An AI Digital Inclusion Research Tool

In many ways, we are at the heyday of broadband. Huge numbers of households are being reached by new broadband networks funded by numerous state and federal grants. Many non-profit groups are working hard to make sure people have the computers and other devices needed to take advantage of connectivity. Many other people are teaching people how to use computers in order to navigate the online world. Digital navigators are helping folks find broadband connections they can afford.

Unfortunately, big changes in the federal government have meant that the funding for many of these activities is quickly evaporating. The administration killed the $2.75 billion Digital Equity Fund, which would have funded digital inclusion work around the country. There is still $21 billion of potential BEAD non-deployment funding, but that money seems to be stuck in limbo, and the general feeling is that even if some of these funds are released, they will only be available for specific purposes that might not include digital inclusion.

It has always been clear that the big federal funds aimed at digital inclusion work were only going to carry the national digital inclusion effort for a few years, but that funding would have given the digital inclusion practitioners the time to mature and be ready in a few years to self-fund and stand on their own. Folks involved in digital inclusion are now scrambling to survive after the abrupt end of funding.

One way forward is for digital inclusion efforts to become more efficient and better organized. That’s not as easy as it might sound. The digital inclusion ecosystem is still relatively new, and there are a lot of different groups in any state with different approaches for tackling digital inclusion solutions. Becoming more efficient might mean digital inclusion practitioners joining forces to gain efficiency. Being efficient with less funding will mean choosing projects where digital inclusion work will produce the best local results.

I’m working with some folks in North Carolina who have developed a tool that can help digital inclusion efforts be more efficient. The core of the tool was developed by Brian Rathbone of Broadband Catalyst. He’s named the new tool Marco Map AI, which is appropriate because it’s a gateway to discovery. This tool starts by gathering every possible data source and database available that has information that could inform the digital inclusion effort. In North Carolina, that means dozens of different data sources.

Some of the data is what everybody would expect, like the FCC broadband maps and U.S. Census data. But there is also a wide range of data available for things like health care data, housing, the location of anchor institutions, and education.

When Brian first brought the data together, it quickly became apparent that the sheer magnitude of the data could be overwhelming, and even a good researcher has a problem making sense of multiple disparate datasets. Brian’s first step to make it easier to understand data was to map everything. It turns out that the human mind can more quickly grasp a map of data points than tables of facts. But even mapping is overwhelming when there are dozens of attributes being mapped.

It turns out that the missing tool to make sense of the huge pile of data is AI. AI can be used to find patterns in complex data sets that a researcher would probably never find on their own. Perhaps the best way to explain how this works is with an example.

Let’s say that a hospital wants to do a better job on improving outcomes for diabetes patients in the region it serves. Research and hospital experience show that enrolling diabetes patients in home monitoring while staying in touch through telemedicine can greatly improve patient outcomes – and hospitals know that proactive care saves money for patients and the hospital. Hospitals already know the patients they are connected to, but how do they find the other people in the region who could benefit from proactive care?

The Marco software with the AI assistance can answer this question in a way that I don’t think a human researcher can easily do. The system can cross-check all of the factors related to given question. It would start with a map of areas that have a higher prevalence of diabetes. It would overlay this with factors related to broadband and telehealth. For example, what areas have good or poor broadband technologies? What is the level of home broadband subscriptions and computer ownership? Where is cellular technology adequate to handle the monitoring needs? How do households incomes and poverty levels impact the ability of homes to afford a broadband connection?

The AI system can answer incredibly detailed questions in a way that I’ve not seen done by other research. For example, you could use the software to identify the neighborhoods that are within twenty miles of a hospital or clinic, where the prevalence of diabetes is higher than average, where people have broadband or good cellular coverage, and where incomes are high enough that many people can afford broadband. After answering this kind of question, it’s easy to quickly modify the parameters of the questions to fine-tune the results until it provides what the hospital system wants to know. There are endless questions that could be posed.

This is amazing tool for policy makers and those who are trying to tackle broadband access or digital inclusion issues. I highly recommend anybody interested in this tool to contact Broadband Catalysts.

The Pending Encryption Crisis

At the recent Fiber Connect 2026 conference, Michio Kaku, a professor at the City University of New York, predicted that quantum computers would be able to break the current encryption on digital telecom networks within three years. Other experts don’t think it will be that soon, but there is almost universal agreement that it will happen sometime in the 2030s.

There are a variety of types of encryption used in broadband networks. Most voice, text, and data being transmitted across networks use symmetrical encryption like the AES standard (Advanced Encryption Standard). The vast majority of this encryption uses AES-128, which uses a 128-bit encryption key. AES-256 uses a 256-bit encryption key and is mostly used to transmit things like top-secret military data or for long-term data storage of important data.

Carriers use public-key encryption when handing data between carriers on the web. This generally means using the older cryptography method, RSA (Rivest-Shamir-Adleman), or the newer ECC (Elliptic Curve Cryptography).

It’s expected that quantum computers will first be able to crack public-key cryptography like RSA and ECC. Quantum computers will have a bigger challenge cracking symmetrical encryption. It’s all going to depend on the strength of the quantum computers. For example, scientists calculate that a quantum computer with 10,000 qubits could crack ECC encryption, but it would take 1,000 days to do so. But a larger computer with 26,000 qubits could crack ECC encryption in a day. The most intense forms of encryption might only be cracked by a quantum computer with 100,000 qubits.

There are still breakthroughs needed for quantum computers to have the power to reasonably decrypt the most common forms of encryption. Today, there is a high level of errors introduced inside the quantum computer, and scientists are working to lower the error rate. The challenge of operating a quantum computer also increases in complexity as the number of qubits is increased. There are working quantum computers in labs with as many as 6,100 qubits, but none of these is working well enough to be used for widespread decryption.

The good news is that there are ways to defeat decryption by quantum computers. The term post-quantum encryption is being used to describe algorithms and techniques specifically designed to block decryption by quantum computers. Quantum computers function best by being able to simultaneously process large numbers of calculations, which makes them perfect for figuring out encryption techniques.  Post-quantum algorithms use complex algebraic structures like lattices and hash functions to confound a quantum computer. The math problems used in the encryption are designed to be too difficult for quantum computers to solve.

The computer world has been working on post-quantum computing and should be able to fend off quantum computers when the time comes. While that is comforting, there is still some bad news. Bad actors have been hacking companies and scraping data off the web to store and wait for the day when quantum computers can decrypt the data. This is being referred to as “harvest now, decrypt later”, and the folks doing that figure there is a lot of encrypted data today that will still be relevant a decade from now. That might mean things like banking and medical records or corporate secrets that can be damaging if ever known by bad actors. This “harvest now” mindset might explain many of the cases where companies have been hacked with no obvious bad results.

The bottom line is that quantum computers are going to get good enough to decrypt current encryption techniques. Most large quantum computers are still in labs and not readily available to the public. Computers and networks are being readied with new post-quantum encryption techniques that should be able to thwart real-time data hacking. The biggest danger from quantum computers might be the ability to decrypt the mountains of stored data that has been encrypted using today’s algorithms.

Are Broadband Prices Dropping?

The FCC recently asked for comments in Docket 26-78, which is the latest iteration of its biennial report to Congress that looks at the State of Competition in the Communications Marketplace. Various industry players provided input to the FCC on issues related to competition and pricing for broadband and cellular service, with fewer caring about voice and cable service.

One of the issues widely discussed in this year’s filing is broadband prices. Some of the big ISPs continue to assert that broadband prices are dropping. For example, USTelecom refers to a report it generated that asserts that Internet prices have fallen for the eleventh straight year. I’ve written about the annual USTelecom reports before, and a big part of their assertion comes from looking at the price over time of the cost per megabit of speed being sold. On that basis, prices are dropping, mostly because ISPs have been increasing the speeds being delivered at a faster pace than prices.

One set of comments came from the Benton Institute, which described the issue perfectly. They cite the example that the price for 200 Mbps was around $50 in 2021. Many ISPs have unilaterally increased speeds without increasing price, and the average price for 400 Mbps in 2025 was also around $50. While the cost per megabit cut in half, customers are still paying $50.

Of course, ISPs don’t sell, and consumers don’t buy broadband by the megabit. Benton made a humorous observation on the big ISP’s focus on cost per megabit. Benton cites a USTelecom comment that the price per megabit for gigabit service is around 7 cents per megabit, or $70 per month. If USTelecom members are happy with that price, then why aren’t they applying that price to slower products so that 200 Mbps would cost $14 per month?

Perhaps the best discussion of prices in the docket comes from a study by John P. Horrigan, PhD, which is attached to the Benton comments. Horrigan takes a neutral look at prices and found that the weighted average for all broadband products increased by 4.8% from 2024 to 2025. Horrigan found that broadband prices for products slower than gigabit declined 8.5% from 2024 to 2025, with prices increasing for faster products.

Horrigan found that low-price options are disappearing from the market. When the ACP plan was operating, 9% pf broadband being sold was priced at $30 or less. He says this fell to just 3% of the market in 2025. This also holds true for plans with slower speeds. In 2022, 57% of consumers were buying Internet at a speed of 100 Mbps or less. In 2025, that has dropped to 32% of the market.

While the Benton Institute comments hint at it, I think most other comments in the docket are missing the bigger picture. Customers are choosing to migrate to lower-cost broadband options. One doesn’t have to look any further than the phenomenal success of FWA cellular. Since 2022, 16.5 million customers have subscribed to FWA cellular. While some of these customers live in rural areas where FWA is the only fast broadband option, I think a vast majority of these folks choose FWA to save money. The list prices for FWA home broadband are in the $50-$60 dollar range. However, there are big discounts for bundling with cellular service and for using autopay, and it’s possible to buy FWA home broadband for as little as $20-$30 per month.

Any analysis that just looks at prices for specific speeds over time will account for folks willing to take less speed for a lower bill. The big ISPs don’t want to talk about this, but there is no other way to discuss the huge success of FWA without talking about customers self-selecting lower prices.

How Good is Rural Cellular Coverage – Part II

Yesterday’s blog looked at AT&T cellular coverage in a typical rural county in Illinois and included the following map. The map shows where AT&T can provide 5G coverage in a moving vehicle in the dark areas, and where somebody standing stationary outdoors could get a 5G signal in the lighter colored areas.

Let’s look at the maps for the other two major carriers in the same areas. The first map below is T-Mobile, and the second is Verizon.

These maps show typical coverage. The two carriers support 5G in moving vehicles in and close to towns and cities. The light colored areas are where somebody standing outdoors can likely get a 5G signal. An indoor cellular coverage map would likely not be a lot larger than the dark areas.

Taken altogether, these maps show a typical rural story of cellular coverage. Cell carriers rarely share towers, and each carrier is on different towers and has different coverage. All three carriers have areas where they have no 5G coverage, and somebody subscribed to any one carrier in this county would find a lot of dead zones. All three carriers have little or no coverage in the northwest sector. These maps show something that every rural delivery driver knows – to work in rural America means carrying multiple cellphones subscribed to different carriers.

When Chairman Carr says that 96.8% of households have 5G coverage, we have to put that into perspective. Over 80% of Americans live in cities and suburbs and likely have good cell coverage. Another substantial percentage live in smaller towns that happen to have at least one cell tower. In this particular county, 60% of people live in incorporated towns and villages, meaning there are a lot of rural residents.

What’s the point of these two blogs? The FCC considers this County to have good 5G coverage. That assumption comes largely from looking at the combined coverage of the three carriers shown for somebody standing stationary outdoors. The light colored areas of the three maps combined cover most of the county.

If the FCC ever decides to finally launch the 5G Fund for Rural America, this county will likely not be a candidate for a grant to build new cell towers. That’s unfortunate, because I estimate that 30% of the residents of this county would say they have poor cellular coverage. They will say that they don’t have good coverage indoors, and no matter which carrier they subscribe to, they hit dead spots when they drive around the county. The FCC’s assertion that 96.8% of homes have good 5G coverage can be supported by the FCC maps – but those maps don’t show the reality of the way that people judge cellular coverage.

How Good is Rural Cellular Coverage – Part I

The FCC has opened a docket that periodically looks at ways to improve the FCC’s broadband and cellular maps. As part of that docket, Chairman Brendan Carr issued the following statement: On the mobile side, 96.8 percent of locations have access to mobile 5G services of at least 7/1 Mbps.

To put that into perspective, there are roughly 116.7 million total passings counted in the FCC maps, and the Chairman is saying that all except 3.7 million have good access to 5G. The Chairman’s statement can be supported by the FCC cellular maps, but I think the reality in rural areas is far different than what is shown on the maps. I’m not saying that the FCC maps are a lie – because I think it’s likely that the maps represent what the FCC asked carriers to report. But I think the maps tell a different story than what Chairman Carr is pushing, and I don’t think anywhere near 96.8% of folks in the country would say they have good cellular coverage.

Let’s look at the FCC maps for 5G coverage in an actual county in Illinois. I didn’t pick this county because it doesn’t have good cell coverage. The coverage in the counties around it would all tell the same story. One thing to note about this county is that there are homes located in all parts of the county – the areas with no coverage on these maps are not parklands or forests.

The following map shows AT&T 5G coverage from the FCC cellular maps. The FCC asks carriers to show coverage in two ways. The darker orange areas are where AT&T claims that 5G coverage will work in a moving vehicle. The lighter areas are where AT&T says that a customer can receive 5G when standing stationary outdoors. AT&T is claiming no 5G coverage in the gray areas.

This AT&T map is typical of rural cell coverage. Cell towers are located roughly in the center of the dark-colored areas, and those areas mostly covering towns and cities. Anybody who understands cellular technology understands that speeds drop quickly with distance from a cell site. The cellular download data speeds at the center of the dark areas could easily be as fast as 300 Mbps. But within two miles of a tower, speeds drop to around 25 Mbps. 5G speeds and coverage in the light-colored areas are a lot slower and spottier, and as you get to the outer parts of the light-colored areas, farthest from the towers, it’s likely that somebody would have to move around in their yard to find the sweet spot where they could make a call.

What this map doesn’t measure, and the FCC doesn’t ask about, is indoor cellular coverage. It’s a general rule of thumb that indoor speeds are roughly half of outdoor speeds. You can easily test this by taking an outdoor cellular speed test and then an indoor test away from a window (turn off your WiFi). If the carriers were to map expected indoor cellular coverage, the areas with indoor coverage would be a lot smaller than the light-colored areas shown for outdoor coverage.

When you ask a rural resident what good cell coverage means, they will define it as working in their home and working in their car. With that definition, AT&T doesn’t have great 5G coverage in the county for people who live or drive outside the dark circles.

Tomorrow’s blog will compare AT&T’s coverage to T-Mobile and Verizon to show the overall picture of cell coverage in this county.

Global Broadband Prices

It’s interesting once in a while to look at how the U.S. compares to the rest of the world in terms of broadband prices. The prices used in this blog come from Broadband Genie, which is a firm that compares local ISP prices in the U.K. For the worldwide price study, it gathered the average broadband prices from 214 countries. Prices were gathered in January and February of this year and are collected from public ISP websites or other trusted broadband comparison websites.

This is far from being a scientific study. Just imagine the difficulty of determining the average broadband price in the U.S. However, the study calculated the average U.S. broadband price of $80, which feels a little high to me, but not by much. You can judge the other prices accordingly. The price comparison doesn’t discuss the availability of broadband in each country, which varies widely across the world. All of the prices quoted below are in U.S. dollars, as calculated by Broadband Genie at the conversion rates at the time of the article. The article includes a database that provides the average cost in the local currency in each country.

There are ten countries with average prices below $10 U.S.. The countries with the lowest-cost broadband are:

Iran                  $2.61

Ukraine           $5.35

Ethiopia           $6.46

Bangladesh     $7.38

Mongolia         $7.41

The most expensive prices are as follows. As might be expected, a lot of the highest broadband prices come from islands, and I imagine the cost of international underwater backhaul has a lot to do with the higher prices.

Eswatini                        $193.21

Saint Barthelemy        $207.26

Turks and Caicos        $252.00

Turkmenistan              $286.24

Wallis and Futana       $373.88

The report also calculates a weighted average price in 22 regions of the world. The lowest prices by region are in Eastern Europe ($15.76) and Northern Africa ($20.83). The highest is Polynesia ($118.48).

Finally, the prices for some of the largest countries include:

India                $8.82

Russia              $9.71

Indonesia        $10.66

China               $14.30

Brazil               $23.08

South Korea    $26.92

France             $29.77

U.K.                  $31.43

Japan               $32.62

Germany         $47.59

South Africa    $50.20

U.S.                  $80.00

Sunsetting the High Cost Fund

SpaceX recently filed comments in the FCC’s open docket looking at the Universal Service Fund (USF) with a recommendation that the FCC should sunset the High-Cost Fund and eventually eliminate it. This is one of the four major components of USF, with an annual budget of $4.5 billion.

SpaceX argues that Starlink has now solved rural broadband connectivity issues with ubiquitous broadband available throughout the country. SpaceX argues that ongoing subsidy payments to support rural voice and broadband networks are no longer needed.

To put the SpaceX comments into perspective, let me start by reviewing the stated goals of the High Cost Fund:

  • Preserve and advance universal availability of voice service.
  • Drive universal availability of modern networks capable of providing voice and broadband service to homes, businesses, and community anchor institutions.
  • Drive universal availability of modern networks capable of providing advanced mobile voice and broadband service.
  • Ensure that rates for broadband and voice services are reasonably comparable in all regions of the nation.
  • Contain administrative costs and minimize the universal service contribution for consumers and businesses through efficient, effective program management.

The High-Cost Fund is the home to a multitude of different subsidy programs:

  • It’s the home of six different Connect America (ACAM) funding mechanisms.
  • This fund is still making the annual subsidy payments for RDOF, which were spread over ten years.
  • The fund has separate funds to support Alaska, Puerto Rico, and the US Virgin Islands.
  • The fund includes the Mobility Fund that pays subsidies to cellular carriers that operate in very rural markets.
  • There are also legacy funds that provide subsidies to regulated telcos operating in high-cost markets.

SpaceX’s recommendation to sunset the various programs refers to the fact that many of the subsidy programs will expire if not renewed. For example, RDOF payments end after the tenth year of payments.

This is not a surprising recommendation. SpaceX and Starlink have been claiming in other forums that satellite broadband technology has solved the universal service problem and that everybody in the U.S. now has access to broadband. That’s been a problematic argument to some extent, since Ookla has been reporting a lot of Starlink speed tests below the FCC’s definition of broadband of 100/20 Mbps. Ookla reported earlier this year that average Starlink speeds had exceeded the 100 Mbps download test and recently reported that Starlink is close to meeting the uplink speed threshold.

However, there is still one troubling aspect of declaring Starlink to be a universal solution everywhere, which is the affordability issue. It’s hard to argue that a product priced at $120 per month, and which requires the purchase of the receiver, is affordable for low-income households. However, there has been no federal effort to define an affordable broadband rate. In the early days of BEAD, before the Benefit of the Bargain changes, various State Broadband Offices around the country were considering a definition of affordable rates between $30 and $50.

There has been a lot of criticism of some of the High-Cost Fund programs over the years. I wrote many times about the ludicrous billions of dollars paid to the largest telcos in the CAF II program that required that rural broadband speeds be increased to 10/1 Mbps – with payments that started months before the FCC raised the definition of broadband to 25/3 Mbps. But there has also been a lot of demonstrable benefits from some of the programs. You don’t have to look much further than the fiber networks built by numerous rural electric cooperatives that were jump-started with the RDOF subsidy.

25-Gigabit Home Broadband

I recently read an article that touted residential 25-gigabit fiber in Switzerland. The article made it sound like the product was available everywhere, and the reality is different, but it is still a great story.

The fiber network being discussed is funded and owned by Swisscom. The company is owned 51% by the Swiss government and 49% by investors. During nationwide discussions in 2008 about the best future path for building fiber in the country, Swisscom pushed for the idea of building multiple fibers whenever new fiber is built. The decision was made to adopt what was called a four-fiber point-to-point model, which means four separate fiber paths built between the network core and each home and business. This would allow for an open-access network with four separate ISPs getting direct layer 1 fiber access to each customer.

In 2020, Swisscom changed its mind and decided to pivot to a point-to-multipoint using splitters where multiple ISPs share bandwidth on the same fiber, which is the traditional open-access architecture that has been used in many communities in this country. This is not entirely surprising since Swisscom doesn’t just own the fiber network, but is also the incumbent telecommunications company that still sells ISP services.

Init7, a small ISP, challenged the change in direction and filed a complaint with COMCO, the regulator in Switzerland. COMCO issued a preliminary decision at the end of 2020 that Swisscom needed to return to the four-fiber model. Swisscom appealed to a federal court, which sided with Init7. In April 2024, COMCO fined Swisscom 18 million francs for being anticompetitive and finalized the ruling that mandated a return to the four-fiber open-access model. Swisscom has now completed fiber construction to over half of the passings in the county and has a goal to pass 75% to 80% of passings by 2030.

The primary ISP offering 25-gigabit service on the Swisscom network is Init7, which uses PON electronics from Zyxel. The company markets under the brand name Fiber 7. The 25-gigabit product is priced at 65.75 francs ($82.73 per month) or 777 francs ($992.70 per year).

There are only a handful of ISPs around the world that widely deploy 25-gigabit broadband technology for residential service. In the U.S., there are now multiple fiber ISPs with products as fast as 5 to 8 Gbps. I have to wonder if there is any practical noticeable difference between these products and 25-gigabit broadband.

Telcom Liechtenstein announced the launch of a nationwide 25-gigabit symmetrical residential product in December 2025. The ISP is using Nokia’s 25G platform. Liechtenstein is unique in that it is one of the few countries that has near-universal fiber coverage. The underlying fiber network is owned by Liechtenstein Kraftwerke, the national power utility, which offers open-access to multiple ISPs.

NURO Hikari in Japan announced the launch of 25-gigabit residential service in parts of Tokyo in March. This network is utilizing electronics provided by So-net, a subsidiary of the Sony Group. The 25-Gbps product is priced at 6,480 yen ($41.08) per month.

Increasing Pushback Against Data Centers

It seems like I’m seeing articles almost every day about local pushback to the creation of new data centers. This sudden surge of antagonism seems to have caught the people who build data centers by surprise.

The following are just a few of the dozens of examples of communities that are skeptical or that don’t want new data centers:

  • After public feedback, local elected officials in Peculiar, Missouri, passed an ordinance to block a $1.5 billion data center proposed by Diode Ventures.
  • A $1.3 billion data center project was withdrawn from consideration in Chesterton, Indiana, following massive community pushback over environmental concerns.
  • In Fauquier County, Virginia, residents successfully pressured Headwaters Site Development to withdraw a $400 million data center project.
  • Residents of Prince George’s County, Maryland, persuaded elected officials to enact a six-month moratorium on data center construction in late 2025.
  • The legislature of Maine passed a new law creating a moratorium on new data centers. While that was vetoed by the governor, the state push was not unique, and similar moratoriums have been discussed by the legislatures in Georgia, Oklahoma, and Vermont. Other legislatures, like Illinois and South Dakota, have scaled back tax incentives that were aimed at attracting new data centers.

It’s an interesting public debate. There are clearly some significant benefits from bringing a data center to a community.

  • Job Creation. There is a big burst of economic benefit while a data center is being constructed. While most data centers bring fewer jobs than suggested by the data center owners, the jobs they bring have high salaries.
  • Tax Base. Assuming that a community assesses them properly, a data center should bring a nice boost to property and other local taxes. The extreme example of this is in Loudoun County, Virginia, which is home to a huge number of data centers. In 2025, the data centers contributed $895 million in local taxes, which represented 95% of the entire County budget.
  • Infrastructure Improvements. The infrastructure needed to support data centers can benefit the wider community if done right. Bringing a data center means new roads, an improved electric grid, modernized water infrastructure, and fiber optics.

The big public pushback comes because there are also downsides to data centers.

  • Huge Users of Electricity. A traditional data center used for cloud services might use as much power as 25,000 homes. An AI data center of the same size might require enough electricity to power 100,000 homes. The new giant data center being built in Louisiana is expected to draw twice as much power as the entire City of New Orleans. Communities worry about higher electric prices, brownouts, and electric shortages.
  • Huge Users of Water. Data centers generate a lot of heat. A chip used for AI consumes 700 to 1,000 watts each, compared to 150 – 300 watts used by a traditional chip used for cloud services. The huge use of power generates heat, so data centers must be cooled. An average AI data center might need up to five million gallons of water per day for cooling. Communities worry about the strain on water systems, particularly in parts of the country that see periodic droughts.
  • Data Centers are Noisy. Data centers generate significant, continuous noise that typically ranges from 55 to 85 decibels. This is generally experienced by neighbors as constant, low-frequency humming, similar in volume to a vacuum cleaner. When backup diesel generators are used or tested, noise can grow to 110 decibels, which is equivalent to the noise generated by a rock concert.
  • Air Pollution. Many data centers are generating their own electricity by constructing a power plant fueled by natural gas or other fossil fuels. Almost all data centers use diesel to power backup generators, and it’s not unusual for a hyperscale data center to have several hundred huge diesel generators. Neighbors say that living close to a data center is like living close to a traditional electric power plant in terms of air pollution.
  • Electronics Waste. The high heat and constant usage for AI can burn out cards in less than two years. This means data centers generate a lot of electronic waste that includes significant amounts of toxic materials and heavy metals. Most local landfills are not prepared for a large quantity of this kind of waste.
  • Require Large Plots of Land. Hyperscale data centers occupy a large plot of land that might otherwise be used for agriculture, residential housing, or industrial expansion. Since nobody wants to be a neighbor to a data center, there is also a larger circle around new data centers where others don’t want to build.
  • Not Transparent. A surprising number of new data center developers are doing things like requiring local officials to sign NDAs before showing their full plans.

The growing distrust of new data centers is not universal, and many communities are actively seeking new data centers because of the benefits. But a growing number of communities are deciding that the downsides outweigh the benefits.

Believing Surveys

A lot of the blogs I write cite the results of surveys on topics I think are relevant to the broadband industry. Every time I see survey results, I ask myself how much trust I can put into the survey results.

There are three elements needed to produce a survey with reliable results. The first element involves who takes the survey. The second important issue is the number of people who take the survey, and the final issue is the quality of the questions asked.

Most surveys cited in articles don’t describe how they found the people who were surveyed. For a survey to be statistically valid, the people chosen to take the survey should be chosen at random. That’s a lot harder than it sounds. Consider a survey that wants to know how many people don’t have a cellphone. The normal process of randomly calling people using landline and cellular numbers will not find people who don’t have any phone service. A lot of surveys cited in articles are clearly not random. For example, a survey given to people who follow a specific website is going to be biased by the type of people who like that website.

Surveys don’t always have to be random to be useful. There is a survey done every year for executives and engineers of cable companies that asks about future technology plans. This survey is clearly not random, so the results don’t have any statistical validity. But since a similar survey is given every year, the survey is great at seeing trends. You probably can’t believe any specific percentages of results that come from this kind of survey, but you can put faith in year-over-year trends.

The number of surveys taken matters. Many business surveys are conducted to be 95% accurate, plus or minus 5%. That accuracy says that if you were to ask the same questions to 100% of the target audience,  the response you receive would be between 90% and 100% the same as the survey results. Consider the following table of the numbers of surveys required to reach a 95% overall accuracy within a given precision for a universe consisting of 5,000 homes, 50,000 homes, or 500,000 homes.

Households ± 5% ± 3% ± 1%
5,000 357 1,351 3,845
50,000 382 1,784 12,486
500,000 384 1,843 16,106

People are almost always amazed at the small number of surveys needed to get a statistically valid and believable answer. What really surprises them is the number of surveys to be able to rely on a survey covering 500,000 homes versus one covering 5,000 homes. The second and third columns show how many additional surveys are needed to have more precision. Many political surveys shoot for an accuracy of plus or minus 3%, which looks like the second column. It’s rare to see somebody shoot for 1% accuracy since it requires such a large number of completed surveys.

The last element of a believable survey is good questions that are not biased. It’s easy to spot obviously biased questions. A survey that asks, “Don’t you just hate customer service at Comcast?” is biased, while the question, “How would you rate Comcast customer service on a scale of 1 to 5?” is not. A lot of bias in questions is more subtle, and the folks writing good surveys work hard to make sure that questions don’t lead respondents to specific responses.

A final element of believing surveys is the topic being covered. People are far more likely to give a false answer when asked about politics or religion than they are about being asked about their preference for a product or company. Professional survey companies say that nearly half of respondents lie about their incomes.

The surveys I mention in my blogs are all over the map in terms of accuracy and reliability. Very few of them describe the process of selecting respondents, and it’s likely that many of the surveys were not administered to a random sample of people. Many published surveys mention the number of surveys given, but don’t mention the universe of possible respondents and don’t report on the accuracy the survey supposedly measures. Many surveys don’t show the exact questions that were asked but instead summarize the results without being specific. The bottom line is that readers should always take survey results with a grain of salt.