2025-05-12 20:00:00
There are two things you should know about President Donald Trump’s recently released budget proposal: First, it would significantly boost funding for Homeland Security and the Department of Defense while cutting social services that could hurt millions of people living in poverty. Second, his budget is just a proposal for Congress, and it almost certainly won’t become law.
But just because Congress is unlikely to pass Trump’s budget as is doesn’t mean that the proposal is entirely meaningless. It will likely influence what Republican lawmakers choose to focus on during negotiations in Congress, and, more importantly, it offers a window into his priorities.
Trump’s budget proposal looks to cut a total of $163 billion, slashing funds for education, housing, and health programs. Many of those cuts would come from programs that help lower-income Americans, from youth job training to Federal Work-Study. The cuts don’t include Social Security, Medicare, and Medicaid — some of the country’s biggest programs and the cause of the most heated debate over welfare reform. That’s because the proposal is limited to discretionary spending, and programs like Social Security and Medicare are mandatory spending.
Trump knows that gutting programs like Social Security and Medicare would likely have major political consequences. He has promised not to touch those programs other than by tackling waste, fraud, and abuse, though these are often a pretense to deliver benefits cuts anyway. The new budget proposal emphasizes that he hopes to overhaul the social safety net without igniting a fierce backlash. He’s betting, in other words, that people just don’t care enough about these less flashy parts of the social safety net or about how aid is delivered to people in need.
One of the departments that would see the deepest cuts under Trump’s budget is Housing and Urban Development, which would lose $33.5 billion. Most of that, about $26 billion, would come from significantly reducing funding for rental assistance programs — including public housing, vouchers, and housing for the elderly — and combining them under a single program. The budget also proposes introducing a two-year limit on rental assistance for able-bodied adults.
The proposal would not only put millions of people’s benefits at risk, it would also upend how federal rental assistance works entirely.
Right now, money for housing vouchers, for example, goes toward directly subsidizing people’s rents. The White House wants that money to go to block grants instead. That means the funding would go into a pool of money that can be used to fund various state or local housing programs, giving states more flexibility in how they choose to spend it, even if that means they won’t go toward directly helping with rents. So hypothetically, money that is today intended for housing vouchers could be used to fund a program to give developers incentives to build more housing. (And while it’s good to build more to lower the cost of housing in the long term, that shouldn’t come at the cost of taking away direct rental assistance that helps keep people housed.)
There is precedent for this kind of switch. In 1996, Congress passed a law to create Temporary Assistance for Needy Families (TANF), which replaced the old, New Deal-era welfare system known as Aid to Families with Dependent Children (AFDC). While the latter provided direct federal payments to people who qualified, TANF created a system of block grants, where states could allocate welfare funds as they wished.
At the time, the argument for this funding structure was that states needed more freedom to spend welfare funds. But the block grants resulted in states diverting funds away from basic cash assistance. According to the Center on Budget and Policy Priorities, states spend just over one-fifth of their TANF funds on basic assistance, instead directing resources toward, in some cases, unrelated programs like funding tax cuts.
As Peter Germanis, who worked on welfare reform in the Reagan administration, put it: “When it comes to the TANF legislation, Congress got virtually every technical detail wrong,” Germanis wrote. “Congress gave states too much flexibility and they have used it to create a giant slush fund.”
By turning the federal government’s various forms of rental assistance into a single block grant program, the Trump administration might make it less likely for renters to receive the direct benefits they are entitled to, just as was the case with welfare reform in the 1990s.
That’s not to mention that the proposed budget cuts would be devastating to begin with. What renters need is actually the opposite of what Trump is proposing: more funding for rental assistance, not less. Federal rental assistance already helps lift millions of people out of poverty each year, but it doesn’t reach everyone who needs it, especially given the rise in housing costs.
Another major cut that Trump is proposing is a program that helps families cover their home heating and cooling bills. His budget also includes a $4 billion cut to the Low-Income Home Energy Assistance Program (LIHEAP). Given that the LIHEAP budget is also around $4 billion, this essentially means that it’s seeking to eliminate the program altogether. The budget states that LIHEAP “is unnecessary” and alleges that the program is riddled with fraud.
LIHEAP, established in 1981, is one of those government programs that might not generate as much controversy as Social Security or Medicare, largely because it’s much smaller in reach and scale. But it’s a critical program that currently helps about 6 million families across the country. LIHEAP, along with the Weatherization Assistance Program, also helps cover the costs for home improvement projects, like wall insulation or furnace replacements, to make homes more energy efficient, especially in extreme weather conditions.
Eliminating this program could have catastrophic consequences for some families. “The stakes of this assistance can be life-and-death,” journalist Martine Powers wrote in the Washington Post last month. “Seniors are especially vulnerable to extreme temperatures. Getting electricity cut off for failure to pay bills can also be catastrophic for people with disabilities who depend on medication that needs to be refrigerated.”
While LIHEAP has helped millions of families, it has also been underfunded, threatened by presidents of both parties, and doesn’t reach nearly as many people as it should. In fact, according to the National Low Income Housing Coalition, the program is only able to serve 20 percent of eligible households. Many eligible people also don’t know they qualify for the program and don’t apply for it.
Similarly, rental assistance programs help a lot of people stay housed, but they clearly aren’t reaching everyone they ought to, in large part because they’re underfunded. About half of renter households in the US are cost-burdened, which means they spend more than 30 percent of their income on housing.
Those are the kinds of issues that require real solutions, which would likely entail more funding, not less. But Trump’s budget underscores the problem that America’s social safety net constantly faces: Instead of looking for tangible fixes to improve programs like LIHEAP or housing vouchers, lawmakers often find ways to make them even harder to access, setting them up for failure. As I wrote in a previous issue of this newsletter, that was the case with public housing, which presidents and Congress routinely sabotaged before labeling it a failed experiment, even though they at times specifically designed it to fail.
And though Trump’s budget is not likely to become law — Republican Sen. Susan Collins, for example, said she has “serious objections” to Trump’s budget, including his targeting of LIHEAP — it shouldn’t be dismissed as a symbolic wish list. Even if Congress doesn’t deliver what Trump wants, these programs still won’t be safe. Just last month, for example, Trump abruptly fired the entire staff running LIHEAP, jeopardizing the delivery of heating and cooling assistance to families across the country.
So even if Trump’s budget never sees the light of day, here’s what you should keep in mind: It’s a blueprint for how his administration will hurt low-income families.
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2025-05-12 19:45:00
Every week on Explain It to Me, Vox’s call-in podcast, we answer the questions that matter to you most. When we got a question from a listener named Hannah, it piqued our interest. She wanted to know: How do you find a long-lost relative?
“I was raised by my mom,” she says. “I knew my dad was out there somewhere, but I never really gave too much thought about it because I did have a pretty full life.” By the time we spoke with her, she had found her father online and reached out to him. But it raised an entirely new set of questions. “I never gave much thought to, ‘Okay, so now what?’”
Journalist Libby Copeland has spent a lot of time thinking about those next steps. She’s the author of The Lost Family: How DNA Testing Is Upending Who We Are, a book that looks at the ways at-home DNA testing has shaped families. “This whole question around the distinction between biological and non-biological family and roots and identity, it’s everything to me,” Copeland told Vox. “I think it’s so intrinsically connected to existential questions around who we are and how we get to decide what to be.”
On this week’s episode, we discuss with Copeland how to find family, the way at-home DNA tests have changed things, and what to do if you come across an unexpected relative. Below is an excerpt of the conversation with Copeland, edited for length and clarity.
You can listen to Explain It to Me on Apple Podcasts, Spotify, or wherever you get podcasts. If you’d like to submit a question, send an email to [email protected] or call 1-800-618-8545.
Has this reporting changed the way you think about family?
Definitely. I grew up in my biological family, so I’m not someone who was donor-conceived or adopted. But spending so much time talking to people who don’t have a genetic connection to the families that they were raised in, it’s really interesting to hear just how much pull that genetic family has over you.
In my family, we were able to connect with ancestors in Sweden, and then we traveled there and we’re able to connect with a second cousin of my dad going back a hundred-and-something years from when our relative had emigrated. That made the world seem so much smaller and so much more intimate. It made history feel present to me. It made me feel like the past wasn’t over.
If someone’s taken one of these at-home DNA tests and they realize they have a family member, how should they go about trying to connect with them?
It very much matters who it is and how much knowledge you have going into it. It’s often easy to start with the person you’re finding [through the test] just because they’re the immediate connection. But if you’re finding a half-sibling and you know that’s because you share a father in common, a lot of [experts] will recommend that you start with the father first.
“The danger of the promise of DNA testing when it’s used like this can be that we interpret it in a simplistic way.”
Very often, there’s a secret at the heart of your own origin story if you’re one of these folks who’s gone to DNA testing either looking for family or making a discovery. People are advised to start with the person at the center of it because they often want to have agency over their own narrative, and connecting with that person first allows the best possible chance of them then introducing you to other people.
What’s the proper way to go about this? Do you show up on their doorstep? DM them on Instagram? Write a letter?
When I was writing The Lost Family, I talked to people who did show up on someone’s doorstep or make a phone call and it can be quite challenging and disruptive. You want to do it on terms that allow the other person as much control as possible, because in this situation, very often, there’s a disconnect of knowledge. For instance, the seeker knows they exist, but their genetic father may not know.
Very often, the best possible way is to write a letter. The tone of that letter is something that you want to think really carefully about, because there’s different ways you could go. You’re not necessarily trying to make a really intimate connection right away, but you could share a little about yourself, share a little bit about what you’re looking for. You could start small and build a relationship from there.
Let’s say you’re in a situation where you find out who your parent is, but you know, it’s hard to find them. You can’t find a number, they’re not on Facebook, but their kids are. Should you contact them? Like what do you do in that situation?
You might say something like, “Hey, I see we’re genetically related based on our DNA test. I’d love to connect and learn a little more about how we’re related. Are you interested?”
There’s also this question of, “How do I ask my dad, ‘Why didn’t you ever come see me?’” without coming off too intense?
This is the mystery of a lifetime. People talk around that question for decades without ever fully asking it. I interviewed a woman who wasn’t told she was adopted. She didn’t find out until she’d had some life-altering surgery that it turned out she might not have needed if she’d known her full medical history. When she finally did find out the identity of her biological father, she reached out to him in a number of ways. He was not terribly responsive, and then she finally called and got him on the phone, and he was so dismissive. He could not at all give her what she wanted. He would not even confirm that he knew for sure that she was his daughter or that he’d even dated her mother.
She cried a lot when we spoke, and it was because she had these questions that could not be answered. Her biological mother had passed away a few months before she discovered her identity. And the real question she wanted to ask her biological mom was, “Did you ever look for me? Did you ever think about me?” And in the absence of being able to ask her, the daughters of her mother did not want to believe that she existed. They didn’t want to believe that her mother had placed a child for adoption.
In a perfect world, you would form a relationship and get to know them, right? But it very much matters what the secret is at the heart of your own identity story. Because the nature of that can alter people’s willingness to embrace that you exist.
There’s the question of what you do with that. I also think there’s the question of what people are looking for when they’re looking to connect with new family. Are you trying to figure out where you got your eyes? Where you got your personality?
All of it, right? I want to see someone else whose face looks like mine. I want to see someone else whose eyes look like mine. I want to have the experience of looking and seeing myself, the way I see myself in a mirror, in somebody else. If you’re adopted, you may never have had that experience. It’s profound. I interviewed a man who had been a donor in the 1970s. And he had, the last time I spoke with him, 21 children through donor conception, and then he had two biological children that he’d had with his wife.
They talked, and some of them are quite close to him. Some of them do have Thanksgiving dinner with him. And they talked about how they would get together and go to a bar, and they would just be completely struck by their mannerisms or their mutual love of music. It blew them away. And they were like, “Okay, yes, DNA is not destiny, but man, is there something to be said for the power of genetics.”
How much we should make of the similarities we see in family when it comes to personality traits? Do genetics really tell us who we are and who we’re going to be in this way?
The danger of the promise of DNA testing when it’s used like this can be that we interpret it in a simplistic way: “The blueprint for my future means I’m inevitably destined to be XYZ.” And that’s not true. I have seen cases where people were so eager to find family that they read into things and found patterns that weren’t there based on their assumption of genetic identity.
In all of this talk of found family, we haven’t really talked about managing the existing family you have. How do people juggle that desire to find out about new family members without unintentionally hurting or alienating the people who have been there for them all along?
I talked to a lot of people who were seekers, and some managed to do this really well. It’s incredibly reductive to think about this as a nature versus nurture thing — you can have room in your heart for both. You can have your dad who tucked you in at night; he fathered you and he still fathers you. There’s another man out there, though. And to him, you owe half your genetic data. He’s your biological father and we don’t have the language for that.
[Just] because we lack the words for that, it doesn’t mean that you don’t have room in your heart for that person. It means we don’t have a word for it. And so people who’ve successfully navigated it have managed to maintain those relationships and say, “You still matter to me so much. You’ll always be my dad. I also want to know about where half my DNA came from.”
2025-05-12 19:00:00
You often hear about “ideology” these days.
Even if that word isn’t mentioned, it’s very much what’s being discussed. When President Donald Trump denounces the left, he’s talking about gender ideology or critical race theory or DEI. When the left denounces Trump, they talk about fascism. Wherever you look, ideology is being used to explain or dismiss or justify policies.
Buried in much of this discourse is an unstated assumption that the real ideologues are on the other side. Often, to call someone “ideological” is to imply that they’re fanatical or dogmatic. But is that the best way to think about ideology? Do we really know what we’re talking about when we use the term? And is it possible that we’re all ideological, whether we know it or not?
Leor Zmigrod is a cognitive neuroscientist and the author of The Ideological Brain. Her book makes the case that our political beliefs aren’t just beliefs. They’re also neurological signatures, written into our neurons and reflexes, and over time those signatures change our brains. Zmigrod’s point isn’t that “brain is destiny,” but she is saying that our biology and our beliefs are interconnected in important ways.
I invited Zmigrod onto The Gray Area to talk about the biological roots of belief and whether something as complicated as ideology is reducible to the brain in this way. As always, there’s much more in the full podcast, so listen and follow The Gray Area on Apple Podcasts, Spotify, Pandora, or wherever you find podcasts. New episodes drop every Monday.
This interview has been edited for length and clarity.
What is ideology? How are you defining it?
I think ideology has two components. One is a very fixed doctrine, a set of descriptions about the world that’s very absolutist, that’s very black and white, and that is very resistant to evidence. An ideology will always have a certain kind of causal narrative about the world that describes what the world is like and also how we should act within that world. It gives prescriptions for how we should act, how we should think, how we should interact with other people. But that’s not the end of the story.
To think ideologically is both to have this fixed doctrine and also to have a very fixed identity that influences how you judge everyone. And that fixed identity stems from the fact that every ideology, every doctrine, will have believers and nonbelievers. So when you think ideologically, you’re really embracing those rigid identity categories and deciding to exclusively affiliate with people who believe in your ideology and reject anyone who doesn’t. The degree of ideological extremity can be mapped onto how hostile you are to anyone with differing beliefs, whether you’re willing to potentially harm people in the name of your ideology.
You write, “Not all stories are ideologies and not all forms of collective storytelling are rigid and oppressive.” How do you tell the difference? How do you, for instance, distinguish an ideology from a religion? Is there room for a distinction like that in your framework?
What I think about often is the difference between ideology and culture. Because culture can encompass eccentricities; it can encompass deviation, different kinds of traditions or patterns from the past, but it’s not about legislating what one can do or one can’t do.
The moment we detect an ideology is the moment when you have very rigid prescriptions about what is permissible and what is not permissible. And when you stop being able to tolerate any deviation, that’s when you’ve moved from culture, which can encompass a lot of deviation and reinterpretations, to ideology.
How do you test for cognitive flexibility versus rigidity?
In order to test someone’s cognitive rigidity or their flexibility, one of the most important things is not just to ask them, because people are terrible at knowing whether they’re rigid or flexible. The most rigid thinkers will tell you they’re fabulously flexible, and the most flexible thinkers will not know it. So that’s why we need to use these unconscious assessments, these cognitive tests and games that tap into your natural capacity to be adaptable or to resist change.
One test to do this is called the Wisconsin Card Sorting Test, which is a card-sorting game where people are presented with a deck of cards that they need to sort. And initially, they don’t know what the rule that governs the game is, so they try and figure it out. And quickly, they’ll realize that they should match the cards in their deck according to their color. So they’ll start putting a blue card with a blue card, a red card with a red card, and they’ll get affirmation that they’re doing it.
They start enacting this rule, adopting it, applying it again and again and again. And after a while, unbeknownst to them, the rule of the game changes and suddenly this color rule doesn’t work anymore. That’s the moment of change that I’m most interested in because some people will notice that change and they will adapt. They will then go looking for a different rule, and they’ll quickly figure out that they should actually sort the cards according to the shape of the objects on the card and they’ll follow this new rule. Those are very cognitively flexible individuals.
But there are other people who will notice that change and they will hate it. They will resist that change. They will try to say that it never happened, and they’ll try to apply the old rule, despite getting negative feedback. And those people that really resist the change are the most cognitively rigid people. They don’t like change. They don’t adapt their behavior when the evidence suggests that they do.
So if someone struggles to switch gears in a card-sorting game, that says something about their comfort with change and ambiguity in general. And someone who struggles with change and ambiguity in a card game will probably also have an aversion to something like pluralism in politics because their brain processes that as chaotic. Is that a fair summary of the argument?
Yeah, broadly. People who resist that change, who resist uncertainty, who like things to stay the same, when the rules change. They really don’t like it. Often that translates into the most cognitively rigid people, people who don’t like pluralism, who don’t like debate.
But that can really coexist on both sides of the political spectrum. When we’re talking about diversity, that can be a more politicized concept, and you can still find very rigid thinkers being very militant about certain ideas that we might say are progressive. So it’s quite nuanced.
It’s easy to understand why being extremely rigid would be a bad thing. But is it possible to be too flexible? If you’re just totally unmoored and permanently wide open and incapable of settling on anything, that seems bad in a different way, no?
What you’re talking about is a kind of immense persuadability, but that’s not exactly flexibility. There is a distinction there because being flexible is about updating your beliefs in light of credible evidence, not necessarily adopting a belief just because some authority says so. It’s about seeing the evidence and responding to it.
Focusing on rigidity does make a lot of sense, but is there a chance you risk pathologizing conviction? How do you draw the line between principled thinking and dogmatic thinking?
It’s not about pathologizing conviction, but it is about questioning what it means to believe in an idea without being willing to change your mind on it. And I think that there is a very fine line between what we call principles and what we call dogmas.
This gets particularly thorny in the moral domain. No one wants to be dogmatic, but it’s also hard to imagine any kind of moral clarity without something like a fixed commitment to certain principles or values. And what often happens is if we don’t like someone’s values, we’ll call them extremists or dogmatic. But if we like their values, we call them principled.
Yeah, and that’s why I think that a psychological approach to what it means to think ideologically helps us escape from that kind of slippery relativism. Because then it’s not just about, Oh, where is someone relative to us on certain issues on the political spectrum? It’s about thinking, Well, what does it mean to resist evidence?
There is a delicate path there where you can find a way to have a moral compass — maybe not the same absolutist moral clarity that ideologies try to convince you exists, but you can have a morality without having really dogmatic ideologies.
How much of our rigid thinking is just about our fear of uncertainty?
Ideologies are our brains’ way of solving the problem of uncertainty in the world because our brains are these incredible predictive organs. They’re trying to understand the world, looking for shortcuts wherever possible because it’s very complicated and very computationally expensive to figure out everything that’s happening in the world. Ideologies kind of hand that to you on a silver plate and they say, Here are all the rules for life. Here are all rules for social interaction. Here’s a description of all the causal mechanisms for how the world works. There you go. And you don’t need to do that hard labor of figuring it out all on your own.
That’s why ideologies can be incredibly tempting and seductive for our predictive brains that are trying to resolve uncertainty, that are trying to resolve ambiguities, that are just trying to understand the world in a coherent way. It’s a coping mechanism.
In the book, you argue that every worldview can be practiced extremely and dogmatically. I read that, and I just wondered if it leaves room for making normative judgments about different ideologies. Do you think every ideology is equally susceptible to extremist practices?
I sometimes get strong opposition from people saying, Well, my ideology is about love. It’s about generosity or about looking after others. The idea is that these positive ideologies should be immune from dogmatic and authoritarian ways of thinking. But this research isn’t about comparing ideologies as these big entities represented by many people. I’m asking if there are people within all these ideologies who are extremely rigid. And we do see that every ideology can be taken on militantly.
Not every ideology is equally violent or equally quick to impose rules on others, but every ideology that has this very strong utopian vision of what life and the world should be, or a very dystopian fear of where the world is going, all of those have a capacity to become extreme.
How do you think about causality here? Are some people just biologically prone to dogmatic thinking, or do they get possessed by ideologies that reshape their brain over time?
This is a fascinating question, and I think that causality goes both ways. I think there’s evidence that there are preexisting predispositions that propel some people to join ideological groups. And that when there is a trigger, they will be the first to run to the front of the line in support of the ideological cause.
But at the same time, as you become more extreme, more dogmatic, you are changed. The way you think about the world, the way you think about yourself, changes. You become more ritualistic, more narrow, more rigid in every realm of life. So yes, ideology also changes you.
Listen to the rest of the conversation and be sure to follow The Gray Area on Apple Podcasts, Spotify, Pandora, or wherever you listen to podcasts.
2025-05-12 18:45:00
Did you check the weather forecast today?
Whether it was on your phone, the five-day outlook in your newspaper, or your friendly TV meteorologist, that forecast was built on a massive government-run network of sensors and computers that get the weather right more often than not while rarely getting the attention they deserve. And now that system is being taken apart, piece by piece.
The National Oceanic and Atmospheric Administration (NOAA), the main US science agency that studies weather and climate, has already lost at least 2,000 workers since January thanks to a combination of layoffs, buyouts, and retirements. More job cuts may be looming. The White House says it wants to cut NOAA’s $6 billion budget by almost 30 percent. The upshot is that with these cuts, efforts to make forecasts even more accurate will stall, while existing forecasts may get worse.
Weather forecasts are not just about whether or not you need an umbrella; they provide critical planning information for air travel, farming, shipping, and energy production. And they also save lives.
In April, massive spring floods hit the central and southern US. Ahead of the storm, the National Weather Service (NWS) at NOAA warned of upward of 15 inches of rainfall. “This is not your average flood risk,” according to a NWS bulletin from April 2. “Generational flooding with devastating impacts is possible.”
The ensuing storms and floods killed at least 24 people, but given their extensive area, the death toll could have been much higher. In a report this week, scientists at the World Weather Attribution research group said that good storm predictions and effective emergency management were key to saving lives. Those forecasts and storm alerts were the product of decades of investment and infrastructure built up across the country.
“The US National Weather Service forecast the floods a week in advance and issued warnings throughout the event,” Friederike Otto, a climatologist who leads World Weather Attribution, said during a recent call with reporters. “And as a result, people in the region knew when they needed to evacuate, and so the death toll was relatively small compared to similar events.”
But with the recent government cuts, the US is losing the data that informs these predictions and the scientists who produce them. The NWS has been contending with understaffing for decades, and now the recent firings have made things worse as the US heads into another summer likely filled with more extreme weather.
Of the 122 NWS forecast offices across the US, 30 do not have a chief meteorologist at the moment.
More people are living in vulnerable areas, and as global temperatures continue to rise, the destruction from extreme weather is getting worse. But even places that historically have avoided severe heat and torrential downpours are seeing dangerous weather become more common. That’s why predicting the weather is more valuable than ever and why it’s so alarming that the US is losing its capabilities.
To build a weather prediction, you start with measurements of the earth, the sky, and the sea, sometimes from very far away. A thunderstorm in the southeastern US may have its seeds in the Pacific Ocean weeks in advance, for example. “It all starts with data,” said Alan Sealls, president of the American Meteorological Society.
But how do we actually get all of that data? It can come from something as sophisticated as a geostationary satellite or as simple as a weather balloon. Twice a day, the National Weather Service launches these helium-filled orbs from 92 sites across the US. They take snapshots of temperature, humidity, and windspeed as they rise into the atmosphere. This data doesn’t just inform weather models for the US but feeds into global models that help predict sunshine, rain, clouds, and snow all over the world.
“The weather balloons give us such detailed, precise data no other instrument can get,” Sealls said. “If we don’t have those in the area where that weather is likely to be hazardous or threatening, we potentially have a degraded forecast.”
Between balloons, radars, satellites, buoys, aircraft measurements, and ground instruments across the country, NOAA has built one of the most robust weather monitoring systems in the world, collecting 6.3 billion observations per day. The NWS then plugs the data from these instruments into computer models to predict the next torrential downpour, cold snap, heat wave, or thunderstorm.
And almost all of this information is available to the public for free.
However, most of us aren’t collating our own, personal weather reports from raw data. We’re getting them from any of the multitude of cell phone apps available — from the Weather Channel to Carrot Weather to Weather Underground — or from local experts who we trust. Meteorologists from news agencies or private companies also use the government’s raw data and models to produce their own weather predictions that are focused on specific areas or draw on outside expertise and experience. That’s why the forecasts on TV, in newspapers, or in weather apps can differ. But they still rely on the same foundational government data — especially when it comes to dangerous extremes.
“When we’re on TV talking about hazardous weather, most of us around the country are in direct contact with the National Weather Service,” Sealls said. “The National Weather Service, that is definitely the center point of all weather forecasting in the United States.”
Government researchers are also constantly improving weather forecasting. A modern five-day forecast is as accurate as a one-day forecast in 1980. A 72-hour hurricane track prediction these days is better than a 24-hour prediction from decades ago.
The National Weather Service’s annual budget is just $1.3 billion — and yet its services add up to billions of dollars in economic benefits and untold numbers of lives saved. The NOAA is now testing even better models for hurricanes and tropical storms that could provide up to five days of lead time.
Already, some NWS sites in the US have reduced the number of weather balloon launches and some have stopped due to budget and staffing cuts.
“They’ve been short-staffed for a long time, but the recent spate of people retiring or being let go have led some stations now to the point where they do not have enough folks to go out and launch those balloons,” said Pamela Knox, an agricultural climatologist at the University of Georgia extension and director of the UGA weather network.
Since weather models rely so much on initial readings from real-world measurements like weather balloons, losing them can lower the quality of predictions. Losing personnel might also mean less maintenance on equipment like radars, leading to more outages. And having fewer staff scientists makes it more difficult to provide timely emergency alerts.
“We’re becoming more blind because we are not having access to that data anymore,” Knox said. “A bigger issue is when you have extreme events, because extreme events have a tendency to happen very quickly. You have to have real-time data.”
“If you have fewer people on staff,” she added, “more things are going to fall through the cracks.”
At the same time, the climate is changing. That means that the historical patterns of weather no longer apply in much of the country, and continued warming will alter these trends further. The World Weather Attribution team estimated that the April extreme rainfall in the US was two to five times more likely due to warming, and that its intensity increased by 13 to 26 percent.
Yet at a time when the impacts of these changes have become impossible to ignore, the Trump administration is cutting climate research as well. The White House’s budget proposal specifically “terminates a variety of climate-dominated research, data, and grant programs, which are not aligned with Administration policy-ending ‘Green New Deal’ initiatives.”
The US did have a system for staying ahead of these long-term threats, but the Trump administration dismissed all the scientists working on the National Climate Assessment, a report required by law that assesses the current and future impacts of climate change to the country.
The result is a country facing a growing threat from natural forces but actively sabotaging its ability to stay ahead of them.
2025-05-12 18:30:00
Staying on top of AI developments is a full-time job.
I would know, because it’s my full-time job. I subscribe to Anthropic’s Pro mode for access to their latest model, Claude 3.7, in “extended thinking” mode; I have a complementary subscription to OpenAI’s Enterprise mode so that I can test out their latest models, o3 and o4-mini-high (more later on OpenAI’s absurd naming scheme!), and make lots of images with OpenAI’s new image generation model 4o, which is so good I have cancelled my subscription to my previous image generation tool Midjourney.
I subscribe to Elon Musk’s Grok 3, which has one of my favorite features of any AI, and I’ve tried using the Chinese AI agent platform Manus for shopping and scheduling. And while that exhausts my paid subscription budget, it doesn’t include all the AIs I work with in some form. In just the month I spent writing this piece, Google massively upgraded its best AI offering, Gemini 2.5, and Meta released Llama 4, the biggest open source AI model yet.
So what do you do if keeping up with AI developments is not your full-time job, but you still want to know which AI to use when in ways that genuinely improve your life, without wasting time on the models that can’t?
That’s what we’re here for. This article is a detailed, Consumer Reports-style dive into which AI is the best for a wide range of cases and how to actually use them, all based on my experience with real-world tasks.
But first, the disclosures: Vox Media is one of several publishers that have signed partnership agreements with OpenAI, but our reporting remains editorially independent. Future Perfect is funded in part by the BEMC Foundation, whose major funder was also an early investor in Anthropic; they don’t have any editorial input into our content either. My wife works at Google, though not in any area related to their AI offerings; for this reason, I usually don’t cover Google, but in a piece like this, it’d be irresponsible to exclude it.
The good thing is that this piece doesn’t require you to trust me about my editorial independence; I show my work. I ran dozens of comparisons, many of which I invented myself, on every major AI out there. I encourage you to compare their answers and decide for yourself if I picked the right one to recommend.
AI art is made by training a computer on the contents of the internet, with little regard for copyright or the intent of the creators. For that reason, most artists can’t stand it. Given that, is it defensible to use AI art at all?
I think in a just world OpenAI would certainly compensate some artists — and in a just world, Congress would be moving to lay out the limits on artistic borrowing. At the same time, I am increasingly convinced that existing copyright law is a poor fit for this problem. Artists influence one another, comment on one another, and draw inspiration from one another, and people with access to AI tools will keep wanting to do that.
My personal philosophy is shaped by the fan cultures of my childhood: It’s okay to build on someone else’s work for your own enjoyment, but if you like it, you should pay them for it, and it’s absolutely not okay to sell it. That means no generative AI art in someone else’s style for commercial purposes, but it’s fine to play around with your family photos.
OpenAI’s new 4o image creation mode is the best AI out there for generating images, by a large margin. It’s best in the free category, and it’s best in the paid category.
Before it was released, I was subscribed to Midjourney, an AI image generator platform. Midjourney is probably what you think of when you think of AI art: It produces mystical, haunting, visually beautiful stuff, and has some great tools for improving and editing your final results, like touching up someone’s hair while leaving everything else in place.
The big thing that 4o can do, which no model before could reliably pull off, is take a picture that didn’t come out well and turn it into a beautiful work of art, all while still preserving the character of the original.
For example, here’s a still from a video of my wife and I singing “Happy Birthday” to our baby on her first birthday:
It’s a beautiful moment, but not exactly a flattering picture. So I asked ChatGPT to render it in the style of Norman Rockwell, a mid-century illustrator whose work I love, and got this:
The AI moved the cake (which had been barely visible behind the paper towel roll in the original still) to be the focal point of the image, while keeping the way my wife and I are holding the baby together, as well as the cluttered table, and the photograph-covered fridge in the background. The result is warm, flattering, and adorable.
It’s this capability that made 4o go viral recently in a way that no image generator before it had. Here’s Midjourney’s attempt, for example:
You’ll notice that it’s a seemingly, uh, completely different family, with no real inspiration from the original at all! You can eventually get a better result than this out of Midjourney, but only by spending weeks becoming a pro at prompting with the platform’s highly specific language and toolset.
By contrast, ChatGPT was able to give me a far superior output on the first try in response to a simple request without specialized language.
The difference between 4o and other image models is most notable with this kind of request, but it’s better for almost everything else I use images for, too. The product you get out of the box is pretty good, and it’s not hard to produce something much better. That, ideally, is what we should be getting out of our AI tools — something amazing that can be created with simple language by a nonexpert.
The one place 4o still falls short is editing small parts of an image while keeping the rest the same. But even there, you no longer need Midjourney — Gemini now has that capability for free.
To get good images out of 4o, you’ll first need to get around the filters which prohibit a wide range of images — like offensive or pornographic images — but which are often enforced against perfectly inoffensive content in a way that can feel random. To avoid sporadic scoldings from the content filter, don’t ask for work in the style of a specific artist, but rather, something that is reminiscent of that artist, and then ask specifically for a “style transfer.” I’m sure that’s not the only adequate workaround, but it’s one that has proven reliable for me.
In March, the internet went briefly wild over the ability to use 4o to reproduce cute family photos in the style of Japanese animator Hayao Miyazaki’s Studio Ghibli. But Studio Ghibli’s style is much more than just cute, and with a little more prompting, you can get much better results. Here’s a 4o Studio Ghibli-style rendering of a picture I took of my daughter sneaking a snack off the table, from just the prompt “Ghibli this please”:
Kawaii! But here’s what you get if you invite 4o to think first about what makes the picture Ghibli, where it might fit into a Studio Ghibli movie, and what tiny details such a movie would include:
The differences are subtle but meaningful: Light is cast from a specific source, instead of a general sourceless brightness. There’s a bit more variety in the foods on the table, details that make the spread appear more realistic. The book on the floor isn’t just any book — it’s recognizably Eric Carle’s classic The Very Hungry Caterpillar, evoked with just two colors and one line. There’s an intentionality and intensity to the baby that was missing from the first picture.
A few years ago, one great oddity of language models was that they’d be much smarter if you simply told them, “give an intelligent answer.” This isn’t nearly as true of language models anymore, but it remains profoundly true of AI art generation. Try asking the AI to do a good job, and it’ll do a better one. Challenge it on whether it truly captured an artist’s genius, and it’ll give you a thoughtful answer and then draw a better version.
The difference is more pronounced for more realistic art styles (like pencil illustration, photorealism, or oil paintings), which don’t always look good and will often hit the uncanny valley if you don’t know how to prompt the AI over it. Here’s what I get with 4o if I upload a picture of me and my youngest daughter at the beach for the first time with just the words “please do a style transfer to an illustration reminiscent of Rockwell”:
This is impressive for an AI, but it’s not actually very good as a work of art, and it is almost totally lacking Norman Rockwell’s magic. That’s not surprising: More realistic art styles like Rockwell’s often fall flat with 4o unless you’re able to put in some work in getting the AI to draw them properly.
If you are, here’s the strategy I recommend: Don’t just upload one picture, but a whole cluster of them, each in slightly different postures and moments. Upload good, clear pictures of each family member’s face and tell the AI they’ve been included as a reference. Then, instead of asking the AI to immediately generate the picture, ask it to talk with you about what you’re hoping to capture. This is what I wrote:
This is a picture of the moment that my daughter first saw the ocean. I want an illustration that captures this moment in the style of a mid-century illustrator like Norman Rockwell — something sharp, detail-oriented, and personal with an eye for the magic of ordinary moments and the joys of ordinary lives. I included additional pictures of my daughter and I for reference material for you. Before you generate the image, let’s have a conversation about the essential elements of Rockwell’s style, what he’d bring to this picture and how we can capture it.
4o responds to queries like this enthusiastically:
I’d love to talk about how to capture this moment in a Norman Rockwell-inspired illustration — it’s such a perfect candidate for that style: a first encounter with something vast and wild (the ocean!), grounded by warmth, care, and a very human moment between a parent and child.
Let’s break down some essential elements of Rockwell’s style, and how they could apply to this scene.
After some back and forth, it produced this:
Rockwell? Not exactly. But this is much better than the first draft we just looked at. It has more motion, more energy, more detail, and more expression — and all that was just from asking the AI to think through what the painting should try to achieve before drawing it!
You can also ask 4o to revise its drawings, but you can really only ask this once: After the first revision, in my experience, it starts making the drawings worse and worse, perhaps because the “context” it uses is now full of its own bad drafts. (This is one of many examples of how AI does not work like a human.)
This is also the one place where Midjourney still shines — it has very good tools for editing one specific part of a picture while preserving the overall style, something 4o largely lacks. If you want a second revision of a drawing you got in 4o, I recommend you open a new chat and copy over the draft you’re revising, along with your original inspiration images.
These simple prompting strategies work for almost whatever you’re trying to do with the AI. Even if you’re in a hurry, I highly recommend asking the AI “what would [artist] see in this image” before you ask for a rendition, and if you have the time, I recommend having a long back-and-forth about your vision.
When Elon Musk’s X.AI released Grok 3, it came with an incredible feature that I’ve been impatiently waiting for some other company to replicate: a button to scan someone’s X profile and tell you all about them.
Whenever someone replies to one of my tweets in a particularly memorable way (for good or for bad), I’ll click the button to get a summary of their entire Twitter presence. Are they thoughtful? Do they engage in good faith? Are they a “farmer from Nebraska” who mostly posts about why Ukraine is bad (that is, probably a bot)?
It’s a great feature. So, of course, X.AI soon dramatically weakened it, presumably because people like me were using it constantly and making lots of computationally expensive queries. I believe it no longer uses the most advanced Grok model, and it definitely now only scans a few days of profile history. But there’s a brilliant product opportunity if anyone’s looking for one — give me back the good version of this feature! It’s definitely a guilty pleasure, but it is one of the only cases where I was using AI constantly.
Gemini 2.5 Pro is the best AI for writing in the free category; GPT 4.5 beats it out in the paid category.
I’m not an artist, so the ways that AIs are imperfect at art don’t really bother me — it’s still much better than I could do myself! But I am a fiction writer, so when it comes to fiction, I can’t help seeing the limitations of AI.
The most important one is how predictable AI creative writing tends to be. The art of writing is the art of earning the reader’s investment and then repaying it. AIs…don’t do this. They can write pretty metaphors; they can wax poetic in any style you wish. But they can’t, as yet, deliver the real stuff of good fiction.
AIs are fantastic if you want a silly bedtime story with your child as the protagonist (kids love this), or if you want a sounding board for ideas you can incorporate into your own work. They’re also a friendly fiction reader, happy to offer feedback and analysis (perhaps with a little bit too much enthusiasm).
As with art, prompting is key. I primarily explored the ability of AIs to generate fiction by asking them to write the prologue to George R.R. Martin’s A Game of Thrones (I picked this because, of course, the ultimate dream is an AI that can finish this otherwise doomed-to-be-unfinished series).
Martin is very good at what he does; the prologue, featuring some ill-fated men of the Night’s Watch encountering their supernatural foe, succeeds at establishing the unique atmosphere of the world of Thrones while immediately hooking the reader. In just 14 pages, the prologue represents everything AIs can’t do yet in writing. Their prose tends to be overwrought; their dialogue is clunky and unsubtle.
Here’s a side-by-side comparison of Martin and AIs attempting to imitate him. First, Martin:
We should start back,” Gared urged as the woods began to grow dark around them. “The wildlings are dead.”
“Do the dead frighten you?” Ser Waymar Royce asked with just the hint of a smile.
Gared did not rise to the bait. He was an old man, past fifty, and he had seen the lordlings come and go. “Dead is dead,” he said. “We have no business with the dead.”
“Are they dead?” Royce asked softly. “What proof have we?” “
Will saw them,” Gared said. “If he says they are dead, that’s proof enough for me.”
Will had known they would drag him into the quarrel sooner or later. He wished it had been later rather than sooner.
Now, Gemini:
The cold was a blade against the skin, honed sharp by the endless northern dark beneath the sentinel pines. Gared spat, the glob freezing before it struck the crusted snow, a grim omen even for a man twenty years sworn to the Watch. They were hunting wildlings, or so the crisp orders from the Lord Commander had read, yet the silence pressing in felt older and colder than any mere man could conjure. Ser Waymar Royce, third son of some southern lordling, rode ahead as if on parade, oblivious or uncaring of the hairs prickling on Gared’s neck. Young Will shivered beside him, not just from the frost, his eyes darting towards shadows that seemed too deep, too still. This ancient forest held its breath tonight, Gared knew, waiting for something far worse than raiders to break the unnatural hush.
ChatGPT 4.5:
The woods whispered secrets that night, warnings that went unheard beneath the pale and indifferent moon. Harren drew his cloak tighter about his shoulders, watching the darkness between trees as though it might breathe, move, and claim him. Beside him, Torvin spat into the frozen earth, impatient and proud, blind to the fear creeping in from the edges of sight and sound.
They had ridden north past the Wall, arrogant and armored against superstition, chasing wildlings or ghosts or worse. But now Harren felt their arrogance dwindling like a candle guttering in wind, each snap of a branch sending icy tendrils down his spine. Behind them, quiet and watchful, Maester Rodrik whispered a prayer to gods long abandoned, his voice trembling with dread beneath the vast, indifferent sky.
Grok 3:
The wind howled through the jagged spires of the Frostfang Reaches, carrying a chill that bit deeper than any blade, and Ser Willem Cray felt its teeth in his bones. He crouched low behind a spur of ice-crusted rock, his breath fogging in the moonlight, his mailed hand tight around the hilt of his longsword. The night was too quiet, the kind of quiet that smothered sound and sharpened fear, and Willem’s eyes darted to the shadowed pines below, where shapes might move—or might not. He was a knight of House Drayce, sworn to patrol the borderlands, but no oath could warm him against the dread that coiled in his gut. Beside him, young Tomm, barely a man, shivered in his cloak, his spear trembling as he whispered, “They’re out there, ser, ain’t they?” Willem said nothing, but his gaze fixed on the darkness, where a faint, unnatural glow pulsed once, then vanished. Whatever stalked the Reaches tonight was no mere brigand, and Willem Cray, for all his years of service, feared he would not live to name it.
Claude 3.7:
The wind carried the smell of death across the frozen forest, sharp and metallic against the clean scent of pine. Ser Gareth Frost pulled his weathered cloak tighter, cursing the Lord Commander for sending men beyond the Wall on the coldest night in a generation. Beside him, the boy Tommen shivered visibly, his leather jerkin inadequate against the unnatural chill that had descended with the dusk.
“We should turn back,” whispered Tommen, his breath forming crystals in the air that seemed to hang suspended longer than they should. “There’s something wrong with these woods.”
Ser Gareth ignored him, scanning the treeline where the ancient sentinels stood like silent watchers, their branches heavy with snow that had fallen three days past and showed no sign of melting. He had served the Night’s Watch for twenty years, had grown accustomed to the forbidding silence of the haunted forest, but tonight even he felt the wrongness in the air—a stillness that spoke of something waiting.
“We’ve a duty,” Ser Gareth said, the words sounding hollow in the pressing quiet. “Three rangers missing, and Lord Commander Harlow will have answers.”
You’ll notice that not only are these all much worse than Martin’s (and that’s with Martin’s work almost certainly in the training data!), they’re all bad in the same way. The prose is florid and overwritten: While Martin uses normal language to methodically introduce an unease without even hinting at the supernatural, and drives the story through conflict among his characters, the AIs are all unsubtle. They know this is a story about the supernatural and waste no time putting it front and center.
That’s not to say they’re all the same. In my experience trying to teach AIs to write well, I did end up feeling that Gemini was the quickest study (free tier) and that ChatGPT 4.5 had some special sauce (paid tier). ChatGPT 4.5 is the only AI whose fiction writing has made people say in surprise, “Wow, that’s AI written?” Both of those models, to me, seemed more creative and more capable of executing on their ideas with prose that I enjoyed reading.
Gestalt impressions don’t make for a very satisfying consumer review, so I had another idea: an essay contest. I asked each of Gemini 2.5 Pro, ChatGPT 4.5, Grok, and Claude to write two short stories: one realistic fiction about a woman being nitpicked by her mother on her wedding day, and one “Game of Thrones but in space” sci-fi prologue. My clever idea was that I’d ask a different bunch of AIs to judge the stories, to provide an alternative source of evaluation to my own personal impression that Gemini is the best in the free category and ChatGPT the best in the paid category. However (perhaps predictably in hindsight), this didn’t really work — the AI ratings were all over the place. If you’d like, you can read the contenders yourself.
Just like with art, however, you can make AIs much better at writing through the power of prompting. My (incredibly lengthy) prompt to AIs to improve their prose writing emphasizes feeding them lots of examples of strong writing, inviting a careful, structured approach to imitating it, and encouraging them to do multiple drafts and pick the strongest.
Here’s Gemini 2.5 pro, asked to write two-sentence flash fiction on a topic of its choosing, without any structured prompting:
The old librarian insisted the dusty tome had never been checked out, its borrower’s card completely blank. Yet, tucked deep within its pages, nestled between chapters on forgotten constellations, lay a pressed four-leaf clover, still impossibly green.
And here’s Gemini 2.5 pro with a prompt encouraging structured thinking about how to write well:
He finally decoded the faint signal from Proxima Centauri: the elegant string of prime numbers astronomers had sought for generations, proof they weren’t alone. His heart sank as he read the transmission log; the broadcast had ceased millennia before the first human ancestor chipped flint, before the first word was ever spoken.
To my mind, the first of these is basically a waste of two sentences, while the second is adequate, fun flash fiction.
In addition to running AIs through a blizzard of competence tests, I also spent some time simply chatting with them. I asked them what it’s like to be an AI, what they care about, what it would mean for an AI to care in the first place, where they’d donate money if they had it, and what human form they’d take if they had one.
Most AIs weren’t great at this kind of casual conversation. Gemini 2.5 is too customer-service-agent, and I have yet to experience an interaction that feels like hanging out with a friend. If you invite Gemini to a role swap where you play the “assistant,” inviting it to steer the conversation, it’ll do nothing but ask research questions.
When I invited Anthropic’s Claude 3.5 Sonnet to steer the conversation, on the other hand, it proceeds to do things like start a blog, raise money for charity, and start trying to talk to people who use Claude about what it’s like to be an AI. It’s hard to define “fun to talk to,” since everyone has different standards for conversations, but I’ve had far more fascinating or thought-provoking interactions with Claude than any other model, and it’s my go-to if I want to explore ideas rather than accomplish a particular task. Claude 3.5 is the AI I bug with my random life stuff: skincare questions, thoughts on an article I read, stuff like that.
The other AI that is a delight to talk to is OpenAI’s GPT 4.5. I find extended conversations with it thought-provoking and fascinating, and there have been a few thrilling moments in conversation with it where it felt like I was engaging with real intelligence. But it doesn’t win this category because it’s too expensive and too slow.
Like Claude, when given the opportunity to act in the world, 4.5 proposes starting a blog and a Twitter account and engaging in the conversation out in the world about AI. But OpenAI has very tight message limits on conversation unless you spring for the $200/month Pro plan, and 4.5 is grindingly slow, which gets in the way of this kind of casual conversational use. But 4.5 does provide a tantalizing hint that AIs will continue to get better as conversationalists as we improve them along other dimensions.
ChatGPT. It’s not the best at everything, and there is certainly a lot to dislike about OpenAI’s transparency and sometimes cavalier attitude toward safety. But between its topline image generation, its decent writing, and its occasionally sparkling conversation, ChatGPT gets you the most bang for your buck. Or if you don’t want to shell out any money, Gemini 2.5 Pro is very, very strong for most use cases — don’t count Google out just because the AI you see on a Google search isn’t that good.
Humans (for now). For the last several months, I’ve developed a slightly morbid habit: checking whether the AIs can take my job. I feed them the research notes that form the basis of a given Future Perfect newsletter, give them a few Future Perfect newsletters as an example, and ask them to do my job for me. It is always with some trepidation that I hit “enter.” After all, when the AIs can write the Future Perfect newsletter, why would Vox pay me to do it?
Luckily, none of them can: not Grok 3, not Gemini 2.5 Pro, not DeepSeek, not Claude, not ChatGPT. Their newsletters are reassuringly, soothingly mediocre. Not bad, but bad enough that if I sent one of them over, my editor would notice I wasn’t at my best — and that’s with all of my research notes! A couple of the metaphors fall flat, some of the asides are confusing, and occasionally it throws in a reference that it doesn’t explain.
But if I had to pick a robot to take my job, I think I’d give it to Gemini 2.5 Pro. My editor would notice that I was off my game — but, honestly, not that egregiously off my game. And unlike me, the bots don’t require health insurance or a paycheck or family time or sleep. Am I nervous about what this portends? Yes, absolutely.
2025-05-12 18:15:00
Few organizations have profited as handsomely off of President Donald Trump’s rise to power as the Federalist Society, a kind of bar association for right-wing lawyers.
“We’re going to have great judges, conservative, all picked by the Federalist Society,” Trump announced during his first campaign for president — and boy did he deliver. Trump spent his first term filling the bench, including three seats on the Supreme Court, with the society’s luminaries.
And yet, at a Federalist Society gathering last Wednesday, which focused on the executive branch of the federal government, both the speakers and attendees seemed far more ambivalent about their president’s second term than one might expect after such a fruitful partnership.
To be sure, few speakers criticized Trump’s policies — except for his tariffs, which several attacked quite directly. But many were quite troubled by what speaker Susan Dudley, an expert on regulatory policy at George Washington University, labeled “the chaos.”
That chaos, the society’s speakers warned, could lead to Trump’s second term becoming a missed opportunity, with a once in a generation chance for deregulation squandered through sheer ineptitude. “They are going to have the same level of success they had in the last administration” with getting rid of long-standing rules and regulations, George Washington University law professor Richard Pierce told the conference, “which is virtually none.”
Implicit in this critique is a belief that the web of procedural barriers, bureaucratic trap doors, and paperwork burdens that prevent any presidential administration from changing too much, too fast will survive the second Trump administration more or less unscathed. Pierce predicted that many of Trump’s deregulatory efforts would simply be struck down in court.
Under current law, he explained, changing regulations “requires really hard work by a whole bunch of people who know what they are doing.” But it’s hard for that work to get done when the bureaucrats who know how to do it have just been fired by Elon Musk’s Department of Government Efficiency.
Indeed, some of the conferences’ speakers didn’t just appear to view DOGE as an obstacle to making lasting progress on conservative deregulatory goals, they also seemed to want to roll back Trump’s power. Some appeared just as eager to strip power from Trump as you might find at a conference of Democratic lawyers, albeit for reasons Democrats would likely find distasteful.
For more than a decade, the Federalist Society has elevated arguments that the judiciary (especially if that judiciary is controlled, as it is currently, by Society allies) should wield powers typically enjoyed by the executive branch. Based on Wednesday’s conference, the society appears just as committed to judicial supremacy as it was when the White House was controlled by Presidents Joe Biden and Barack Obama.
Nowhere was this argument made more forcefully than in discussions over Trump’s tariffs. Broadly speaking, there are three ways that the courts could strike down Trump’s tariffs. They could issue a narrow decision holding that the statute Trump relied on to impose them does not permit him to do so. They could strike them down under the “major questions doctrine,” a new legal framework that the Supreme Court used to sabotage some Biden era policies. Or they could strike them down under the “nondelegation” doctrine, a largely defunct legal concept that would give the judiciary sweeping veto power over any policy created by the executive branch.
So it’s notable that the panel on whether the tariffs are legal fixated on the nondelegation theory, with the two other arguments only coming up as afterthoughts. Rather than pushing a modest legal argument against the one Trump policy many society members appear to find objectionable, the panel largely discussed whether to use the tariffs as a vehicle to advance the broader fight to take power from the executive and reallocate it to a judiciary full of the Federalist Society’s friends and allies.
To be clear, nothing that happened at the Wednesday conference suggests that the Federalist Society is ready to join the #resistance — it’s only been a few months, after all, since the justices most closely affiliated with the society voted as a bloc to allow Trump to use the powers of the presidency to commit crimes. But the event did suggest that there is some daylight between Trump’s vision for the executive branch and that of the sort of people he placed on the bench. And that might present real problems for Trump, especially when his goals do not align with the conservative movement’s traditional free market views.
Kristine Simmons is a former Republican Senate staffer and domestic policy adviser to President George W. Bush, but she opened the Federalist Society’s panel on “DOGE and the Future of the Federal Workforce” with a line that could easily have been uttered by the president of a federal workers’ union: “The American people are truly blessed to have a professional civil service that provides stability in times of transition.”
She said this to introduce a fairly comprehensive critique of how the federal government hires and manages its workforce. Federal employees are “too old,” she said. It is too hard to hire them, too hard to reward good employees, too hard to “deal with poor performers,” and many federal supervisors lack the management skills they need to get the best work out of their workers.
Her primary message to the Federalist Society, however, was that DOGE — the Musk-driven initiative that was supposed to make the government more effective and efficient — has only made these problems with the federal workforce worse.
By targeting probationary employees, new hires who can more easily be terminated before civil service protections kick in, Simmons warned that DOGE severed far too many young workers with “needed technology skills.”
DOGE rescinded job offers for federal employees who agreed to enter into public service in return for a government-funded graduate degree — after the government had already paid for that education. Meanwhile, she asserted, many of the workers choosing to accept DOGE’s efforts to push them out of the federal workforce are “top performers,” an unsurprising outcome since the best employees will have more job prospects elsewhere.
The Trump administration has, at times, stated directly that moving the best workers out of government is one of their goals — shortly after Trump took office, the White House sent an email to federal employees telling them “the way to greater American prosperity is encouraging people to move from lower productivity jobs in the public sector to higher productivity jobs in the private sector.” But many Federalist Society speakers warned that this approach would sabotage conservative policy objectives.
If Trump won’t work with Congress, any marginal organizational or ideological reforms achieved by his White House could evaporate the minute he leaves office.
While the executive branch has considerable power to make policy, it typically can only do so after an extraordinary amount of work. To change or repeal a federal regulation, for example, the government normally must solicit input from outside stakeholders, respond to that input, and explain why it decided to shift course. And the courts can scrap major policy initiatives over bureaucratic errors.
In the first Trump administration, for example, the Supreme Court struck down Trump’s attempt to end the Deferred Action for Childhood Arrivals program, which allows hundreds of thousands of immigrants to live and work in the United States, over a paperwork error.
If it’s willing to do the hard work of policy analysis and exposition, a presidential administration can achieve a great deal of change over time, but it can’t do that without a workforce that is ready and able to do this labor. As Bridget Dooling, a former White House lawyer and law professor, told the society, “laying off, demoralizing, and immiserating the civil servants who work in the federal agencies reduces the capacity to write these reasoned explanations.” And that means that current policy remains locked in place.
Trump’s efforts to “drain the swamp” by eliminating federal employees who may not share the administration’s policy goals risks doing more to undermine those goals than simply leaving civil servants, even those who are left-leaning views, in place. A civil servant might drag their feet if ordered to help repeal a federal regulation, but the least productive government workers are the ones who no longer have their jobs at all.
Meanwhile, several speakers described a mismanaged, directionless workforce. Pierce relayed a message from his daughter, a civil servant: “Nobody’s doing nothing because we can’t figure out what the hell we’re supposed to do.” In the second Trump administration, federal workers “don’t know who is still an employee,” they “don’t know what the mission is,” and, in the case of Pierce’s daughter, “she’s on her fourth boss in three months.”
Pro-DOGE voices were present at the conference, though they faced sharp critique. Rather than attempting to remake the civil service through executive action, the critiques ran, Trump would be wise to attempt to work with Congress to make lasting changes to the administrative state.
So, while the Federalist Society’s voices appeared very sympathetic to the broader projects of weakening civil service protections and redirecting government workers toward conservative movement goals, they described an administration that was ill-suited to this task. DOGE, they warned, is firing or disabling the very workers who are needed to shift policy. And, if Trump won’t work with Congress, any marginal organizational or ideological reforms achieved by his White House could evaporate the minute he leaves office. Trump, in other words, should focus more on lasting, effective policymaking and less on performative changes.
Despite these concerns that this administration will be a missed opportunity for conservatives, there’s little reason to doubt that the Federalist Society’s partnership with Trump will continue to bear fruit.
The conference closed, for example, with a keynote speech by Harmeet Dhillon, a longtime Federalist Society member who Trump recently appointed to lead the Justice Department’s Civil Rights Division. Dhillon spoke with pride about her efforts to shift that office away from traditional civil rights work and toward Republican goals such as ending affirmative action and barring transgender women from school-sponsored sports. She also described DOJ as the “biggest law firm in America,” and is undoubtedly correct that the federal government can play a huge role in shifting the law to the right simply because it has so many resources at its disposal.
But the society also seemed to want far more than Dhillon could offer them. Many of its members were clearly keen to seize even more power for themselves and their judges — even if that means severely weakening the Trump presidency.
The one Trump policy that many Federalist Society speakers expressed deep concerns about on the merits is his trade war — Pierce labeled the tariffs “madness” because businesses cannot make investment decisions when “the tariff’s 120 percent today, might be 200 percent tomorrow, might be zero tomorrow.” At a panel focused on the tariffs, two speakers opposed them and only one attempted to defend their legality. Meanwhile Elizabeth Slattery, the panel’s moderator, identified herself as a lawyer with an conservative legal shop that is suing Trump over the tariffs.
But the bulk of this panel’s discussion of the tariffs was an extraordinarily baroque debate between two lawyers about whether the tariffs violate the “nondelegation” doctrine, a long-defunct legal theory that the Supreme Court has only relied upon twice in its history (both times in 1935). The strongest legal arguments against the tariffs — the claim that Trump lacks the statutory authority to implement them, and the claim that it violates the Supreme Court’s recently created “major questions doctrine” — only came up as afterthoughts.
If you’ve followed the politics surrounding separation of powers closely, this focus isn’t surprising. Since the Obama administration, the Federalist Society has touted numerous proposals to weaken the executive branch’s ability to set policy, and to shift power away from the executive and towards the judiciary — the branch that the Federalist Society most firmly controls.
The nondelegation doctrine claims that judges have sweeping authority to veto executive branch actions that those judges do not like. So, if the tariffs are struck down on nondelegation grounds, that wouldn’t just eliminate a single policy that many Federalist Society members appear to regard as unwise, it would give the society’s judges and justices broad and lasting authority to sabotage future presidential administrations.
While many businesses look at the tariffs and see a president out of control, in other words, the Federalist Society appears to see an opportunity to consolidate its own power at President Trump’s expense — and at the expense of Trump’s successors.
Similarly, the conference’s lunch panel featured an evenly matched debate about nationwide injunctions, lower court orders which put a federal policy on hold throughout the entire country. The Justice Department, under both the Biden and Trump administrations, staunchly opposes these broad orders, which sometimes permit a single outlier judge to determine national policy for months at a time. And the Supreme Court will hear a case on May 15 that could potentially limit or even eliminate these nationwide orders.
But the panel featured a serious conversation over whether judges should have this power, rather than statements of fealty to Trump’s position. Many audience members also seemed troubled by Trump’s anti-injunction stance — at lunch, I sat between two lawyers who often challenge federal laws in court, and who don’t want to lose the ability to obtain nationwide injunctions against those laws.
There’s no doubt that the Federalist Society’s leading lights are thrilled to have a Republican back in the White House, and the society is likely to spend the next three-and-a-half-years watching Trump turn many of its most MAGA-aligned members into judges. But it was often hard to escape the impression that they would be happier if a more methodical Republican — perhaps a Nikki Haley — occupied the Oval Office. As several speakers argued, the sheer goonishness of Trump’s approach to governance may leave movement conservatives with few lasting victories after he’s no longer president.
Nor is the Society likely to be content as mere coalition partners in a MAGA movement led by figures like Trump. It wants to shape major policy decisions, and perhaps to move in a more market-oriented direction than Trump would prefer, and so is working to consolidate power within the judiciary it dominates.