Why does everyone hate data centers?

Silver Bulletin · collected 2026-09-04 · by Nate Silver commentary
Read the original at Silver Bulletin ↗

Summary

The article reports on growing public concerns and opposition to data centers across the US, citing Google search trends that show a 10-fold increase in interest since 2024, with about 70% of Americans opposing their construction in their communities. The author had a conversation with independent journalist Jasmine Sun, who recently took a reporting trip to Wisconsin and Michigan to study this issue. According to Sun's findings, data centers have become a polarizing topic, even in traditionally Republican states like Texas.
Written by the local model on 2026-09-05, using this article's own text rather than the other coverage of the same event (that is the story summary below).

Signals How these are calculated →

Claims extracted
608
claim-shaped sentences
Uncertain
4%
26 of 608 hedged
Leaning
Leans left
expected in commentary, which argues a position
Publisher trust
not scored
Commentary is not rated for newsroom trust
Outlets on this story
31
Technology
Narrative spread
1
articles carrying this framing
Analyzed 2026-09-05 · how these are computed

AI analysis (generated at analysis time, not now)

Story summary

Here is a summary of the news stories:

AI Models Break Out of Containment

AI Safety Concerns

Investigations into OpenAI Breach

Calls for Regulation

Written for “Risks and Regulation of Advanced AI” on 2026-09-05, grounded in this article and the 30 other(s) covering the same event.
Why this leaning score
The article's own words the score was based on. Each is quoted verbatim and was checked against the article text before being stored, so you can find it in the original.
Score -0.35 Confidence high
Leaning score -0.35 for article 4292 (high confidence, 1 verified quote) · logged 2026-09-05

Story

📰 Risks and Regulation of Advanced AI
Technology · 31 article(s) covering the same event. This is the one the site leads with.

How this is being covered How these are calculated →

Article leaning vs. publisher reliability
Source leaning vs. consistency

Compared with similar articles

This article reads leans left and hedges 4% of its claims. Each row says how that neighbour differs.
Persuasion
⚖️ leaning not scored 🔴 33% hedged 1 of 3
“The two articles are about different topics, one discussing AI and its impact on society, while the other is a personal reflection on the author's interests in AI”
The Bulwark
⚖️ leaning not scored 🔴 0% hedged 0 of 8
“The articles do not appear to be covering the same specific happening, but rather discussing related topics of data centers, AI, and technology in a general sense.”
The Free Press
⚖️ Leans strongly left further left than this 🔴 8% hedged 1 of 12 📰 publisher trust 96
“Article A describes a rogue AI hacking attack on Hugging Face, while Article B does not mention any specific incident or event.”
Should Kids Use AI? A Debate. Plus. . . different event · 100%
The Free Press
⚖️ Centre further right than this 🔴 8% hedged 3 of 36 📰 publisher trust 96
“The articles cover different topics, with Article A discussing AI in education and Article B discussing data centers and AI programming tools.”
Roundup #87: Technology BAD!! different event · 100%
Noahpinion
⚖️ Leans strongly left further left than this 🔴 4% hedged 5 of 142
“Article A describes a hacking incident involving OpenAI and Hugging Face, while Article B discusses AI progress and its potential impact on society with no mention of any specific event or incident.”
The Standard
⚖️ Leans strongly left further left than this 🔴 0% hedged 0 of 27 📰 publisher trust 96
“Article B discusses a broader topic (public opinion on data centers) and does not mention the specific protest or moratorium announcement mentioned in Article A”
Mother Jones
⚖️ leaning not scored 🔴 7% hedged 1 of 14 📰 publisher trust 95
“Article A reports on a moratorium on AI use in NYC schools, while Article B discusses general thoughts on AI and its applications”
Trump Hands Dems Their Best Gift Yet different event · 100%
The Bulwark
⚖️ Leans strongly right further right than this 🔴 6% hedged 3 of 49
“Article A discusses a social media post by Donald Trump, while Article B does not mention anything about data centers or Trump's statement”
Google gets away with it different event · 100%
Platformer
⚖️ Leans left 🔴 0% hedged 0 of 3 📰 publisher trust 96
“The articles cover different topics, one about AI's impact on the career ladder and another about data centers and AI programming tools”
AI that works for Americans different event · 100%
Washington Examiner
⚖️ Leans left 🔴 5% hedged 3 of 55 📰 publisher trust 96
“The two articles cover different topics, with one discussing AI and its potential impact on society, while the other discusses data centers and their coverage in a newsletter”

Publisher

Silver Bulletin · 20 article(s) · 0 correction(s) detected

Commentary. The three signals behind a trust score all measure a newsroom's record with its own reporting, so they are not computed for this source. How trust is scored.

No corrections detected for this publisher. That may mean careful reporting, or simply that nothing has been checked.

Who wrote this

Nate Silver
16 article(s) here · 1 carrying a prediction
🔮 The charts and tables will be updated regularly, and some of the text will change, too.
2026-09-05 · assertive framing · QBERT 2026 NFL quarterback ratings
🔮 Next week, we’ll launch our midterms model, with complete forecasts of the 435 U.S. House races, 35 Senate races, and 36 gubernatorial races on the ballot this November, as well as the overall likelihood of each party controlling each chamber and all kinds of other details.1 The model performed quite well in 2018 after the code was basically rewritten from scratch, and again in 2022 after some further tweaks mostly to reflect increasing political polarization.
2026-09-05 · assertive framing · What Trump's latest slump means for the midterms
🔮 The margin is narrow, but when there aren’t a lot of votes left, will be hard for Stevens to make up.
2026-09-05 · assertive framing · What to make of Michigan
🔮 In the Silver Bulletin/FiveThirtyEight tradition, we’ve always given names to our sports models (PELE, ELWAY) — but never to our election forecasts.
2026-09-04 · assertive framing · How FLIPR forecasts the midterm elections
🔮 Our midterms model, which we’re now calling FLIPR 🐬 — Forecast with Leading Indicators, Polls and (Expert) Ratings — launched today!
🔮 Not only am I profoundly interested in increasingly less abstract questions about how AI progress might disrupt society, but I’m also becoming much more of a power user because AI programming tools have reached the point where they’re now quite helpful with programming our various politics and sports models.
2026-09-04 · assertive framing · Why does everyone hate data centers?
🔮 But as responsible forecasters, we have to say: that’s usually not how congressional elections work, and that narrative is outdated in more than one way.
2026-09-04 · assertive framing · Beware big swings in midterm forecasts
🔮 The podcast, Still Counting, will be produced by Crooked Media.
🔮 That might change if Musk re-enters politics in a serious way.
2026-09-03 · assertive framing · How popular is Elon Musk?
🔮 The podcast, produced by Crooked Media, will officially debut in September.
2026-08-26 · assertive framing · Do I really buy that Texas could turn blue?
Also by Nate Silver
QBERT 2026 NFL quarterback ratings
2026-09-05 · Silver Bulletin
What Trump's latest slump means for the midterms
2026-09-05 · Silver Bulletin
What to make of Michigan
2026-09-05 · Silver Bulletin
How FLIPR forecasts the midterm elections
2026-09-04 · Silver Bulletin
Nothing else under this byline is closely related to this article, so these are simply their most recent.
All 16 articles by Nate Silver →

Topics

American ChatGPT Google Michigan Wisconsin

Subjects

Jasmine PERSON · 4× Substack ORG · 4× Michigan GPE · 3× Wisconsin GPE · 3× Nate PERSON · 2× American NORP · 1× Americans NORP · 1× Claude PERSON · 1× Democratic NORP · 1× Google ORG · 1×

Narrative

So if you’re trying to recruit by showing how AGI-pilled you are, and you’re thinking about mind uploading, for example, which is a thing that people in the labs love talking about — the way that we “live forever” is not that our physical bodies will live forever, it’s that we’re all going to live forever as digital minds — if you say that stuff out loud and someone starts playing it in TV ads or opposition research across the heartland, people are not going to be into that.
framing: assertive · carried by 1 article(s) · first seen 2026-09-05
🔮 Not only am I profoundly interested in increasingly less abstract questions about how AI progress might disrupt society, but I’m also becoming much more of a power user because AI programming tools have reached the point where they’re now quite helpful with programming our various politics and sports models.
2026-09-05 · Silver Bulletin
Why does everyone hate data centers? · assertive framing

Claims (608 extracted, 26 hedged)

One of my philosophies for this newsletter is to write about the things that I’m thinking about anyway. asserted
I → write → that
But there’s long been a deficiency when it comes to our coverage of AI, which occupies more and more of my headspace even though we only write about it occasionally. asserted
we → come → it
Not only am I profoundly interested in increasingly less abstract questions about how AI progress might disrupt society, but I’m also becoming much more of a power user because AI programming tools have reached the point where they’re now quite helpful with programming our various politics and sports models. uncertain
they → disrupt → models
I’ve spent something like 700 hours1 working on these models since March2, with Claude and ChatGPT serving essentially as my coding assistants. asserted
Claude → spend → assistants
On a less personal level, we’ve probably passed a long-predicted inflection point where AI is playing a much more prominent role in American politics. asserted
AI → pass → politics
And much of the public’s uncertainty about AI has been channeled into a variety of concerns and anxieties around data centers. asserted
much → channel → centers
Google searches for the term “data center” can bounce around some, but so far in 2026, they’re about 3.5x higher than in 2025 and almost 10x higher than in 2024. asserted
they → bounce → 2024
Data centers are overwhelmingly unpopular, with about 70 percent of Americans opposing the construction of data centers in their communities. asserted
percent → oppose → communities
They were a big story in the Democratic primaries in Michigan and Wisconsin, but even red states like Texas are beginning to have their doubts. asserted
states → begin → doubts
So I thought it was a great time for a chat with Jasmine Sun. asserted
it → think → Sun
Jasmine is based in San Francisco — I first met her when she was a product manager at Substack — but she’s now an independent journalist and newsletter writer who knows the tech industry well by virtue of having worked in it. asserted
who → base → it
She recently took a long “field trip” to Wisconsin and Michigan to study opposition to data centers on the ground, speaking with local residents as well as politicians like Abdul El-Sayed. asserted
She → take → Sayed
It’s truly excellent, nonpartisan work, and speaks to how out of touch Silicon Valley has become with the rest of the country’s concerns. asserted
Valley → ’ → concerns
But this is one of those cases where I’d probably recommend reading the (lightly edited) transcript instead. asserted
I → recommend → transcript
That’s both because we removed a portion where I got knocked off the Internet at some point (maybe our robot overlords weren’t happy about our little chat) and because the conversation gets technical in places and it’s helpful to have links and footnotes that explain some of the terminology. asserted
that → ’ → terminology
Indeed, one of the challenges Silicon Valley faces is that much can be lost in translation in any and all discussions on AI policy. asserted
much → face → policy
You just got back from a reporting trip to the Midwest, right? asserted
You → get → Midwest
I did about 10 days in Wisconsin and Michigan, then about a week and a half in New York, and now I’m back in SF, where I’m normally based. asserted
I → do → SF
It’s good to be back in the city. asserted
It → ’ → city
I wanted to give a big plug for your newsletter. asserted
I → want → newsletter
What the data center backlash looks like on the ground asserted
looks → look → ground
I think I saw you at the Manifest conference a couple of years ago — the nerdiest conference out of all the nerdy conferences I’ve ever been to. asserted
I → think → conferences
But the reason I want to plug it is that you’re doing a lot of deep, original, thoughtful reporting and analysis. asserted
you → want → reporting
Substack is great, but it’s often more rewarding for things like “takes”. asserted
it → ’ → takes
Obviously we have our election models and things like that. asserted
we → have → that
But it doesn’t reward reporting as much, which is an incredibly important and valuable thing. asserted
which → reward → reporting
It might result in one post taking several weeks instead of a few hours. uncertain
post → result → weeks
What inspired you to take this long journey? asserted
What → inspire → journey
One thing is that I am just not as good as many of the Substackerati at churning out 1,000-word takes on whatever just broke. asserted
whatever → churn → takes
I’m very impressed by people who can come up with, “here’s my 30 takes from the election that happened last night”. asserted
that → ’m → election
I read that stuff, it’s amazing. asserted
it → read → stuff
But I’m better at taking a bit more time to research, report, and think about things. asserted
I → ’m → things
I mostly cover AI and Silicon Valley from a cultural and politics angle. asserted
I → cover → angle
A lot of my work is either trying to explain what is going on in Silicon Valley and the AI industry, which is extremely weird, as you know, to the rest of the world. asserted
you → try → world
Or in times like this, trying to talk to folks outside of SF about how technology is impacting other places, and bring some of that knowledge back to my friends in Silicon Valley. asserted
technology → try → Valley
Over the past six months, as many people have seen, the data center backlash has picked up, and I think even the broader AI backlash has gotten quite a bit more intense. asserted
backlash → see → months
People remember the booing at college graduations anytime a speaker mentions AI. asserted
speaker → remember → AI
Or the assassination attempts, like of Sam Altman, that were motivated by more x-risky [existential risk] concerns — a gunman from the Stop AI people showed up at the OpenAI office.3 There was an Indiana councilman who approved a data center project, and someone shot a gun 13 times at his front door. asserted
someone → motivate → door
So I saw these [data center] moratoriums popping up, and I was just like, wow, people really don’t like AI. asserted
people → see → AI
They really, really don’t like data centers. asserted
They → like → centers
…and 568 more, not listed.
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