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At a New York Mets game this weekend, I saw something I’m not used to seeing until late summer. No, not the inexplicable late-season implosion of a beloved local franchise — a neon-red setting sun.
West Coasters know this sun well. I call it the “Eye of Sauron” sun; others say it’s “blood-red.” In reality, the color is harder to describe, more like the red-orange-pink insides of a halved grapefruit. It feels unnatural and eerie, and is the effect of shorter wavelengths of light being filtered out of a sunrise or sunset by particles in the air caused by pollution, including wildfire smoke.
I immediately grabbed my phone to find the source of the haze, but a quick Google search of “Where is this smoke coming from?” didn’t turn up any immediate results. In fact, it can be frustratingly difficult to figure out the origin of wildfire smoke when you see or smell it. This only gets more difficult as fire season wears on; is the smoke you’re inhaling from a small nearby fire, or part of a bigger burn blowing in from somewhere else?
Unfortunately, there isn’t a handy app yet that will simply tell you “the smoke overhead is from the Canadian fires” — which, in the case of the pollution I was experiencing in Flushing Meadows, it actually was. But you can cobble together an answer about where smoke is coming from by using a few different methods.
When you climb a mountain, an inaccurate forecast can be the difference between life and death. I learned about the MyRadar app from an experienced mountaineering guide who swears it is the most accurate weather app on the market. It’s also become my go-to app for figuring out where the wildfire smoke I’m inhaling is coming from.
The app pulls data from the United States Geological Survey, InciWeb, and the United States Forest Service’s Risk Incident Information Management System to build its smoke and fire maps (it also received a wildfire detection grant from the National Oceanic and Atmospheric Administration last year). Hovering over my house at around 2 p.m. on Monday, the app clearly told me I was experiencing “moderate air quality” and “heavy smoke hazard.” Zooming out, it’s easy to guess based on the shape of the “heavy smoke hazard” cloud that the pollution is wrapping down from the massive fires burning in Alberta, Saskatchewan, and British Columbia. You can also overlay wind patterns on the app for further confirmation.

MyRadar’s visuals can get a little cluttered, though, and parsing this information still leaves you with an informed guess. But it’s one that can be easily cross-checked against the EPA’s AirNow app.
The EPA app is a little more straightforward: It gives users an upfront measurement of their air quality index, or AQI, which, with a click, can be broken down into “primary pollutants.” In the case of New York City on Monday, it was PM2.5, the expected particle from wildfire smoke (and also “the bad one” when it comes to your health). The app also shows a “forecast” of how the AQI is expected to develop over the coming hours; in New York’s case, it was going to get worse before it got better.
The AirNow app additionally has a “smoke” tab that shows a similar smoke plume overlay as MyRadar’s. By clicking on the globe in the upper left-hand corner, you can view additional fire information, including how far away the nearest burn is, and confirm if you’re under a smoke plume. Using these two pieces of information together, you can further deduce if the smoke you’re experiencing is blowing in from somewhere far away or nearby (some of New York’s smoke may be from the Cannon Ball 2 Fire to our northwest, in Passaic County, New Jersey, but the app shows me that fire is fairly small — 107 total acres — and so in this case, it is not the main culprit).

The BlueSky Canada Smoke Forecasting System (FireSmoke Canada) is run by the University of British Columbia, and while it has an emphasis on Canadian air quality, it is run in partnership with the United States Forest Service and includes U.S. data too. The FireSmoke Canada website specifically tracks PM2.5 smoke particles at ground level from wildfires across North America (“ground level” is an important distinction because sometimes smoke plumes will be too high in the atmosphere to actually affect your health). The FireSmoke Canada map throws in a time-lapse animation and for my purposes, it clearly showed that the smoke in New York was coming down from the Canadian fires.
The FireSmoke Canada map is also a great way to figure out the origin of local fire smoke too since it often shows plumes from even small blazes (though it has technical limitations too, which it details in its FAQ). Unfortunately, the service doesn’t allow users to click on a fire to learn more information about it, which means toggling back and forth between the AirNow or MyRadar app, or the FIRMS U.S./Canada website, to get a fuller picture of what is going on.

Other discrepancies between the apps can be frustrating; AirNow, for example, still shows the Great Lakes Wildfire as burning in North Carolina, though it’s not appearing on FireSmoke Canada’s tracker; MyRadar provides the most context, showing the containment at 90% and labeling its status as “minimal.” On the other hand, MyRadar and AirNow don’t show a fire near Hanford, Washington, while MySmoke Canada does.
Short of doing your own detective work with various wildfire tracking services, local media otherwise remain the best option for figuring out where smoke is coming from. The Hanford blaze that eluded MyRadar and AirNow, for example, is easily confirmed by the regional press; started by lightning, the fire reportedly burned around 1,000 acres and is now 100% contained.
Turns out, Googling “Why is it smoky outside” — while it might feel archaic — still might be one of the best options.
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A conversation with the Guardrails Alliance’s Shaunna Thomas.
This week’s Q&A is with Shaunna Thomas of the Democrat-allied super PAC Guardrails Alliance, which describes itself as “not anti-technology” but supportive of AI “rules, accountability, and a government that actually represents the public.” Part of that AI accountability they’re calling for is on data centers.
After the midterms, Guardrails Alliance sent a memorandum to all House and Senate Democratic offices arguing for AI and data center accountability to be a key part of their message and plans heading into the new Congress. Described as a “playbook for how to understand and channel anxieties about AI and data centers,” the document laid out “key narratives” that they said voters who care about these issues want to see reflected and echoed by their politics. They said the push against data centers could help Democrats build more lasting political power.
I reached out and asked if Thomas could explain further what all of this means to my readers. She kindly obliged.
The following conversation was lightly edited for clarity.
Let’s start with the elections. What were your takeaways when it came to what voters want to see on data centers?
I think the elections were a rebuke of the status quo on a number of fronts. We saw across the board that people are frustrated with what amounts to legalized corruption and the forcing without consent of new technology, and new infrastructure to support a technology that they didn’t ask for in ways that are harmful to their lives and the country.
What we saw in polling is that the data center backlash is one of the most bipartisan political issues of our time, driven by everything from noise pollution to rate hikes to Big Tech trying to steamroll state and local governments. Americans are sick and tired of the AI industry trying to control our lives by building data centers in our communities, which goes along with trying to control our data and who represents us in government. The AI industry was also trying to spend a lot on elections trying to control the outcome.
When we dig deeper on all that, it’s not just about elections. They’re seeing this unholy alliance between Big Tech and the Trump administration.
In the post-election analysis laid out in that memo, you explain these key narratives that you think Democrats should pick up against the tech sector. Can you explain how you developed these?
What we dug into during the primaries and the lead-up to the general election was questions in focus groups and polling with Republicans and Democrats about what was behind the frustration. Is this just about buildings they don’t want in their backyard or is this connected to AI and bigger picture concerns over who makes choices? About control? The data centers people were most opposed to were data centers specifically for AI, which was a really important indicator it was both/and.
We then started to talk to voters in Ohio and Iowa and Michigan about what they’d want to see in terms of changes, in terms of new leadership, how they would want to see this framed. What was appealing? We tested a number of frames and these key narratives are a compilation of that data. So for example, a key narrative says, The AI oligarchs and their political allies are wildly out of step with a supermajority of the public. There’s also sample messaging under it in the memo. And it’s a reflection of the sentiment and the tone and the language a lot of people used when they got into robust conversations about what they’re really concerned about or what they want to see their leaders doing differently.
Can you say more about these focus groups? And can you say more about what you saw in terms of bipartisan shared concern around not just data centers but these messages you’re bringing up?
I can tell you about some of the key findings of the focus groups we did in Michigan and Ohio and Iowa in August and September. People are generally open to the idea AI can have some benefit to their lives, and they’re open to using it personally. But everyone we talked to expressed some concern about the pace it was being developed. You can see technology having value but also see there’s no regulation in place or guardrails around the technology itself.
Most people we spoke to expressed concerns about how the technology has been affecting society and the environment — that came up a lot in data center conversations. People are also concerned about the role chatbots could have in their children’s lives, and that AI could replace teachers.
It’s also a lot of concern about and a lack of confidence in either government regulators or AI companies to properly regulate the technology. You saw more support for regulators at the state level and people deeply opposed to federal pre-emption, because they see more evidence of democracy working at the state level as opposed to the federal level.
People express mixed reviews about the specific policy solutions. What we’re seeing is people see AI as a vehicle for a small handful to amass more wealth and power. I don’t think we have had enough of a robust debate about how you deal with that problem.
So, on that point in particular, I want to drill down. What do we know about what voters want to see? What does accountability or guardrails look like to them?
First of all, there’s blanket support for federal regulations in general to deal with the way the technology is developed and deployed. We see a lot of clarity from voters about the fact they may not have a lot of confidence the federal government will step in. They want to see it.
When it comes to the economy, where there’s still broad public support is taxing billionaires and CEOs of these companies and raising the minimum wage and raising the social safety net. People’s interest in seeing that move forward has been growing in intensity.
On AI specifically, people don’t want to have a conversation about distribution of wealth without a conversation about distribution of power. They don’t want to be bribed to accept the acceleration of AI in their lives. They want to know that the power of those companies to do what they’re doing is going to be significantly limited and safety guardrails are put in place to keep us all safe from what the new technology is capable of.
I think once the safety conversation is step one. Step two is the conversation about how you distribute wealth from a technology built on other people’s labor and intellectual property.
On the concern about bribes, we’ve been reporting on Trump’s call for cash payments to communities to accept data centers. Are you telling me proposals like that might not be a good political strategy?
It was precisely because Trump was talking about it that we heard it brought up in focus groups, and how it was described was that voters may get some short term incentive to accept a technology they don’t trust is designed to help them fundamentally. They believe it is being deployed to more deeply consolidate power and wealth. And they don’t want that. When the president or a big AI company says they agree with it, it’ll have an impact on how the idea is perceived.
It has to also be coupled with a set of policies that are putting democratic governance over the technology itself before its deployment. People want to see technology isn’t going to continue to advance without guardrails.
Distinct from Trump’s data center dividend, some policymakers have suggested a “data dividend” — a distribution of wealth from the usage of AI products because they’re using people’s data. That’s more of what we’re talking about.
What do we know about what the public wants to see regarding data centers?
It’s important we recognize local leaders have had demands driven by their local communities. But as a structural matter, the public sees slowing down data centers as a mechanism for slowing down the project of AI generally. It remains an open question about how you do that.
There are federal policymakers working on a set of solutions that could create more space for people at the local level to be in the driver’s seat on when, how, or if data centers get built. I think we’ll see more proposals on that front.
So where do you think this conversation goes next?
I would expect the public to continue to make demands from policymakers and I would expect the Big Tech sector to continue down the path they’re going, which is, we were always Democrats and pro-regulation all the time. This will look like policies resembling always being okay with regulation but actually avoid putting checks on their power. And that’ll mean the public has even more at stake and the government has an even bigger obligation to make sure AI is deployed for public benefit as opposed to for the profits of a few companies and CEOs.
Plus more of the week’s biggest development fights.
1. New York City — We have a new must-watch offshore wind lawsuit with potential implications for the entire sector — and this time, it’s from lobstermen seeking damages.
2. Hinds County, Mississippi — The largest proposed solar farm in Mississippi is moving forward after an appeals court rejected arguments from aggrieved local residents that it had been improperly approved.
3. Dakota County, Minnesota — I’m scrutinizing a lawsuit against a data center developer centering on allegedly improper permitting of its cooling technology.
4. Polk County, Florida — Will the Sunshine State remain a challenging place for data centers after Ron DeSantis? A test case could reveal the future quite quickly.
Trump’s “data center dividend” appears to have backfired. Our latest poll results help explain why.
This year’s midterm elections called into question the efficacy of a push to pay local residents directly in exchange for building data centers.
Before the elections, I profiled the campaign for politicians to embrace the data center “dividend,” a policy idea modeled off Alaska’s Permanent Fund, which doles out checks to residents from profits off state oil, gas and mineral royalties. The Bitcoin Policy Institute, a tech policy think tank, was one of the first to trumpet the concept, but it was quickly taken up by President Donald Trump, who started raising it in speeches and on social media. “If companies want to make their Data Centers popular, pay the community, and/or individuals within the community, a ‘dividend,’” Trump posted to Truth Social on October 21.
Clearly the idea didn’t stop the bleeding. Democrats trounced Trump’s party in the midterms on a message that was heavy on attacks against data centers. But that still doesn’t explain why direct payments did so little to move the American public.
A Heatmap Pro poll conducted in early-to-mid October, right before the midterm elections, gives us an answer. As part of a broader survey of 2,500 registered voters, we asked about the idea — what we believe to be the first independent poll on direct payments for data centers by a news organization. We asked respondents whether there was a specific dollar amount they’d accept as a one-time cash payment in exchange for a data center being built near them. We also gave them the option to say no amount of money was sufficient.
Shockingly, a majority of people surveyed said they’d reject the data center cash payment in any amount. Among those who said they’d actually take the money, the median figure was around $10,000. The average was a whopping $146,000, skewed by the number of people who wrote $999,999, the maximum allowed by the survey.
This tracks what we’re seeing play out in communities where developers have tried this idea. In Hazle Township, Pennsylvania, NorthPoint — developer of an Amazon-linked data center project — proposed $10,000 cash payments to residents, no catch. Residents compared it to a bribe. In De Soto, Kansas, data center developer Digital Realty is offering annual $1,000 tax credits for a decade to neighbors of its proposed data center project. That proposal has been reportedly met with mixed reviews, too.
Clearly one of the problems here is that data centers not only face public perception issues around their local impacts, but are also more broadly associated with systemic inequality in the U.S. economy. The same Heatmap Pro survey found that a majority of voters believed AI companies have more control over the government than the oil and gas industry, pharmaceutical companies, banks, or other large industries.
Shaunna Thomas, executive director of Democratic-allied super PAC Guardrails Alliance, told me that during the campaign season they found that residents often associated the dividends with bribes, and that the president’s support for direct payments ultimately fed into voter sentiments about the tech sector controlling the government and society.
“People don’t want to have a conversation about distribution of wealth disconnected from a conversation about distribution of power,” Thomas said. “Specifically because Trump was saying that, we started hearing from voters in focus groups that it didn’t work for them. They’re hearing it as a bribe. They’re hearing they may get some sort of short-term economic or financial incentive to accept a technology they don’t trust is designed to help them.”
The Heatmap Pro survey results about cash payments ultimately reveal how emotionally driven the data center debate has become, said Sam Lyman of the Bitcoin Policy Institute. I asked Lyman to respond to the results because I thought they called into question the political effectiveness of the proposal we’d discussed months earlier. Lyman stipulated that he thinks the one-time payment nature of the question may have undermined the results, saying he prefers the dividends be paid out “in perpetuity.” But he acknowledged they also show “there’s still a lot of education to be done on data centers, what they do, and the impacts they have on the places where they’re built.”
“I think there’s a lot of Americans out there who have legitimate concerns that the future economy doesn’t include them. That’s something that needs to be addressed,” said Lyman, who said he laid part of the blame on what he called “irresponsible rhetoric” from AI industry executives about their technology’s impacts on society. “With data center dividends, the idea behind this policy is to help Americans understand the AI economy includes them. To give them a very material stake in that economy as it gets built out, especially in the rural communities that make data centers possible in the first place.”