The AI freakout of the past few weeks has centered on nothing less than the risk of human extinction — on the possibility that artificial intelligence could wipe us all out. But the reality is, AI programs are already having a direct and sinister effect on people’s physical health: UnitedHealth Group, the largest health insurer in the US, has been accused of using AI programs to deny payments to people, despite their doctors saying the care was necessary, and is facing a class-action lawsuit. 

Humana and Cigna are facing their own litigation over similar allegations. Meanwhile, Medicare has launched its own AI tool that will help the government determine whether to approve prior authorizations, and doctors are sending the federal government reports of patients at their offices who are in tears because they can’t get the medicine to manage their chronic pain.   

The claims in the legal complaints are harrowing: Families are desperate for an elderly loved one who recently experienced a serious fall to be allowed to stay in a nursing home. Doctors are flummoxed when a patient who may need months of rehab is cut off by an algorithm after a couple of weeks. 

This is AI’s threat to people’s health right now. 

While the current conversation may be fixated on something more Hollywood, private insurers and the Trump administration are already deploying AI programs to vet people’s health insurance claims — and the evidence is growing that these programs are not always doing a good job and are instead putting people’s health at risk. Until these lawsuits are settled or policymakers can figure out a way to regulate how insurers use this new technology, it will be up to each of us to make sure that an AI program isn’t being used to cheat us out of insurance benefits that we’re entitled to.

“The type of care that clinicians deliver is very sensitive to the patient’s unique circumstances. That may not really show up as a number. There’s not a numeric value that tells you the completeness and connection of a patient’s social network,” said Mika Hamer, a health services researcher at the University of Maryland. “There really are a lot of factors that really can’t be quantified and so aren’t really suitable to go into these models. If we start to rely exclusively on the models, I think we run the risk of losing that human touch.”

Patients say private health insurers are using AI to deny claims

Insurers and patients fighting over medical claims is nothing new: Policyholders want the most coverage they can get and payers have a business incentive to pay as little as they can. Health insurers have also used algorithms for decades: Plug in somebody’s age, their weight, whether or not they smoke, and one of the old-fashioned algorithms could spit out a rough estimate of how much medical care they would need before they died. Simple — and comparatively transparent. 

When you submitted a claim or sought prior authorization, there was supposed to be a human doctor who could review all of the relevant information on behalf of the insurer and make the final decision, in theory with the patient’s best interests in mind. It didn’t always work that way in practice, of course, but that was the idea.

What’s different right now, according to Daniel Schwarcz, a law professor at the University of Minnesota who has looked at health insurers’ AI use, is that these newer programs can make very specific predictions about someone’s future health based on the information that’s fed into them, and those predictions are being used in the process of approving or denying medical claims. And exactly what went into making those predictions — and whether it is the AI or the human who ultimately holds the final authority — is often opaque from the outside.

“The reason we want human review is we want human substantive judgment. We want AI to be supporting that,” Schwarcz said. “But the difficulty is distinguishing between AI supporting meaningful human processing and AI basically replacing the human with the human just passively defaulting to the AI judgment. It’s just incredibly hard to distinguish between those two in practice, particularly in rules or regulations.”

And those questions are at the heart of the lawsuits brought against three major insurers in the past few years about their use of AI in processing claims.

In May 2022, Gene Lokken, then 91 years old, fell in his home. He was taken to the nearby hospital in Tomahawk, Wisconsin, and treated for a broken leg and a broken ankle. Less than a week later, he was placed in the health system’s hospice care because, according to the lawsuit filed by his family, he was “very weak, not communicative, and in constant pain.”

But a month later, after receiving skilled nursing care, Lokken started to improve. By late June, his doctor had removed his splint and placed his leg in a removable boot. In July, he started physical therapy to get up and walk again. And for a while, his Medicare Advantage plan sold by UnitedHealth covered all of the services he needed.

Until July 20. Around that time, according to the lawsuit, UnitedHealth denied any more services at the nursing facility where Lokken had been for the past two months. It insisted that he could be safely discharged and more time at the nursing care facility “was not medically necessary.”

The insurer’s decision left Lokken and his physician “dumbfounded.” The physical therapist notes from the time said Lokken was still suffering paralysis and weakness after only a couple weeks of rehab. His family appealed, but UnitedHealth continued to deny the claims, asserting that because Lokken could feed himself and did not require help to clean himself, he did not need nursing care and could go home. 

From July 2022 to July 2023, Lokken remained at the nursing home, but his family had to pay between $12,000 and $14,000 monthly to keep him there. And on July 17, 2023, Lokken died — having never left the facility.

The lawsuit alleges that the decision to stop covering Lokken’s nursing-home stay was largely made by an AI algorithm, called nH Predict, which UnitedHealth follows so unquestioningly that employees were allegedly at risk of being disciplined or fired if their claims decisions went against the AI’s projections. The complaint alleges that the AI model would typically start denying claims after two weeks of nursing home care — and the attorneys have more examples than Lokken.

Glennette Kell required emergency surgery after a fall in late August 2023 and was referred to a nursing home rehab center. By mid-September, UnitedHealth was denying her claims for nursing care, despite the fact that, according to the lawsuit, she still could not walk. Kell had to pay $10,000 of her own money to cover the rest of her bills. Darlene Buckner suffered a heart attack in October 2023 and underwent triple-bypass surgery. She was readmitted to the hospital in late November because she was experiencing complications, but less than two weeks later, UnitedHealth allegedly denied any further treatment at the hospital because it was deemed medically unnecessary. At the time, according to the class-action lawsuit, Buckner was experiencing “an open infected wound near her heart from the open-heart surgery, she was on blood thinners, and was receiving antibiotics through an IV.” 

UnitedHealth, in its responses to the plaintiffs, has asserted that federal laws and regulations already require all claims decisions ultimately be made by a human doctor, not an AI program, and raised several other technical legal objections (such as saying the plaintiffs have not fully exhausted their administrative appeal options). The plaintiffs, however, allege that UnitedHealth employees “are instructed not to deviate” from the AI model’s projections, and then tell patients the AI-generated information is proprietary when they or their doctor try to inquire about why their claims are being denied. 

And, to be clear, UnitedHealth is not the only insurer being sued for using AI programs to deny claims. Humana is facing its own lawsuit brought by other Medicare Advantage patients who allege the same nH Predict program also led to their claims being wrongfully denied. Joanne Barrows, then 86, fell in November 2021 and went to a rehab nursing facility after her hospital stay. And just two weeks later, Humana began denying her claims for further care, according to the complaint, leaving her and her doctor “bewildered” because she was under doctor’s orders not to put any weight on her leg.

And the third lawsuit, filed against Cigna, alleges the company used a different AI algorithm that allowed its doctors to deny claims in huge batches — hundreds or thousands at a time — if they did not meet certain predetermined criteria. One patient, Suzanne Kisting-Leung, had claims denied for two ultrasounds done by her doctor to check for ovarian cancer, putting her on the hook for more than $700 in medical bills because, the lawsuit alleges, Cigna’s AI program determined that the scans were not medically necessary. The plaintiffs say that their claims were instantly rejected, without their medical files ever being opened. As for the law that human doctors have to make the final call? According to the lawsuit, the algorithm “enable[s] its doctors to automatically deny payments in batches of hundreds or thousands at a time for treatments that do not match certain pre-set criteria, thereby evading the legally required individual physician review process.”

These people, many of them elderly, had no idea AI was being used to make decisions about their coverage — until it was too late.

“From their perspective, you might as well have been speaking Esperanto. They just had no idea what it was that was being said to them when they were being told. They usually heard about it for the first time when they were being told that they needed to leave,” Glenn Danas, one of the attorneys in the class-action litigation against United, Humana, and Cigna, told me. “They just had no idea what was going on or why this was being done to them.”

AI is now making decisions for traditional Medicare claims too

It’s not just private insurers either. The Trump administration is now pushing traditional Medicare and Medicaid to use AI to adjudicate insurance claims too. In June 2025, nearly two years after those lawsuits had been filed against Cigna, Humana, and UnitedHealth, the US Department of Health and Human Services announced it would deploy a new program called the WISeR (Wasteful and Inappropriate Service Reduction) model to make prior authorization decisions for about a dozen procedures for the people on traditional Medicare in six states — “leveraging enhanced technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), along with human clinical review to ensure timely and appropriate Medicare payment for select items and services.” It would be a pilot program, before federal officials decide whether to take the program nationwide.

It was a quiet, massive change for traditional Medicare, which covers about half of the 66 million Americans on the program. (Medicare Advantage plans, in which private companies administer Medicare benefits under slightly different parameters and which were the subject of the earlier AI-related class-action litigation, cover the rest.) People on traditional Medicare had historically not been required to get prior authorization for most services; now they would be, and a novel AI program would play a significant role in which claims get approved and which ones don’t.

From the start, physician and patient advocates warned about the potentially adverse consequences of the WISeR program; the Center for Medicare Advocacy said the program would likely “complicate, delay and even outright deny necessary care.” According to media reports and internal government documents, that’s exactly what has happened since the model went live in January. 

The Washington Post first reported in March that physicians and their patients were experiencing approval delays or denials for medical services that should have been covered. One glitch led to a denial of payment for services that had been approved. Doctors noticed that certain procedures seemed to give the AI model problems — such as two competing treatments for incontinence — and were weighing whether or not to stop offering one of those services altogether. The Post reported on one Arizona patient who had been receiving steroid injections for chronic back pain before being denied multiple times after the AI program’s launch. The pain became so severe, he said, that he could not exercise at all.

Then this month, the Electronic Frontier Foundation released a trove of documents it received in response to a Freedom of Information Act lawsuit related to the WISeR model. The documents revealed aggressive denials — one company using the AI model had actually denied more prior authorization requests than it had approved — and there were delays even when the care was ultimately approved. One review took 83 days when the model was supposed to make a decision within 72 hours.

The direct feedback from doctors in the federal documents obtained by EFF was devastating.

“We have patients calling our offices crying in pain because their procedures are being delayed while awaiting approvals or guidance tied to this model,” one doctor wrote. “A 3-4 day delay for necessary pain procedures is already difficult for vulnerable patients, but when providers cannot obtain answers for weeks, the situation becomes unacceptable.”

According to the federal documents, the Trump administration was already discussing ways to expand the program. Despite the outcry from doctors and patients, and growing concern among their representatives in Congress, it doesn’t look like WISeR is going away.

How can we make sure AI doesn’t take over insurance claims?

AI is becoming a part of healthcare — it is already happening. And many of those uses could be truly beneficial. Anthropic recently announced an initiative to apply the theoretical findings of its AI models to real-life lab work that could lead to new drugs being developed in the future. In terms of scientific discovery and the potential to translate it into new treatments, the excitement among clinicians about its potential is palpable.

And nobody denies that health insurance administration is chaotic and burdensome and would benefit from being made more efficient and streamlined — tasks which AI is at least superficially well-suited for.

But as the past few years have already shown, rushed and sloppy deployment of AI to take responsibility for approving or denying payment for people’s medical care has created serious problems. The issue is that this technology is being adopted more quickly than any regulator can oversee it. We don’t really know how health insurers are using AI tools. We don’t have a good framework for what keeping a “human in the loop” of insurance decisions — which is what people want — would really mean, Schwarcz said. 

“I think everyone agrees at a high level of generality, ‘Yes, AI should be used to enhance human review and not to replace it,’ but no one actually knows how to write rules to enforce it,” he told me. “I don’t think that there’s anything I’ve seen that has effectively defined what it means for a human to be meaningfully in the loop in the sense of retaining independent judgment as opposed to just reviewing and deferring. It is incredibly hard to specify in rules or regulations a standard that is verifiable and enforceable. That is still, as far as I know, an unsolved problem.”

Some states have started adopting rules requiring transparency for AI use in insurance claims, and lawmakers in Congress have put forward proposals requiring human involvement, including the bipartisan Protecting Patients from Automated Denials Act. But these technologies are so ubiquitous and so flexible that rigorously regulating their use is going to be difficult. Meanwhile, the profit incentive for companies to adopt these tools and deploy them widely is extremely strong. We don’t even know how widespread their use really is.

Danas said he and his clients hoped their litigation would help with “putting the brakes” on AI’s use in insurance. Until we figure out what to do from a policy perspective, what can each of us do in the meantime? Hamer told me that the old advice is still the best advice: If your claim is denied, appeal it. An enormous number of denied claims end up getting overturned on appeal. 

“You do not necessarily have to accept that the first answer from your insurance company is the final determination,” she said.

Welcome to The Midterms, Actually. Every week I’ll be writing about two things: one big idea or trend I see forming across the 2026 primaries, and one thing I’m hearing from a voice on the ground. Let’s get into it. You can sign up here to get it in your inbox every week. Let’s get into it.

One big idea: Latinos didn’t come home. They’re just in motion.

In the last presidential election, President Donald Trump’s strong support with Latino voters ended up one of the biggest stories of the night. After years of Democrats telling themselves that the growing number of Hispanic Americans would help lead to a permanent liberal majority, their dreams were first dashed in 2016 (when many of those voters stayed home) and then buried in 2024 (when they, and other nonwhite voters, swung toward Trump).

But just as Democrats have at times been too confident that minority voters would fall in line, it now seems Republicans have replicated their mistake. Poll after poll shows a historic reversal among Latino voters in Trump’s second term, and these days even Republican members of Congress are beginning to call Trump out on his deportation efforts. 

Why? It comes back to the numbers.

As Nate Cohn observed in the New York Times this week, Democrats now lead Republicans among Hispanic likely voters by 35 percentage points on the generic congressional ballot, 64-29 — a 28-point swing from 2024, when Kamala Harris carried Hispanic voters by just 7 points. The shift is a big reason the polling has Democrats in “blue wave” territory this November.

Last week on America, Actually I explored this shift in detail — by talking to Stephanie Valencia, co-founder and president of Equis, the research firm that has spent a decade digging into the Latino electorate. And the first thing she wanted us all to know: Get rid of the idea that Latinos will ever be permanently Democratic or permanently Republican. Part of the electoral power is that a larger section of the electorate defines itself more independently.

“Latinos often get given the title, the sleeping giant, which I just want to rid that out of everybody’s vocabulary. We should be called the swinging giant based on how much shift we have seen election to election. A third of Latinos consider themselves kind of independent or apolitical nonpartisan, and that’s that swinging middle that really is deciding every single election.”

Here are three more trends Valencia pointed out, which help explain why this all-important voting group has done such a drastic 180 on Trump in his second term.

1. It’s the economy (again)

As with all things in Trump’s second term, it starts with the fundamental problem of his second term: He has not delivered on lower prices. Equis found that Trump’s net approval with Latinos on cost of living sits at -52 — and his number on the economy (-45) is worse than his overall approval with the group (-31). Both are dramatically worse than where he sits with non-Latinos, who put him at -39 on cost of living and -25 on the economy. Among Latino men 18 to 39, cost of living hits a stunning -63.

Here’s what Valencia said:

“Latinos make up more of the wage workforce than any other racial subgroup. And so what that means is when wages are down and inflation is high, Latinos feel it more. We have less savings. We have less rates of home ownership. So the kind of safety nets that other people might have, we just don’t have.”

She also pointed this out:

“In Trump 1.0, his approval on the economy and the cost of living was actually better than his everyday approval… And he has been underwater with Latinos almost this entire term so far on the cost of living and the economy. It’s almost been a complete and total reversal.”

One of the arguments Trump made to Hispanic communities (and other groups also) was that he’d economically empower them, and that this was more important than prioritizing social causes that didn’t have a material benefit. That’s also been his fundamental flaw. From tariffs to rising gas prices, he has not only not delivered — people also feel worse off than before.

2. The immigration backlash

Valencia’s data was undeniable: More and more Latinos turned on Trump as he broadened his deportation efforts, which were broadly unpopular. But what I didn’t understand is why it took until Trump’s second term for people to realize those threats were legitimate, considering they were so front and center during his campaign. (They held up “Mass Deportation Now!” signs at the Republican National Convention!)

Here’s what Valencia said:

“I think this is really important for us as avid news consumers to understand what it is that the average voter, and especially that voter who’s coming in and out of elections, the kind of news they’re consuming. What they were seeing on mainstream media, perhaps even Fox News at the time, was a focus on Trump surrogates who said he’s gonna focus on serious criminals, securing the border, and violent criminals. And so that’s what people bought.”

“Fast-forward to 2026, the people who feel most regretful who voted for Trump in 2024 are most regretful because of immigration. They feel like there was a broken promise there. Like, they were told he was gonna focus on the border, which everybody agreed was chaos, and he was gonna focus on violent criminals and serious threats, and at the end of the day, he has not complied with that.”

There’s also an element of disbelief. When Trump said he would deport “bad people,” a lot of people thought he was only talking about people in other communities — or immigrants with criminal legal histories — not the more far-reaching immigration sweeps we’ve seen since he’s been in office. A striking ad from Rep. María Elvira Salazar (R-FL) this week where she directly criticizes Trump’s immigration policy explicitly made this distinction. 

The Equis numbers track that shift almost perfectly. In December 2024, 65 percent of Latino Trump voters believed he would target only criminals and recent arrivals. Today, 62 percent of Latinos overall say he’s going after undocumented immigrants broadly — and among his own Latino voters, the share who say that has jumped from 26 percent to 37 percent. That perception is the whole ballgame: Latino Trump voters who still believe he’s targeting only criminals give him +84 net approval. Among those who’ve concluded he’s targeting everyone, it collapses to +31.

The backlash isn’t about the border. It’s about what’s happening in the interior — the raids, the family separations, the citizens and legal residents swept up. 

Equis finds 68 percent of Latinos say Republicans promised to deport criminals and deported hardworking people instead — and 67 percent say Democrats promise immigration reform and never deliver. Forty-two percent say both parties broke their promises.

“I think it is a huge mistake for Democrats to assume or to rest on their laurels and think that because of what people are feeling around Trump and Republicans and the sense of disappointment and broken promises, that that is automatically going to translate to them as a party and as a brand. Right now, the Democratic brand has suffered a repeated set of blows among Latino voters. 20 years of comprehensive immigration reform that hasn’t been delivered. It’s a thing that comes up in almost every focus group.”

3. Meeting voters where they are

The third trend isn’t about persuasion at all. It’s about the fact that a lot of campaigns are still bad at the mechanics of reaching this electorate — and Valencia’s examples were almost comically basic.

Their testing found that more than 70 percent of Latinos who see an ad in Spanish come away thinking that candidate or party cares more about Latinos. That’s not a persuasion effect. That’s a respect effect, and it’s enormous for the price of one ad buy.

So how do campaigns blow it? Some examples, according to Valencia: translating English ads directly into Spanish, rather than tailoring them to the language and culture; and assuming English speakers and Spanish speakers are separate categories when voters often shift between media in both languages. 

The deeper error is the monolith problem — the group is still treated as a voting bloc that moves in unison, rather than a diverse set of people from varying countries of origin and contexts. And the fastest-moving division isn’t the country of origin at all. It’s age — an electorate replenishing itself faster than either party’s model of it.

“There are a million Latinos who turn 18 every single year, and an 18-year-old who turns 18 this year and will vote in this year’s election was born the year Barack Obama was elected president. … The era of politics for an 18-year-old today is chaos, Covid, and corruption. They do not remember the hopium of Obama and the beautiful coalition that we built. That is all ancient history to them.”

A million new voters a year, completely up for grabs. Nobody is inheriting these voters. Neither party owns them. Because as Valencia put it: Demographics have proven not to be destiny — effort and intention matter more.

What I’m hearing

This week I called Matthew Eadie, a reporter at Evanston Now, who has been covering an ICE stop in Evanston, Illinois that has since attracted national attention. On the morning of Sunday, September 20, federal agents stopped a man walking on Howard Street. He turned out to be a US citizen, and not the person they were looking for. Agents reportedly left him on the ground with injuries to his head, neck, and teeth. DHS says he “refused to identify himself. Now the community is demanding answers.”

What’s the community reaction been?

People are really furious. If you remember the fall here — Operation Midway Blitz, the heightened Border Patrol enforcement across the Chicago area, Gregory Bovino parading around the streets with camera crews, the protests at the Broadview processing center — people here were very aware of how impactful it was. It was also happening around the elections, so it was prominent news everywhere and everybody was talking about it.

Over the summer it really died down, and I don’t think people have paid much attention since. ICE has been around all year, but they haven’t been as flashy about it, which has been talked about nationally too. This was a flare-up, and it’s a reminder that it’s still going on even after Bovino left. There have been protests at Broadview this week unrelated to the Evanston incident. So either people are starting to pay more attention as the election gets closer, or the incidents are actually picking up again.

What are the unanswered questions you’re still chasing?

Who were they looking for? Were they actually looking for somebody? That’s been their story — a specific individual — and a lot of people I’ve talked to are really skeptical that’s the case. One witness at the scene told me he felt like they just picked him and drove up on him. Essentially what’s been called a “Kavanaugh stop” — if they’re suspicious of you, they can pretty much find a reason to detain you. And then they dropped it once they realized either that he was a US citizen, which he says he is, or that there were too many people around taking videos for it to be worth their time.

So: What happened in the lead-up, and who specifically were they looking for? 

Afterward, the agents talked to Evanston police — that’s an Evanston police policy; they’re supposed to try to get information from ICE officers. I’ve FOIAed all the body cam footage. I want to see what those conversations were like, and what exactly the agents told police officers when they talked privately.

Part of what we’re trying to do is see the issues that play out from the bottom up rather than the way they get framed nationally. Beyond immigration, is there anything in your coverage that’s shaping local politics more than the national conversation reflects?

The national issues matter to everybody, but they hit communities in completely different ways. Evanston is affluent — college town, Northwestern, wealthier than most suburbs. Affordability is a buzzword that comes up everywhere, but people here talk about it differently.

This is an overwhelmingly progressive Democratic city. Some people in Evanston certainly need it to be more affordable for themselves. But you also have progressive voters saying we want to make Evanston more affordable and more inclusive for other people. Sometimes the affordability conversation gets framed as “life is too expensive for me and we need to make it cheaper for me,” which is true in a lot of places. In somewhere like Evanston, where there are a lot of affluent people who are also very progressive voters, it’s more: If we actually want to say we’re a progressive community, we have to show it. And showing it maybe means building affordable housing.

It’s also a city that passed reparations, which the federal government is challenging right now. That’s going to be a federal court case through the end of this year and probably into next year — the feds challenging the city’s reparations program. That’s something the city prides itself on. Those are big issues here that come out of the national conversation but sound different than how we hear them in national media.