Illustration: Sarah Grillo/Axios. Stock: Getty Images
The AI boom is pushing companies across the economy — from tech giants to automakers — deep into the energy business, Axios national energy correspondent Amy Harder writes.
Why it matters: The scramble for electricity has become the gold rush beneath the AI boom, creating enormous value and enormous risk if demand falls short.
Electricity — long treated as a cheap, abundant commodity — is suddenly emerging as one of the most valuable strategic assets in business.
“Everyone to some extent is either dependent on energy as a core input or they see energy as a huge opportunity,” said Brian Janous, who was Microsoft’s first energy hire 15 years ago and is now co-founder of data center developer Cloverleaf Infrastructure.
The latest: Ford this month began its expansion into energy storage for data centers and other large power users.
It launched a new subsidiary called Ford Energy in response to what it calls “the massive demand for domestic energy storage.
“Follow the money: Investors are rewarding companies pivoting to — or doubling down on — the power behind the AI boom:
Ford’s stock price rose to its highest level in three years after it announced its $2 billion energy business.
Bloom Energy, long seen as a niche energy player whose tech can deliver on-site power fast, saw its stock price skyrocket more than 1,200% over the past year.
Fervo Energy, a geothermal startup once viewed as speculative climate tech, surged after going public earlier this month as Wall Street hunts for new electricity sources to feed data centers.
GE Vernovabooked $2.4 billion in electrical equipment ordersfor data centers in the first quarter alone, more than it booked all of last year. Its stock is up about 60% this year.
Reality check: Beneath the surging stock prices, trouble is mounting. Opposition to data centers is intensifying, and some of the biggest projects may never come to fruition.”A lot of people are going to lose a lot of money in this space,” Janous said — not because of a lack of demand, but because so many mega projects are chasing that demand.
The bottom line: For decades, energy was an input. In the AI era, it’s becoming the product.Share this story.
The MSC Gülsün is one of the largest container ships ever built. It can carry 23,756 containers at once. Line them up end to end and they'd stretch 145 kilometers.
Early in 2020, a cell phone captured the fatal attack of a jogger named Ahmaud Arbery by three white men in Georgia. That video was critical evidence in the criminal cases against the assailants, who were convicted of murder, and helped fuel a nationwide wave of Black Lives Matter protests that year.
Just six years later, the landscape for recorded media looks slightly different, as artificial intelligence tools have become ubiquitous, and AI-generated text, audio, and video have flooded the internet. Can we still believe the things we see, hear, and read? And how could our newfound doubt affect our ability to seek justice under the law?
Duncan Levin is a white-collar defense attorney and former federal prosecutor with the U.S. Department of Justice, and lecturer on law who in the winter term taught Cash, Crime, and the Constitution: The Legal Frontiers of Asset Forfeiture and Money Laundering at Harvard Law School. He argues that as AI-generated media blurs reality, the technology has the potential to “destabilize” some aspects of the criminal system.
“I think AI may change not only what people think about evidence, but what they think evidence is,” says Levin.
Levin argues that as people become more skeptical of long-accepted types of evidence, prosecutors, defense attorneys, and judges will have to radically rethink their approach. But while he believes that this adjustment might be painful in the short-term, over the long haul, it could “force the system to become more sophisticated.”
In an interview with Harvard Law Today, Levin shared his views on how artificial intelligence could impact the criminal trial — and why, all told, AI could serve as a “healthy pressure, even if it is an uncomfortable one.”
HLT: In your experience as a prosecutor and defense attorney, what unique problems might AI pose in criminal cases as opposed to civil litigation?
Levin: Most of the conversation about AI in law has centered on civil practice, and understandably so. Civil litigation is where questions of efficiency, cost, scale, and automation are most visible. And of course, the courts have been dealing with the problem of lawyers citing to “hallucinated” cases. But criminal law presents a different problem altogether because criminal trials are not just about resolving disputes efficiently. They are about the state’s attempt to take liberty from an individual, and they are structured around a constitutional burden of proof designed to minimize the risk of factual error.
That is why AI poses a more profound challenge in criminal cases than in civil ones. In a civil case, if the authenticity of a document or recording is disputed, that may affect weight, credibility, or liability. In a criminal case, the same uncertainty can operate at a deeper level, because the government is required to prove guilt beyond a reasonable doubt. The possibility that an exhibit may be synthetic, manipulated, or otherwise unreliable is not just another evidentiary skirmish. It can go directly to whether the prosecution has met the burden that due process demands.
There is also a structural difference in the function of evidence. Criminal cases often depend on a relatively narrow set of key exhibits — a recording, a video, a sequence of text messages, a social media post, a geolocation trail. Those exhibits are often presented to juries not as peripheral details but as anchors of narrative truth. AI threatens to destabilize that. It introduces the possibility that what appears to be the most concrete evidence in the case may in fact be the least secure.
And that challenge cuts in both directions. As a former prosecutor, I can see how AI may make it harder for the government to secure convictions in cases that rely heavily on digital proof. As a defense lawyer, I can also see the danger that once skepticism becomes generalized, defendants may have a harder time persuading juries with authentic exculpatory evidence. So, the issue is not simply that AI helps one side or the other. It puts pressure on the truth-finding function of the criminal trial itself.
HLT: What kinds of evidence currently admissible in criminal trials might be at risk of being created or manipulated by AI?
Levin: The obvious answer is audio and video, because those are the forms of evidence people most readily associate with deepfakes. If a jury hears what sounds like the defendant’s voice, or sees what appears to be a defendant on video, that evidence can be enormously powerful. But the real problem is broader than the familiar deepfake example.
Modern criminal prosecutions rely heavily on digital artifacts of all kinds: photographs, surveillance footage, text messages, emails, direct messages, social media posts, screenshots, online account records, and digitally generated timelines of location or activity. Each of those forms of evidence carries with it an implied claim of authenticity. It says, in effect, this happened, this was said, this account was used, this image reflects reality. AI makes those implied claims easier to counterfeit and harder for laypeople to assess.
What concerns me especially is that the danger is not limited to wholesale fabrication. AI may also be used to alter, enhance, splice, recontextualize, or simulate evidence in subtler ways. A manipulated image need not be entirely fabricated to mislead. A voice recording need not be entirely synthetic to create a false impression. A sequence of messages can be selectively generated or altered in ways that preserve surface plausibility while changing substantive meaning. In other words, the challenge is not just false evidence; it is persuasive false evidence.
There is also what I think of as the atmospheric effect of AI. Even where the evidence is genuine, jurors may know enough about digital manipulation to wonder whether it is not. So, AI changes not only the risk profile of false exhibits entering the courtroom. It changes the epistemic status of real exhibits as well. Evidence that once seemed solid may now seem contingent. That is a profound development in a system that has long relied on jurors’ common-sense confidence in what they can see and hear.
“The danger is not limited to wholesale fabrication. AI may also be used to alter, enhance, splice, recontextualize, or simulate evidence in subtler ways. … the challenge is not just false evidence; it is persuasive false evidence.”
HLT: What are the traditional methods of authentication and reliability for evidence in a criminal case, and how does AI challenge those longstanding doctrines?
Levin: Traditionally, authentication has been understood as a threshold requirement, not an ultimate one. Under the rules of evidence, the proponent need only offer sufficient evidence for a reasonable juror to conclude that an exhibit is what it is claimed to be. That burden has never been especially onerous. A witness with knowledge may identify a photograph. Someone familiar with a speaker’s voice may identify an audio recording. A chain of custody may support the admission of physical or digital evidence. Distinctive characteristics, surrounding circumstances, and metadata may all contribute to the foundation.
That framework reflects an important doctrinal assumption: Authentication is a gatekeeping inquiry, and the adversarial process can do the rest. Courts have long assumed that the principal risks involve ordinary tampering, misidentification, or incomplete handling. Those are serious issues, of course, but they are still issues within a world where the underlying exhibit is presumptively tethered to some real event or communication.
AI complicates that premise because it attacks the distinction between authenticity and plausibility. A piece of evidence may now look authentic, sound authentic, and fit coherently into surrounding facts, while still being entirely or materially synthetic. That matters because many of the doctrines we use to authenticate evidence are not really designed to test whether the artifact itself was born of reality. They are designed to test whether there is enough circumstantial basis for a jury to consider it.
HLT: Could you give us an example?
Levin: Take voice identification. The classic question is: Do you recognize the speaker’s voice? A witness may answer that question honestly and persuasively. But that only establishes familiarity with the voiceprint; it does not resolve whether the recording is a genuine capture of an actual conversation rather than an artificial simulation. The doctrine assumes that voice recognition is doing more work than it may in fact be capable of doing in an age of generative audio.
The same is true more broadly. Distinctive characteristics may no longer be very distinctive. Metadata may be vulnerable to manipulation or may require expert interpretation. Chain of custody remains important, but chain of custody alone may not answer whether a digital artifact was altered before it entered the chain. So, the legal system may increasingly find that doctrines built to address tampering are inadequate for a world of synthetic creation.
That is why I think this is a doctrinal problem, not just a technological one. AI exposes that the law of authentication rests on assumptions about the nature of evidence that may no longer hold.
“Many of the doctrines we use to authenticate evidence are not really designed to test whether the artifact itself was born of reality.”
HLT: Most of us have heard of the requirement that a jury find a defendant guilty “beyond a reasonable doubt.” What does that mean? Could the possibility of fabricated digital evidence affect the meaning of proof beyond a reasonable doubt?
Levin: “Beyond a reasonable doubt” is the law’s way of expressing a moral and constitutional judgment that when the state seeks to deprive someone of liberty, ordinary confidence is not enough. The standard does not require certainty in an absolute sense, and it does not mean beyond all possible doubt. But it does reflect a deliberate choice to tolerate some risk that guilty people will go free in order to reduce the risk that innocent people will be wrongly convicted.
That principle assumes, however, that jurors are evaluating evidence in a world where the central questions are credibility, consistency, perception, memory, and corroboration. In other words, the standard developed in a setting where doubt typically attaches to witnesses or interpretations of facts. AI introduces a different layer of doubt. It raises the possibility that the exhibit itself — the recording, the image, the post, the message — may not be what anyone says it is.
That distinction matters. A juror may conclude that a witness is sincere and still have reasonable doubt because the underlying exhibit seems potentially synthetic. So, AI may affect the operation of the reasonable-doubt standard not by changing its formal definition, but by changing the kinds of uncertainty that jurors bring to their deliberations. The question becomes not just “Do I believe this witness?” but “Do I believe the ontology of this evidence at all?” That is a more foundational inquiry.
In that sense, AI may sharpen the reasonable-doubt standard by making visible something that was once implicit: proof is not simply about persuasion, but about epistemic confidence in the reality of the proof itself. If jurors begin to feel that digital evidence carries an irreducible possibility of artificiality, that may alter the practical meaning of the government’s burden even without any doctrinal change in the jury instructions.
The larger point is that reasonable doubt is not just a verbal formula. It is a mechanism for allocating the risk of uncertainty in criminal adjudication. AI may dramatically increase one category of uncertainty — uncertainty about authenticity — and if that happens, the burden of proof will feel heavier in practice, because jurors will be less willing to treat digital exhibits as fixed points of reference. That is why AI has the potential to reshape not merely evidence law, but the lived meaning of the constitutional standard itself.
HLT: What new burdens, if any, should be placed on parties to verify that evidence is not AI-manipulated? Who should bear that burden?
Levin: In criminal cases, the answer has to begin with first principles. The government bears the burden of proof. It is the government that seeks conviction. So, if digital evidence is central to the prosecution’s case, the prosecution should bear the primary burden of establishing authenticity with greater rigor than courts have often demanded in the past.
I do not mean that every case should require a parade of experts or a mini-trial on digital forensics. The law has to remain workable. But I do think courts will need to move away from the instinct that a thin foundation is always enough, and that any deeper concerns go only to weight. In some cases, especially those turning on audio, video, or disputed digital communications, authenticity may require more than witness familiarity or a simple chain of custody. It may require forensic examination, clearer provenance, stronger metadata analysis, or expert testimony sufficient to assure the court that the exhibit has not been materially altered or synthetically generated.
“AI introduces a different layer of doubt. It raises the possibility that the exhibit itself — the recording, the image, the post, the message — may not be what anyone says it is.”
At the same time, I would not frame this only as a burden on prosecutors. If a defendant seeks to introduce affirmative digital evidence, courts may also require a stronger showing of authenticity. But the asymmetry still matters. A defendant does not carry the burden of proving innocence. So, while both sides may need to satisfy more robust evidentiary standards, the constitutional burden should remain where it belongs: on the state when it seeks to imprison.
Over time, I suspect the law will move toward a combination of doctrinal and technological solutions. On the doctrinal side, courts may become more exacting under existing authentication rules. On the technological side, provenance tools, cryptographic signatures, or secure capture systems may emerge as more reliable ways of showing authenticity at the point of creation. But until those systems are more widespread, judges will have to decide whether traditional foundations remain adequate in a world where fabrication is easier, cheaper, and harder to detect.
So, the real burden is not just evidentiary. It is institutional. Courts will need to decide how much uncertainty the criminal process can tolerate before the risk of error becomes unacceptable.
HLT: In your view, how might AI influence the way people think about evidence and the criminal justice system in general?
Levin: I think AI may change not only what people think about evidence, but what they think evidence is. For a long time, visual and digital evidence carried an aura of objectivity. People might dispute what a witness remembered or why a witness was lying, but a video, a recording, or a contemporaneous text exchange often felt like a harder kind of proof. That intuition was always somewhat overstated, but it was real and legally important. AI weakens it.
Once the public internalizes that highly realistic digital evidence can be fabricated, the entire evidentiary environment changes. People may become more skeptical, more cautious, and in some settings more cynical. That skepticism has some virtue. Criminal law should not be built on naïve faith in official narratives or in the infallibility of seemingly objective evidence. But skepticism can also become corrosive if it dissolves confidence indiscriminately.
That is the larger institutional concern. The justice system depends on public confidence not only that trials are fair, but that they are capable of reaching truth through lawful procedures. If jurors begin from the premise that any recording may be fake, any image may be manufactured, and any digital communication may be spoofed, then the criminal trial risks becoming less an exercise in fact-finding than an exercise in generalized epistemic anxiety. That is not healthy for either side.
At the same time, this moment may force the system to become more sophisticated. Judges, lawyers, jurors, and investigators may all need to become more literate about the creation, preservation, and forensic evaluation of digital evidence. Courts may have to speak more candidly about what they do and do not know. In that sense, AI may force a deeper legal honesty. It may make explicit that evidentiary trust has always rested on a combination of doctrine, technology, and social confidence.
So, I think the long-term influence of AI will be double-edged. It may deepen mistrust in the short term, but it may also push the criminal legal system toward a more rigorous and transparent account of what it means to prove something. And in a system built around the idea that liberty should not be taken without very high confidence, that is ultimately a healthy pressure, even if it is an uncomfortable one.
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Nvidia CEO Jensen Huang. Photo: Patrick T. Fallon/AFP via Getty Images
The company best known for powering the AI boom is coming for the PC: Next week, Nvidia is expected to debut the first Windows computers that use its chips as the main processor, sources confirm to Axios’ Ina Fried.
Why it matters: Microsoft’s first AI PC push stumbled. But Nvidia’s arrival gives it a second chance, this time with the world’s hottest chipmaker attached.
Nvidia and Microsoft will unveil their joint work and the first computers running the chips at two key industry conferences — the Computex trade show in Taiwan and Microsoft’s Build developer conference in San Francisco.
Nvidia-powered PCs are expected from both Microsoft’s homegrown Surface brand and other computer makers, including Dell, sources confirmed.
Microsoft is also expected to debut software that makes it easier for people to have AI agents do work locally on their Windows computer.Share this story.
In the new phase of the war, the enemy, through economic pressure and media campaigns, seeks to create division and destroy the country's cohesion in order to compensate for its military defeat and force us to surrender.
Kevin Warsh has some levers to pull—but there’s little he can do about runaway government spending.Al Drago—Bloomberg/Getty Images
In the days before the Memorial Day weekend, rates on 30 year Treasury bonds hit their highest level in 19 years at 5.2%, and the benchmark 10-year reached 4.7%, the top reading since mid-2007. If those kinds of yields take hold, the scenario for federal interest expense posited in the CBO’s “Budget and Economic Outlook: 2026 to 2036,” released in February, descends from dire to near-disastrous. Takeaway: America’s track to fiscal safety has lost all margin for error, and nothing demonstrates that better than the long-term impact of loftier than expected rates. America’s got so little room to maneuver that even yields that modestly exceed the CBO’s “baseline,” as the numbers compound in the years ahead, deliver a huge extra blow by crowding out big chunks of revenue that would otherwise go towards funding such essentials as Defense, Social Security and Medicare.
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The CBO forecasts that yields on the 30 and 10-year Treasuries will respectively average about 4.65% and 4.15% through FY 2036. That’s roughly 55 basis points lower than the multi-year summit briefly notched in late May. Doesn’t sound like much of a difference, right? And if the interest expense on our gigantic and ballooning national debt of $39 trillion weren’t already running at nearly $1 trillion a year, bigger than Medicare spending and equaling two-thirds of Social Security outlays, the half-point upward shift would likely prove manageable.
But a recent report from the non-partisan Committee for a Responsible Federal Budget quantifies the deep damage even a continuation at the recent peaks would inflict. By 2036, interest expense would jump from absorbing 14% of all revenues to devouring 30%, five points more than under the CBO’s forecast. At $2.5 trillion, 2.5x today’s number, the carrying costs would become the second largest budget category, beating Medicare by one-third. Interest cost per household would soar from $7,900 last year to $17,000 a decade hence.
Much of today’s extreme vulnerability to even slightly higher rates arises from the need to both refinance existing debt, and shoulder trillions more in newly-issued bonds to cover deficits, at much higher cost. All told, the federal government will need to borrow almost $10 trillion in the next 12 months, equivalent to one-third our total debt. That amount consists of around $7.5 trillion to repay the Treasuries coming due, and $2 trillion for plugging the shortfall between revenues and spending. A major reason the U.S. accumulated so much debt in the first place was the lure of ultra-bargain yields orchestrated by the Fed’s easy money policy during and following the COVID crisis. In 2021 through early 2022, Treasury Bills, instruments that mature within a year, offered around a minuscule 0.2%. Today, that cost’s 18 times fatter at 3.7%.
Rates have also climbed for the Treasury Notes running 5 to 30 years that account for over half of all federal debt outstanding. Because we could borrow so cheaply for so long, the average rate on the Notes stands at just 3.23%. But the U.S. is refinancing the bonds that roll off for a lot more, 5.2% on the 30 year as of just before Memorial Day, and 4.7% on the 10-year.
In fact, the borrowing blowout that got the U.S. in so much trouble resembles the rush into “teaser” home loans in the 2007 runup to the housing meltdown; folks fell for temporary, super-low “teasers” rates that when they reset higher, saddled the borrowers with monthly payments they couldn’t afford. A similar dynamic’s at play as the U.S. refinances low-yielding Treasuries issued when it looked like a deal to finance huge government spending—at today’s much higher rates.
As of May 26, news that the Iran War may end soon pushed yields for the 30 and 10 year down slightly, so that they’re now sitting around 35 basis points above the CBO forecast. Still, the threat they’ll bounce back to the half-point-plus margin that’s so scary raises a stern warning for the new Fed chief Kevin Warsh. It’s encouraging that Warsh publicly favors tightening monetary policy by lowering the immense holdings of Treasuries on Fed’s balance sheet, a policy that involves unloading a big portion of its portfolio to the public. That gambit transforms trillions that would otherwise be spent into savings.
The Fed balance sheet shrink would also shrink what’s causing the problem: Extremely high “aggregate demand” across the economy that sends too many dollars chasing a volume of goods that’s growing far more slowly. (Noted economist Will Luther described this phenomenon in my recent story.) Warsh can also raise the Fed Funds rate, or even announce he has no plans for a reduction, to cool the still relatively-plentiful credit that’s fueling big spending by consumers and of course, humongous outlays for AI data centers. But the primary reason aggregate demand’s way too high is excessive levels of government spending that if left unchecked, could lead to even higher rates than the peak numbers that just unleashed such a jolt. Warsh can help by lifting the cost of credit to throttle both consumer and corporate spending, and sell bonds the Fed’s holding to target the latter. But he can’t control the big one, the runaway federal budget.
That responsibility falls on the President and on Congress. As the CRFB states in their analysis on the impact of rising yields, “The best way to accomplish these goals is through deficit reduction, which can help the Federal Reserve lower rates by reducing near-term inflationary pressures, put downward pressure on long-term rates by reducing economic crowd-out [that diverts money needed for budget must-pays to interest], and reduce the debt burden on which the government must pay interest.” The CRFB adds that yields that hang in the pre-Memorial Day range or push higher threaten to “spark a fiscal crisis.”
Nothing better illustrates that AMERICA IS BROKE than how an increase in yields that wouldn’t seem to matter much in most times could spell a cataclysm now that our fiscal state’s so fragile. Neither party wants to talk about how broke we really are, or do much to address the problem. Unfortunately, it may take an outbreak of unaffordable interest rates to force our lawmakers into facing the peril of their own making.
Sir Niall Ferguson in recent communications has referenced this Scottish law
The “Ferguson Limit”: This is the tipping point where interest payments exceed defense spending, leading to reduced resources for national security. [1]
He survived the Titanic and braved the Somme. But perhaps his greatest achievement was photographing peasants and priests across a long lost Ireland with a sympathetic yet unflinching eye. Meet Father Francis Browne SJ. Jesuit, war hero, and accidental documentarian of a vanishing world.
He was born in 1880 in Cork into a life privilege but tragedy. His ma died days after his birth, and his da drowned when he was just nine. Frank was raised by his uncle, the Bishop of Cloyne, who gave him two things that shaped his life. A Jesuit education and a box camera. He studied alongside James Joyce (who immortalised him in Finnegans Wake) and snapped his first great photo in 1897 on a Grand Tour of Europe. Years later, Pope Pius X let him take his portrait.
In 1912, Browne was given a first-class ticket for the Titanic’s maiden voyage, the lesser notorious trip from Southampton to Queenstown. He photographed its gymnasium, wireless room, dining saloon, and fellow passengers. The fateful vessels officers, abundant millionaires and children playing on the doomed decks. A wealthy American couple offered to pay his fare on to New York. This was an oppurtunity of a lifetime for the budding photographer, but he had to ask his Jesuit superior via cable for persmission. The stern reply left no room for further debate. “GET OFF THAT SHIP!” The cable said, Browne obeyed. Two days later, Titanic sank.
His photos instantly became world-famous. Eastman Kodak even gave him free film for life. Then came the Great War. As a chaplain with the Irish Guards in WWI, he witnessed the horror of the Somme, Ypres, and Passchendaele. Gassed, wounded five times and decorated with the Military Cross and Bar, his courage in the trenches matched his quiet obsession with taking snaps. His war album “Watch on the Rhine,” is still studied for its stark humanity.
After the war, he returned to Ireland and never stopped shooting. From Dublin slums to Kerry farms and Belfast shipyards, Browne recorded over 42,000 photographs. He cycled from parish to parish on mission work, always with camera in tow. Children stared back from barefoot streets. Coal darkened workers strained under the weight of tools. Nuns scrubbed floors in silent convents. Aeroplanes thundered into Shannon Airport as his last rolls clicked into place. He meticulously archived everything, but they were to him simply a private collection and so were essentially unknown to the world.
He died in 1960 and was buried in Glasnevin. It wouldn’t be until 1985, when a rusting trunk was discovered in the Jesuit archives. Inside were thousands of perfectly preserved negatives, a priceless treasure of Irish culture. The Sunday Times called it “the photographic equivalent of the Dead Sea Scrolls.” Browne’s images are now digitised, restored, and published in dozens of volumes.
Texas state Rep. and Democratic nominee James Talarico. Photo: Danielle Villasana/Getty Images
The Texas Senate race has become a national laboratory for anti-“woke” politics, testing whether voters still recoil from the language of 2020 amid the economic pain of 2026, Axios’ Zachary Basu writes.
Why it matters: Republicans came away from 2024 convinced they had won more than an election — they had broken through on culture, turning Democrats’ progressive language and identity politics into symbols of elite detachment.
The durability of that culture-war coup is now an open question, as the GOP tries to redeploy the same playbook in a far more hostile midterm environment.
Zoom in: Texas has produced a Senate race in which both parties see the other nominee as the perfect caricature of everything voters hate about the opposition.Left: Talarico (DNC via X). Right: Texas Attorney General Ken Paxton at a campaign stop May 15 in Little Elm, Texas. Photo: Ron Jenkins/Getty Images
For Republicans: Texas state Rep. James Talarico offers the dream target — a young, viral progressive whose old comments can be stripped of context and turned into a one-man museum of “woke” Democratic excess.
Republicans have seized on Talarico’s 2021 floor speech declaring that “God is nonbinary,” along with past comments on racism, whiteness and trans children, to cast him as a radical disguised as a Texas preacher.
The attacks already are veering into sexuality- and masculinity-coded territory: Talarico’s opponent, Texas Attorney General Ken Paxton, has mocked him as “Low-T,” while White House adviser Stephen Miller falsely labeled him as Democrats’ “first transgender Senate candidate.
“Talarico has conceded that he “missed the mark” on some “cringey comments,” while insisting his underlying principles — that “racism is immoral and wrong” and that “trans people deserve dignity and equality” — flow from his Christian faith.
For Democrats: Paxton is a scandal-scarred Trump ally whose legal and ethical baggage could turn even a red-state Senate race into a referendum on Republican corruption.
Paxton was impeached by the GOP-led Texas House in 2023 — then acquitted by the Texas Senate — over allegations that he abused his office to benefit a donor.
He spent nearly a decade under indictment on fraud charges before reaching a pretrial deal in 2024. He has been plagued by whistleblower claims, a now-closed federal corruption probe and a very public divorce tied to allegations of adultery.
Talarico’s campaign wants to make Paxton the face of Republican impunity — arguing that his scandals aren’t distractions from the race, but the clearest evidence of what the GOP has become.
The bottom line: Texas will be the ultimate test of whether the GOP’s anti-“woke” strategy can survive the transition from insurgency to incumbency.Share this story.
Relying on reactive willpower to resist constant digital notifications exhausts finite attentional reserves, whereas utilizing proactive control and self-hypnosis preserves cognitive bandwidth to optimize deep flow states. Credit: Neuroscience News
Summary: A comprehensive neurobiological assessment mapped the structural, age-related, and environmental forces driving the modern crisis of human attention. The research details how smartphones and communication platforms intentionally exploit the brain’s evolutionary dopamine-reward pathways, substituting effortful, long-term focus with zero-effort wins.
By dismantling the myth of raw willpower, Stanford experts demonstrate that cognitive sustainability requires structural lifestyle intervention, specifically shifting from reactive resistance to “proactive control,” integrating physiological “bio” breaks, and utilizing self-hypnosis to systematically lock the brain into highly focused “flow” states.
Key Facts
The Dopamine Exploitation Loop: The human brain is evolutionarily wired to scan its environment for quick rewards, a survival mechanism that modern technology actively hijacks. Pings from emails, texts, and social media feeds provide immediate dopamine hits. Once the brain becomes accustomed to these low-effort wins, it struggles to muster the massive metabolic energy required for deep, long-term concentrated thinking.
The Vulnerability of Developing Minds: Attention capacity is not static; it scales dramatically during development. Research tracking response variability shows that attention function improves continuously in children from ages 9 to 18. However, children require strictly protected, distraction-free time—spent reading books, solving mathematics, or playing chess—to build this neural capacity. Conditioning developing brains to zero-effort social media rewards actively cripples their long-term ability to think deeply.
The Reality of Working Memory Decay: In older adults, general memory capacity should not experience a drastic decline simply due to age. “Working memory”, the short-term biological scratchpad used to hold temporary data without writing it down, does experience minor, typical age-related drops, such as slipping from remembering a seven-digit phone number to a six-digit code. Progressive, compounding losses beyond this baseline warrant a formal neurological evaluation.
The Failure of Raw Willpower: Relying purely on grit to block out digital static is a mathematically losing strategy. Every act of resisting temptation actively drains a finite cognitive reservoir. Because modern environments demand constant resistance, willpower reserves are rapidly depleted, leaving the mind exhausted.
Bypassing Temptation via Proactive Control: Instead of training the mind to resist a distraction, Stanford neuroscientists advocate for “proactive control”, the physical removal of the temptation altogether. Simple behavioral shifts, such as moving a smartphone to a different room while working or using application-blocking hardware, drastically lower cognitive friction, returning attentional sovereignty back to the user.
The Physical Mandate for Brain Breaks: Cognitive processing speeds decline without planned downtime. Sleep serves as the ultimate neurological recovery period, necessary to consolidate daily memories and restore the next day’s attentional bandwidth. During waking hours, clinicians recommend taking a 10-minute break for every hour of work. This can be effortlessly forced by consistently drinking water throughout the day, ensuring the body naturally demands movement, stretching, and physical “bio” breaks.
Self-Hypnosis as a Gateway to Flow: Far removed from theatrical tropes, clinical self-hypnosis is a validated method to direct highly focused, immersive attention toward a complex task. By combining somatic visualization with physical relaxation techniques, individuals can enter “flow” states that tune out competitive or environmental background noise. Stanford psychiatrists utilize this protocol to optimize elite athletic performance and enhance deep academic study.
Source: Stanford
News alerts ping your phone. Your watch buzzes, reminding you to stand up. Slack notifications sound on your desktop. And that’s all before you open your email inbox.
The world is constantly vying for our attention and, at least evolutionarily, we’re primed for distraction. But it’s still possible to block out the noise, hone your focus, and concentrate on what’s most important.
“We’re bombarded with information, some of which we want and a lot of which we don’t,” said David Spiegel, MD, the Jack, Lulu, and Sam Willson Professor in Medicine and associate chair of psychiatry and behavioral sciences. “In a world that is painfully distracting most of the time, it’s particularly important to hone your skills to focus on what matters.”
We asked Spiegel and other Stanford Medicine experts why it feels harder than ever to focus – and how we can improve our own ability to concentrate. Here are five key takeaways.
1. It’s not just you – it really is that hard to focus and concentrate
The human brain is wired to detect rewards and, increasingly, our smartphones are wired to dole them out, said Weidong Cai, PhD, a clinical associate professor of psychiatry and behavioral sciences. Our brains get a boost – in the form of a dopamine hit – when our smartphones ping us with a new message, for instance.
“We find it rewarding to read new emails, Slacks, a friend’s post, even when they’re not relevant to the task at hand,” Cai said. “Every time you see something fresh, you feel a reward.”
Once the brain becomes accustomed to those easy wins, Cai said, it’s more difficult to perform the effortful, long-term thinking that demands focus and concentration. “You need to put a lot more energy into the actual hard work,” he said.
2. Our attention and memory capabilities change with age
Cai studies response variability – that is, the different lengths of time during which people respond to the same stimuli. Research shows that response variability continually drops in children from ages 9 to age 18, suggesting that attention function improves as children get older.
But, Cai said, children need protected time to develop their attention capacity through activities like reading a book, solving math problems, or playing chess. “If they get used to zero-effort rewards from things like social media,” he said, “they might have difficulty developing the capacity to think longer and deeper.”
For older adults, memory capacity shouldn’t drastically diminish with age, said Sharon Sha, MD, a clinical professor of neurology and neurological sciences and chief for the Memory Disorders Division and the Stanford Center for Memory Disorders.
“Working memory” is the information we can hold in our minds without writing it down. As we get older, it’s typical for working memory to decline slightly – as in, we can’t remember a seven-digit phone number, but can still recall a six-digit passcode, Sha said. If your working memory is consistently getting worse than that over time, she said, talk to your doctor.
3. Willpower alone won’t strengthen your focus
It’s tempting to rely on willpower to keep the relentless distractions at bay. But, Cai said, it’s not that easy. Each exertion of your willpower depletes your attention capacity a bit more. That’s because it takes effort to resist the temptation of distractions – and in today’s world, we have to resist constantly. Eventually our willpower stores get used up.
A better approach is proactive control, Cai said, or keeping the distractions away altogether. “You want to protect time for writing or studying, so you move the smartphone to a different room,” he said. “Instead of training yourself to resist the temptation, it’s better to move the temptation away.”
Proactive control is the idea behind tools like Brick, a device that blocks distracting apps like news websites and social media from your smartphone. “You get to decide what you pay attention to,” Spiegel said, “not what people on the news or apps tell you.”
4. Be sure to build in breaks
Though it might seem counterintuitive, Sha said, taking breaks can be a boon for focus and concentration. “As much as we keep pumping the caffeine” to push through, she said, “our brains do need a break.”
Sleep is the ultimate brain break, Sha said, and studies show that quality sleep leads to better cognitive performance. “Your brain needs that time, not only to consolidate the memories from the day, but also so you can have concentration for the next day,” she said. “It’s going to really diminish your attention if you’re not sleeping.”
Daytime breaks are also crucial, Sha said. She recommended a 10-minute break each hour. “I can’t say I follow that all the time,” Sha admitted. “If it’s not feasible, try to at least block out time for one or two breaks in the morning.”
One way to ensure you take breaks is to drink water throughout the day so your body will demand “bio” breaks, Sha said. A trip to the bathroom, combined with a stretch and some fresh air, can work wonders.
5. Self-hypnosis could lead to “flow” states
Want an out-of-the-box way to hone your focus? Try hypnosis.
Unlike the stylized hypnotizing we’ve seen in the movies, self-hypnosis is a way to direct highly focused attention to a specific task, said Spiegel, who is also director of the Center on Stress and Health, and medical director of the Center for Integrative Medicine. Think of it as using the techniques of meditation, like physical sensations and visualization, to put yourself into a “flow” state of immersion during a challenging and rewarding task.
“Hypnosis is about going into this altered state for a purpose: to study better, to control pain,” Spiegel said. “You gain control by choosing what to attend to.”
When the Stanford women’s swim team was swimming faster in practices than in meets, the coach came to Spiegel for help. He discovered that, during meets, the swimmers were focusing too much on their opponents in neighboring lanes. Spiegel trained the team to practice self-hypnosis before meets by picturing how they controlled their bodies as they swim their best race in their minds, ignoring those in the next lanes – and the women swam faster.
Spiegel is co-founder and scientific adviser of Reveri Health Inc., a hypnosis app company. But he said anyone can practice the tenets of hypnosis on their own. Imagine yourself floating (the floating is essential because it makes you feel physically supported and comfortable, and therefore physically relaxed but mentally more focused). In your mind’s eye, picture a task or problem on the left side and a possible solution on the right. Float and focus, he said.
“Focus is a skill, an advantage that we humans have that allows us to determine where and how we deploy our attention,” he said. “It’s an opportunity to prove to ourselves how much control we have over our bodies and our minds.”
Key Questions Answered:
Q: Why does it feel physically and mentally harder to concentrate on deep tasks today than it did years ago?
A: Because your brain’s natural reward system is being systematically outmaneuvered by modern technology. Human biology is hardwired to seek out easy wins, and devices are engineered to constantly deliver them via dopamine-inducing pings, messages, and alerts. Once your brain gets used to receiving these zero-effort rewards every few minutes, it recalibrates its expectations, making the intense, energy-consuming hard work of long-term thinking feel incredibly difficult to sustain.
Q: If trying to force ourselves to focus through pure willpower doesn’t work, what actually does?
A: Shifting from reactive willpower to a strategy called “proactive control”. Willpower is a finite, drainable resource; every single time you force yourself to ignore a buzzing phone, you use up a piece of your daily attention budget. Instead of expending energy trying to resist temptation, the smarter neurological approach is to remove the temptation entirely, such as physically leaving your phone in a completely different room or using tech-blocking tools to curate your environment.
Q: How can a clinical tool like self-hypnosis be used practically to block out distraction and improve focus?
A: By using focused visualization to enter a state of deep, immersive immersion known as a “flow” state. True self-hypnosis is simply a skill that allows you to choose exactly where to deploy your attention while physically relaxing your body. By visualizing yourself floating to induce physical comfort, and picturing your creative challenge on one side of your mind and a solution on the other, you can completely tune out peripheral noise and regain complete control over your mind.
Editorial Notes:
This article was edited by a Neuroscience News editor.
Journal paper reviewed in full.
Additional context added by our staff.
About this neuroscience research news
Author: Christina Hernandez Sherwood Source: Stanford Contact: Christina Hernandez Sherwood – Stanford Image: The image is credited to Neuroscience News
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