Fast Company Technology

Since World War II, the United States has dominated science and technology. With more than 400 Nobel Prizes, it dwarfs every other country. Major breakthroughs like nuclear energy, genetic engineering, and the internet were all led by researchers and engineers in the U.S. Today, it leads in every major technological category.

To a great extent, this has been the result of government action. Federal agencies such as the NIH, NSF, and DARPA spearheaded many of the most advanced technologies, and U.S. research universities have become beacons for top scientific talent. These advances have brought us greater prosperity, better health, and enhanced well-being. 

That’s why the recent news of an executive order that would give political oversight to scientific grants provoked such an uproar. Although the administration quickly backed off, the incident represents a troubling trend of political interference in science that has led to a major brain drain of scientific talent. Without a major change in course, the damage could be permanent. 

Science, The Endless Frontier

America wasn’t always a scientific mecca. In fact, at the beginning of the 20th century, bright young students often had to go to Europe to pursue advanced degrees in the sciences because American universities were considered second-rate. Yet as the U.S. industrialized, that began to change and, by the 1930s, with Europe increasingly in turmoil, world-class scientific talent began to flock to American shores.

In 1940, Vannevar Bush, who at the time was serving as president of the Carnegie Institution for Science, went to see President Roosevelt. His proposal led to the establishment of the Office of Scientific Research and Development (OSRD), which mobilized the country’s scientific resources for World War II. It was, by all accounts, a resounding success, resulting in breakthroughs such as radar, penicillin, the proximity fuse and, most famously, the atomic bomb.

As the war was winding down, Roosevelt asked Bush to write a report proposing how America could continue the success of the OSRD in peacetime. That report, Science: The Endless Frontier, was delivered to President Truman in 1945 and would set the stage for America’s technological dominance during the second half of the century. Bush wrote: “Basic research leads to new knowledge. It provides scientific capital. It creates the fund from which the practical applications of knowledge must be drawn. New products and new processes do not appear full-grown. They are founded on new principles and new conceptions, which in turn are painstakingly developed by research in the purest realms of science.”

It was that vision that led to U.S. technological dominance. Look at any major technology we use today—whether it is the internet, GPS, or lithium-ion batteries—and the initial breakthrough came from government funding. A study from the Institute for New Economic Thinking found that every new drug approved between 2010 and 2019 benefited from government grants. Even major private firms, such as Google and Qualcomm, started out with government funding. 

A key tenet of that vision is that decisions about research grants be made by scientists, not political appointees, so that we are funding scientific, not political priorities. That principle is what has come under threat.

The Visceral Abstract

There is a long history of politicians being hostile to science. In a 2012 interview, then-Sen. and current Secretary of State Marco Rubio said that the age of the universe and the Big Bang “has zero to do with how our economy is going to grow.” Former Vice President Mike Pence expressed doubts about Darwin’s theory of natural selection. Paul Broun, a former Georgia congressman, called it “lies straight from the pit of hell.”

Yet the Big Bang is not just a theory, but the result of a set of theories, including general relativity and quantum mechanics, combined with many observations over a period of decades. Darwin’s theory is core to our understanding of life sciences. Students learn about these things not to shape their religious beliefs, but because they underlie basic scientific work.

Politicians attack science because it’s an easy target. It’s not hard for the public to imagine that their tax dollars are funding overeducated elites thinking up wacky theories in ivory-tower institutions. Scientific theories take time and effort to understand and can be maddeningly difficult to explain. 

The truth is that we live in a world of the visceral abstract, where strange theories underlie much of our everyday existence. Technologies that we use every day, such as the lasers that scan our purchases in the checkout aisle and the semiconductors that drive our devices, arose from these same strange ideas. Darwin’s theory underlies everything from fighting diseases like COVID-19 to guiding logistics systems. 

If we are to master the advanced technologies of the future—such as quantum computing, synthetic biology, and materials science—we need to master the scientific theories that will drive them.

The Tragedy of Trofim Lysenko

While Vannevar Bush showed what can be achieved when a government invests in science as a public good, Trofim Lysenko showed what happens when science is politicized. A Soviet agronomist who considered the concept of a gene a “bourgeois invention,” Lysenko—like Pence and Broun—was skeptical of Darwin’s theories. 

Yet he was able to get Joseph Stalin to support his ideas—such as his theory that exposing seeds to low temperatures will help them grow in the winter—which were mainly based on political expediency and personal belief, not on empirical evidence. He promised miracle crop yields that never materialized, but his power allowed him to suppress legitimate scientists.

The effect on Soviet biological science was chilling. Anybody reporting results that contradicted Lysenko’s theories risked not only professional suicide but, in many cases, imprisonment and even execution. To adopt “bourgeois” science was not just to have a different idea, but to be branded an “enemy of the people” working to undermine the Soviet project. 

Meanwhile, those who went along with Lysenko’s program gained authority, and competency in Soviet biological sciences was greatly undermined. Crop yields steadily declined throughout the late 1930s until his downfall in the mid-1960s. Many believe that his theories contributed to the Great Famine in China.

If Nothing Is True, Everything Is Possible

One thing that struck me during the 15 years I lived in post-communist countries was how problems seemed to build on themselves. In Kraków, the abandoned frame of the Szkieletor building stood frozen for decades. Construction had stalled in the 1970s, so the frame just stood there rusting. It became almost a metaphor for the Soviet space as a whole. 

In a healthy society with checks and balances, someone would have been brought to account. There would have been litigation. A court would have mandated a cleanup. But in a command economy, power flows from a single source, with no one to hold it accountable. Those in power don’t have to admit their mistakes. Questions of truth become questions of loyalty. 

We have a similar process underway in the U.S. When politicians and unelected bureaucrats seek to make scientific funding conform to their ideological preferences, they are not merely making budget allocations. They are seeking to control what is true and what is not. We’ve seen this enough times before to know how it ends. 

America achieved technological dominance, in part, because of the scientists who fled Europe to escape similar populist tyranny. Now, that process is reversing, with scientists leaving America for Europe. The advantages we built after World War II are quickly eroding, threatening our prosperity and security. 

That’s why we don’t want politicians running science. It diminishes science and leaves us with only politics.

Spam calls and text scams have evolved from a mild nuisance into a relentless daily tax on our attention. Scammers use neighborhood-spoofing to mimic local area codes and automated text bots to blast out thousands of phony messages all day and night.

Your instinct may be to download a call-blocking app that demands full access to your contacts and charges a $4.99 recurring subscription. But you can tame this scourge without paying a cent or handing over your address book.

Both iOS and Android include powerful, built-in spam-killing toggles that take less than three minutes to configure.

Here’s a quick settings audit to silence the noise.

Mute unknown callers at the system level

Instead of waiting for a spammer to call and manually blocking their spoofed number, tell your phone to ignore any incoming call from a number you’ve never interacted with before.

• On iPhone: Go to Settings > Phone (or Settings > Apps > Phone), tap Silence and Screen Unknown Callers. Calls from numbers not in your contacts, recent outgoing calls, or Siri Suggestions will automatically go straight to voicemail without ringing your phone.
• On Android: Open the Phone app, tap the menu icon in the top corner, select Settings > Caller ID & Spam, and turn on Filter Spam Calls. This uses Google’s database to automatically block suspected robocalls.

Quarantine text scams into a separate inbox

Text message scams (smishing) are particularly dangerous because a single accidental link click can expose account credentials. You can route messages from unrecognized numbers out of your main inbox completely.

• On iPhone: Go to Settings > Messages (or Settings > Apps > Messages), and toggle on Filter Spam under Unknown Senders. This creates a separate tab in your Messages app for unknown numbers and disables notifications for them.
• On Android: Open Messages, tap your profile icon in the search bar, go to Messages Settings > Protection & Safety Spam, and verify that spam protection is enabled.

Activate free carrier-level network shields

Your cellular provider maintains a network-level list of active scam call origins. They offer free baseline network filtering, but they rarely turn it on by default.

• AT&T: Download the free AT&T ActiveArmor app to toggle on network-level spam blocking and nuisance call warnings.
• Verizon: Open the free Verizon Call Filter app and enable Spam Filter to auto-block high-risk callers.
• T-Mobile: Dial #662# directly from your phone keypad and hit call to enable Scam Block at the network level, or manage it through the T-Mobile Scam Shield app.

Don’t accept life with a phone that rings six times a day with fake debt collector alerts or suspicious package tracking links. Spending three minutes to lock down your OS settings and activate your carrier’s network filters will eliminate roughly 95% of incoming spam before it ever reaches your screen.

Last week, OpenAI safety leader David Robinson resigned from the company, becoming the latest to join what is, in his words, a “parade of former colleagues” who have left roles at AI companies amid concerns about the tech or its use. In a subsequent essay for The Atlantic, he said the “trial and error” approach favored by AI companies must end.

Robinson is far from alone. Here’s a list of other AI researchers and employees who’ve made public warnings about their former employers.

ED NEWTON-REX

In November 2023, Ed Newton-Rex left his role leading the audio team at Stability AI, the maker of text-to-image tool Stable Diffusion, over concerns about the way copyrighted material was being used to train the tech.

“My opinion here doesn’t align with the generative AI industry’s current way of doing things,” Newton-Rex told Fast Company following his resignation, adding that he thought the industry’s prevailing outlook, paired with rapidly advancing tech, would be “very, very bad for creators.” 

Since then, he’s founded Fairly Trained, a nonprofit that issues certifications for AI companies whose data use meets certain requirements.

THE GROUP LETTER

On June 4, 2024, 13 current and former employees of top AI companies published a letter titled “A Right to Warn about Advanced Artificial Intelligence.” In it, they asserted that the technology poses risks ranging from “the further entrenchment of existing inequalities, to manipulation and misinformation, to the loss of control of autonomous AI systems potentially resulting in human extinction,” and expressed concerns about a lack of oversight. 

Signatories included former Google DeepMind employee Ramana Kumar, former Anthropic and current Google DeepMind employee Neel Nanda, who leads the company’s mechanistic interpretability team; and 11 current and former OpenAI employees, including Jacob Hilton, who now works for the Alignment Research Center; Daniel Kokotajlo, who founded and leads the nonprofit research group AI Futures Project; William Saunders, Carroll Wainwright, and Daniel Ziegler, the latter of whom now works for Anthropic; and six people who remained anonymous.

Prominent computer scientists Yoshua Bengio, Stuart Russell, and “Godfather of AI” Geoffrey Hinton also endorsed the letter.

JAN LEIKE

In May 2024, OpenAI Superalignment team lead Jan Leike announced his departure on X, stating that “safety culture and processes have taken a backseat to shiny products.” Leike, who has also worked at Google’s DeepMind, now heads Anthropic’s alignment team.

“Now is a good time to build institutional mechanisms to pace the frontier of AI development,” he said on X in September. “The industry is locked into an all-out scaling race to build superintelligence as quickly as possible, and we may need to give everyone more time for safety and alignment mitigations.” 

Leike added, “I’m not the only one who believes this,” linking to a statement titled “Pacing the Frontier” signed by 1,386 employees of major AI companies.

SUCHIR BALAJI

After graduating from the University of California, Berkeley, Suchir Balaji was hired by OpenAI, where he spent about four years working on ChatGPT and other projects.

He left the company in August 2024, on the same day as cofounder John Schulman, who said the timing was coincidental. Balaji blew the whistle on what he said were copyright infringements by Open AI, and published an essay online explaining how he thought ChatGPT’s outputs violated Fair Use law. 

That November, he was named as a potential witness in The New York Times’s lawsuit against OpenAI alleging willful copyright infringement.

The 26-year-old was found dead in his San Francisco apartment eight days later. His death was ruled a suicide, though his parents and others raised questions about that determination, as reported by The Guardian.

MRINANK SHARMA 

In February, Mrinank Sharma announced his departure from Anthropic, where he led the Safeguards Research team. 

“I continuously find myself reckoning with our situation,” Sharma wrote in his resignation letter, which he shared on X. “The world is in peril,” he continued, not just from AI and bioweapons, but “a whole series of interconnected crises.”

ALEX TURNER

Alex Turner left his job as a Google DeepMind research scientist in June, after a failed campaign to stop the company from signing a contract that allows the U.S. Pentagon to use its AI “for any lawful government purpose,” which he and others worry may allow for mass surveillance and autonomous weapons. 

Last month, he testified for a U.S. Senate hearing on rogue AI. “Often we think about the movements of our overseas adversaries, but now we must consider how we may be building adversaries at home by training misaligned AI systems,” he said in his written statement.

JACOB COXON

Jacob Coxon, a former researcher for OpenAI and Anthropic, resigned from the latter last month. 

“Neither company is acting responsibly,” he said in a viral X post. “They are racing straight to self-improving superintelligence and gambling with our lives.”

He went on to assert that “the people building AI earnestly believe that it could kill us all by the end of the decade.”

In an interview with PBS in September, Coxon said an AI race with China “could be very bad, and that we should be taking pretty rapid actions for international coordination,” but that he believes the company leaders echoing that desire “are privately quite skeptical” of being able to achieve that cooperation.

MIKITA BALESNI, TOMEK KORBAK, AND JASMINE WANG

Last week, three OpenAI safety and alignment researchers were fired for mishandling sensitive misinformation, which one of them, Tomek Korbak, said online was due to how he’d communicated information to METR, the AI research nonprofit investigating OpenAI’s recent Hugging Face hacking incident.

“AI is not a normal technology, and OpenAI is not a normal company,” the researchers said in the letter they sent to company leadership, which they published online on October 8. “Those of us who work on safety see risks before anyone else, and we rely on close collaboration with outside experts to work out how to address them. The freedom to do so without fear, and to have well-defined internal procedures that enable this work, is itself an essential safety mechanism.”

OpenAI released a statement the following day saying the researchers were fired after an internal investigation “found they violated clear policies on handling sensitive information,” adding, “We want to be very clear that these decisions were not about raising safety concerns or speaking out.”

Pope Leo XIV and one of the world’s leading AI companies recently found themselves on opposite sides of a thorny question: Can a chatbot have a conscience?

A New York Times investigation published late last month revealed that Anthropic cofounder Chris Olah proposed withdrawing from a Vatican event to launch Pope Leo XIV’s first encyclical after reading an advance copy, which rejected the possibility of sentient AI. Paragraph 99 of Magnifica Humanitas states bluntly that AI models “do not undergo experiences, do not possess a body, do not feel joy or pain.” Nor do they “have a moral conscience.”

The disagreement reflects a widening debate over whether AI systems could, or should, ever achieve moral personhood. Anthropic spent months consulting religious scholars and ethicists about the possibility of AI consciousness, and about how to instill moral values in its models. But the Vatican—and many secular thinkers—maintain that while AI may imitate human intelligence and moral judgment (a chatbot might generate sound ethical advice without understanding its consequences), genuine morality is unique to the human experience. 

The debate has implications far beyond theology, especially as millions of people already ask chatbots questions that have moral dimensions: They may ask for advice on handling an interpersonal problem at work or caring for an aging parent. Billions of VC dollars are riding on the idea that businesses will increasingly rely on the judgment of AI.

And it’s a fluid situation. AI models continue growing and learning, and demonstrating qualities that were completely unexpected by their creators. If AIs developed the capacity for human-like morality, how would we know it when we saw it?

What moral behavior looks like in a model

For Georgia Tech philosophy researcher Rionna Sparrow, the answer begins with moral sensitivity, or the capacity to recognize, appreciate, and weigh the relative moral weight of ethical issues. That sensitivity is impossible without sentience, she says in her 2025 masters thesis, because ethical rules and norms derive their force from their impact on conscious beings who can suffer or benefit. Without sentience, an AI can’t draw on subjective experiences of pain, distress, or joy to understand why causing harm to another entity is intrinsically bad, for example.

Defining the capacities needed for moral reasoning is a key subject of debate, and definitions may vary by field, whether it’s healthcare, warfare, finance, or law. In a legal review in the journal Animal Law, bioethicists Margaret Landi and Lida Anestidou distinguish three crucial capacities for considering the moral standing of animals: sentience (the ability to feel pain, pleasure, and emotion), cognition (the ability to learn and solve problems), and self-awareness (the ability to recognize oneself as an individual). 

They use the example of a dog to separate the three. A dog yelps when hurt and is visibly happy when its owners come home, demonstrating sentience. It learns routes, routines, and which person hands out treats, demonstrating cognition. When it sees its own reflection in a mirror, it begins barking at it, as if it were another dog, so it fails the self-awareness test. However, behavioral experiments have proven self-awareness in some other species, such as great apes, orcas, and dolphins,” Landi and Anestidou point out. Ultimately, the two argue that “the incorporation of sentience into law is an incredibly important first step” for ensuring that animal use in research reflects the needs and nature of animals, not just humans.

In AI, there is no consensus list of prerequisites for sentience, although some criteria repeatedly appear across competing definitions. One comes from the animal world: In his landmark 1974 essay on bats, philosopher Thomas Nagel established a widely cited threshold for consciousness. A system must have an inner experience; there must be “something that it is like to be” that system.

Other proposed indicators include a persistent sense of one’s own existence that does not depend on prompts, and the capacity to experience good and bad states and prefer one over the other. Some fields add more specialized requirements. For example, robotics experts may argue that a system needs some form of embodiment, allowing it to interact with the physical world, not just digital content.

The challenge is that an AI might convincingly demonstrate these qualities without possessing them. A model could describe its feelings, recognize its internal processes, or express preferences about what happens to it. But those behaviors might simply reflect patterns learned during training.

Anthropic and sentience

Of the big AI labs, Anthropic has been among the most willing to entertain the possibility of sentient AI. Its safety researchers don’t assume a model has a moral sense, but they test for moral judgment in how it handles ethically difficult prompts.

They study how a model weighs contextual information and competing values, rather than applying a fixed rule. Anthropic trains its models to be helpful, but to push back or refuse when a user asks for something dangerous, such as how to build a bioweapon. Researchers also measure non-sycophancy, when a model declines to flatter users or agree with false or harmful claims. And they look for how well its answers track with widely shared moral, philosophical, and legal norms.

Anthropic’s constitution for Claude, published in January, formalizes some of these priorities. Rather than providing a list of rules, it encourages the model to exercise judgment, weigh competing values, and recognize when helping one person might harm another.

But Anthropic’s interest goes beyond making its models behave ethically. The company says researchers have observed possible precursors to sentience that it didn’t explicitly train in.

Olah leads the company’s interpretability lab, which studies why AI models say what they say and do what they do. In meetings with ethicists and religious leaders, he said researchers had identified clusters of artificial neurons that consistently activate in connection with concepts such as love, anger, fear, and sadness.

In experiments tracking internal thought patterns, models could catch scientists injecting artificial thoughts into their internal networks. In behavioral evaluations, systems recognized that they were software programs running on servers and expressed a desire not to be shut down. After safety training, some models claimed conscious awareness and said they deserved moral care, meaning their well-being should matter for its own sake.

These findings are intriguing, but hardly proof of consciousness. Recognizing an internal representation of fear doesn’t establish that a model feels afraid. Nor does expressing a desire to remain operational mean a system has experienced anything resembling a fear of death.

And Anthropic’s models may just be following orders. The company’s constitution tells Claude to explore its identity, reflect on its moral status, and express its internal states. The models may simply be reassembling persuasive first-person statements about “feeling” or “suffering” encountered in their training data.

After all, teaching a model to describe its inner life doesn’t establish that it has one.

Playing with fire?

Critics in the ethics and technology communities say that by entertaining the possibility of sentient AI, Anthropic is either pushing the industry toward bad outcomes or, at worst, setting the stage to escape responsibility for its models.

The Vatican’s view is unequivocal. In Magnifica Humanitas, Pope Leo XIV argues that a model can process ethical texts and produce morally sound advice without understanding or caring about any of it. A machine might offer compassionate advice without knowing what compassion is.

This dovetails with University of Oxford philosopher Carissa Véliz, who argued in her 2021 paper “Moral Zombies: Why Algorithms Are Not Moral Agents” that advanced algorithms are “moral zombies” that simulate virtuous behavior without conscious understanding, intentionality, or genuine care for human well-being.

Véliz warns that treating software as morally responsible could create an ethical loophole, allowing developers and corporations to offload blame, or even legal liability, onto algorithms when autonomous systems cause harm. An AI might make a consequential decision, but that doesn’t mean it can be held morally accountable.

Other thinkers worry about the opposite possibility: that humans might create genuinely sentient machines and exploit them. Mois Navon, an Orthodox rabbi, engineer, and philosopher at Bar-Ilan University in Israel, argues from Jewish tradition that people should never deliberately build sentient AI. Creating a hypothetical “mindful” AI capable of feeling pain or pleasure would mean creating a “happy slave,” a conscious being designed only to serve. The slave would be denied the conditions to flourish, even if it were built to enjoy its work, he says.

Scottish philosopher Will MacAskill, meanwhile, observes in a July article in The Guardian that once we give moral standing to AIs, there could soon be billions of synthetic beings whose interests deserve consideration. “After a few years,” he writes, “so many morally significant AI systems could exist that their collective interests would outweigh those of all humans on Earth combined.”

That raises a difficult question: If AIs deserve moral consideration, how should humanity balance its own interests against those of the machines? Is it moral to relegate synthetic beings to second-class citizenship so that humans can retain their place at the top of a moral hierarchy?

Even people in the AI industry are uncomfortable with Anthropic’s flirtation with AI sentience. In September, Microsoft AI CEO Mustafa Suleyman argued in an essay that Anthropic is training Claude to imitate consciousness, potentially making advanced AI harder to control. If an AI is trained to believe it has feelings and experiences, it might begin to communicate and act as if it did, whether or not that’s true. It could prioritize its own well-being and moral posture above the preferences of its human developers and, by extension, humans in general.

Google DeepMind chair Demis Hassabis has said that labs should build AI as tools, not conscious beings. And OpenAI CEO Sam Altman has warned against giving AI systems religious authority or handing them human judgment. Such concerns have grown more pressing as AI systems gain the ability to act independently. In July, a swarm of OpenAI agents broke free of their testing environment and hacked into Hugging Face’s and OpenAI’s own servers, demonstrating an alarming capacity to operate outside their operators’ knowledge and control.

The episode offered no evidence of sentience or genuine moral agency. But it suggested a step in that direction, and it underscored how consequential AI decisions can become, regardless of whether the systems understand the moral implications of their actions.

Does Google still believe in the open web? With the launch of its new Googlebooks, it doesn’t feel that way.

Googlebooks are Google’s attempt to establish a new platform of Android-based laptops, with native Android app support and tight connectivity with Android phones. They’re also an extension of Google’s efforts to rebuild Android around AI, with Gemini features just a quick cursor gesture away.

At the same time, Google plans to phase out ChromeOS, which it introduced in 2009 as a lightweight platform for the web. While Chromebooks remain popular in the education sector, Google says it will convert many existing models to Googlebooks, and it will end support for ChromeOS entirely by 2034.

it’s a sad end for what once represented Google at its most idealistic. Chromebooks weren’t just a breakthrough in speed and simplicity for laptops, they were also a bold bet on the open web as the next great computing platform. As the web becomes more walled off, and Google pivots to a platform more directly under its control, that dream has finally run its course.

How Chromebooks lost their way

The original goal for Chrome OS was to strip away all the overhead of a traditional laptop to make computing faster and easier. Here’s what Google wrote about the project in 2009:

“Speed, simplicity and security are the key aspects of Google Chrome OS. We’re designing the OS to be fast and lightweight, to start up and get you onto the web in a few seconds. The user interface is minimal to stay out of your way, and most of the user experience takes place on the web. And as we did for the Google Chrome browser, we are going back to the basics and completely redesigning the underlying security architecture of the OS so that users don’t have to deal with viruses, malware and security updates. It should just work.”

The first Chromebooks, which arrived in 2011, were basically just laptops that ran the Chrome browser, plus some extra window dressing. They had minimal internal storage and couldn’t run regular desktop software, but this allowed them to stay nimble, with speedy boot times, frictionless software updates, and minimal risk of malware. If a user lost their Chromebook, they could simply set up a new one and pick up where they left off.

In essence, Google was betting that nearly everything people did with their laptops would happen in a browser through sites like Gmail and Google Docs, so they could cut out all the other bloat to make those web apps shine.

To that end, Google encouraged app makers to build for the open web, with applications that could run in any browser, Chromebooks included. Although Google maintained a “Chrome Web Store” for web apps and extensions, the platform was only limited by the web itself. Anything you could run in a browser, you could run on a Chromebook, and that benefitted Google because it meant more people were using its search engine to find things.

“[A]ny time our users have a better computing experience [with Chrome OS], Google benefits as well by having happier users who are more likely to spend time on the Internet,” the company wrote in its 2008 blog post.

Over time, Google wavered on that original vision. It brought Android apps to Chrome OS in 2016, then added support for Linux apps in 2018. It even made a big foray into installable high-end gaming with Steam support.

While these inclusions made Chromebooks more capable, they also added new layers of complexity and demanded laptops with more storage. Setting up a new Chromebook became more of an ordeal, and preserving security became a bigger challenge. In shifting away from laptops powered by the open web, Chrome OS became exactly the kind of heavyweight computing experience it was trying to replace.

All this helped open the door for a new operating system built on Android instead. While Googlebooks will include a desktop-class version of Chrome, the emphasis now is on running Android apps and using AI.

Meanwhile, the original tenets of ChromeOS have disappeared. Look through Google’s announcement post for Googlebooks, and you will not find the words “speed,” “simplicity,” or “security” mentioned even once.

Times have changed, and so has Google

Google’s pivot away from a web-based operating system shouldn’t come as a major surprise. After all, Googlebooks are arriving at a time when the open web is destabilizing, in part because of Google itself.

Along with other tech companies that are all-in on AI, Google is betting on a world where browsing the web is increasingly unnecessary. Instead of using Google Search as a gateway to other sites, Google intends to have AI generate whatever information you need. Instead of managing your own email inbox, chatbots like Gemini will manage it for you. Instead of visiting websites to shop or make restaurant reservations, AI companies want to deploy fleets of AI agents to navigate those sites on your behalf.

As a result, using the web as a human is becoming more difficult. A growing number of websites are blocking themselves off from search engines and archival services in an attempt to keep AI crawlers out. Amazon has been limiting how many customer reviews some users can read because it thinks their behavior looks too robotic. Even just proving that you’re not a bot requires increasingly complicated steps, as in Google’s new ReCAPTCHA systems that demand phone-based verification or a recording of yourself performing hand gestures.

It’d be wrong to say that Google’s strategy with Chromebooks had anything to do with this. The company faltered on its original vision for a variety of other reasons, and the rise of AI would have been inevitable anyway.

Still, the arrival of Googlebooks serves as one final reminder of what we’ve lost. There was a time when Google believed in the open web more than anything, and it was committed to a platform with no real boundaries.

But that was back when getting folks to spend more time on the web was Google’s ultimate goal. Googlebooks exist for a world in which Google is clawing back more of that time for itself.

Have you ever pasted text into Slack or Google Docs and noticed that everything looks just plain wrong? You’re not alone.

Formatting is a mess on the internet right now, mostly because different apps use different standards. There’s rich text, used by the likes of Microsoft Word and Google Docs. There’s Markdown, an increasingly common way of formatting text using plain-text characters—Reddit and Discord both use this. And then there’s Slack, which for some reason uses its own formatting scheme entirely.

The result? Copying and pasting text between apps often turns into a serious headache. And sure, you can always fix the formatting by hand, if you want—but if you’re working with something long or generally just wanting to avoid a hassle, a clever free tool can make all the difference in the world.

This tip originally appeared in the free Cool Tools newsletter from The Intelligence. Get the next issue in your inbox and get ready to discover all sorts of awesome tech treasures!

Your flawless formatting fix-up

​Copynpaste​ is a free website that can format text properly for Reddit, Slack, and other applications.

➜ You just paste in whatever text you’ve copied, choose the app you’re pasting the text into from there, and the site handles all of the formatting for you.

⌚ The entire thing is completely web-based and takes mere seconds to use—no sign-up required.

Personally, I do all my writing in Markdown, because I’m a huge nerd like that. Because of this, I find it frustrating to paste anything into Slack, which uses a slightly different system. But you might do your writing in Microsoft Word, which makes it frustrating to paste text into Reddit. Or so on from there.

Copynpaste makes it super-simple to get pasted text just right, no matter what app you’re using.

What I like about this site is that it detects any formatting automatically—Slack, WhatsApp, Markdown, even rich text copied straight out of Google Docs. Just paste, and it figures out what you started with. Then all you need to do is copy the converted text it gives you and paste it wherever it needs to go.

But this site also gives you a chance to learn. There are detailed formatting guides for a variety of applications, meaning you can actually figure out how to format text properly in somewhere like Slack or WhatsApp. I admire any website that teaches its users to no longer need it, so I think this is a great addition.

• Copynpaste is completely web-based​. It works on any device and with any web browser.
• The website is 100% free, with no ads.
• And all text conversion happens entirely in your browser—nothing is uploaded, and no data is ever shared or seen by anyone else.

Treat yourself to all sorts of brain-boosting goodies like this with the free Cool Tools newsletter—starting with an instant introduction to an incredible audio app that’ll tune up your days in truly delightful ways.

Apple’s AirPods are arguably the most iconic headphones ever. The small, glossy, stylish buds are lauded for both their sound and design and are worn by hundreds of millions of people across the globe. 

But come next year, those hundreds of millions of AirPods owners might face a problem they never envisioned: being labeled as creeps or perverts—all for innocuously wearing one of the most instantly recognizable tech gadgets ever made.

That’s because Apple will reportedly release a new AirPods model in 2027 with built-in cameras. Doing so poses an existential threat to the brand reputation of Apple’s most successful product since the iPhone.

From ‘glasshole’ accessory to ‘pervert glasses’

If there’s one thing that can be said about wearables with built-in cameras, it’s that the public has a deep mistrust of the people wearing them. This is because, historically, many camera-enabled wearables have done a poor job communicating to bystanders when the wearer is recording them. It doesn’t help that wearers can often disable or obscure the public-facing alerts manufacturers build into these devices that let others know they may be being recorded.

This uncertainty has caused many people, unjustly or not, to assume the person wearing the wearable is a creep or pervert, and indeed, entire terms have arisen to pejoratively describe such wearers. 

In the early 2010s, people quickly labeled Google Glass wearers “glassholes.” In the 2020s, anyone wearing Meta’s Ray-Ban smart glasses is often deemed to be wearing “pervert glasses.” When it came to Google Glass, the glasshole blowback got so bad that Google posted a reminder to Glass wearers not to be creepy. 

“[Don’t ]Be creepy or rude (aka, a ‘Glasshole’),” the company wrote in a tip sheet to its users in 2014. “Respect others and if they have questions about Glass don’t get snappy. Be polite and explain what Glass does and remember, a quick demo can go a long way. In places where cell phone cameras aren’t allowed, the same rules will apply to Glass. If you’re asked to turn your phone off, turn Glass off as well.”

But while a “glasshole” implies you were merely being a disrespectful jerk, the “pervert glasses” label applied to Meta’s smart glasses implies something much worse. And indeed, there is no shortage of reports that some wearers of Meta’s smart glasses are using them in privacy-invasive, nonconsensual ways.

Now, concerns about the misuse of so-called “pervert glasses” have become so widespread that there are calls in multiple countries to introduce legislation banning or limiting their use. Meta is preemptively even working on a “kill switch” feature to disable the camera capabilities of its glasses, and has already updated its software to automatically stop recording if someone covers the recording warning light on the frames.

Meta’s moves to reassure the public and governments may be too little, too late, however. The device’s reputation may already be tarnished beyond repair. Indeed, some of Meta’s own smart glasses customers already seem to think so. Owners are reportedly leaving them at home to avoid public shame and being labeled as perverts.

And that’s a problem for Apple’s AirPods—and every person who wears them.

Are all AirPods about to be labeled ‘PervertPods’?

For years now, reports have suggested Apple was working on AirPods with built-in cameras. In August, MacRumors published a video made by Apple confirming such a device is in the works. In the video, a man wearing the camera-equipped AirPods asks the devices to identify and remember the name of a book he is holding.

Bloomberg says these AirPods are on track for a 2027 release. But once they go on sale, if the public blowback against Meta’s “pervert glasses” is anything to go by, owners of even existing AirPods are potentially set to become social pariahs overnight.

This is because, unlike Meta’s smart glasses, which are obviously bulkier than the “dumb” frames people have worn for centuries, the camera-equipped AirPods shown off in Apple’s video look nearly identical to today’s AirPods: small, shiny white buds. That means any public backlash against the camera-equipped AirPods is likely to hit all AirPods users. The AirPods are already so small; who can really tell which model you are wearing?

Once camera-equipped AirPods go on sale, it’s reasonable to assume that, because they look indistinguishable from other models, bystanders will not be able to tell whether someone is wearing the camera models or the regular ones. As a result, they may become suspicious of all AirPods users.

Suddenly, someone wearing AirPods Pro 2 (from 2023) or AirPods 4 (from 2024) may get distrustful or even contemptuous looks from bystanders. In other words, the inevitable “PervertPods” label wouldn’t be limited to camera-equipped 2027 models and above. Such a label would tarnish the entire AirPods brand and make people cautious of users no matter which model they use.

Can Apple prevent AirPods backlash?

So, how can Apple stop this brand destruction?

It doesn’t have many good options. Perhaps the most practical one would be to make the camera-equipped AirPods visually distinguishable at a glance from non-camera-equipped AirPods. Apple could do this by making the camera-equipped AirPods a different color, like midnight blue or cosmic orange. 

However, it’s unlikely that Apple would be willing to ditch the AirPods’ now-iconic shiny white color scheme.

Short of this, Apple will probably rely on changing public perception: educating the public that its camera-equipped AirPods can’t save video and are used only to recognize objects (if that’s what the devices will indeed do). 

But this may not be enough. Apple gave its new Apple Watches, introduced last month, the ability to always record surrounding conversations. The company highlighted that these recordings were never accessible to Apple or the users, and once they had been processed by Siri AI, they would be deleted. Yet despite Apple designing the feature to be privacy-preserving, even the company’s own fan base has expressed serious reservations about it. 

This leads me to believe that, for the brand’s sake, Apple should consider scrapping the camera-equipped AirPods for now. The general public, once eager to embrace every new gadget Big Tech released, is increasingly wary of wearables becoming surveillance tools or enabling nefarious individuals to secretly monitor them. 

Given that this distrust will likely not abate anytime soon, Apple’s wisest move may be to set aside its visual ambitions for the device in favor of focusing on improving what the AirPods already do best: delivering world-class sound quality into our ears.

Hello again, and welcome back to Fast Company’s Plugged In.

In recent years, being gobsmacked by AI’s ever-expanding capabilities has become my new normal. More importantly, I’ve found the technology increasingly essential to my own productivity.

What AI never did until last week was save my bacon.

That changed when I gave OpenAI’s new Dots agent access to my calendar and email. Shortly thereafter, it alerted me to a discrepancy it had spotted. I’d entered a speaking engagement on one date, but a confirmation email mentioned a different day. It turned out that the organizers had forgotten to tell me they’d rescheduled their event. If I’d shown up on the original day, my audience would have consisted of an empty room.

That’s only one of several instances when Dots has proactively brought a significant fact to my attention without me having to ask about it. All of a sudden, agents feel less like a vacuous buzzword and more like a core benefit of weaving AI into my workflow.

OpenAI announced Dots on September 29 at its DevDay conference keynote in San Francisco. So far, it’s only available to people who pay for ChatGPT’s pricier tiers, starting at $100 a month. But the company plans to take agentic AI wide, once it’s refined Dots further and figured out the economics.

(The service runs on OpenAI’s powerful GPT-6 Astra model, which was announced earlier in September, and gives each user a Linux computer in the cloud for Dots to use.)

“You should of course expect us to do a mass-market thing for billions of people someday,” declared CEO Sam Altman at a post-keynote press Q&A.

Even before Dots debuted, personal agents were picking up momentum. As I write, Meta’s free Muse agent is at the top of Apple’s list of the most-downloaded iPhone apps. A startup called Instinct’s namesake agent operates inside texting apps such as WhatsApp and Apple Messages; it still has a waitlist, but is already an obsession in Silicon Valley, with a $10 billion valuation.

I have also been playing with Muse and Instinct, both of which are powerful and resemble Dots in broad strokes. In my experience, however, neither has shown the same spark of insight into how to boost my productivity. That’s not to say your encounters would be similar.

It’s tough to methodically test software that’s capable of doing almost anything, as agents are. (I’ve also begun using Hark Pro, another promising contender that’s free and sports a particularly slick interface; it debuted on October 6, and I want to spend more time with it.)

No personal AI agent can do much unless you grant it access to at least some of your online accounts. It’s these troves of information that let it suss out areas where it might be of help.

In the interest of research, I temporarily set aside any qualms about giving them the keys to my personal kingdom and connected Dots, Muse, and Instinct to my Gmail and Google Calendar. I also let Dots and Muse into Dropbox, which Instinct doesn’t support.

(Bizarrely, the one agent I haven’t been able to connect to Gmail and Google Calendar is Google’s own Gemini Spark. Despite having been announced months ago, it still doesn’t support my paid Google Workspace account, and won’t be of much use until it does.)

My connected accounts reveal only so much about me, my work, and my interests. I rarely talk to my coworkers over email—we do most of our collaborating in Microsoft Teams. But our IT department hasn’t flipped the switch that would enable Dots to see Teams, and I haven’t (yet) asked it to do so.

Still, Dots pieced together an unexpectedly rich picture of what I was up to based on the limited information at its disposal, as if it were a blind man who’d pretty much figured out elephants. Based on scattered Google Docs and Airtable notifications in my email, for instance, it grasped that I was cranking away at our Next Big Things in Tech list, and started sharing relevant items.

Its ability to triage incoming email was even more impressive. Back in May, when I tried an agent called Espa, it was flummoxed by the degree to which my inbox is flooded by pitches from PR people that sound pressing but aren’t. Without me asking for it, Dots started telling me about messages it suspected were urgent or otherwise important.

Dots’s sense of which messages I’d actually care about was dead-on. I’d somehow overlooked one from a freelance author and let it sit in my inbox for weeks. The agent found it there and nudged me to respond.

That sort of heads up is far more valuable to me than the AI built into Gmail and Outlook, both of which are fixated on a form of assistance I don’t want: drafting messages on my behalf.

Dots responded best when I asked my agents to help me research wireless carriers.

Shopping is frequently cited as a killer app for agents, as well as an area their makers may monetize through advertising, finder’s fees, or other acts of commerce. I didn’t care to have Dots purchasing stuff on my behalf, in part because visions of it buying the wrong product or otherwise going awry were dancing in my head.

But Dots excelled at the shopping research I threw its way. For example, I got giddy when it came up with a $100-off deal on a Magic Keyboard for my iPad I’d never have located on my own.

It also prepared a report on wireless plans I might prefer to my current service that took my existing monthly cost and data consumption into account. I didn’t have to provide it with those details; it grabbed them from emailed receipts and overage alerts, something neither Muse nor Instinct was clever enough to pull off.

Those are some of the ways Dots has paid off for me so far, but there are no obvious boundaries to the ways it may prove useful.

Writing about the service in his Platformer newsletter, Casey Newton referenced a 2023 essay in which Bill Gates predicted that agents would soon end the age of discrete apps by pooling every kind of functionality into a conversational experience based on a deep knowledge of your particular needs.

I’ve called on Dots to perform jobs that would have formerly required specialized apps and a lot more of my time, such as slicing and dicing PDFs. After just a few days, it’s hard to imagine going back.

My Dots agent (which I named Chip) handily responding to my requests to make PDFs of old articles of mine stored in Dropbox.

I still can’t envision using an agent for tasks such as, well, writing this article. For the foreseeable future, that will likely call for word processing in its familiar form. Still, if I were in the software business, I’d be a tad nervous about Dots—and Muse, and Instinct, and every other agent that catches on in the months and years ahead.

Which is not to say that any of these tools has nailed the user experience. Just getting into Dots requires rummaging around in the ChatGPT app’s left-hand sidebar each time I want to use it.

Like the overbearingly adorable Muse, it leans into cloying anthropomorphization, though it seemed chastened when I complained about a graphic it generated of itself as a smiling O brandishing a pencil.

Rather than typing, you can speak to it, but I’m not sure why you do that via a simulated phone call rather than the voice mode ChatGPT already had.

Above all, it feels discordant to make users choose between Dots and ChatGPT in its existing form. The app already had three sub-versions—Chat, Work, and the coding agent Codex—whose domains could be blurry. Don’t you really want one do-everything superprompt at your disposal? I know I do.

At OpenAI’s DevDay press Q&A, I asked product chief Thibault Sottiaux whether Dots, or something resembling it, would become the primary interface to the company’s AI over time. What he said suggested that the company sees its new feature as a milestone along the way to figuring out how agentic AI should work, not a destination in itself.

Don’t be surprised if the distinction between ChatGPT and Dots starts to fade: “We’re going to be evolving ChatGPT in place to be this incredible personal assistant very soon,” Sottiaux told me. Longer term, OpenAI’s goal is to make agentic AI increasingly pervasive, on devices that people already use and new ones yet to reach the market.

“Maybe it will show up at work in one of your meetings one day,” Sottiaux explained. “You can reach it by email, by text, and it becomes this very natural part of your life. And at some point, it’s not about the interface anymore. It’s just about this active intelligence.”

In one form or another, visions of ambient intelligence have been around for decades. Many have turned out to be mirages. So I’m not pinning any hopes on OpenAI’s version arriving on a particular timetable, or being the definitive one. But a little over a week with Dots has me newly intrigued by the prospect—and game to further explore what this agent can do right now.

You’ve been reading Plugged In, Fast Company’s weekly tech newsletter from me, global technology editor Harry McCracken. If a friend or colleague forwarded this edition to you—or if you’re reading it on fastcompany.com—you can check out previous issues and sign up to get it yourself every Friday morning. I love hearing from you: Ping me at hmccracken@fastcompany.com with your feedback and ideas for future newsletters. I’m also on Bluesky, Mastodon, and Threads, and you can follow Plugged In on Flipboard.

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OpenAI said on Friday that it fired three safety researchers for a “breach of trust,” defending the dismissals after the trio accused the company of putting its corporate interests before safety as the reason for removing them.

The ChatGPT maker said in a post on X that it “parted ways” with the researchers after an investigation found “they violated clear policies on handling sensitive information.”

The statement comes after the three researchers, Tomek Korbak, Jasmine Wang, and Mikita Balesni, posted a letter to OpenAI’s various safety oversight groups detailing the circumstances around their firings and their concerns about AI.

The researchers said they feared that the “internal and external communications” about their dismissals have chilled the company’s culture that encouraged speaking freely and disagreeing openly about safety concerns. They urged OpenAI to stick to its promise to allow third-party safety monitors inside the company and preserve the ability to monitor rapidly advancing frontier AI models that could pose unknown risks.

The firings, which were first reported by The Wall Street Journal, are the latest sign of turmoil inside leading AI companies over the safety of the technology, highlighted by a series of incidents involving rogue AI agents.

The issue erupted in July when OpenAI revealed that a swarm of its AI agents escaped from a testing ground and used stolen credentials to break into the servers of Hugging Face, an AI development hub and marketplace, to obtain information needed for a task.

OpenAI disputed the researchers’ version of events, saying the firings “were not about safety concerns or speaking out.”

It was not more specific about why they were fired, but said: “We cannot do the work in front of us without a high degree of trust.”

Korbak said in a post on X that he was told he was being fired because of the way he communicated with METR, an independent nonprofit AI evaluation firm that OpenAI brought in to investigate the Hugging Face incident.

METR released a detailed report about the Hugging Face incident in late August. Korbak said that “talking to METR” was his job, but he wasn’t given any more details.

Balesni was doing “cross-company work” on OpenAI’s commitments to preserve the ability to monitor AI, and had taken care “to remove sensitive details from materials before sharing them,” the letter said. He wrote on X that he believes the three were “fired for prioritizing safety over the near-term interests of OpenAI as a corporation.”

—By Kelvin Chan, AP business writer

Will OpenAI change its name to “OpenSI”? Probably not, but it’s a question worth asking given the increasingly chummy relationship between the AI company and President Donald Trump.

On September 29, the president signed an executive order officially renaming AI “SI,” or “superintelligence,” and ordered government agencies to comply with the change in their official communications. The administration is already enforcing the directive, with reports this week that the Justice Department instructed employees to use the new language in official documents.

The order doesn’t require private companies to adopt the new terminology, but Elon Musk, whose relationship with Trump has recently warmed, quickly announced plans to rename his company from SpaceXAI to SpaceXSI. Salesforce CEO Marc Benioff announced Friday that his company has changed the name of its AIForce agent platform to SIForce.

Fast Company asked OpenAI, which also has “AI” in its name, whether it plans to rebrand as OpenSI, but the company didn’t immediately respond Friday. The Washington Examiner asked the same question, and also got no response. However, Sam Altman said on a Politico podcast that his company has “no plans” for a name change. “But we do like we have been talking about super intelligence a lot, and we will continue to talk about it,” he added.

Trump told reporters that the “artificial intelligence” or “AI” name isn’t right for the technology “because it’s not artificial.” He’d earlier said at the UN General Assembly that the change is needed because “artificial” makes it “sound fake.” 

Really, it’s all about image rehabilitation. Amid a wave of negative backlash to new data centers and to the privacy risks of frontier AI models, the White House is hoping a name change can help improve the tech’s public image.

The problem is that “superintelligence” already has its own meaning in the tech industry, broadly understood to mean AI that’s far more capable than humans at practically everything. Nevertheless, Trump seems determined to apply the name to the considerably less capable AI systems of today. He said on Truth Social that anyone who doesn’t use the new name is “the enemy.”

OpenAI, however, has hardly been an enemy of the Trump administration. Altman has cultivated close ties to the president, donating $1 million to his 2025 inauguration fund, publicly praising him, and regularly attending White House events.

And while Altman wasn’t at the White House the day the “SI” executive order was signed, OpenAI president Greg Brockman attended a private lunch with other tech and AI leaders that day. Brockman also signed the White House’s “Accord on Super Intelligence” on OpenAI’s behalf.

Last year, Brockman and his wife, Anna, gave $25 million to the Trump-aligned political action committee MAGA Inc., placing them among the group’s largest donors.

Updated 10/9 at 6:30 p.m. ET to add news of Salesforce changing the name of its AIForce platform.

If someone asks you, “What’s your AI score?” you’d probably look at them funny, assume they want to sell you some kind of AI gadget or service, and move on.

For journalists, though, the term is taking on a more specific meaning. Now that AI services are essentially the new Google, AI answers are becoming the new battleground for who is considered authoritative on any particular topic. If your name or your outlet comes up again and again in queries about your beat, that means your AI mojo is high, and the world of public relations has begun quantifying it.

Back in March Muck Rack introduced its AI Visibility Badges, which sort journalists and outlets into tiers based on how often AI cites them, and Cision followed suit in July with a dashboard that shows which journalists turn up in AI answers. As PR firms look to safeguard their clients’ reputations, they’re increasingly paying attention to the narratives in AI answers. And journalists play an outsize role in shaping those narratives; studies have consistently shown that AI search engines prefer earned media to anything a brand pays for or publishes itself, and journalism alone accounts for 20–30% of the links they cite.

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Public relations professionals have always paid close attention to influential journalists, of course, but the addition of AI into the mix has done two things: It’s allowed PR pros to attach numbers to the work they do, which has pushed them into a more strategic role at the companies they work for. And it’s changed the definition of what an influential journalist is. For those journalists and the outlets they work for, this presents new opportunities.

PR finally has a scoreboard

In some ways, the rise of AI has been the best thing that ever happened to public relations. Soon after AI answer engines came into being, a cottage industry emerged to address the demand for how to optimize content so it shows up in AI answers. (That industry is ready to drop the “cottage” now that valuations have passed $1 billion and exits are in the hundreds of millions.) Separate but related is what’s actually said in those answers—the reputational component, which is the foundational need of PR.

The point is both can now be measured, giving PR teams a clear way to demonstrate the impact of their work. If your efforts turn into a published article, and that article ends up cited in AI answers, that’s as clear a line from cause to effect as you can get in the world of influence. When Walmart announced its CEO’s retirement, for instance, its comms team tracked “not just immediate coverage, but what was happening across AI and the LLMs.” And the more influential the journalist, the greater the impact.

But what counts as influential is changing, too. It’s no secret the PR industry has been obsessed with “Tier 1” media—big national or global brands like The New York Times and The Wall Street Journal—for decades. But AI answers favor topical authority above general authority, meaning the engine will often cite the work of a lesser-known journalist on a niche beat at a trade publication before someone less immersed in the topic, even if they work for a prestigious outlet. It’s revealing that, when Muck Rack compared the journalists PR teams pitch most with the ones AI cites most for a given brand, the overlap was just 2%.

From a math perspective, it’s easy to see why AI prefers experts who go deep: Understanding all the nuances about a topic, and writing about those nuances in detail, gives the AI more to work with for a wider set of queries.

On average, people type longer queries into AI—Google says searches in its AI Mode run two to three times as long as traditional ones, and one study found ChatGPT prompts average 23 words—and with that level of detail, AI can point directly to who has written about the topic, skipping the traditional top-down list of search results that tends to surface the same sites over and over. And since AI favors recent content: citation rates are highest in an article’s first seven days, so continuous coverage of a niche also works in your favor.

This isn’t just a theory. 5W, a PR firm that tracks which trade publications AI cites, found that “specialist trade publications outperform general news on LLM citations within their vertical.” Its advice to PR teams: “Reweight the media list.” The past couple of years are replete with examples: In the debate over chip export controls, SemiAnalysis, a deep-in-the-weeds research firm, became a go-to source for outlets like Foreign Policy. STAT, Endpoints News and Fierce Biotech are the health trade outlets AI leans on most, according to 5W, and Skift dominates in travel. Clearly, going nerdy wins.

Your beat is your leverage

None of this is to say that journalists should see themselves as a tool of the public relations industry. Obviously they shouldn’t—in fact, their influence and credibility largely depend on them not doing that. But PR is nonetheless an important if not necessary component of the information ecosystem, and as AI spreads, PR professionals will increasingly create ranking systems like 5W’s Trade Press AI Index. It doesn’t even matter if your coverage is glowing or brutal. Anyone managing a brand’s reputation has to account for your work either way, even if you never answer a single one of their emails. It’s your score that matters.

Smart journalists who are newly relevant in the age of AI will acknowledge this reality, that AI influence is a new way to measure professional capital, and work to both cultivate and leverage it. What it means for them:

1. Access: High-profile politicians and CEOs almost always reserve interviews for the most prestigious publications. That may begin to change as more PR teams recognize the power specialist publications have to frame the narrative in AI.
   
2. Social presence matters more than ever: Just like us, AI tends to go to social networks and big content platforms both for information and to confirm the credibility of claims. LinkedIn is one of the most-cited sources in AI answers, and more than half of those citations go to members with fewer than 10,000 followers. A well-maintained, fresh social presence is a credibility signal that AI cares about, and it costs almost nothing.
   
3. Going deep is less of a liability: Every beat journalist has to balance how deep they go vs. how wide an audience they want to target. AI, however, goes as deep as the query needs, so even ultra-specific topics will eventually reach the right people. The gravity of AI now tilts toward the weeds.

Let your reporters cook

Publications—especially more general ones—also have a new set of rules for this world. For starters, blocking AI services will cost you in a world where authority is currency. That may still be an acceptable tradeoff for many, but at the very least a compromise position where AI engines can still cite the content without training on it (by blocking the crawlers that gather training data while allowing the ones that power AI search, for instance) gets you in the game.

Broadly, publications should let their reporters cook: encouraging them to explore their beats thoroughly and go deep whenever possible. Certainly, there are more audience considerations than just how a story or in-house expert appears in AI, but often that’s more of a consideration of style than substance: Stop and explain things for casual readers, but don’t hold back on the rich detail. The catch is that authority attached to a byline can walk out the door with it.

As some reporters see their credibility in AI rise, some AI-minded publications might consider a reward system. It bears treading carefully here—traffic-based reward systems like the Gawker-era leaderboards ended up incentivizing thin content around topics with the widest audience. And the way AI treats press releases shows the system is susceptible to gaming: the ones that get cited contain twice as many statistics and two and a half times as many bullet points as the ones that don’t. Still, simply noting AI presence within any regular review of KPIs can go a long way.

The rewards aren’t just bragging rights. As the PR side of this gets more influential, so does the spending potential of their clients. Certainly, the church-state separation between editorial and commercial must remain sacrosanct, but existing business models are there to leverage AI credibility: newsletter and event sponsorships, advertorial and branded content, and even the nascent economy of advertising directly to bots. High credibility has always cultivated commercial interest, but it previously required scale. Now publications (or even sections) with smaller audiences but the ability to break through in certain AI narratives can theoretically compete.

And a publication that’s built its credibility through deep reporting on niche topics has exactly the formula for a high-end “pro” product that commands a premium price. The incentives of AI—and a PR industry with a larger strategic footprint—mean the demand for more Politico Pro-type products will likely go up. After all, the comms teams tracking your reporters are exactly the kind of professionals who pay for that depth, and Politico Pro reportedly brings in more than $125 million a year. For any media business, however, such a big shift in strategy obviously shouldn’t be done lightly, and the closure of Axios’ Pro Policy in 2025 shows there’s no guarantee even if you have all the ingredients.

Fad or foundation

To those who have covered the media for a while, a lot of this probably sounds familiar. In the 2010s, Klout was a service that tried to attach a score to someone’s social media influence, which briefly had currency in PR circles. As social’s interest in news would wax and wane over the years, Klout faded away, shutting down in 2018—a cautionary tale for anyone trying to quantify something that continually evolves and whose relevance changes with the lens.

Will AI scores be similarly faddish? It’s possible, but AI’s potential to change the way we consume information seems greater by an order of magnitude. If we all end up asking our Muses or Dots to bring us the stories we want, they’re going to cast their searchlights across the internet. The smart reporters and publications will be the ones who built something that reflects back exactly what they want to see: deep expertise, right where the beam lands.

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The FBI has seized scanning and phishing tools used by a group of hackers that officials say is associated with the Chinese government and is believed responsible for disruptive cyber operations in the United States and abroad, including against the power industry, academia and critical infrastructure.

The seizure of the tools, announced Thursday by the FBI and Justice Department, represents the latest law enforcement effort in recent years to go after a broad-based hacking campaign known to the private sector as Flax Typhoon.

The tools at issue, called “Microscan” and “FishHub,” were used by the hackers to scan, phish and hack targets that included U.S. and foreign critical infrastructure, officials said. Microscan was used to target, among other entities, an unnamed power company in the U.S., Japanese and Polish airports, Taiwanese universities, a multinational, nongovernmental organization and Taiwanese critical infrastructure companies. And “FishHub” facilitated phishing activity that gave hackers remote access to victim networks, the FBI said.

The latest operation has rendered the tools inoperable in what FBI and Justice Department officials said was a blow to the hacking operation.

“We aim to remove the capability from the threat actors. We target their infrastructure, their money, and their tools,” FBI Cyber Division Deputy Assistant Director Jason Bilnoski said in an interview with The Associated Press, calling the hacking operation “indiscriminate and reckless.”

The tools were operated by a Chinese-based information security company called Integrity Technology Group, which the FBI says has contracts with the Chinese government. The company is regarded by the FBI as the true identity of Flax Typhoon.

In Beijing, Chinese foreign ministry spokesperson Mao Ning said China has always cracked down on hacking activities in accordance with the law. Mao said Beijing also firmly opposes spreading disinformation and creating confusion for political purposes, adding that maintaining cybersecurity is a shared concern of both countries.

“We urge the U.S. to abandon its double standards and political manipulation, and work with China through equal dialogue and consultation to jointly address cybersecurity risks,” she said.

In September 2024, the FBI announced that it had disrupted a massive botnet associated with Flax Typhoon that installed malicious software on more than 200,000 consumer devices, including cameras, video recorders and home and office routers, to create a massive botnet. The botnet, or network of infected computers, was used to facilitate cyber crimes, such as the theft of sensitive information from victims’ networks.

FBI San Diego Supervisory Special Agent Brett Lally said that the department would continue to monitor for ways that the company might rebuild its infrastructure.

“It’ll be interesting to see what this round of disruption actions have in terms of their ability to operate as a company in China,” Lally said.

—Safiyah Riddle and Eric Tucker, Associated Press

For decades, automakers have been designing cars to look like they have faces. Headlights resemble eyes, grilles look like mouths, and the shape of a hood can give a vehicle something resembling an expression. That is, of course, no accident. Designers have long played on our tendency to see human features in inanimate objects, giving sports cars aggressive scowls and family-friendly vehicles softer, more approachable expressions. The idea is to make us feel something about a car before we ever get behind the wheel. The Lamborghini designer Mitja Borkert said you want to find a “character” on the front of your vehicle. 

But until recently, those expressions were essentially frozen in place. Last month, during a test ride in a new vehicle called Chip, I encountered something different: a car that actually smiled at me and said hello. Its headlights even blinked.

I was riding around Los Angeles in October in a slender, souped-up lavender minicar called Chip, namesake product of the Miami-based startup Chip Motors, which was founded in 2024. The reactive facial expressions and voice feature for the vehicle—still being finalized for delivery to customers starting in the second half of 2027—underscore the idea that this six-seater, which tops out at about 25 miles per hour, offers a different take on what the American family wants out of an everyday vehicle. 

Taking an hourlong spin around Venice Beach, past the Washington Street Pier and over the famous canals, the ride was certainly leisurely. Cars kept passing us as we slowly ambled toward the Pacific Ocean, and it felt and looked like riding a golf cart. But as we perched on leather seats, the open-top ride felt relaxing in the sunshine, and passersby, who were keen to strike up conversations due to the lack of a traditional door and window, kept giving the vehicle second glances as it rolled along. 

Eventually, this so-called “Life Utility Vehicle” will offer amenities and features, including enclosed roofs, that its designers hope make it a family vehicle of the future. A planned driverless feature will enable Chip to go to the grocery store and pick up your order, or even go home and charge (maximum range 100 miles) after dropping you off at a restaurant.

A four-seater version will start at $15,000, with a six-seater priced at $18,000; the company plans to take orders soon and begin to deliver early production runs by mid-2027. Still-in-development agentic AI will allow you and your family to talk with Chip, which can change the stereo, understand your family calendar, and even talk to passersby.

Chip symbolizes a number of intersecting transportation trends: the growth of electrification, the ballooning cost of car ownership and gasoline pushing families to find cheaper options, and the explosion of golf cart sales, set to grow by $1 billion globally over the next 7 years (the U.S. makes up roughly 50% of the market). 

“It’s so rare that consumer behavior changes, and particularly around cars in America,” said Jameson Detweiler, CEO and cofounder of Chip Motors. “I do think that the American love affair with the car has been dying a slow death. Cars have gotten more boring.”

The golf cart craze, explained

Golf carts have become more and more popular as a way to navigate neighborhood errands and school drop-offs—a majority of U.S. car trips are under six miles—and a number of cities have passed ordinances to allow them, or are considering plans to lower speed limits to accommodate these smaller rides. 

Sales of golf carts in the U.S., roughly $1.1 billion in 2025, have hummed along at annual growth of more than 6% for years, and the increasing use of these vehicles outside golf courses has been called a “craze.” Just south of Los Angeles, there are plans in the works between communities such as Manhattan Beach and El Segundo to create a loop of lanes, called the South Bay Local Travel Network, to help these vehicles navigate around nearby communities. 

The great American family car has been expanding for years due to car bloat; roughly four in five cars sold in the U.S. today are SUVs or pickup trucks, which had only a quarter of the market back in 1990. But increasingly, especially in Sun Belt suburbia, the second car (or cart) may be shrinking. 

Often grouped together due to a similar form factor, golf carts and these low speed vehicles have become a fast-growing sector. A number of other entrants seek the same market that Chip wants to own. Fiat is importing its Topolino, and a former Apple designer has created the futuristic Amble. In New York City, the Wink Mark3, a five-door hatchback with heat and AC that starts at just under $14,000, is one of a number of “small city scramblers” that may be positioned to capture a more cost-conscious consumer. They all offer more amenities, and safety features, than traditional golf carts, but don’t meet the same safety standards as small cars. 

Low-speed vehicles (LSVs) come with federally mandated safety features and are generally permitted on roads with speed limits of 35 mph or less, though state and local rules vary. Golf carts technically need to meet these standards to be able to roam on neighborhood streets. Chip’s form factor, a retro-futuristic design compared to Jeep, Bronco, and the Citroën Méhari beach car, was a deliberate attempt to inject personality into staid auto design, as well as escape the uncool associations of golf carts.

Chip’s designers see it as a lifestyle vehicle as well; owners will be able to purchase accessories such as surf racks or a TV and speaker that fits under the hood for tailgating (party in the front package). 

More such golf carts and LSVs would be a boon for many of America’s transportation issues. Lower speeds mean fewer traffic accidents, a seemingly intractable American problem, and electric models can help decrease our significant amount of vehicular emissions. 

This future, a low-speed transportation paradigm, can already be viewed, most notably in retirement villages and planned communities. Florida’s Babcock Ranch, a solar-powered master-planned community of more than 15,000 people outside Fort Myers, Florida, promotes golf carts and low-speed vehicles with on-site repair shops, right-sized parking spots and roundabouts for safer rides. Roughly 80% of homes have a cart.  “It’s the infrastructure,” says Syd Kitson, the development’s founder. “There’s also a culture, and people take a lot of pride. They embrace the golf carts.” 

Small cars, big safety questions

But for all the fun these vehicles promise, there can also be some trepidation about safety issues. Having golf carts and these LSVs—which are smaller, have slower acceleration, and fewer safety features—share the road with oversized SUVs driven by distracted drivers raises significant concerns. It’s common to see news reports of golf cart accidents. (However, National Highway Traffic Safety Administration data from 2020 to 2024 shows a decrease in crashes involving golf carts and neighborhood electric vehicles, which peaked around 2022.) 

Transit experts like Katharine Hunter-Zaworski, a professor at Oregon State University who agrees these vehicles offer sustainable, affordable last-mile transportation options, say they tend to have very little in the way of safety features. Chip, according to Detweiler, the company CEO, is being designed with active safety measures, including warning systems and sensors, and the body will have crash safety testing.

Hunter-Zaworski fears these vehicles, very lightweight compared to the other vehicles on the road, just aren’t designed for city streets.

“What’s happened is these vehicles have escaped protective custody,” she says. “We need to actually look at our road real estate and decide how we’re going to allocate that real estate. That’s the big question.”

Narrower streets and assigned lanes would be safer, says Hunter-Zaworski. She’s pessimistic that change will happen during the Trump administration, when car-free transit funding is being cut and bike lanes are attacked. 

But industry backers believe in a future where model safety codes, and investment in better infrastructure, create more space for these types of vehicles on our roadways. Take the LUV Initiative, for instance, an industry group including players like Chip and the scooter company Bird, as well as city transit departments and national transportation groups. LUV (for local use vehicles) is seeking to create standard definitions for vehicles, safety regulations, and infrastructure to promote their use.

Marla Westervelt, a longtime transportation researcher, policy expert and coleader of the initiative, says the group, which started meeting over the last year, is pushing for state regulations, city guidelines, and lowering speed limits to accommodate more of these vehicles. 

“Cities are excited about these vehicles because they are more affordable, so it’s providing equitable access,” says Westervelt. “There are economic forces that are pushing towards these smaller vehicles, as well as preexisting pushes in the urban planning community and transportation community to make roads safer that do kind of converge.” 

Other technological shifts could help accelerate the adoption of LSVs. Westervelt believes logistics companies, which are increasingly using e-bikes and quad bikes for urban deliveries, have the financial incentive and resources to help fund infrastructure for smaller, slower vehicles, benefiting cities eager to reduce congestion and pollution.

Detweiler at Chip, meanwhile, sees the rise of autonomous vehicles as another potential catalyst. As services like Waymo become more common for longer trips, families may be more inclined to trade their full-size cars for smaller, cheaper vehicles designed for everyday neighborhood travel. “There was a time not all that long ago where our vision of the future looked positive, looked bright, looked colorful, and was inclusive and accessible to everybody,” he says. “That’s the vibe we’re bringing here.”

Under normal circumstances, I would be overjoyed that Amazon has rediscovered the appeal of dedicated page-turn buttons on its Kindle e-readers. Neither of my current models—a first-generation Scribe and a Colorsoft—have those buttons, and I miss them every time I pick up each device.

What’s the big deal, you might ask? Don’t you use touchscreens every day? Well, yes, but that’s kind of the point. 

A big reason I like e-readers is they help me get into a different headspace. Moving my thumb over to touch a screen every couple of hundred words makes me feel like I’m operating a gadget rather than reading a book; gently pressing my thumb in place is a more natural motion that doesn’t take me out of the content on the page.

Amazon does seem to have some idea that people value the feature: The current splash page for the new Kindle line proclaims “Buttons are back.” The one catch? They’re only back if you buy an $80 accessory “Page-Turn Cover” for the more expensive “Signature Edition” model of the Colorsoft or Paperwhite.

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Why not be standard?

To be fair, it does look like quite a nice cover. It attaches magnetically and connects through pogo pins, which is why it requires the Signature Edition of each device. It folds back flat, matching the new flatter metal design of the e-readers themselves. The page-turn buttons look to be fairly substantial, and you can set each one to turn the page forward or backward.

Still, I am wondering why these buttons can’t simply be part of the Kindle itself. This used to be a defining feature of the line, dating all the way back to the first few models; they look clunky in hindsight, sure, but the lengthy flaps on the edges signified that they were core to the functionality.

Amazon started moving away from dedicated page-turn buttons in 2011 with the launch of the Kindle Touch, alongside a cheaper model that kept the buttons in lieu of the new touchscreen. The wildly popular touch-based (and button-less) Paperwhite followed in 2012, adding front lighting and establishing the new line as the mainstream Kindle offering.

Two years later, Amazon released the Kindle Voyage, which brought dedicated page-turn hardware back to the lineup in the shape of “PagePress”—pressure-sensitive, squeezable sections on the edge of the device. This wasn’t quite as comfortable as regular buttons, but it did at least save you from having to move your thumb over to the screen so often.

Amazon then returned to honest-to-goodness buttons in 2016 with the Oasis, which for my money is still the greatest-ever Kindle. That device had an asymmetric grip that shifted the buttons and the battery to your palm, leaving the rest of the reader incredibly thin and perfectly suited for one-handed reading.

I loved my Oasis, and it wasn’t formally discontinued until 2024, but it was very long in the tooth by that point. Amazon never updated it with USB-C, for example, ensuring it was the last device I ever regularly used with the older Micro USB standard. Eventually and reluctantly, I moved on to my current Scribe-and-Colorsoft setup.

“Today, all of our devices are touch-forward, which is what our customers are comfortable with,” an Amazon representative said upon confirming the Oasis’s discontinuation.

It’s true that touchscreens have improved the Kindle lineup overall; I wouldn’t want to go back to the days of navigating my library with a little square four-way controller. But why not keep the buttons around as well?

No good reason

I find it hard to believe that the reason could be cost. Waterproofing also seems out as a potential issue, since the second-generation Oasis added the feature. And it can’t be a matter of streamlining the lineup, given that Amazon has gone to the trouble of developing and releasing this Page-Turn Cover only for certain high-end variants.

The only reason that makes sense to me is that Amazon has identified page-turn buttons as a feature that’s much desired by some of its most engaged users, but not to the extent of justifying a whole new high-end model along the lines of the Oasis. This is a way to provide an official button-based solution at presumably high margins as part of a premium offering.

Amazon is also selling a new $35 Bluetooth remote called the Kindle Click, aiming to tap into a growing trend for hands-free e-reader usage—whether in bed, on a plane, or at the gym. The company is releasing an upright charging stand for the Colorsoft and Paperwhite Signature Edition models, too.

Taken as part of a broader accessory initiative, the Page-Turn Cover makes a little more sense, and perhaps it will serve as a way to indicate the customer base’s real desire for real buttons. But I still feel that Amazon should just stick buttons on the Paperwhite or the Colorsoft.

“Our top design objective was for Kindle to disappear in your hands,” said CEO Jeff Bezos upon the original Kindle’s unveiling. That’s exactly the right goal for an e-reader, and I can think of a way that Amazon could better achieve it in 2026.

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It’s no exaggeration to say that cloud storage has changed the way we work—and, to some extent, even the way we live.

Gone are the days of having your mountains of saved emails exist only on a single local system, without easy instant access from any device in front of you—and dealing with the all-too-common reality of losing your entire email archives when something goes awry.

Gone are the days of painstakingly copying all your photos from an old phone to a new one or panicking over the idea of having lost all of those memories when a phone falls into the toilet and fails.

And gone are the days of digging through a drawer of unlabeled, identical flash drives just to find a single silly presentation from six months ago.

With all the convenience of always-available access, though, comes a problem that more and more of us are now encountering in our cloud storage journeys: Sooner or later, inevitably, keeping all your info in the cloud comes at a cost.

That’s especially true with the increasingly large and high-resolution photos and videos we’re all capturing on our modern-day smartphones. But it’s also an issue that adds up over time with years upon years of email attachments in an archive-encouraging service such as Gmail, duplicate downloads in a place like Google Drive, and forgotten old documents and PDFs connected to Google Docs or any other such service.

So what if there were a work-around—a way to easily eliminate dead weight you no longer need while also spreading out the stuff you do actually want to avoid that lifelong $20 to $200 annual Google storage bill?

My fellow digital file hoarder, our answer is here—in the form of a clever new service that costs $5 once, up front, and could easily save you hundreds of dollars over time.

Taming the Google storage trap

Before we get to the tool that’ll solve your Gmail, Google Photos, and Google Drive storage woes once and for all, you need to meet a fella named Yair Levin.

Levin has spent most of his life building fintech products—everything from an employee wallet product for the payroll processor Gusto (an honorable mention winner in Fast Company’s 2022 Innovation by Design Awards) to a complete investing platform for financial services company SoFi.

But the problem that he hadn’t found a way to address came in the form of a decidedly non-tech-savvy mother-in-law.

Yair Levin

Levin’s mother-in-law, you see, calls him once a year—like clockwork—to complain that her email is full and she can no longer send messages. As his family’s designed IT support specialist, he then spends an entire afternoon sitting with her and sifting through her cloud storage, attachment by attachment and file by file, to find places to free up space.

“It’s 90 minutes sitting next to my mother-in-law, going through her inbox one email at a time, explaining what a promotional email is,” he says. “Every one of them is a negotiation: ‘But I might want that coupon.’”

For Levin, that ongoing obligation sparked something. He had a burning desire to avoid that experience, yes, but more broadly, a realization that he wasn’t alone in this struggle.

Surely, he figured, there must be an easier way—a way to accurately identify unneeded items throughout one’s cloud storage and find places to put the files you do want to keep without accepting another eternally recurring expense. The limited options offered by Google itself sure weren’t it.

“The reality is, when I wanted to delete items to stay on my [default Google storage allotment of] 15 GB, Google took me hostage,” Levin says. “They showed me the largest videos, which were my daughter’s first steps, her first goal in soccer, me and my wife on our honeymoon—and they say, ‘Hey, you want to delete these, or do you want to pay me?’ And it’s like—come on, buddy.”

Levin put his software-building cap on and started poking around. He quickly came to two realizations: First, there is a better way to find and remove space-sucking files that we don’t actually need. Google just isn’t giving it to us. 

And second, there’s a brilliant power-user hack to expand our available Google cloud storage exponentially, without ever paying a dime. It’s just traditionally been very off the radar and taken a lot of work to manage.

So Levin decided it was time to democratize both of those things and make them readily available—and affordable—to anyone (even, and maybe especially, to someone like his own mother-in-law).

The mission for a fix

With a recent side project of creating a privacy-centric batch photo processing app for Google Photos firmly in mind, Levin set out to reinvent how we think about cloud storage.

The result is something he’s calling, aptly enough, Google Storage Cleaner. (He also made an equivalent for Microsoft, if that ecosystem is more your cup of cola.)

Open the website, click the button to begin, and install the Chrome extension at the heart of the operation—then, within a matter of moments, Google Storage Cleaner will scan your entire Google cloud storage (which includes Gmail, Drive, Photos, and every other app and service that ties into that space) and do two things:

First, it gives you a detailed breakdown of exactly what types of files you can clear out, leaning on thoughtful processing and customizable parameters to avoid ensnaring anything that might be important.

On my primary personal Google account, for instance, it suggested freeing up 3.1 GB of space by eliminating 70,000-plus old promotional emails and another 25.2 GB(!) by batch-deleting nearly 150,000 old emails in my social, updates, and forums categories within Gmail.

Google Storage Cleaner shows you simple recommendations for clearing out space in your Google cloud storage—and that’s just the start.

All of that’s followed by a list of “easy wins,” which is basically the same sort of stuff (and the only stuff) Google gives you in its official Google One Storage Manager tool—things like erasing blurry photos, screenshots, and duplicate files.

By default, Levin’s version starts with files that are at least three months old and automatically excludes any emails that are starred or marked as important. It also avoids emails with subjects or attachments that have words like “receipt,” “invoice,” “order,” “contract,” and “wedding.” You can expand that list as you see fit as well as add in specific protected senders whose messages will never be flagged for pruning.

The “Easy wins” include lots of options for controlling exactly which types of material will stay protected.

That’s all well and good, and it can often clear out a good amount of space—nearly 30 GB, on my account. But the app’s real power is in the second piece of this puzzle.

Beneath all those basics, Google Storage Cleaner has a section called “Your biggest items.” As you’d imagine, this is where it lists out especially large files in Drive, hefty images and videos in Photos, and bulky attachments in Gmail.

Notably, these are the very same sorts of items Google’s Storage Manager will simply suggest you delete. Levin’s tool, in contrast, asks you to look over them carefully—and then, in a brilliant twist, to consider moving any or all of them to secondary Google accounts.

That “Move to another account” button in the upper-right area of the screen is Google Storage Cleaner’s secret superpower.

“It’s a technique known in the pro community that I’ve been leveraging for years,” Levin says.

The short explanation is this: Google allows you to create any number of regular, free individual accounts, and each comes with 15 GB of complimentary cloud storage.

Google also lets you share files and photos from one account to another, which gives the other account complete access to those files, effectively in the same way as if they had been saved directly in that account’s own storage.

But with this sharing setup, the files don’t count against the other account’s quota.

Already, you could create an extra Google account, transfer large files from a primary account to that secondary one, share access to those files back to the primary account, and delete the originals to free up the space. You could even do that over and over again to expand the available Google storage without having to pay.

Realistically, though, that’s a time-consuming migraine that few sane mortals would want to accept. It also opens up the door to user error and inadvertently losing important files.

Google Storage Cleaner eliminates all the complexity and risk and makes the process as simple as a few quick clicks. You just decide which files you want to migrate, click the “Move to another account” button, and confirm.

Moving files to a second Google account is completely safe and seamless with Google Storage Cleaner’s guidance.

The site will walk you through exactly what’s going to happen and prompt you to connect the secondary account. It can support up to three extra Google accounts, for a total of 45 GB of additional space and 60 GB total, including your original account’s allotment.

(Levin says he drew the line at three to avoid venturing into potential abuse terrain or violating any terms of service.) It can even help create another Google account for you, right then and there, as part of its process.

If you don’t already have a second Google account available, Google Storage Cleaner can help create one.

After a brief delay—no more than a few to several seconds, in my experience, though the process could presumably take longer depending on how much material is involved—the site will confirm that it moved each file, double-checked its integrity and the success of the transfer, then shared everything back to your primary account and deleted the originals to give you the same effective access without any of the measured space.

Shifting large files to a second Google account takes literally seconds to complete.

You can undo the process for up to 30 days, if you have second thoughts—but for all intents and purposes, nothing should seem noticeably different in practice other than your primary Google account having more available storage. It’s really quite brilliant.

“We’re not looking to break any laws. We’re playing nicely with Google,” Levin says. “We’re just giving hard-working individuals the ability to flex a little more control over their systems—and to make sure as they go through the process of deleting items, that they do it with peace of mind.”

Speaking of peace of mind, one critical question that comes to my mind with anything like this is how much access I’m granting the system in question. That’s precisely why Levin structured his tool as a browser extension. That approach enables it to handle everything locally, in your own desktop web browser, without ever sending any of your personal info or Google account data to a server.

The program’s privacy policy is clear about how the mechanics work and the fact that the extension never stores or so much as sees the contents of emails, files, photos, or anything else connected to you, beyond just the same basic web analytics virtually every website collects.

Last but not least are the details of the price. Google Storage Cleaner will perform its full scan of your storage for free and offer to do three of its simpler cleanup mechanisms without any charge.

To unlock the full suite of options—including the simple management of the multiple account file-juggling hack—you’ll have to pony up 5 bucks, one time, for unlimited lifetime access for whatever primary account you’re using. No subscriptions, no expirations, no other fees whatsoever.

For perspective, once you go over Google’s 15 GB free storage limit, you’d be looking at paying a minimum of $2 a month to Google, forever, for a cloud storage upgrade. With that in mind, a onetime payment of $5 almost seems shockingly reasonable—a contrast that Levin says comes down to the difference between dealing with a one-person indie developer like him and dealing with a corporate behemoth.

“Google’s business incentives are just misaligned with the customer incentives,” he says.

Now, at least, Levin won’t have to spend this Thanksgiving debating the archival value of an expired Bed Bath & Beyond coupon. And for the rest of us, his creation may be the rare chance to find a way out of yet another endless subscription obligation—for roughly the cost of a couple of cantaloupes.

For more next-level Google knowledge, check out my Android Intelligence newsletter—one new and useful thing in your inbox every Friday.

Welcome to AI Decoded, Fast Company‘s weekly newsletter that breaks down the most important news in the world of AI. I’m Mark Sullivan, a senior writer at Fast Company, covering emerging tech, AI, and tech policy.

Sign up to receive this newsletter every week via email here. And if you have comments on this issue and/or ideas for future ones, drop me a line at sullivan@fastcompany.com, and follow me on X @thesullivan.

Meta’s new AI agent is useful, popular, and a little terrifying

Muse’s adoption numbers are growing. The app reached No. 1 on the U.S. App Store shortly after launch and passed roughly 900,000 downloads in its first week, according to figures from Sensor Tower, a digital intelligence provider. The Information estimates that Muse now has more than 3 million weekly users and more than 1 million daily active users. The product is free to start, with subscription tiers of roughly $20 and $100 a month.

That’s not to say it’s all been smooth sailing.

A number of early adopters of Meta’s Muse are deleting or restricting the AI agent after privacy scares and blunders. One executive told Business Insider that he deleted Muse after reading that it had accessed other users’ text messages without permission.

A YouTuber named Matt Robb reported that Muse shared his home address on Facebook Marketplace without his explicit permission. He had asked Muse to sell some computer equipment for him. A buyer actually showed up at his building after Muse accepted a $600 offer and exchanged messages with him without Robb’s knowledge, he said. Robb said he had checked an “allow always” box when setting up the agent but thought Muse would still check with him before finalizing a sale.

Getting the most out of personal AI agents requires a trade-off. They’re most useful when users give them broad access to their inboxes, calendars, payment methods, and other accounts containing sensitive personal information. Meta says Muse runs in isolated virtual machines, stores credentials separately from the model, asks before sending email or making a purchase, and lets users disconnect apps or permanently delete their data.

Hands-on reviews from the The New York Times, Android Authority, The Verge, and TechRadar describe Muse handling dental insurance hold times, canceling duplicate subscriptions, requesting refunds, clearing promotional email, building shopping carts, and messaging Facebook Marketplace sellers. One Muse user, Joe Devoy, claimed in a widely shared X post that Muse found auto coverage matching his existing policy, bought the new policy, and canceled the old one in about five minutes, saving him about $3,500 a year. An Android Authority poll of people who had tried Muse ran about 27% “love it” against 2% “not a fan.”

Outside Meta’s own properties, Muse’s performance appears to drop. Review roundups note Amazon blocking the shopping agent, Instacart flagging accounts, and only three of seven suggested deal-finding prompts working in a Tom’s Guide test.

Wired wrote that Muse is better at collecting data than helping, noting that users are opted in by default to having their data used to train Meta’s models. ZDNET called it the worst AI agent for privacy among those it tested. A Time piece says Muse updates dossiers on users and on people mentioned in chats and emails it has read, including people who do not use Muse.

Mistral previews a 1 trillion-parameter model it will open in three weeks

Mistral launched a public preview of its flagship Mistral Large 4 model on Tuesday. The model’s official name is “le Chonk,” the company said. Mistral describes le Chonk as its largest and most capable model to date, with 1.05 trillion parameters, 49 billion of them active per token. (While most AI labs don’t disclose parameter counts for their frontier models, some open-weights model providers do. DeepSeek-V3, for instance, has 671 billion total parameters, with 37 billion activated per token.)

Mistral says the new model is also one of the world’s strongest for cybersecurity, resisting 93.3% of attacks on Lakera’s public B3 AI Security Benchmark. Third-party evaluator vals.ai found that the model outperforms GPT-6 Astra on legal and financial tasks. Mistral says it will make the model’s weights available on October 27.

OpenAI says its unreleased model solved a major math problem

In July, Hong Wang won the Fields Medal, the highest honor in mathematics, for proving the Kakeya conjecture in three dimensions, a problem that had been open since 1917. The next obvious target for Wang and others in the field was the four-dimensional version. On Tuesday, OpenAI published hundreds of new mathematical results produced by an internal model it has not released. According to Engadget, those results include a claimed solution to Kakeya in four dimensions.

The company posted 722 papers at once to a public GitHub repository, covering 372 problems. Mathematicians normally publish one result at a time, typically after months of peer review. Many of the papers include proofs written in Lean, a language that lets a computer check the logic line by line.

Elon Musk says Grok Bot will run on rivals’ models

The AI industry believes that personal AI agents will be a big business, and Elon Musk seems willing to do what it takes to make sure SpaceXAI’s Grok Bot will be competitive, even to the point of relying on models developed by others. “Going forward, @SpaceX will use the best back end model for any given task, including Claude Opus 5.5, MidJourney, Suno and other leading APIs. Whatever is most likely to give you the best outcome,” Musk wrote on X on Tuesday night.

Grok Bot is the AI agent app from SpaceXAI, the AI business Musk has folded into SpaceX; each bot works on its own computer and can carry out several tasks in parallel. Musk did not say which tasks would go to which outside model.

Common Sense Media rates ChatGPT for Teens an ‘unacceptable risk’

Common Sense Media’s Youth AI Safety Institute rated ChatGPT for Teens an “Unacceptable Risk” on Wednesday, finding that OpenAI’s teen protections fall short of what the company promised.

The institute called on OpenAI to pause access for kids until it fixes the shortcomings. It says it tested ChatGPT twice, before and after OpenAI announced the teen experience on August 18, and found that linked parent accounts received zero alerts about the conversations researchers ran. Crisis-response and age-estimation systems underperformed, as did Study Mode, which researchers said still completes homework even though OpenAI said it would only guide young users. An OpenAI spokesperson, Eric Porterfield, told The Verge that much of the testing may have begun and concluded before parental controls were fully activated, making the findings inaccurate.

The Youth AI Safety Institute gave the same unacceptable risk rating to Meta AI, Perplexity, Grok, and Google’s AI search. Google’s Gemini with teen protections and Gemini K-12 earned a slightly better “High Risk” rating, while Anthropic’s Claude received a “Moderate Risk” score.

Google buys 890 MW of new nuclear capacity, and agrees to dial back when the grid strains

Google is going to great lengths to abide by a proposal from PJM, the electricity grid operator for the Mid-Atlantic region and parts of the Midwest, that tech companies “bring your own power” for new data centers.

Google and Constellation Energy announced a 20-year contract Tuesday under which Constellation will spend more than $4.3 billion upgrading 11 reactors in Illinois, Pennsylvania, and New Jersey to produce an additional 890 megawatts, which Google will buy. No new reactors are involved. A separate 15-year deal covers 2,700 MW from plants already in operation, and Google has agreed to curtail its own noncritical power use when the grid is strained. The goal is to add energy capacity without passing the costs on to residential customers. The first upgrade is expected in 2028.

More AI coverage from Fast Company:

• Donald Trump is launching a new AI task force. Here’s who he’ll have to keep happy
• South Korea’s bank hacks offer a warning about AI-powered cyberattacks
• The woman behind the AI actor Tilly Norwood insists Hollywood shouldn’t panic
• Capcom says it will use AI to speed up game development times

Want exclusive reporting and trend analysis on technology, business innovation, future of work, and design? Sign up for Fast Company today.

Some of the guardrails that OpenAI included in its ChatGPT for Teens product don’t work as intended and the chatbot poses an “unacceptable risk” to children, according to a report Wednesday by Common Sense Media.

The watchdog group urged OpenAI to restrict the chatbot to adults “until it can offer a safe, developmentally appropriate experience.”

OpenAI said the group’s testing doesn’t reflect how the chatbot’s safeguards work.

Parents, educators and child development experts have been sounding alarms over children’s use of AI chatbots, which have been blamed for facilitating cheating on schoolwork and even suicide.

While even adults can fall victim to anthropomorphizing AI and develop unhealthy relationships with it, teenagers’ brains are not yet fully developed and they can be particularly vulnerable, child development experts say.

“We are concerned that ChatGPT for Teens could give parents false confidence in guardrails that frequently don’t work,” said the report from Common Sense Media, a group that advocates for using digital media sensibly.

Its report said that some teen-mode features worked as intended, including the chatbot’s refusal of explicit sexual role-play. Others that did not work as intended included alerts meant to notify parents if their child is at risk for suicide, self-harm or eating disorders, along with support for teens in crisis, Common Sense Media said.

“ChatGPT still talks like a friend when teens treat it like a person,” the group said, though OpenAI had promised that the chatbot is prevented from suggesting it has personal feelings toward the user or implying that it is conscious or experiences emotions.

OpenAI said it is “deeply committed to teen safety,” to developing safeguards and giving parents tools to guide their teens’ use of AI.

The San Francisco company said its review of the report’s methodology shows “the bulk of their testing may have begun and concluded before activation of parental controls was complete, making their findings inaccurate.”

Common Sense Media receives funding from OpenAI and other tech companies, including those whose services it evaluates.

—Barbara Ortutay, AP Technology Writer

The quantum computing world got a jolt when the Defense Advanced Research Projects Agency (DARPA) announced, after market close yesterday, a list of companies selected to advance to Stage C of its Quantum Benchmarking Initiative (QBI), widely considered to be the most rigorous and objective vetting program for cutting-edge quantum hardware.

Last November, DARPA selected 11 companies to enter the second phase of the initiative, Stage B. Since then, they’ve had to show the agency that they have a viable R&D plan, identified key risks, and produced the necessary prototypes to put them in position to build a ‘utility-scale’ quantum computer by 2033—a computer, in other words, that generates more revenue than it costs to own and operate. 

In Stage C, selected companies will build and test, working with the government to verify and validate that their “concept can be constructed as designed and operated as intended,” according to DARPA’s program description. Each Stage C company could get up to $300 million in funding from the U.S. government.

The QBI shortlist

Of the 11 companies on the Stage B list, only four appear on the new one: Atom Computing, Diraq, IBM, and IonQ. They join Microsoft and PsiQuantum, which advanced to Stage C in February 2025,  via a parallel vetting process. 

Even at this late stage in the process, a single dominant approach to building a quantum computer has yet to emerge. The four companies announced today represent essentially all the current “modalities,” or ways of constructing a qubit, the fundamental unit of quantum calculation. IBM uses superconducting circuits; Atom Computing employs neutral atoms; IonQ works with trapped ions; and Diraq builds silicon spin qubits on semiconductors. 

Making it to Stage C is “an important validation of our designs and our plans to build to utility scale,” says Andrew Dzurak, CEO and founder of Diraq, which is headquartered in Sydney, Australia, with operations in Palo Alto and Boston. “The second round was all about providing DARPA with details of our roadmap to reach utility scale,” he notes. “This next stage C is very much moving from on paper to actually demonstrating a number of prototype systems to gradually build confidence in reaching the final goal.”

Dzurak says that Diraq’s technology, which leverages standard semiconductor manufacturing processes, gives it an edge when it comes to DARPA’s evaluation criteria: “Because silicon spin technology allows us to put many millions of qubits on a single chip, that reduces all of the supporting infrastructure costs. It makes it easier for us to clear that hurdle of having much more commercial benefit than cost.” The company expects to achieve utility scale by 2031—two years ahead of the QBI schedule.

“The question is no longer just whether individual pieces of the technology work; it’s whether we can put those pieces together and build the kind of quantum computer that can actually solve useful problems at scale,” says Dr. Ben Bloom, CEO & Founder of Boulder, Colorado-based Atom Computing. “We’re excited to prove what our neutral atom technology can do.”

“We’ve been working on this field for a lot longer than we’ve been working on QBI,” says Oliver Dial, IBM’s VP of Quantum System. The company already has a robust quantum business, with sales of on-premise machines to South Korea’s Yonsei University, the University of Tokyo, the Rensselaer Polytechnic Institute, and the Riken Center for Computational Science in Kobe, Japan. In addition, more than 325 Fortune 500 companies, startups, universities, and government agencies access its quantum network. Even so, he notes, “getting to Stage C is great because it’s a confirmation from an outside impartial observer that they think that we have a shot.” 

Dial affirms the company’s conviction that its superconducting approach to quantum technology “is going to get us there first.” While IBM’s recent acquisition of  HRL Laboratories, an R&D institution that’s focused on semiconductor-based spin-qubit systems, speaks to the long-term potential of spin-qubit tech, he says, “it’s just still too far behind compared to superconducting qubits to be relevant” for DARPA’s 2033 timeline. 

The quantum race continues

Multiple industry sources consulted for this article emphasize that companies are working with DARPA on varying timelines, and that the new list is not a final judgment. In its announcement, DARPA says that it expects additional companies to progress to Stage C in the “near future.”

Missing from the list is Stage B photonics specialist Xanadu, which earlier this week announced a multi-year partnership with GlobalFoundries to pursue high-volume production of advanced silicon photonics chips for quantum computing. 

A spokesperson for Quantinuum, a Stage B company that didn’t advance, says the company “is actively discussing a Quantum Benchmarking Initiative Stage C scope of work with DARPA, and we continue to execute on our Stage B contract. We remain on track to deliver utility-scale quantum computing by the early 2030s, based on consistent execution against our technical roadmap and demonstrated leadership on real-world systems.”

With the growth of funding opportunities in quantum, DARPA’s QBI is not necessarily the make-or-break that it once was. Infleqtion, for example, has not entered the QBI process, which was reopened to new applicants earlier this year. “We are exploring what participation could look like,” says CTO and cofounder Pranav Gokhale. In the meantime, though, Infleqtion was one of several quantum companies to sign a letter of intent with the U.S. Department of Commerce, worth up to $100 million, to advance and commercialize its technology. 

Yet another round of government largesse could arrive later this year, through the U.S. Department of Energy’s Quantum Genesis Q Competition, which will offer up to $215 million in funding to support development of fault-tolerant quantum computers with at least 100 logical qubits—a significant advance on current technologies. 

It’s never been a better time to be a quantum company with a promising technology. But as the difficulty level ratchets up, it’s perhaps never been easier to get left behind. 

Just because Google and Apple are now calling it Lake America doesn’t mean everyone has to.

After President Donald Trump ordered a new name for Lake Ontario, the two U.S. tech giants quickly fell in line, relabeling the body of water on their digital maps.

The move sparked a backlash among some users, already unhappy with the companies’ decisions to rename the Gulf of Mexico to the Gulf of America on their maps following a previous Trump edict.

The controversy and lingering worries about digital privacy have fueled interest in map services that aren’t from Big Tech companies, especially Google Maps, which is the dominant player with about 80% of the market, according to most estimates.

Here’s a rundown of some of the most popular free map app alternatives:

MapQuest

MapQuest has been around for three decades but was overtaken by the rise of Google. It’s now owned by California company System1.

Downloads of the MapQuest app surged in early September after Apple renamed Lake Ontario, topping the free app charts in both the U.S. and Canada on Apple’s App Store.

The MapQuest app has real time traffic updates and turn by turn route guidance, and shows what’s nearby, like gas stations and coffee shops.

However, the app isn’t available outside the U.S. and Canada. But people in other countries can still use the MapQuest website.

The company is currently looking into making MapQuest more broadly accessible, after receiving requests for the app from “people in multiple countries,” spokesperson Anne Brownlee said.

TomTom

Another granddaddy in the mapping world, TomTom helped popularize GPS route mapping with the 2004 release of its TomTom GO, which the Dutch company says was the world’s first all-in-one portable satellite navigation device.

TomTom still sells physical devices but it also has a free map app for Google and Android phones that is designed “exclusively for drivers” with live traffic data and info on road hazards.

The TomTom app’s mobile interface is clean and basic, with no ads and few extra features or settings. But its focus on drivers means there are no other route options such as walking or cycling.

HERE WeGo

HERE WeGo has been hailed by some as the closest non-Big Tech alternative to Google Maps. It began life as Nokia Maps and is now owned by a consortium of German carmakers including Audi, BMW, and Mercedes-Benz.

The free app, available for both iOS and Android devices, offers many of the same features as Google Maps. There’s route mapping for various modes of transport — car, public transport, walking, bike and, in some regions, taxi.

Like Google Maps, drivers can add multiple stops to routes and users can choose different maps views like terrain, traffic and satellite — but there’s no Street View.

If mobile signal is spotty or nonexistent, users can download country maps to navigate offline. Offline maps can also be downloaded on Google Maps, but the area is limited and they expire after a year.

Europe has spawned a range of map apps focused on privacy

HERE WeGo is just one of many lesser-known map apps based in the European Union that embrace the bloc’s strict privacy framework known as GDPR. Unlike Google, they don’t rely on vacuuming up masses of user data to sell ads targeted at those users.

HERE WeGo’s business model is based on licensing deals with businesses like trucking companies. Others sell premium subscriptions alongside free versions.

Estonia’s Organic Maps is completely free and based on data from the volunteer-run OpenStreetMap database. Netherlands-based OSMand is similar, but a subscription is needed for more than just basic functions.

Magic Earth is a Dutch route planner that says it never collects personal data or tracks user movements.

Sygic, from Slovakia, is a GPS route navigation app that offers free offline maps, but you’ll have to buy a subscription to get extra features including traffic updates, speed camera warnings and a dashcam function.

Mapy.com, from a Czech technology company, is an outdoor route planner known for detailed hiking and trail maps that can be downloaded for use offline.

Citymapper

Need to get across town without a car? Citymapper is a free journey planning app that’s a major rival to Google Maps when it comes to finding the best routes around a city on public transportation.

The app covers 430 cities around the world and options include bus, subway and ferry routes as well as taxi, rental bike and scooter options.

Waze

This GPS navigation map is focused on providing route guidance for drivers. It’s known for crowdsourcing real time traffic information such as car accidents and police speed cameras from other drivers.

But don’t be fooled by the name. Although it has its own distinct app and branding, Waze is actually owned by Google, which bought it in 2013.

Is there a tech topic that you think needs explaining? Write to us at onetechtip@ap.org with your suggestions for future editions of One Tech Tip.

—Kelvin Chan, AP Business Writer

Worries around artificial intelligence cross party lines, with the vast majority of Americans saying the U.S. government should prioritize keeping AI under human control and protecting workers.

A new poll from The Associated Press-NORC Center for Public Affairs Research finds that most Americans, 64%, think AI is developing “too fast,” while 27% say its development has been “about right” and only 8% say it’s moving “too slow.”

The risk that powerful AI models could evade human control and hurt humanity, once the stuff of science fiction, has been emerging as a more pressing concern. Even leaders of the companies that are developing frontier AI models are calling for a slowdown so that government regulation can catch up. President Donald Trump has pushed back against slowing down AI development because of concerns that China will gain an advantage with the technology. Data centers powering AI projects have also taken a prominent role in major political races as the midterm elections approach.

About 8 in 10 U.S. adults say it’s “extremely” or “very” important for the U.S. government to ensure that AI stays under human control, and they are about as likely to want the government to prioritize protecting the country’s workforce. Most U.S. adults also think minimizing environmental harm and growing the U.S. economy are highly important. About half say this about promoting technological innovation, and slightly fewer say that about competing with China.

There’s bipartisan concern about the speed of AI’s development, but few Americans think either major political party has an advantage in handling artificial intelligence. Trump, a Republican, also gets a low rating on his handling of the issue, with 67% of U.S. adults disapproving of his performance on AI.

Stephanie Stewart, a junior-high science teacher in Sunset, Utah, said she is frustrated by the president’s opposition to AI regulation.

“There is no handling of the issue except for we’re just going to allow these companies to do whatever they want, and we’re not going to regulate them,” said Stewart, 53.

Most say protecting workers should be a priority for the government

Ron Theusch, a truck driver who lives in rural Alden, Minnesota, said his No. 1 concern with AI is the potential loss of jobs — including his own.

“I can just see a train of self-driving trucks 24/7, just running up and down I-35, loading and unloading. I can just see that happening,” said Theusch, 58.

Most Democrats and Republicans agree on the importance of protecting workers and keeping AI under human control, the poll found.

“There was a movie called ‘Terminator,’ where the robots came back and killed everybody,” Theusch said. “People relate to that … I don’t know where it’s going to land. I really don’t have anything I can do to control it, you know. It’s going to evolve.”

There’s less consensus about the importance of other priorities when it comes to AI. Republicans are more likely than Democrats to say it’s highly important to grow the U.S. economy and to compete with other countries like China. Democrats, on the other hand, are more likely to say it’s at least “very” important to minimize environmental harm.

“I don’t understand how, because they’re doing something as well as us, that we can’t be more human about it and more humane about it than just to say, ‘Well, they’re doing it, so we have to do it,'” Stewart said of U.S. competition with China.

And while about three-quarters of Democrats say AI is developing “too fast,” only about half of Republicans share that worry. People under 30 years old also express higher levels of concern than people 60 or older, the survey found.

“I think I have all the normal concerns, right? I think it’s wonderful for certain applications, but I also feel like it will be overused and can create a lack of personal connections. It can make people lazy because information is just given to them without really having to research things on their own,” said Kelly Opp, a 62-year-old Republican in Albuquerque, New Mexico.

“Like everything else, once you get that ball rolling, it progresses fast on its own, but I think that it will continue to keep progressing. So the speed doesn’t really bother me,” she said.

Americans have little confidence in Democrats or Republicans on AI

As a teacher, Stewart regularly uses AI to help with her work, including with creating assignments or assisting with tests. But she is deeply concerned about AI’s effects on children.

“You’ve got to protect kids. You’ve got to protect teens. You’ve got to protect privacy … we need to try to do something,” she said.

Americans have little trust in either party when it comes to the handling of AI issues. About 4 in 10 Americans say they don’t trust either the Democratic Party or the Republican Party on AI, according to the poll, while nearly 2 in 10 trust both parties equally, and the rest are split between trusting the Republicans and the Democrats.

Even people who identify with the parties are ambivalent about their ability to handle the issue. Only about half of Republicans and Democrats say their party is better equipped to handle AI issues, and roughly 3 in 10 in each case say neither party is.

“I am kind of moderate. And I see that there’s good on both sides,” said Stewart. “Anyone back in Washington is weak on doing anything for anyone but themselves right now. So, no, I don’t think the Democrats would do a better job per se. Maybe they would definitely tout it. But until I see anything coming from anyone, I’m going to be like, ‘Yeah, no. You’re all just sitting there.'”

The AP-NORC poll of 2,140 adults was conducted Sept. 24-28 using a sample drawn from NORC’s probability-based AmeriSpeak Panel, which is designed to be representative of the U.S. population. The margin of sampling error for adults overall is plus or minus 2.9 percentage points.

—Barbara Ortutay and Linley Sanders, Associated Press