President Donald Trump is sending more than 20 million Medicare recipients a one-time $90 payment — less than half the cost of a single month’s standard Medicare Part B premium — just weeks before the midterm elections.
Trump announced the payments late Friday on Truth Social, describing them as “Checks” of nearly $100 for “wonderful Seniors.”
The White House clarified that eligible recipients will receive $90, mostly through direct deposit beginning in early October. The standard Medicare Part B premium is $202.90 per month in 2026.
The payments will come from the Medicare Improvement Fund, established by Congress in 2008 to fund improvements to Medicare’s fee-for-service program. The White House said approximately $2 billion is available in the fund and that it has never previously been used to make direct payments to Medicare recipients.
Trump called the fund a “pointless ‘Slush Fund’” that Democrats had used for “Waste, Fraud, and Abuse for their Special Interest friends.”
Most Medicare Part B recipients will qualify, although people whose premiums are paid by Medicaid and higher-income recipients who pay an income-related adjustment will not, according to the White House.
The payments are the latest in a series of cash promises from Trump as Republicans approach the Nov. 3 midterms. His administration has also announced $500 refunds for nearly 1 million Affordable Care Act enrollees who it says were overcharged under the Biden administration.
Trump used the same Truth Social post announcing the $90 Medicare payments to renew another, substantially larger promise.
Americans, he said, “can also rest assured” that a $5,000 “Trump Dividend” would be distributed to every U.S. citizen “if, and when, the Republicans win the Midterm Elections!”
The administration has not detailed how such a $5,000 payment would be funded or enacted.
Defense Secretary Pete Hegseth is putting religion closer to the top of the Pentagon’s chain of command.
Hegseth announced the creation of a new Office of Religious Affairs during his State of the Force address Wednesday. The office will report directly to Hegseth and advise Pentagon leadership on religious policy, funding and the “spiritual readiness” of U.S. service members.
“No staff filters, no bureaucratic dilution — a direct line to the secretary,” Hegseth said.
The office will also oversee the Armed Forces Chaplains Board and advocate for funding for religious programs across the military.
The Pentagon memo establishing the office says it cannot “compel religious participation” or diminish the rights of service members, civilian employees or family members “of any faith or no faith.”
“Our department is, you might say, putting on the full armor of God because while we wage physical war, we all know the real battle is spiritual,” Hegseth said. “God is good. Evil is not. And America’s military must understand the difference.”
Hegseth also criticized what he called the military’s previous embrace of “political correctness and secular humanism” and claimed fewer than 5% of service members identify as nonreligious.
“So 95% of our force recognizes an Almighty God,” he said.
The Pentagon’s most recent publicly released data, from 2019, found roughly 70% of active-duty personnel identified as Christian. Nearly a quarter had an unknown or unclassified religious affiliation.
The office follows a series of changes Hegseth has made to religious life in the military. The Pentagon this year condensed more than 200 religious affiliation codes to 31, initially eliminating specific classifications for atheists, Unitarian Universalists, pagans and Wiccans, among others.
Hegseth has also hosted Christian worship services at the Pentagon. During one service in March, he prayed for God to enable U.S. troops to inflict violence “against those who deserve no mercy.”
The university where the term artificial intelligence was coined is ringing in the field’s 70th birthday in fitting fashion: with an academic-integrity scandal. Last month, Dartmouth College’s president, Sian Leah Beilock, published an essay in The Atlantic headlined: “Why I Want More AI at Dartmouth.” Now Beilock is launching a review of whether her top deputy used too much AI.
On September 21, the student newspaper The Dartmouth reported that Provost Santiago Schnell appeared to have relied heavily on AI to write all nine of the articles he’s published this year—including a Washington Post op-ed about students outsourcing their writing to AI. Schnell’s response to the accusation didn’t help his cause. According to the student paper, he sent an email statement acknowledging that he uses AI chatbots as “assistive tools” in his writing but downplayed their role in his process. Even Schnell’s statement, the paper found, registered as “100% AI-written” on Pangram, an AI-detection service that is imperfect but boasts a very low error rate. A Dartmouth spokesperson told me that neither Beilock nor Schnell would comment for this story.
Schnell is the latest example of an ironic phenomenon: People whose job involves writing about the appropriate uses of AI—or even setting the rules on AI use for others—keep getting caught using AI to do it. There was the Australian university professor whose op-ed about the importance of students doing their own writing turned out to be at least partly AI-generated. There was the nonprofit executive whose book about the future of truth in the AI age turned out to include quotes fabricated by AI. There was the AI beat reporter who reportedly lost his job after he accidentally copied quotes invented by AI into one of his stories. And there was the Stanford misinformation expert who got upbraided by a judge when his declaration supporting an anti-AI-deepfake law turned out to contain ChatGPT-hallucinated citations.
It’s one thing to embrace AI writing openly or shamelessly, like the billionaire financier who readily acknowledged the technology’s role in his Wall Street Journal op-ed (albeit only after it was discovered). It’s another to use AI to inveigh against improper uses of AI, and it raises an awkward question: Why do some of the people warning us most loudly about the technology’s pitfalls keep tumbling headfirst into them?
I reached out to all five of the individuals listed above for an answer, but the only one who agreed to speak with me on the record was Steven Rosenbaum, the author of the book The Future of Truth: How AI Reshapes Reality and the executive director of the nonprofit Sustainable Media Center. Unlike some of the others, Rosenbaum disclosed his use of AI in the writing and editing process, and he has never tried to tell other people not to use it. But that didn’t save him from ignominy when The New York Timesreported in May that the book was riddled with AI-generated misquotes. I spoke with him at the time, and he told me that he felt “betrayed” by ChatGPT. Five months on, Rosenbaum seems to have accepted a bit more responsibility for the mistakes. He told me that he is preparing to publish a revised version of his book with all of the errors corrected, an author’s note, and a new chapter on (what else?) AI hallucinations. He still believes that the fault lies more with the technology’s makers than its users, though. “As a technology, it is incredibly seductive,” he said.
Rosenbaum said that he’d started out using AI to better understand the technology. He’d gradually come to rely on it as a writing partner that made the work both easier and less lonely. He described his experience of writing with AI as a messy process, one in which the work of the human and that of the machine get all tangled up. “The line between thinking and researching and reading and outlining and drafting and writing is really blurry,” he said.
A simple solution, of course, would be not to use AI at all. Rosenbaum, however, has no interest in that. He said that he still plans to use chatbots as a writing companion—just “more carefully” now, double-checking all of their claims and citations before adopting them. He’s not alone in his unwillingness to abandon the tools that got him in trouble. Although each of the people caught using AI to warn about AI has commented publicly on the episode in some form, none responded by swearing off the technology. Rosenbaum, for his part, thinks we’re headed toward a world in which writing with AI is the norm and all that matters is the result. “I don’t think readers care how the sausage is made,” he said. “They care that it’s delicious.”
I’m not so sure. I too have experimented with using AI as a research tool in my writing. But The Atlantic has a strict policy against the use of AI-generated prose, and so do I. I’ve found that having a personal red line is both useful and clarifying: I might ask a chatbot questions, get its feedback on a word choice or an explanation, or ask it to poke holes in my argument, but I will not ask it to write for me or use its writing in my own drafts. I think readers value knowing that every word they’re reading was chosen by the author and not an algorithm. That said, I can see how the distinction between using AI for research and writing could feel slippery to some. It’s conceivable, for instance, that a chatbot’s biases could be infiltrating my ideas, if not my precise words. (Then again, so could the biases of Google’s search-ranking engine or my social-media feeds.)
I have another theory as to why people who caution others about AI seem to be using it themselves. In a scenario strikingly similar to the one at Dartmouth, the professor in charge of academic integrity at Western Sydney University wrote an op-ed in May on the importance of students not delegating their work to AI. “Don’t cut corners,” Cath Ellis, the university’s pro-vice-chancellor for quality and integrity, wrote in The Sydney Morning Herald. “Don’t outsource your thinking, however tempting that may be.” The op-ed, it soon became clear, had been generated at least partly by AI. In that case, a university spokesperson defended Ellis’s use of the technology as “sophisticated and appropriate,” because she had fed her own past work into the AI tool before asking it to help her draft the op-ed. Ellis toldThe Sydney Morning Herald that the op-ed hadn’t been written “by” AI: “It was written with AI, and there’s a really big difference there,” she said.
Ellis’s excuse might ring hollow to the students she chastised, but it’s revealing to those of us trying to wrap our minds around the apparent hypocrisy. In her op-ed, Ellis implied that students who use AI to write are outsourcing their thinking. In defending her own AI use, she distinguished between the writing (which she outsourced) and the ideas (which she claimed were original). Likewise, Schnell fretted in his op-ed that “students can now produce proficient prose without performing much of the intellectual work the prose appears to represent.” Yet when confronted with his own AI use, he claimed authorship of the “ideas and arguments” even if bots did some of the writing.
These guardians of academic integrity might be right that what they did is meaningfully different from a student simply feeding a professor’s assignment into a chatbot and handing in whatever it spits out. Of course, students can use AI in more nuanced ways too. No doubt plenty of students accused of AI cheating have mounted defenses that sounded a lot like Ellis’s and Schnell’s.
Writing is thinking has become a common refrain among critics of those who use AI tools to do their writing. What we see again and again in defenses of AI writing is that the people using AI don’t seem to apply that maxim to themselves. And experts on the perils of AI fakery such as Rosenbaum and the Stanford misinformation expert, Jeff Hancock, appeared to have overestimated their own ability to steer clear of AI falsehoods. It’s reminiscent of what the sociologist W. Phillips Davison called the “third-person effect” in mass media: people’s tendency to believe that they’re immune to persuasive messaging even as they expect it to influence others.
It is a form of hypocrisy, and it’s hard to feel much sympathy for thought leaders who get caught practicing what they preach against. But the fact that even professed AI experts blunder into overrelying on the technology suggests that Rosenbaum is onto something: Chatbots might come with fine-print disclaimers that they can make mistakes, but they bend over backwards in their interactions with users to come across as honest and trustworthy. It’s also true that society has yet to develop a vocabulary for all the ways of writing with AI that fall in between “AI-generated” and “entirely human-written.”
Here’s where I acknowledge that even my own bright line on AI use might be fuzzier than I realize. In the process of writing this story, I described the thrust of my argument to Google and Claude and asked them for examples of AI-writing hypocrisy that I may have missed. Neither managed to surface any that I hadn’t previously been aware of. On a whim, I followed up with Claude by asking it to brainstorm some hypotheses as to why AI skeptics might fail to heed their own advice.
I had my own ideas, and I had also solicited the thoughts of colleagues, but I wanted to see what the chatbot would come up with. One of its suggestions struck me as a sharper version of a thought I’d been struggling to formulate: “Writing is thinking is a rule for other people,” it mused. I didn’t use Claude’s language, but the AI model had crisply summarized a notion I’d been thinking over. That formulation no doubt informed how I thought about this story’s framing. Am I an AI-writing hypocrite now too?
I talked through some of this with a journalist who once got in trouble over a story that contained AI-generated errors. We corresponded on the condition of anonymity because they said that resurfacing the incident could damage their job prospects. This was the lesson they said they had learned: “AI is a power tool, and like any power tool it’s dangerous if you’re careless with it. You can be the guy who warned everyone that a table saw can cut your fingers off and still lose a finger one day, because that risk is built into the machine. It goes up the more you use it.”
When you think about it that way, it makes sense that some of the people relying on AI would be the same ones sounding the alarm about its risks. They know its flaws, but they also know its power. And they just can’t bring themselves to give that up.
By his own admission, David Robinson is “something of a cliché”: an employee at a leading AI company who issues a dire warning while resigning from their job.
Even experienced coders sometimes need a little help. Microsoft Visual Studio Professional 2026 combines professional development tools with AI-powered assistance to help you tackle code more efficiently. — Read the rest
The 50-year-old, who was convicted of first-degree murder and sentenced to death for the 1995 murder of 19-year-old Colleen Slemmer, survived a severely botched execution by lethal injection on Wednesday. The drugs meant to kill her did not do their job, and she is now in critical condition, intubated, unconscious and on a ventilator in a Nashville-area hospital. According to her lawyer, Pike’s prognosis is unclear, as is the question of whether she will suffer a serious brain injury and loss of function.
Amid questions and a media storm, Tennessee Republican Gov. Bill Lee ordered a third-party review and paused executions for the remainder of the year. On Saturday he announced that Frank Strada, the head of the state’s prison system, would be stepping down.
Meanwhile, politicians like Sen. Marsha Blackburn, R-Tenn., who is currently running for Tennessee governor, promised that if she is elected and Pike survives, she would try again to execute her — by other means, if necessary. “While there should be a thorough review of what happened and why the process failed,” Blackburn wrote on X, “the answer is simple: bring back the electric chair and deliver justice for these victims. As your governor, I will do just that.”
Not to be outdone, Rep. Tim Burchett, R-Tenn., told NewsNation that he would “Prop her up and bring her to a firing squad.”
Such heartless statements should not distract us from the fact that what happened to Pike might have been prevented had the state of Tennessee paid attention to repeated warnings: that her small veins and history of a blood disorder would make lethal injection a cruel procedure.
Pike’s failed execution also highlights another need. If death penalty states are going to continue to use lethal injections, they should be required to have competent medical professionals on hand to help carry them out. Doctors, good doctors, are needed to help make sure that the process goes as smoothly as possible — and that the condemned person does not suffer needlessly.
In Pike’s case, that did not happen.
The New York Times reported that “The execution team went through at least seven needles trying to find a vein suitable for delivering doses of a lethal drug [and Pike] was left with blistering and burning around the intravenous insertion sites that the execution team ultimately used to deliver the drug.”
According to some outside medical experts, she likely “survived the procedure because the drug, pentobarbital, probably poured into tissue surrounding the insertion sites instead of entering her bloodstream.” If accurate, this apparently happened because the intravenous lines needed to carry the lethal drugs were not placed correctly.
The people tasked with the job of finding a usable vein and securing an IV are not phlebotomists with specialized training or nurses. And in states like Tennessee, which does not carry out many lethal injection executions, members of the execution team do not have the chance to perfect their skill by using it a lot.
Pike’s case was not an isolated event. Such problems have occurred many other times, though generally they have not prevented executions from proceeding. The people tasked with the job of finding a usable vein and securing an IV are not phlebotomists with specialized training or nurses. And in states like Tennessee, which does not carry out many lethal injection executions, members of the execution team do not have the chance to perfect their skill by using it a lot.
As Corinna Barrett Lain, a death penalty expert and professor at the University of Richmond School of Law told CNN, lethal injection is “a highly delicate, error-prone procedure that is done by people who are not trained . . . It’s a recipe for disaster from the start.”
In Pike’s case, a doctor was present — but he had a checkered history with executions. Dr. Mark Fowler was reportedly part of yet another bungled execution in Tennessee only months ago, when attempts to establish an IV line in 57-year-old Tony Carruthers, who was convicted of being involved in a triple murder in Memphis in 1994, failed repeatedly. (Following the attempted execution, Tennessee Gov. Bill Lee gave Carruthers a one-year temporary reprieve.) In the wake of the Carruthers debacle, substantial questions were raised about Fowler’s ethics and competence, but they did not deter Tennessee from calling on him again.
Tennessee is one of 17 states with laws requiring doctors to play some role in the execution process. In those states, “Doctors have signed death warrants, rendered inmates competent, provided intravenous access, monitored vital signs, administered lethal injections and declared death.”
But at the same time, since the dawn of the lethal injection era, the American Medical Association has held that it is a violation of medical ethics for doctors to participate in executions: “Physician participation in execution is defined as actions that fall into one or more of the following categories: Would directly cause the death of the condemned. Would assist, supervise, or contribute to the ability of another individual to directly cause the death of the condemned.”
According to AMA guidelines, doctors involved in lethal injections cannot choose injection sites, start IV lines to administer the lethal medicine or be involved in prescribing, preparing, administering, or supervising injection drugs or their doses or types.” Other professional associations, including the American Nursing Association and the American Society of Anesthesiologists, have established similar regulations.
The result is that states have been forced to turn to unlicensed medical personnel. Hundreds of them have played a role in executions — but they have done so in the shadows.
That is not good enough when someone’s life is being extinguished. As is the case with physician assistance in dying, the choice is between professional purity and the need for expertise in making sure the end of life will be as peaceful as possible.
In the wake of Carruthers’ botched execution, a group of more than 40 doctors and nurses came down on the side of purity. They sent a letter to Lee asking him to change the state’s execution process so that medical professionals no longer would have to be involved. “[T]he health care professionals who agree to take part in Tennessee’s executions are those willing to set aside their professional ethics,” they wrote. “The problems that we have seen, such as in Mr. Carruthers’s case, are the predictable result of working with such unscrupulous actors.”
But here’s a thought: Maybe the problem is not with Tennessee law but instead with the ethical standards that keep reputable medical professionals from participating in executions.
The doctors treating Pike know that “[i]f she recovers, Tennessee might try to kill her again [and] that their job is to do the best they can for the patient in front of them and not to think about that.’”
There will be time to do so if the savage cries of politicians like Blackburn and Burchett are heard. But with Pike currently in critical condition from a cruel, mangled procedure, it’s unclear if and when that might happen. But if it does, doctors should do their part to see to it that she is treated with as much compassion in the death chamber as she is in the hospital.
President Donald Trump’s motorcade approached 100 mph on wet highways Thursday after bad weather grounded his aircraft — and the president boasted about the high-speed trip in real time.
Trump was traveling from a campaign event at a Peterbilt Motors plant in Denton, Texas, to a rally roughly 90 miles away in Durant, Oklahoma, when stormy weather disrupted his travel plans. The president would typically make the trip by air, but conditions prevented planes and helicopters from landing in Oklahoma.
Rather than postpone the rally, Trump opted for the presidential motorcade.
“The Beast is going faster than it has ever gone before,” Trump wrote on Truth Social, referring to the heavily armored presidential limousine.
Reporters traveling with the president confirmed the unusually speedy trip. A White House press van reached 98 mph at one point as the motorcade traveled north toward Oklahoma, according to Reuters and CBS News.
A little more than 20 minutes after his first post, Trump offered another update.
“I’m almost there Oklahoma — 10 minutes!” he wrote.
Trump ultimately arrived in Durant nearly two hours behind schedule. Once onstage, he gave supporters his own account of the decision to make the drive.
Trump said aides had warned him that the weather was too bad to take either a helicopter or plane and suggested canceling the Oklahoma appearance. He instead asked how fast his presidential limousine could travel.
“We could go close to 100 miles per hour,” Trump recalled being told.
“Get your asses in that car,” Trump said he responded. “We’re going to Oklahoma.”
The president was in Oklahoma as part of a 32-day campaign blitz ahead of the Nov. 3 midterm elections, campaigning in Durant for Republican gubernatorial candidate Mike Mazzei and U.S. Senate candidate Kevin Hern after appearing with Republican Senate candidate Ken Paxton in Texas.
Trump said he refused to skip Oklahoma in part because of his electoral history in the state, telling the crowd that he had won all 77 counties in each of his three presidential campaigns.
No injuries were reported during the high-speed motorcade. Trump did not provide a measured speed for the Beast itself. The speed limits on the roads between the two cities range from 45 mph to 75 mph depending on the stretch of road.
Editor’s Note:Washington Week With The Atlantic is a partnership between NewsHour Productions, WETA, and The Atlantic airing every Friday on PBS stations nationwide. Check your local listings, watch full episodes here, or listen to the weekly podcast here.
President Trump has begun traveling to red states in a bid to generate voter enthusiasm ahead of the midterms. On Washington Week With The Atlantic, panelists joined to discuss how the president is trying to maintain his control over the GOP as the election draws nearer.
Because of rising prices, the prolonged conflict in Iran, and other factors, “Republicans are not in a good place; the White House is not in a good place,” Zolan Kanno-Youngs, a White House correspondent at The New York Times, argued last night. “In response to that challenge, you are seeing the president not say, Distance yourself from me; do what you’ve got to do, but rather, Pretend I am on the ballot.”
Joining the editor in chief of The Atlantic, Jeffrey Goldberg, to discuss this and more: Kanno-Youngs; Janay Kingsberry, a staff writer at The Atlantic; Michelle Price, a White House reporter at The Associated Press; Steve Inskeep, the host of NPR’s Morning Edition.
Earlier this year, one of my fishing partners sent a 1 a.m. message to our group chat. It was a link to an Instagram post of an angler holding a sizable striped bass. Dappled gold and silver with a dozen distinct black lines that stretched from gills to tail, it would have been a gorgeous fish if not for two problems: Striped bass usually have seven stripes, not 12, and men usually have five fingers, not six. The photo, it seemed, was AI-generated. To say we were dismayed would be an understatement.
From May to November each year, I spend most of my nights doing an extreme version of surf fishing for striped bass called “wetsuiting,” which involves wading or swimming out to distant ocean rocks and sandbars after dark. This kind of surf casting is a niche activity, and like many niche activities, the community for it is small. Wetsuiters can be found in a smattering of localfishing clubs throughout the Northeast—the typical range of the striped bass—but are primarily connected through Instagram, where some people, mostly for bragging rights, post images of fish they’ve caught.
In our group chat, my fishing partners and I spend too much time scrutinizing photos of bass that other anglers have posted. People who fish are habitual liars (I say this fondly), and most of our conversations take the form of debates about whether a fish is really as big as someone claims. Lately, though, we’ve been asking a different question: Is that fish even real?
In recent months, the small corner of Fishing Instagram devoted to surf casting has been plagued by a slow drip of AI-generated or AI-enhanced fish. Sometimes, the fraud is egregious—one of my friends, a fishing photographer, discovered that another angler had stolen one of his photos and crudely replaced my friend’s face with her own. More often, the distortions are subtle. Typically, a fish or fisherman looks ever so slightly off, usually in ways that a casual observer might not notice: A bass’s fins aren’t quite right, or the lure in its mouth looks oddly distorted, or the angler’s arms are a bit too long. In my favorite example, a man lifts a large striped bass just as he is getting pummeled by a wave. The scene looks daunting—until you realize that the ocean behind him is peaceful. Where did this rogue wave come from? One suspects that the enterprising angler, wanting to look more hard-core to his Instagram followers, prompted a bot to dial up the intensity. ChatGPT, make me look badass.
Fishing magazines report growing concern about AI-generated fish in freelance photo submissions. I have written occasionally for the small online magazine Surfcaster’s Journal. Over the summer, the Journal announced that it would now run all manuscripts and photographs through AI-detection software. “For some reason, I naively assumed that fishermen wouldn’t stoop to the ‘core of the earth’ lows required to use AI to prop oneself up as a fisherman worthy of clicking the follow icon,” Dave Anderson, a well-respected wetsuiter and an editor at The Fisherman, wrote in an article lamenting the scourge of artificially generated fish on social media. “I was very wrong about this.”
Angling, even extreme angling, is just a hobby, but although the stakes may be low, the anger about artificial fish is real. Partly, I think this is because of the work that being even remotely good at the sport demands. Striped bass move and feed in locally specific patterns that can take months or years to crack. There is a risk of drowning, and the mounting reports of bull sharks, tiger sharks, and great whites in the Northeast call attention to another layer of danger: We smell like fish, swim in dark water, and look like clumsy seals in our black neoprene. Wetsuiting does not change the world, but it is an activity that is hard and honest and, in that way, human.
Even taking a picture of a fish is demanding, requiring salt-water-proof cameras and often wading or swimming a bass back to shallow water, where it can safely be photographed and then released. The Photoshopping of fish pictures—and of the natural world in general—has been an issue for years, but AI, with its ability to conjure a simulacrum of reality out of nothing at all, is another matter. It automates away the need not only to photograph a fish, but to even catch one in the first place.
The problem extends to other sports and hobbies, many of which are now defined by what Stuart Franklin—who took one of the celebrated “Tank Man” photos at Tiananmen Square—calls the “documentary impulse.” Social media has turbo-charged that impulse into an imperative. A good local skateboarder’s or surfer’s reputation would once have been built through word of mouth. Today, posted photographs and short-form videos may constitute the primary proof of ability. Concerns about AI slop are already being raised in cycling, skiing, and other activities. ClimbingMagazine recently called out an AI-saturated YouTube channel purporting to chronicle climbing disasters that in fact never happened.
As AI-generated fish have appeared more frequently in my social-media feed, I’ve been reminded of a scene in the bird-watching documentaryListers, where a highly competitive birder is asked whether he would keep bird-watching if the photo-logging website eBird disappeared. His answer—“No”—was unsettling, not least because one suspects that this sentiment is widespread in hobbies besides birding. I have often wondered if, for some of the wetsuiters who populate surf-casting Instagram, the dopamine hit from the likes and fire emoji is sweeter than the hit from catching the fish itself. Now that posted images are being looked upon with an ever greater degree of suspicion, I also wonder how much longer the dopamine hits will come for them at all.
This is hardly the greatest challenge posed to humanity by the advent of AI. But hobbies, particularly those that require some measure of skill and endurance, have an influence that extends beyond those who directly participate in them. Free Solo, the Oscar-winning 2018 documentary about the death-defying rock climber Alex Honnold, found a wide audience outside the narrow world of climbing because people are invested in seeing other people do difficult things. I love videos of big-wave surfing even though I never plan to climb onto a surfboard. If AI makes it impossible to trust what we see, even something as simple as a surfing video, then we have lost more than the integrity of any one sport. We have lost the ability to believe in the accomplishments of others.
This article appears in the November 2026 print edition with the headline “The Fish Are Getting Bigger.”
One of humanity’s most remarkable cultural achievements is the division of explanatory labor. When my daughter came down with a fever, I solved the problem by consulting a pediatrician, who shared a likely diagnosis of the flu. Unlike the doctor, I wasn’t able to tell my daughter much about the mechanism by which the flu leads to fever, or exactly why it was so important for her to keep drinking fluids. But the explanation I acquired—roughly “fever because flu”—was what was needed to treat her.
Society runs on this efficient type of information sharing. Just as coordinating specialized skills can streamline the fabrication of products—be it pins or cars or newspapers—coordinating specialized knowledge can facilitate the answering of questions. You can drive a car even if you don’t have the expertise to manufacture one yourself, and I benefited from the pediatrician’s explanation even though his understanding far exceeded my own.
We can thank this divide-and-conquer method for many advancements in medicine and science, engineering and commerce; in fact, it has helped drive the accumulation of human knowledge across communities and over time. But it also leaves us susceptible to illusions of understanding: cases in which we mistake the understanding of others for our own.
Humans’ sense of whom to ask for what is fine-tuned by evolution, culture, and personal experience. Even 3-to-5-year-olds are more likely to say that you should ask a doctor rather than a mechanic about fixing a broken arm, and a mechanic rather than a doctor about fixing a flat tire. As kids mature, they develop an even deeper understanding of expertise. In a 2004 study published in Child Development, for example, 11- and 12-year-olds tasked with finding out why tennis balls bounce better on the sidewalk than on grass were more likely to suggest asking someone who knows why bubble wrap keeps glass things from breaking (which is also relevant to physics) than someone who knows why tennis balls come in cans of three (which just happens to also involve tennis balls). Their choice of whom to ask was based on fundamental principles—not just superficial similarities.
With plenty of time and care, years of education, and a healthy appetite for learning, most of us transition from children who know little about science or other expert domains to … adults who know little about science or other expert domains. Even those of us who acquire expertise in one area are unlikely to do so in many others. So the ability to track outside expertise is no less important for adults than it is for children. We need to know who can explain a child’s fever, a wilting plant, a clause in a will, or an imperfect soufflé—and research finds that adults seem to do this pretty well. (As a population, of course, we do not do this perfectly: Plenty of people trust in bad advice from their friends, influencers, and self-proclaimed experts.) A study from Germany found that even college students who aren’t science majors do a good job of guessing which kinds of scientific expertise are relevant to different scientific topics.
So far, so good. The trouble arises when our connections to other minds become a little too seamless, and we start to lose track of where our own understanding ends and another’s begins. When we receive an explanation from an expert—such as “fever because flu”—we might mistakenly conclude that we’ve learned more than we really have.
In fact, research finds that merely having access to expert answers can lead to illusions of understanding. In one set of studies, participants read about various fictional scientific discoveries and reported how well they understood the phenomenon described in each one. For instance, some participants received the following short passage:
A May 19, 2014, study in the journal Geology reported the discovery of a new rock that scientists have thoroughly explained. The rock is similar to calcite, yet it glows in the absence of a light source. The authors of the study, Rittenour, Clark, and Xu, fully understand how it works; they provided a description of the remarkable appearance of the mineral and outlined future experiments.
The passage didn’t actually include any explanations about why the rock glows. And yet, after reading the passage, participants thought they had some comprehension: what the authors call “a contagious sense of understanding,” because they seem to have caught it from the scientists described in the passage. When participants instead read that scientists “have not yet explained” the glowing rock, and that they “do not yet understand” how it works, there was no contagious sense of understanding; participant ratings of their own understanding nearly hit the bottom of the scale.
More recent work has shown that a contagious sense of understanding can even infect our interactions with technology. In one study, participants learned about a bank’s “robo-adviser,” which could provide investment recommendations. Participants also learned that an explanation of how the robo-adviser works had been published in a scientific journal. But half were told that the explanation was available to them on the journal’s website, and half were told that the journal had a subscription paywall. Those who thought the explanation was available to them reported a better understanding of how the robo-adviser works. They also reported a greater likelihood of using the robo-adviser themselves.
These results raise a pressing question. As information becomes more accessible through AI assistants, chatbots, and other technology, will these illusions of understanding become even more pronounced? Some early evidence suggests that the answer is yes. Several studies have now found that when people have information available to them through the internet, they overestimate how much they themselves know.
For example, in one study, participants were asked to explain how something works, such as a zipper, and half were given access to the internet to “confirm the details of the explanation.” All participants were then asked how well they could offer detailed answers to unrelated questions, such as why cloudy nights are warm. Those who had access to the internet in the first part of the study rated themselves significantly more capable of explaining in the second part—suggesting that the experience of having more knowledge at their fingertips supported the illusion that the knowledge was in their own heads.
Interactions with fast and informative chatbots will only heighten such illusions, but with a worrisome twist: The evidence so far suggests that humans aren’t great at tracking who knows what when it comes to large language models such as ChatGPT and Claude. For instance, when people in a study learned about an LLM that could correctly answer a question about economics, they expected it to correctly solve a basic algebra problem—but they were wrong. And when they learned that an LLM could answer a question about moral philosophy, they thought it could identify which character in a scenario had done something immoral—but they were wrong again. Participants almost certainly applied assumptions about how knowledge clusters in human minds to the AI system, and in both cases, this led them astray.
The kinds of errors that AI systems make are likely to change as AI develops, and human intuition about AI will probably evolve alongside these changes. As we expand our community of explainers beyond human experts to chatbots and other forms of AI, we create new opportunities for human understanding. But we also introduce an increased potential for illusion and error.
Earlier this year, one of my fishing partners sent a 1 a.m. message to our group chat. It was a link to an Instagram post of an angler holding a sizable striped bass. Dappled gold and silver with a dozen distinct black lines that stretched from gills to tail, it would have been a gorgeous fish if not for two problems: Striped bass usually have seven stripes, not 12, and men usually have five fingers, not six. The photo, it seemed, was AI-generated. To say we were dismayed would be an understatement.
From May to November each year, I spend most of my nights doing an extreme version of surf fishing for striped bass called “wetsuiting,” which involves wading or swimming out to distant ocean rocks and sandbars after dark. This kind of surf casting is a niche activity, and like many niche activities, the community for it is small. Wetsuiters can be found in a smattering of localfishing clubs throughout the Northeast—the typical range of the striped bass—but are primarily connected through Instagram, where some people, mostly for bragging rights, post images of fish they’ve caught.
In our group chat, my fishing partners and I spend too much time scrutinizing photos of bass that other anglers have posted. People who fish are habitual liars (I say this fondly), and most of our conversations take the form of debates about whether a fish is really as big as someone claims. Lately, though, we’ve been asking a different question: Is that fish even real?
In recent months, the small corner of Fishing Instagram devoted to surf casting has been plagued by a slow drip of AI-generated or AI-enhanced fish. Sometimes, the fraud is egregious—one of my friends, a fishing photographer, discovered that another angler had stolen one of his photos and crudely replaced my friend’s face with her own. More often, the distortions are subtle. Typically, a fish or fisherman looks ever so slightly off, usually in ways that a casual observer might not notice: A bass’s fins aren’t quite right, or the lure in its mouth looks oddly distorted, or the angler’s arms are a bit too long. In my favorite example, a man lifts a large striped bass just as he is getting pummeled by a wave. The scene looks daunting—until you realize that the ocean behind him is peaceful. Where did this rogue wave come from? One suspects that the enterprising angler, wanting to look more hard-core to his Instagram followers, prompted a bot to dial up the intensity. ChatGPT, make me look badass.
Fishing magazines report growing concern about AI-generated fish in freelance photo submissions. I have written occasionally for the small online magazine Surfcaster’s Journal. Over the summer, the Journal announced that it would now run all manuscripts and photographs through AI-detection software. “For some reason, I naively assumed that fishermen wouldn’t stoop to the ‘core of the earth’ lows required to use AI to prop oneself up as a fisherman worthy of clicking the follow icon,” Dave Anderson, a well-respected wetsuiter and an editor at The Fisherman, wrote in an article lamenting the scourge of artificially generated fish on social media. “I was very wrong about this.”
Angling, even extreme angling, is just a hobby, but although the stakes may be low, the anger about artificial fish is real. Partly, I think this is because of the work that being even remotely good at the sport demands. Striped bass move and feed in locally specific patterns that can take months or years to crack. There is a risk of drowning, and the mounting reports of bull sharks, tiger sharks, and great whites in the Northeast call attention to another layer of danger: We smell like fish, swim in dark water, and look like clumsy seals in our black neoprene. Wetsuiting does not change the world, but it is an activity that is hard and honest and, in that way, human.
Even taking a picture of a fish is demanding, requiring salt-water-proof cameras and often wading or swimming a bass back to shallow water, where it can safely be photographed and then released. The Photoshopping of fish pictures—and of the natural world in general—has been an issue for years, but AI, with its ability to conjure a simulacrum of reality out of nothing at all, is another matter. It automates away the need not only to photograph a fish, but to even catch one in the first place.
The problem extends to other sports and hobbies, many of which are now defined by what Stuart Franklin—who took one of the celebrated “Tank Man” photos at Tiananmen Square—calls the “documentary impulse.” Social media has turbo-charged that impulse into an imperative. A good local skateboarder’s or surfer’s reputation would once have been built through word of mouth. Today, posted photographs and short-form videos may constitute the primary proof of ability. Concerns about AI slop are already being raised in cycling, skiing, and other activities. ClimbingMagazine recently called out an AI-saturated YouTube channel purporting to chronicle climbing disasters that in fact never happened.
As AI-generated fish have appeared more frequently in my social-media feed, I’ve been reminded of a scene in the bird-watching documentaryListers, where a highly competitive birder is asked whether he would keep bird-watching if the photo-logging website eBird disappeared. His answer—“No”—was unsettling, not least because one suspects that this sentiment is widespread in hobbies besides birding. I have often wondered if, for some of the wetsuiters who populate surf-casting Instagram, the dopamine hit from the likes and fire emoji is sweeter than the hit from catching the fish itself. Now that posted images are being looked upon with an ever greater degree of suspicion, I also wonder how much longer the dopamine hits will come for them at all.
This is hardly the greatest challenge posed to humanity by the advent of AI. But hobbies, particularly those that require some measure of skill and endurance, have an influence that extends beyond those who directly participate in them. Free Solo, the Oscar-winning 2018 documentary about the death-defying rock climber Alex Honnold, found a wide audience outside the narrow world of climbing because people are invested in seeing other people do difficult things. I love videos of big-wave surfing even though I never plan to climb onto a surfboard. If AI makes it impossible to trust what we see, even something as simple as a surfing video, then we have lost more than the integrity of any one sport. We have lost the ability to believe in the accomplishments of others.
This article appears in the November 2026 print edition with the headline “The Fish Are Getting Bigger.”
For many people, using AI chatbots is incredible at first. It makes them feel productive, confident, maybe even smarter. But later, there’s a hangover. Perhaps there are problems with their memory, or certain skills, like writing or coding, don’t seem to be as sharp as they once were. Maybe they feel like they can’t solve problems or make decisions or remember facts as well as they could before they had the help of AI.
Susette Brooks, a marketing director living in Philadelphia, said she started using AI tools reluctantly but ultimately relented. She let AI write some of her emails, which lightened her workload, but then the dulling effects sank in. “I felt my writing and thinking decline as it was happening,” said Brooks, who has an MFA in nonfiction writing. “I had a harder time recalling information and synthesizing ideas.”
When you use external tools to reduce the cognitive effort required to do a task, you’re doing something called cognitive offloading. If you’ve ever used a calculator to do a math problem or used a calendar to remember an appointment, you’ve engaged in cognitive offloading. Tools like Claude and ChatGPT can do math problems and remember your appointments, but they can also write your term papers or create your work presentations. This is cognitive offloading at a scale we’ve never seen before.
Cognitive offloading isn’t necessarily bad. It’s actually what makes it possible for humans to be so productive. But as you outsource more and more cognitive tasks, you can start to become forgetful or see certain skills, like writing, start to decline.
There’s a term for this: de-skilling. This is an old economics term that has emerged as a bit of a buzzword used to describe the perceived downward spiral of competency that’s accompanied the proliferation of AI tools. And it certainly sounds bad, especially if you’re a novice who needs to build skills. De-skilling can affect your critical thinking, your writing abilities, and your creative process. It can also affect your recall, as relying too heavily on AI tools can make it harder to remember things.
Key takeaways
AI can make you more productive while quietly making you less capable on your own.
Offloading more tedious or mind-numbing tasks is less likely to make you feel dumber.
The long-term solution isn’t necessarily less AI. It’s being more intentional about the tasks you use AI for.
Young people, at least, are worried about the long-term consequences of frictionless thinking. A recent survey by Gallup and researchers from the University of Pennsylvania found that 68 percent of Gen Z adults in the United States are concerned that offloading too many cognitive tasks is robbing them of important skill-building. About the same percentage of those surveyed worry that AI discourages them from critical thinking and social learning. Some 37 percent of US adults under 30 say that AI will have a negative effect on them personally, according to a Pew Research Center study published in June. And yet, more than half of Gen Z Americans use AI on a weekly basis.
The paradox of AI is that, even if we feel like using these tools is bad for us, saving time and avoiding the friction of thinking is too tempting. We’re hardwired to seek out the path of least resistance, according to Daniel Willingham, a psychology professor at the University of Virginia, because cognitive activity is so taxing, and may or may not get you to the right solution. Memory, on the other hand, is efficient and effective — you know that something worked in the past, and it will work again.
“Our mind is really set up to save you from having to think,” Willingham told me. “Thinking is what you do when you’re in trouble.”
The good news is that experts say it’s possible to use AI in a way that helps you save time and protects your cognitive abilities instead of diminishing them. Here’s their advice.
It’s not your imagination — too much AI use can erode your skills over time
Derek Salyers, a content creator in Ohio, started using AI to get more done, faster. But over time, two things happened. First, the work got worse. “A lot of what I was putting out became AI slop, for lack of a better term,” Salyers told me. And then, his brain got worse, too.
“When you get used to the AI making the decision, you stop pausing to actually think about things,” Salyers said. “And if you were never really present with it, you don’t remember it later. I wasn’t forgetting things because my memory got worse; I was forgetting because I was never really thinking in the first place.”
This effect is showing up in classrooms, too. One study of nearly 1,000 high school students found that those using ChatGPT scored 48 percent higher on a math test than their peers who didn’t have access to the AI tool. But when they were tested again without the chatbot, their scores were 17 percent lower than the students in the control group who had never had ChatGPT access. Similarly, researchers at the University of California Irvine looked at longitudinal data from online tests starting in 2015, and found that students spent less time and performed better on the text-based questions after the introduction of ChatGPT. (ChatGPT is very good at helping with text-based questions.) But when those students were later given offline tests, without the ability to use AI help, they performed worse.
All of these students, it appears, were offloading the cognitive work to AI, which provided short-term gains. But in the long term, their thinking skills suffered.
Your basic cognitive abilities, like your working memory and selective attention, are quite resilient.
Evan Risko is a psychology professor at the University of Waterloo in Canada who co-authored the foundational paper on cognitive offloading a decade ago. He recently told me there’s not a lot of research into what’s going on in our brains when we’re cognitive offloading, but scientists are gaining a pretty clear picture of the pros and cons of doing it. The advantages vary depending on the task, but in general, cognitive offloading allows us to extend our imperfect memory systems, which you’ve probably done if you’ve ever set a reminder for yourself. The downside, Risko said, comes in offloading mental processes that are important. “Then we risk compromising our cognitive performance,” he said.
Your basic cognitive abilities, like your working memory and selective attention, are quite resilient. But as Risko and his colleagues explained in a paper this year — bluntly titled “Is AI making us stupid?” — other skills, like doing arithmetic and flying planes, are learned behaviors. You first have to acquire them and then, in order to retain them, you have to practice. AI use can compromise both the acquisition and retention of these skills — and people might not even realize this is happening to them, because AI makes them believe they’re more capable than they really are.
“People may have difficulty realizing that their skills are decaying or that they are failing to learn when using AI tools because the output and their performance with AI is at a high level,” said Brooke Macnamara, a psychology professor at Purdue University who co-authored the “Is AI making us stupid?” paper. “They may not realize that if the AI tool were unavailable how low their independent performance might be.”
Be intentional about the tasks you use AI for
The most important step to preserving your cognitive performance is to ask yourself if you should be using AI for a given task at all.
“Just because AI is a tool that’s available to us and it can accomplish a lot of tasks for us, it doesn’t mean that we should always use it,” Anjali Singh, a human-AI interaction researcher at the University of Texas at Austin, told me. Writing, for example, is something that a lot of people are now using AI for. But offloading that work means that you lose out on the independent thinking and reasoning that goes into expressing your thoughts. You also miss the chance to improve your writing skills if you don’t actually write.
“We keep outsourcing these kinds of skills to AI over time and do not engage in those activities ourselves, then the de-skilling occurs,” Singh told me. “And that is I think probably one of the main reasons people could be feeling that they’re getting dumber as they’re using AI over time.”
“We are not getting these moments to reflect.”
Anjali Singh, Univeristy of Texas
It might seem counterintuitive, but it’s actually best to use AI for things you’re already pretty good at, the tasks you’re fully capable of performing yourself. A recent working paper by MIT economist David Autor and his colleagues (note: Several of them work for Google, who funded the study) describes how giving AI tools to 133 patent lawyers and then taking away those tools led to different outcomes, depending on the lawyers’ level of experience. All lawyers saw performance gains while using the AI tools, but those gains disappeared for the younger lawyers when the tools went away. Experienced lawyers, however, performed better afterward than their counterparts who never had access to AI tools.
A similar effect showed up in a recent experiment by Middlebury College researchers. In the first session, more than 200 undergraduates learned about an unfamiliar topic and then wrote an analytical essay, some with the help of an off-the-shelf AI tool. They performed a similar test a week later, except this time none of the students had access to AI. The students who had AI access improved across the board, but what’s telling is that there appeared to be two types of AI users: augmentation users, who used AI to improve their work, and automation users, who just had AI do the work for them. The augmentation group performed better than everyone.
“Using AI to deepen or develop one’s own thinking on or understanding of a topic, rather than letting AI do all of the thinking, seems like the best way to use these tools,” Lauren Richmond, a cognitive science professor at Stony Brook University in New York, told me.
Tell your chatbot to treat you like a student
If you, like me, have ever fallen down a rabbit hole while trying to understand the geopolitical nuances that led to the outbreak of World War I and ended up staring blankly at a mountain of text feeling more confused than when you started, you know that using AI to learn doesn’t always go as planned. You may have also had the experience of writing prompts or asking questions and then receiving a long, overly detailed response. That can initially seem satisfying, but it’s often too much text to digest at once, so maybe you ask another question — and get back another wall of text.
Older ways of accessing information, like reading books or even using Google to do research, happened more slowly, and that gave us time to process the information, Singh from UT Austin said. But that’s gone now. “We are not getting these moments to reflect,” she said.
If you find yourself drowning in content, that’s also a sign that you’re probably not expert enough in the material, or you’re not being intentional enough about your approach.
It starts in the settings. Here, you should explain that you’re trying to build skills, not offload them, and instruct the AI to challenge you and engage with you. If you’re using ChatGPT, you can plug in custom instructions by going into the personalization tools. Claude has similar options called Instructions for Claude.
If you’re explicitly trying to learn something new, you might also try some of the tools these companies have designed for this. OpenAI has study mode in ChatGPT. Anthropic offers Claude for Education. Google has Gemini for Students. Instead of simply providing answers, these tools act more like tutors, by asking questions, working through problems, and encouraging you to come up with solutions on your own.
Slow down and embrace friction
Something that’s both tempting and dangerous about AI is how fast it can do work. Vibe coding an app can take minutes, rather than days of manual coding. That’s very appealing if you have too much on your plate and want to get through it all quickly.
“The workload was so heavy and crazy, you have no time to think,” Joei Chen, a former brand director at a tech company, told me. “So you just throw stuff into AI and say, ‘What do you think?’”
At the same time, creating more code does not necessarily lead to more finished software, according to a recent Wharton School study. That increased productivity also doesn’t necessarily lead to happier workers. And the faster you move, the more critical thinking you’re going to offload. “Your boss asks you, ‘What does Claude think of this?’” Chen said, so AI “inadvertently becomes the final boss.”
Slowing down and forcing yourself to do more critical thinking is an easy way to hold onto some agency — not to mention some brain power. One easy way to do this is to make your interactions with AI more collaborative than transactional. For example, if you are going to use AI to help you write something, ask for five options of a draft instead of one, and then read each of them yourself and decide which is the best.
“Ask for feedback, hints, examples, explanations, advice, practice questions.”
Evan Risko, University of Waterloo
“Just the simple act of comparing things stimulates a great deal of the critical thinking processes that we kind of care about,” said Advait Sarkar, an AI researcher at the University of Cambridge, “and has beneficial effects for things like developing your judgment, your own awareness of what you don’t already know, and stimulating your recall.”
The word that came up again and again as I talked to experts about how to use AI without getting dumber was metacognition, or thinking about thinking. A lot of AI users let metacognition take a back seat to whatever content is flowing freely from a chatbot. And it can happen fast.
While letting AI do all of the thinking for you is tempting, Matt Beane, an associate professor at the University of California Santa Barbara and author of The Skill Code: How to Save Human Ability in an Age of Intelligent Machines, told me that approaching AI this way “is your worst enemy.” To counteract this, you have to introduce more friction.
“You must be very aggressive about how you experiment with it,” Beane said. Risko, the cognitive offloading expert, echoed this advice. “Ask for feedback, hints, examples, explanations, advice, practice questions,” he said.
The best test for judging whether you’re offloading too much thinking to AI and the technology is chipping away at your skillset: Stop using AI and use your brain, and see what happens. You don’t have to stop forever, but you should, for example, spend a day writing emails without AI’s help to see if you’re as fluent as you used to be. Or revert to using Google for research and confirm that you can still find facts without a chatbot finding them for you. Build an app with your own code and see if it flows naturally.
You might be troubled to find that AI made you worse at something. But you’re not actually dumber than you were before, and you can rebuild your lost skills the old-fashioned way: read, write, do arithmetic. If something requires thinking, go ahead and think.
New York Gov. Kathy Hochul and New York Attorney General Letitia James at a news conference in New York City on October 2, 2026. | Michael Nagle/Bloomberg via Getty Images
In October 2024, students at Cornell University received a campus crime alert about a reported sexual assault. At the time, it was just a campus story. Nearly two years later, on September 16, the victim, known only as “Jane Doe,” filed a civil lawsuit that brought national attention to her story. People across the country are asking what happened and why criminal charges never followed.
Doe alleges that seven men drugged and sexually assaulted her at the Chi Phi fraternity house two years ago. Her lawsuit also accuses the university, fraternity and sorority organizations, and a local bar of failing to protect her.
The lawyers for several of the men have denied the allegations and any wrongdoing. Cornell says its disciplinary actions led to suspensions and expulsions for some of the young men, and that the Chi Phi fraternity remains barred from campus.
Doe went to campus police in November 2024, and the district attorney’s office reviewed her account and declined to bring charges. Tompkins County District Attorney Matthew Van Houten has said that what she described to Cornell police didn’t meet the state’s requirements for criminal charges.
To break down why Van Houten didn’t pursue the case at the time and what should have happened instead, Today, Explained co-host Noel King spoke with Lauren Hersh, a former Brooklyn prosecutor who led the office’s sex trafficking unit and CEO of World Without Exploitation, about how authorities handled Jane Doe’s allegations, the limits of New York’s consent laws, and what needs to change.
Hersh also explains where she believes the case should go next and what a special prosecutor can do to investigate (the interview took place prior to James’s appointment).
Below is an excerpt of Hersh’s conversation with Noel edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.
I want to start with what we know in 2024. A young woman who we know as “Jane Doe” goes to the Cornell campus police and says she had gone to a frat house while under the influence of alcohol.
At the frat house, she was given more alcohol and ketamine. Several men had sex with her while she was intoxicated. This is what she tells Cornell campus police. What, in your view, is supposed to happen next?
There are a number of things that could happen. What I would say about these cases is there is no perfect scenario of what is supposed to happen, because what is critically important is we listen to the desire of the survivor.
We want to take this at her pace. We want to be guided by her wishes. We want her to decide if she is ready to go forward, if she wants to speak to campus police, the Title IX office, if she wants to speak to the local law enforcement. There are a lot of variables here, but for me, what is critically important is that we’re listening to the survivor and what she ultimately wants to happen.
In the present day, the district attorney who was involved has said that his office reviewed Jane Doe’s statement at the time and found at the time that what she described didn’t meet the legal definition of a crime.
I think people want to understand, Lauren, how is that possible?
To be really candid with you, Noel, this is an area that seems super unclear to me because the role of the district attorney in that moment is to investigate.
When you first get a case file, you first get a victim statement, and especially with facts as horrific as these facts are, or our understanding of this six-page document that the DA read — I would never say that this is a clear-cut case where there’ll be a conviction at the end. We never know that.
What I can say with 100 percent certainty is if you get a document like that, as a prosecutor, that is a significant investigative lead. And so, as a prosecutor, what I believe to be good practice is starting to pull the layers back, trying to understand what transpired here. Interviewing the victim. That feels critical. That never happened. We now know that there are all these text messages that were shared between these boys, and the prosecutor’s now saying, “I didn’t know about the text messages.”
It’s my understanding that there were a lot of boys on that particular text thread. And so a good investigator would have gone to that fraternity house and tried to interview some of those boys, tried to understand what were the contemporaneous statements made at that time. Were there any text messages? Was there any social media activity? And I believe that had they done that in a timely fashion, they likely would have come up with these text messages at that time and not two years later.
What you’re saying is interesting because the DA has come out publicly and defended himself by saying, essentially, the details of this lawsuit, which was filed in September of this year, are different from the details in the young woman’s 2024 statement to the police.
He has used that in his defense, right? “Here’s what I knew at the time versus what this young woman is saying today.” I think I hear you saying that maybe that’s not an excuse?
You’re asking about the inconsistent statements, and I find it troubling that the DA is leading with this notion that the victim has inconsistent statements because that feels to me like here we are making excuses and blaming the victim.
To my knowledge, the DA has not yet interviewed this victim. Perhaps he’s talking about the civil complaint, which I would think is written in a way where she has worked with her lawyer to put this together. And the initial statement, the initial six-page document that the DA read, my understanding is that it is basically a summary of a conversation.
Inconsistencies come in all shapes and sizes, so it’s hard to know exactly what we’re talking about here, but it is very common for there to be some inconsistencies. That is not a dealbreaker, despite the fact that this prosecutor wants the public to believe that it is.
What do you make of the prosecutor speaking publicly in the way that he is at this moment?
I find it rather confusing. I’m not really understanding why he is doing a media tour rather than sitting in his office doing the work, interviewing this particular victim, interviewing witnesses, seeing what evidence actually exists.
It seems to me that the DA has gotten to a conclusion before he’s done the work in actually investigating the case, and it is deeply troubling. And I think the governor should consider appointing a special prosecutor because I am not certain, based on this media tour, that this DA is able to give this particular survivor a full and fair investigation of the facts.
Drugs and alcohol are central to this case, right? The young woman admits she had been drinking and she was using ketamine. Under New York law, how does that affect whether or not someone is believed to be capable of consenting to sex?
New York law is actually really problematic here. It’s a place where I believe we are desperate for a legislative fix. I think that there have been a lot of advocates who’ve been championing a correction to this voluntary intoxication loophole for a lot of years, and we’ve not been able to get it.
New York law makes it very, very hard to prosecute a person when the victim is voluntarily intoxicated, but not unconscious, and this new law would allow the prosecutors the ability to bring cases when the victim is so severely intoxicated but not physically helpless and where a reasonable person should have known the victim’s condition.
In this particular case, based on what we’re hearing, she was in a condition where a reasonable person should have known her condition. And so in this particular instance, the DA is right. This is a very, very hard case to prove in this moment, but I’m a big believer. We don’t not prosecute cases because they’re hard cases. But at the same time, we know that a change to the law is critically important.
You clearly want more investigation here. What questions do you want asked? Who do you want to be [interviewed]?
Before I say who and how and what that investigation looks like, I think it’s really important to say that when two years have passed and the DA did not investigate these cases immediately, we have a big problem on our hands.
The fact that the DA did not investigate this from the moment he found out about this, it’s really problematic because as we know, evidence disappears, memories fade. When you’re dealing on a college campus with a specific culture, there may be a narrative that takes hold. And so it’s important to talk about the time lapse and how that harms the case.
That said, I still believe that the investigation is critically important. I don’t believe that this DA is the right person to do the investigation. I think a special prosecutor should be appointed. And then I think that the prosecutor and law enforcement should be interviewing everybody who was in that fraternity on that night. Anybody who saw this victim before, saw this victim after. Were there any statements in the immediate aftermath of her leaving that fraternity? Was there an outcry witness? We know that some text messages have come to light. Are there other text messages? I suspect that there are.
I’d want to interview as many of those boys as possible to understand what was going on because some of those text messages that have come to light — one says, “Free pussy” — don’t sound like a mindset that is engaging in consensual sex.
I think it is critically important that we understand all of the correspondence of that night. I think we want to see what is out there that helps us get closer to understanding what transpired that night.
I’ve seen two lines of thinking about this. One is that this is a horrific incident that never should have happened, but it is in some ways singular. But I’ve seen another line of thinking that says, “No, this is a systemic failure. This kind of thing goes on on college campuses, and the steps that follow the outcomes are often the same.”
I wonder if you think this is a systemic failure, and if you think it is, what would need to be done to fix this problem?
That’s a big question. I do think it’s a systemic failure. I also think it’s a cultural failure. And the reason that I would say this is because I don’t think this is isolated to this specific college campus. I think that sexual assault is happening across the country on college campuses everywhere.
In terms of additional systemic failures, I’ve been working with the Epstein survivors for the last year and a half, so I’ve seen so many systemic failures, so many prosecutorial failures, so much failure with law enforcement. I think that this is yet another example of prosecutorial failure.
I think the law enforcement failed this young person — the fact that there’s no investigation that happened immediately in the aftermath of this incident, no investigation. We just continue to fail survivors all over the place, and we have to start doing better.
We created a list of the most notable AI agents that can live in your text messages, from general assistants to agents designed for families, travel, and work.
Is American Culture Simply Bad Now? I’ve been hanging with my friend Matt while he’s here in Tokyo for a trip, which he refers to as his “America is Cooked Tour” as he keeps running across things that are much better here.
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