportunity costs: we cannot spend the money to solve additional problems. 

Any engineering problem involves choices. Any allocation of societal resources likewise requires choices. Those choices have consequences. 

It is a perfectly logical and appropriate issue to suggest that serving more people, right now,  is a value as great as serving them with a particular solution or capability. Likewise, being efficient in the use of public resources also is a value we tend to believe makes sense. Virtually nobody ever advocates “waste, fraud and abuse.” 

But as a practical matter, it might well be a waste of scarce resources to insist on one particular solution for all home broadband requirements, when other workable solutions exist. 

For every public purpose there are corresponding private interests. Critical thinking might be said to aid decision making when scarce resources must be committed. And that critical thinking might include weighing claims that certain approaches mean “fewer homes will get internet,” when the truth is that the claim only means “fewer homes will get internet using FTTH:

• in areas where other providers already exist

• where there are locations that might not actually require access (an area might have business users but no home users)

• there are other reasons why subsidized service will still be available

• In areas too expensive to serve using FTTH.

In our justified zeal to ensure that critical thinking skills are not diminished by AI, we should not forget that critical thinking skills often are ignored when vested interests interpret reality in ways that serve those interests.

"Everyone" Wants More Housing. Just Not "In My Backyard"

Land use regulations including zoning laws, density restrictions, minimum lot sizes, height limits, rules on parking spaces and growth controls increase the cost of housing and limit its construction.

That matters if the U.S. housing supply is 4.7 million homes short of demand. It’s just basic supply and demand economics. And focusing on supply matters.

Local zoning, land use, density regulations and so forth often limit the amount, type, and location of new housing development, effectively constraining supply even as population growth, urbanization, and economic demand for housing rise.

This supply shortage pushes up prices and rents, making housing less affordable, particularly for low- and middle-income households.

For instance, regulations can impose lengthy permitting processes, environmental reviews, or inclusionary requirements that raise development costs, which are then passed on to buyers or renters.

But the bigger problem is simply that such rules are among many reasons more housing is not created.

 

To be sure, the rationale often is compelling: preserving community character, protecting the environment, or preventing urban sprawl.

But those very same rules create disincentives to build affordable housing, as they all restrict housing density or volume. 

Study Title	Authors	Year	Methodology and Key Findings
The Effect of Land Use Regulation on Housing and Land Prices	Keith R. Ihlanfeldt	2007	Used an endogenous index of regulatory restrictiveness across over 100 Florida cities; found greater restrictiveness increases house prices, decreases land prices, and leads to larger new homes.
The Effects of Land Use Regulation on the Price of Housing: What Do We Know? What Can We Learn?	John M. Quigley and Larry A. Rosenthal	2005	Reviewed empirical literature using surveys, econometric models (e.g., OLS, hedonic pricing), and regulatory indices; regulations like zoning and growth boundaries are associated with higher prices, but causality is not firmly established due to endogeneity and data limitations.
Land-Use Reforms and Housing Costs	Christina Plerhoples Stacy et al.	2023	Analyzed a panel dataset of 180 reforms in 1,136 U.S. cities (2000–2019) using machine learning, manual coding, and fixed-effects models; loosening restrictions increases supply by 0.8% over 3–9 years (mainly high-end units), while tightening raises median rents and reduces affordable units.
How Land-Use Regulation Undermines Affordable Housing	Sanford Ikeda and Emily Washington	2015	Reviewed literature and urban policy data; regulations reduce supply relative to free-market levels, increase costs (e.g., 10%+ "regulatory tax" in major cities), and disproportionately affect low-income households, potentially lowering GDP by limiting growth in productive areas.
Regulation and Housing Supply	Joseph Gyourko and Raven Molloy	2014	Literature review with surveys, panel data, and regression analyses (e.g., OLS, instrumental variables); strong positive link between regulation and prices (17–22% increases), reduced construction (4–22%), and lower supply elasticity, leading to volatility.
Zoning, Land-Use Planning, and Housing Affordability	Randal O'Toole	2017	Regression analysis of court decisions as proxies for regulation intensity (2000–2010 data); rising land-use and zoning regulations correlate with higher home prices in 44 and 36 states, respectively, with federal aid flowing more to restrictive states.
The Impact of Zoning on Housing Affordability	Edward L. Glaeser and Joseph Gyourko	2002	Compared house prices to construction costs across U.S. markets; zoning drives prices above costs in high-regulation areas (e.g., NYC, California), suggesting supply restrictions exacerbate affordability issues more than demand alone.
Do Restrictive Land Use Regulations Make Housing More Expensive Everywhere?	John Landis and Vincent J. Reina	2021	Examined 336 metro areas with multiple stringency measures and growth variables; restrictive regulations pervasively raise home values and rents, especially in growing/prosperous economies, but effects on supply vary by market.

"Not in my backyard" remains an important problem as well. We might say we want "X" as a policy. But almost nobody says they want "X" implemented in their own neighborhood. "Do it to somebody else" is the inevitable real-world, up close and personal answer, whatever the loftier images people have of themselves.

And that generally applies to all of us, as we ponder the impact of land use rules. It makes a huge difference whether we are among the "haves" or the "have nots."

Density will not appeal to those already living in low-density areas.

Conversely, density might make all the difference for those entering the owned-housing market.

To be crude, do land use planning rules preserve "privilege" for some at the expense of many others? Of course they do.

Well-Intentioned Regulations Can Backfire

Land use regulations including zoning laws, density restrictions, minimum lot sizes, height limits, rules on parking spaces and growth controls increase the cost of housing and limit its construction. 

That matters if the U.S. housing supply is 4.7 million homes short of demand. It’s just basic supply and demand economics. 

And focusing on supply matters. Such regulations often limit the amount, type, and location of new housing development, effectively constraining supply even as population growth, urbanization, and economic demand for housing rise. 

 This supply shortage pushes up prices and rents, making housing less affordable, particularly for low- and middle-income households. 

 For instance, regulations can impose lengthy permitting processes, environmental reviews, or inclusionary requirements that raise development costs, which are then passed on to buyers or renters. 

 But the bigger problem is simply that such rules are among the reasons more housing is not created. And there are several reasons, one might argue. Labor availability and costs; lumber availability and cost; tax rules and other government policies play a role. 

 

But land use planning rules matter. To be sure, the rationale often is compelling: preserving community character, protecting the environment, or preventing urban sprawl. 

 But those very same rules create disincentives to build affordable housing, as they all restrict housing density or volume. 

Study Title	Authors	Year	Methodology and Key Findings
The Effect of Land Use Regulation on Housing and Land Prices	Keith R. Ihlanfeldt	2007	Used an endogenous index of regulatory restrictiveness across over 100 Florida cities; found greater restrictiveness increases house prices, decreases land prices, and leads to larger new homes.
The Effects of Land Use Regulation on the Price of Housing: What Do We Know? What Can We Learn?	John M. Quigley and Larry A. Rosenthal	2005	Reviewed empirical literature using surveys, econometric models (e.g., OLS, hedonic pricing), and regulatory indices; regulations like zoning and growth boundaries are associated with higher prices, but causality is not firmly established due to endogeneity and data limitations.
https://www.urban.org/research/publication/land-use-reforms-and-housing-costs	Christina Plerhoples Stacy et al.	2023	Analyzed a panel dataset of 180 reforms in 1,136 U.S. cities (2000–2019) using machine learning, manual coding, and fixed-effects models; loosening restrictions increases supply by 0.8% over 3–9 years (mainly high-end units), while tightening raises median rents and reduces affordable units.
How Land-Use Regulation Undermines Affordable Housing	Sanford Ikeda and Emily Washington	2015	Reviewed literature and urban policy data; regulations reduce supply relative to free-market levels, increase costs (e.g., 10%+ "regulatory tax" in major cities), and disproportionately affect low-income households, potentially lowering GDP by limiting growth in productive areas.
Regulation and Housing Supply	Joseph Gyourko and Raven Molloy	2014	Literature review with surveys, panel data, and regression analyses (e.g., OLS, instrumental variables); strong positive link between regulation and prices (17–22% increases), reduced construction (4–22%), and lower supply elasticity, leading to volatility.
Zoning, Land-Use Planning, and Housing Affordability	Randal O'Toole	2017	Regression analysis of court decisions as proxies for regulation intensity (2000–2010 data); rising land-use and zoning regulations correlate with higher home prices in 44 and 36 states, respectively, with federal aid flowing more to restrictive states.
The Impact of Zoning on Housing Affordability	Edward L. Glaeser and Joseph Gyourko	2002	Compared house prices to construction costs across U.S. markets; zoning drives prices above costs in high-regulation areas (e.g., NYC, California), suggesting supply restrictions exacerbate affordability issues more than demand alone.
Do Restrictive Land Use Regulations Make Housing More Expensive Everywhere?	John Landis and Vincent J. Reina	2021	Examined 336 metro areas with multiple stringency measures and growth variables; restrictive regulations pervasively raise home values and rents, especially in growing/prosperous economies, but effects on supply vary by market.

Why Product Bundling is Key to Payoff from AT&T Purchase of Lumen Consumer Fiber Assets

Lots of observers argue that the Verizon purchase of Frontier Communications assets (buying back an asset it had previously sold off) is not a wise use of capital, with the arguments often suggesting Verizon should be investing more in artificial intelligence in some way.

Of course, there is an argument to be made that such forays into applications, content or additional roles in the value chain have not worked out very well.

And some of the same questions are raised about AT&T's purchase of Lumen Technologies mass market fiber-to-home assets. The concern is that the purchase will not have a near-term impact on profits and could be a case where the opportunity cost is too high.

AT&T believes it can justify the purchase of Lumen Technologies consumer fiber business based in part on the ability to drive higher revenues by bundling mobile services, and also boosting take rates from the current 25 percent level to perhaps 40 percent. 

But other buyers without the ability to bundle with owned mobile services also could have interest in acquiring significant copper access assets and then upgrading for fiber access. In many cases the upside comes more from asset value increases than actual operating cash flow or profits, though. 

As always, much hinges on the assumptions. Assume a copper access asset with:

• 500,000 copper broadband and voice customers, with 80 percent convertible to fiber over 10 years (much higher than AT&T expects with its bundled services approach)

• Copper assets are valued at 4–8x EBITDA. Assuming annual EBITDA of $100 million for the copper business, acquisition cost is estimated at $600 million (6x EBITDA).

• Fiber Upgrade Costs: 800–$1,200 per home passed, plus $300–$500 per connected subscriber. Assume $1,000 per home passed and $400 per connected subscriber.

• Revenue: Copper ARPU (Average Revenue Per User) at $40/month, fiber ARPU at $60/month. Fiber adoption grows linearly to 80 percent (400,000 customers) by year 10.

• Copper maintenance costs are high ($300/customer/year), while fiber reduces this to $100/customer/year.

• CapEx: Fiber deployment spread over 5 years, with 20 percent of customers upgraded annually.

• Financing: 50% equity, 50% debt at 5% interest rate.

• Depreciation: Fiber assets depreciated over 20 years (straight-line).

• Market Dynamics: Copper demand declines 5% annually; fiber demand grows with 10% annual subscriber growth post-upgrade.

• Copper Recycling: Recycled copper yields $7,000/ton, with 5,000 tons recoverable (based on scaled-down estimates from TXO’s $7 billion market potential for 963,000 tons).

Perhaps the key sensitivity here are take rates. The business model here assumes take rates at 80 percent in a decade. That is more likely for rural and other lower-density markets, where competitors are deterred from investing. It is hard to imagine such take rates in competitive urban markets. 

Component	Details	Year 1	Year 5	Year 10
Acquisition Costs
Purchase Price	6x EBITDA ($100M) for 500,000 customers	$600M	$0	$0
Transaction Costs	Legal, advisory fees (2% of purchase price)	$12M	$0	$0
Total Acquisition Cost		$612M	$0	$0
Fiber Upgrade Costs
Homes Passed	$1,000/home × 500,000 homes (spread over 5 years, 100,000/year)	$100M	$100M	$0
Subscriber Connections	$400/subscriber × 100,000/year (20% of customers annually)	$40M	$40M	$0
Equipment & Installation	Network upgrades, ONTs, etc. ($200/home × 100,000/year)	$20M	$20M	$0
Total Upgrade CapEx		$160M	$160M	$0
Revenue
Copper Revenue	$40/month × 500,000 (Year 1), declining 5%/year	$240M	$193M	$144M
Fiber Revenue	$60/month × 100,000 (Year 1), growing to 400,000 by Year 10	$72M	$288M	$288M
Copper Recycling Revenue	5,000 tons × $7,000/ton (one-time, Year 1–2)	$35M	$0	$0
Total Revenue		$347M	$481M	$432M
Operating Expenses (OpEx)
Copper Maintenance	$300/customer × remaining copper customers	$150M	$90M	$30M
Fiber Maintenance	$100/customer × fiber customers	$10M	$40M	$40M
General OpEx	Marketing, admin (10% of revenue)	$34.7M	$48.1M	$43.2M
Total OpEx		$194.7M	$178.1M	$113.2M
EBITDA	Revenue – OpEx	$152.3M	$302.9M	$318.8M
Cash Flow Implications
Operating Cash Flow	EBITDA – Taxes (25%)	$114.2M	$227.2M	$239.1M
Free Cash Flow (FCF)	Operating Cash Flow – CapEx – Interest ($30M/year, 5% on $600M debt)	-$75.8M	$37.2M	$239.1M
Profit Implications
Depreciation	$612M acquisition (20 years) + $800M fiber CapEx (20 years)	$70.6M	$70.6M	$70.6M
Net Income	EBITDA – Depreciation – Interest – Taxes	$51.7M	$166.6M	$182.5M
Equity Increase Implications
Enterprise Value (EV)	10x EBITDA (fiber) + 6x EBITDA (copper)	$1.05B	$2.45B	$2.94B
Equity Value	EV – Debt ($600M)	$450M	$1.85B	$2.34B
Equity Increase (from Year 0)	Initial equity investment: $306M (50% of acquisition)	$144M	$1.54B	$2.03B