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Posted on 10/02/2026 7:46:04 AM PDT by Az Joe
(Straight from Amazon) One of the big lessons that the United States took from World War II was the need for national transportation infrastructure back at home. A system of interconnected highways, bridges, and roads was critical for national defense and would also provide much needed economic prosperity following the war. In 1956, the government began to build the National System of Interstate and Defense Highways, an infrastructure project larger than anything the country had seen since the railroads a century earlier—and paid for entirely with taxpayer money. The buildout of America’s modern transportation system transformed the U.S. economy and way of life, creating countless new businesses and jobs, and connecting communities in ways that reshaped how Americans lived and worked. Seventy years later, we’re in the midst of the largest infrastructure buildout since the highways—our digital infrastructure.
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But I'd separate Amazon's four "myths" this way.
1. “Data centers are taking all our water.” Amazon is substantially right that the nationwide picture is often exaggerated. Data centers do not consume anything close to the majority of U.S. water, and agriculture remains enormously larger.
But Amazon's national comparison can conceal the real issue: water is fundamentally a local resource.
A data center using a relatively small percentage of total U.S. water can still be significant if it is concentrated in a drought-prone county or competes with municipal supplies. That's particularly relevant in the Southwest. Arizona, for example, continues to experience serious long-term drought conditions, and commercial and industrial users—including data centers—are an important part of metropolitan water planning.
Amazon also appears to be genuinely more water-efficient than many older data-center designs. Its claim that AWS has dramatically improved its water efficiency is plausible and consistent with its documented shift toward air cooling and reclaimed water. But the very impressive figures—such as being "seven times more efficient than the industry average"—are Amazon's own metrics and comparisons rather than an independent nationwide audit.
So I would rewrite Amazon's claim as:
Data centers are not a major share of total U.S. water consumption, but they can be a major local water issue depending on geography, cooling design and water source. That's quite different from simply calling the concern a "myth."
2. “Data centers aren't driving electricity rates higher.” This is probably the most misleading part of the article. Amazon is correct about one important point: data centers do not automatically cause residential electricity prices to rise. If utilities design their rates properly and require data centers to pay for generation, substations, transmission lines and other infrastructure needed specifically for them, existing customers can be protected. But the risk of cost shifting is absolutely real. The U.S. Department of Energy explicitly identifies the need to prevent infrastructure costs associated with large loads from being unfairly shifted onto other customers.
And just this week, FERC has been dealing directly with that issue in PJM. FERC officials have said that customers generating new infrastructure costs should bear appropriate responsibility rather than leaving existing customers to pay them.
So Amazon's statement that rising prices are primarily because "the grid is old" is incomplete.
The fuller causal chain is:
old grid + inadequate generation + rapidly rising electricity demand + slow permitting/interconnection + data-center growth + other industrial/electrification demand = enormous new investment requirements.
Data centers are not the sole cause, but they are becoming one of the largest new sources of load growth. Berkeley Lab says electricity use by data centers nearly tripled from 2016 to 2023 and could rise substantially again by 2030.
So calling concern over electricity prices "convenient scapegoating" is unfair.
3. “Backup diesel pollution is a myth.” Amazon has a reasonable point here, but again it oversimplifies.
Emergency generators really do spend most of their lives idle, and permit documents showing theoretical maximum annual emissions can create a misleading impression if somebody presents those maximums as actual annual emissions. But that does not mean diesel-generator pollution is imaginary.
EPA specifically regulates stationary engines and backup generators at data centers because they emit pollutants including nitrogen oxides, particulate matter and hazardous air pollutants.
There is another wrinkle Amazon doesn't mention: grid stress can cause generators to run for reasons beyond occasional maintenance or rare site-level outages. EPA notes that during extreme electricity demand in 2026, DOE orders allowed or required large customers including data centers to operate backup generation as an emergency grid measure.
Thus the fair conclusion is:
Routine diesel emissions from a well-operated data center are probably much smaller than some critics imply, but emissions are real and can matter locally, especially where many facilities are clustered together.
Amazon turns a question of magnitude into a yes-or-no "myth," which makes the argument sound cleaner than reality is.
4. “Communities get nothing from data centers.” Here Amazon has a strong case against the literal claim. Data centers can generate enormous property-tax revenue. Loudoun County, Virginia—the biggest U.S. data-center concentration—is compelling evidence. In FY2026, data centers generated about $1.2 billion in local real and personal property taxes, around 39% of the county budget. The county says that revenue has helped finance schools, public safety and infrastructure while allowing it to keep property-tax rates comparatively low.
So anyone saying data centers provide no local economic benefit is plainly wrong.
We couldn’t lose the arms race, we couldn’t lose the space race, we couldn’t lost the race for renewable energy, now we MUST rush headlong into the Data Center race.
From the article: “we aren’t the only country that sees the benefits of AI”
Does “our country” see benefits equaling the trillions being invested in it with borrowed money? Our country also sees reasons to fear a massive AI.
The article, as is the case with virtually all pro-AI articles, mentions no specific benefits.
Nor do they quantitatively mention the revenue the AI providers are receiving from customers.
As others have wondered, are we headed for an AI financial bust?
So anyone saying data centers provide no local economic benefit is plainly wrong.
Community investment - the best one BY FAR is to set up a local electrical power generation with additional capability, to power the data centers, and just to make it economically competitive, use the technology that involves the use of Small Modular Nuclear Reactors, which get around almost all the objections of early-model Light Water Reactors, which were huge behemoths and dinosaurs almost from the first day they went into operation.
https://www.energy.gov/ne/advanced-small-modular-reactors-smrs
F@#$ you. The data centers are no more than power centers that produce leccy. Almost all privately built — mebbe insured by Fed if weird tech is used.
Calling for Fed $$ to build or even support data centers is typical ploy by parasites. See Solyndra and the BulletTrain — nothing but scams that were skimmed by the clowns in charge by bribing the politicos involved.
The printing press, 1400s–1500s: Authorities feared uncontrolled information, religious upheaval, propaganda, and loss of control over knowledge.
Industrial machinery, 1700s–1800s: Workers feared permanent job destruction. The Luddites became famous for attacking machinery they believed threatened their livelihoods. Railroads, 1800s: Some people feared high-speed travel would physically harm passengers, while others worried railroads would destroy established communities and ways of life.
Electricity, late 1800s: Electrocution, fires, and invisible electrical forces caused considerable public anxiety. The telephone, late 1800s: Critics worried it would invade privacy, weaken face-to-face relationships, and allow strangers into the home socially.
Automobiles, early 1900s: Cars were seen as dangerous, disruptive, noisy, and socially destabilizing. Traffic deaths rapidly became a major concern.
Radio and television, 1920s–1950s: People worried about propaganda, political manipulation, advertising, violence, and the effect of mass media on children.
Nuclear technology, 1940s onward: This produced perhaps the closest historical parallel to the most extreme AI fears because the technology genuinely raised the possibility of civilization-scale destruction.
Automation and computers, 1950s–1970s: There were repeated predictions that computers and robots would eliminate huge numbers of jobs and create mass unemployment.
Genetic engineering, 1970s onward: Scientists themselves worried about accidentally creating dangerous organisms. The 1975 Asilomar conference was organized specifically to establish safeguards.
Personal computers and computer networks, 1980s–1990s: Concerns included job displacement, hacking, viruses, privacy loss, and dependence on machines.
The Internet, 1990s–2000s: Fears centered on pornography, scams, identity theft, misinformation, children encountering harmful material, and the destruction of traditional businesses.
Social media, 2000s–present: Concerns shifted toward addiction, polarization, misinformation, surveillance, mental health effects, and political manipulation.
One important pattern repeats throughout history: people often correctly identify that a technology will cause major disruption, but they are much less accurate about exactly what that disruption will look like.
AI is unusual because it combines several earlier fears at once. It resembles industrial machinery because of jobs, the Internet because of information and misinformation, nuclear technology because of catastrophic-risk arguments, and computer viruses because of fears that increasingly autonomous systems could become difficult to contain.
The five closest historical parallels to today’s AI fears are probably these:
Industrial machinery and automation — 1800s onward. This is the strongest parallel for job loss. Workers feared machines would replace human labor, reduce wages, and concentrate power in the hands of factory owners. Those fears were partly justified, although new industries and occupations also emerged. Nuclear technology — 1940s onward. This is the closest comparison to existential AI fears. Nuclear weapons introduced the idea that human beings had created a technology powerful enough to threaten civilization itself. AI discussions about catastrophic loss of control echo that concern, although the technologies and risks are very different.
The Internet — 1990s–2000s. This closely resembles AI because it rapidly transformed commerce, communication, media, privacy, crime, and everyday life. Early predictions ranged from a utopian global community to fears of rampant fraud, pornography, misinformation, and social isolation. Both the benefits and some of the dangers turned out to be substantial. Radio and television — 1920s–1950s. These produced major concern about propaganda and manipulation of public opinion. Governments suddenly had technologies capable of reaching tens of millions of people simultaneously. AI-generated voices, images, video, and personalized persuasion raise a modern version of the same problem.
Genetic engineering — 1970s onward. The similarity here is that the scientists developing the technology themselves raised concerns and called for safeguards. In the 1970s, researchers worried about accidentally creating dangerous organisms, leading to the 1975 Asilomar conference and voluntary safety rules. The AI field has had similar debates about testing, containment, and regulation.
What makes AI especially unusual is that it potentially combines all five concerns: Automation → jobs Nuclear technology → catastrophic risk Internet → rapid societal disruption Mass media → manipulation and misinformation Genetic engineering → scientists warning about their own creation
That combination helps explain why the anxiety surrounding AI can feel greater than the fear surrounding most earlier technologies.
The phrase “AI War” is nebulous enough such that it can mean whatever its proponents want it to mean. It is frequently used by tech executives and political figures as a high-stakes buzzword to bypass local resistance, and is a powerful rhetorical tool often used by data center developers, tech conglomerates, and aligned policymakers to create a sense of national urgency. By framing data center expansion as a matter of national survival, proponents can bypass local opposition and fast-track approvals.
Tech companies define “winning” as raw compute capacity (more data centers, more chips, more power). This directly aligns with their business goals of corporate growth and market capitalization.
While the benefits of winning the AI war are framed as public and national, the profits remain strictly private. Tech companies use public infrastructure (water, electrical grids) and often receive massive local tax breaks under the guise of patriotic necessity.
There is no agreed-upon finish line for an “AI war.” Because tech evolves constantly, the argument creates a permanent state of emergency that justifies indefinite, rapid data center expansion.
The vast majority of data center capacity is currently being built to power commercial products like search engines, ad-targeting, productivity software, and consumer chatbots, not systems deemed necessary for national security.
See post #8 doofus
EXCELLENT JOB putting that clarification (Amazon data centers) in your headline!!!!
(Straight from Amazon)
The article link definitely caught my eye
AI Overview:
Whole Foods removed its Amazon One hand-scanning payment system because of limited customer adoption and low usage
Why the Technology Was Stopped
Low Demand:
Shoppers did not use the palm-scanning terminals enough to make the program worthwhile across more than 500 locations.
Privacy Concerns:
Many customers felt uncomfortable sharing biometric data, such as palm and vein patterns, tied directly to their credit cards and personal identities.
Corporate Shift:
Amazon decided to pull the hardware and shut down the retail palm recognition service entirely, removing the devices from all Whole Foods stores by June 3, 2026.
What Happened to the Data
Amazon announced that it permanently and securely deleted all stored customer information, including palm scans, names, phone numbers, and linked credit card details, after shutting down the service.
🤔🤔🤔
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I suspect that The Chinese Social Credit Score System will eventually return - but another FReeper had mentioned Whole Foods on another thread several weeks ago
HOW ABOUT PUTTING THE DATA CENTERS INTO MILITARY BASES???
LOTS OF CLOSED LOCATIONS.
AGRICULTURE FEEDS US ALL.
WHAT FOOD DOES A DATA CENTER PRODUCE?????????//
DATA CENTERS ARE NOT USING ARTIFICIAL WATER.
DATA CENTERS ARE NOT USING ARTIFICIAL ELECTRICITY.
During the Covid hysteria did you wear a surgical mask when driving alone?
You are good at using AI to defend AI.
What do you know?
People are scared that AI could become so powerful that it could destroy all of humanity. But it could also have negative impacts.
Remember, folks, none of you can live without Griffin brand snake oil.
Nobody goes lower to the ground than Griffin.
Nobody is slimier than Griffin.
On a more serious note, what is the value of more data centers?
Ten minutes of video instead of eight, when I shun videos?
If you can’t state your case in plain English words and a few pictures or graphs, maybe your case is weak.
“did you wear a surgical mask “
Only when required
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