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Tech giants are making grand promises for the AI age. The technology, we are told, might discover a new generation of medical interventions, and possibly answer some of the most difficult questions facing physics and mathematics. Large language models could soon rival human intellectual abilities, they claim, and artificial superintelligence might even best us. This is exciting, but also scary, they say, since the rise of AGI, or artificial general intelligence, could pose an uncontrollable threat to the human species. U.S. government officials working with AI, including those charged with both implementing and regulating the tech in the government, are taking a different tack. They admit that the government is still falling behind the private sector in implementing LLM tech, and there’s a reason for agencies to speed up adoption. Still, many question the hyperbolic terminology used by AI companies to promote the technology. And they warn that the biggest dangers presented by AI are not those associated with AGI that might rival human abilities, but other concerns, including unreliability and the risk that LLMs are eventually used to undercut democratic values and civil rights. Fast Company spoke with seven people whove worked at the intersection of government and technology on the hype behind AIand what excites and worries them about the technology. Heres what they said. Charles Sun, former federal IT official Sun, a former employee at the Department of Homeland Security, believes AI is, yes, overhypedespecially, he says, when people claim that AI is bigger than the internet. He describes the technology simply as large-scale pattern recognition powered by statistical modeling, noting AIs current wave is impressive but not miraculous. Sun argues that the tech is an accelerator of human cognition, not a replacement for it. I prefer to say that AI will out-process us, not outthink us. Systems can already surpass human capacity in data scale and speed, but intelligence is not a linear metric. We created the algorithms, and we define the rules of their operation. AI in government should be treated as a critical-infrastructure component, not a novelty, he continues. The danger isnt that AI becomes ‘too intelligent,’ but that it becomes too influential without accountability. The real threat is unexamined adoption, not runaway intelligence. Former White House AI official I was worried at the beginning of this . . . when we decided that instead of focusing on mundane everyday use cases for workers, we decided at a national security front that we need to wholesale replace much of our critical infrastructure to support and be used by AI, says the person, who spoke on background. That creates a massive single point of failure for us that depends largely on compute and data centers never failing, and models being impervious to attacksneither of which I don’t think anyone, no matter how technical they are or not, would place their faith in. The former official says theyre not worried about AGI, at least for now: Next token prediction is not nearly enough for us to model complex behaviors and pattern recognition that we would qualify as general intelligence. David Nesting, former White House AI and cybersecurity adviser AI is fantastic at getting insights out of large amounts of data. Those who have AI will be better capable of using data to make better decisions, and to do so in seconds rather than days or weeks. Theres so much data about us out there that hasnt really hurt us because nobodys ever really had the tools to exploit it all, but thats changing quickly, Nesting says. Im worried about the government turning AI against its own people, and Im worried about AI being used to deprive people of their rights in ways that they cant easily understand or appeal. Nesting adds: Im also worried about the government setting requirements for AI models intended to eliminate ‘bias,’ but without a clear definition of what ‘bias’ means. Instead, we get AI models biased toward some ‘official’ ideological viewpoint. Weve already seen this in China: Ask DeepSeek about Tiananmen Square. Will American AI models be expected to maintain an official viewpoint on the January 6th riots? I think were going to be arguing about what AGI means long after its effectively here, he continues. Computers have been doing certain tasks better than people for nearly a century. AI is just expanding that set of tasks more quickly. I think the more alarming milestone will be the point at which AI can be exploited by people to increase their own power and harm others. You dont need AGI for that, and in some ways were already there, Nesting says. Americans today are increasingly and unknowingly interacting online with fake accounts run by AI that are indistinguishable from real peopleeven whole communities of peopleconfirming every fear and anxiety they have, and validating their outrage and hatred. Abigail Haddad, former member of the AI Corps at DHS The biggest problem currently, Haddad argues, is that AI is actually being underused in government. An immense amount of work went into making these tools available inside of federal agencies, she notes, but whats available in the government is still behind whats available commercially. There are concerns about LLMs training on data, but those tools are operating on cloud systems that follow federal cybersecurity standards. People who care about public services and state capacity should be irate at how much is still happening manually and in Excel, she says. Tony Arcadi, former chief information officer of the Treasury Department Computers are already smarter than us. It’s a very nebulous term. What does that really consist of? At least my computer is smarter than me when it comes to complex mathematical calculations, Arcadi says. The sudden emergence of AGI or the singularity, there’s this thing called Rokos basilisk, where the AI will go back in time andI don’t remember the exact thingbut kill people who interfered with this development. I don’t really go for all of that. He adds: The big challenge that I see leveraging AI in government is less around, if you will, the fear factor of the AI gone rogue, but more around the resiliency, reliability, and dependability of AI, which, today, is not great. Eric Hysen, former chief information officer at DHS When asked a few months ago about whether AI might become so powerful that the process of governing might be offloaded to software, Hysen shared the following: I think there is something fundamentally human that Americans expect about their government. . . . Government decision-making, at some level, is fundamentally different than the way private companies make decisions, even if they are of very similar complexity. Some decisions, he added, “we’re always going to want to be fundamentally made by a human being, even if i’s AI-assisted in a lot of ways. It’s going to look more long term like heavy use of AI that will still ultimately feed for a lot of key things to human decision makers. Arati Prabhakar, former science and technology adviser to President Biden Prabhakar, who led the Office of Science and Technology Policy under President Joe Biden, is concerned that the conversation about AGI is being used to influence policy around the technology more broadly. Shes also skeptical that the technology is as powerful as people foretell. I really feel like Im in a freshman dorm room at 2 in the morning when I start hearing those conversations, she says. Your brain is using 20 or 25 watts to do all the things that it does. That includes all kinds of things that are way beyond LLMs. [Its] about 25 watts compared to the mega data centers that it takes to train and then to use AI models. Thats just one hint that we are so far from anything approximating human intelligence, she argues. “Most troubling is it puts the focus on the technology rather than the human choices that are being made in companies by policymakers about what to build, where to use it, and what kind of guardrails really will make it effective.” This story was supported by the Tarbell Center for AI Journalism.
Category:
E-Commerce
President Trump recently promised to make America the “crypto capital of the world.” And his administration is working hard to make that pledge a reality. White House officials have established a working group on digital asset markets and directed federal agencies to craft a strategy to cement U.S. leadership. The president’s legislative team, meanwhile, helped push the GENIUS Act (Guiding and Establishing National Innovation for U.S. Stablecoins Act),through Congress earlier this summer, thus creating the first federal framework for stablecoins. And they’re working to pass the Clarity Act (Digital Asset Market Clarity Act), which would finally settle disputes over which regulator oversees digital assets. It’s refreshing to see our political leaders working to bring digital assets into the financial mainstream, especially after years of hostility from the prior administration. But the work is far from finishedand achieving universal legitimacy will require not just favorable laws and regulations, but also behavioral changes at leading crypto firms. Conflicting guidance For more than a decade, crypto innovators faced a patchwork of state regimes and conflicting federal guidance. The lack of clear regulation led to a proliferation of scams and bad actorsand kept many investors on the sidelines. Big banks and other legacy financial institutions hesitated to adopt cryptocurrencies and the underlying blockchain technology they’re based on, even as top financiers acknowledged blockchain’s potential to reshape the entire industry. The GENIUS Act represents Washington’s first serious attempt to genuinely regulaterather than ignore or suppressone of the leading forms of cryptocurrency. The new law requires stablecoin issuers to maintain dollar-for-dollar reserves and submit to audits. Far from rejecting this level of regulation, crypto leaders practically begged for it. They recognized that federal oversight and transparent standards are needed to transform what the public previously viewed as a speculative product into a reliable payment instrument. That’s why industry leaders are also working with the White House and Congress to finalize the Clarity Act, which would define the boundaries of authority between the Securities and Exchange Commission and the Commodity Futures Trading Commission, delivering the kind of predictability that underpins every functioning capital market. Cultural shift But better regulation alone won’t bring about the mainstream approval that industry leaders seek. Only an internal cultural shiftand rigorous self-policingcan deliver that. Every blockchain transaction depends on various forms of intellectual propertyfrom patents on mobile crypto wallets and bitcoin mining data centers to trade secrets in proprietary trading algorithms, and copyrights protecting exchange software to trademarks that build consumer trust. Coinbase, for instance, holds nearly 200 active patents. But most of the intellectual property powering today’s blockchain activity belongs to third parties outside the crypto industry. Yet even as leading platforms generate billions in revenue, the industry remains reluctant to acknowledge the legitimacy of IP rights. This reluctance is playing out in court. In May, Bancor’s nonprofit arm sued Uniswap, alleging that the leading decentralized exchange built its multibillion-dollar business on Bancor’s patented automated market maker technology without authorization. And earlier this summer, Malikie Innovations filed suits against Core Scientific and Marathon Digital, claiming their bitcoin mining operations infringe on Malikie’s patents for elliptic curve cryptography. Elliptic Curve Cryptography (ECC), a cryptographic technique developed and patented by Certicom years before crypto went mainstream, was licensed by companies like Cisco and Motorola as well as the National Security Agency. Cases like these highlight the tension: Crypto companies depend on IP to function, but too many are willing to disregard the IP rights of others, even as they clamor for legitimacy. Not how respectable companies operate This simply isn’t the way respectable companies in mature industries operate. Spotify and Apple Music wouldn’t enjoy their positive reputations if they refused to pay royalties to artists and record labels. Streaming platforms like Netflix and Hulu would be pariahs if they pirated films. Banks would be shunned by investors alike if they treated software licenses as optional. If leading crypto firms want to be seen as respectable, investable pillars of the global economy, they need to meet those same standards when it comes to intellectual property. Digital assets are here to stay. But universal legitimacy will come only from a combination of comprehensive regulation and a cultural shift within the industry itself.
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E-Commerce
If you slip a tiny wearable device on your fingertip and slide it over a smooth surface like a touchscreen, you can feel digital textures like denim or mesh. The device, designed by researchers at Northwestern University, is the first of its kind to achieve human resolution, meaning that it can more accurately match the complex way a human fingertip senses the world. In previous attempts at haptic devices like this, once you compare them to real textures, you realize theres something still missing, says Sylvia Tan, a PhD student at Northwestern and one of the authors of a new study in Science Advances about the research. Its close, but not quite there. Our work is trying to just get that one step closer. [Photo: Northwestern University] The wearable, made from flexible, paper-thin latex, is embedded with tiny nodes that push into the skin in a precise way and can move up to 800 times per second. Past devices had low resolutionthe touch equivalent of a pixelated image or an early movie from the 1890s with so few frames that the movement looks jerky. Using nodes and arranging them in a particular density improves that resolution. [Photo: Northwestern University] Earlier devices were also bulky. The ultrathin new technology, which weighs less than a gram, is designed to be comfortable to wear. A big goal was to make it very lightweight so you arent distracted by it, Tan says. And [to make] something that we call ‘haptically transparent’that means that even when youre wearing it, you can still perceive the real world, so you can perform everyday tasks. [Photo: Northwestern University] In the study, users could identify fabrics like corduroy or leather with 81% accuracy. The technology is still in development, but in the future, it could make it possible to feel products as you shop online. It could also have more immediate uses for people who are visually impaired, like making it possible to feel a tactile map or translating text on a screen to braille without a large, expensive device. On devices like microwaves, where physical buttons have often been replaced by flat touchscreens, the wearable could help a visually impaired person know where to push. It could also help improve human-robot interfaces. “In the medical field, the Da Vinci robot has very good kinesthetic force feedback,” Tan says. “But getting a surgeon to feel exactly what’s happening at your fingertip as you move the angle of your finger is not quite there. And that’s very important for high-skill workers.”
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E-Commerce
When it comes to podcasting, it’s Joe Rogan’s world. The Joe Rogan Experience was the most popular podcast of 2025, according to Apple’s just-released rankings. This is the first year Rogan has topped the Apple charts. Last year, he took the bronze medal, behind The Daily and Crime Junkie (both of which still made the Top 10 this year). Two years ago, he didn’t make the list (thanks to an exclusivity agreement with Spotify, signed in 2020where he also currently holds the No. 1 spot). Rogan’s podcast certainly had head-turning guests this year, including a much-listened-to interview with Elon Musk. The Daily, from The New York Times, was Apple’s second-most popular podcast this year, with The Mel Robbins Podcast debuting at No. 3, after not making the list in 2024. Robbins, whose podcast offers advice to people who want to change their lives, said she was shocked by the high placement. (Her podcast was also the most followed show on Apple in 2025 and had the most shared episode.) “I just cant believe it,” she wrote to listeners on social media. “Our small team, you, and this global community turned this little podcast that started in a room above my garage into one of the biggest podcasts in the world. I am so proud and so grateful.” Alex Coopers Call Her Daddy and The Ezra Klein Show were the other new additions to the 2025 list. True crime, news, and big podcasting names dominated the top shows. Here’s how the list ranked the podcasts for 2025. The Joe Rogan Experience The Daily The Mel Robbins Podcast Crime Junkie Dateline NBC SmartLess Call Her Daddy This American Life Huberman Lab The Ezra Klein Show Amy Poehler’s Good Hang with Amy Poehler was the top new podcast of the year, followed by Not Gonna Lie with Kylie Kelce and several true-crime offerings. Among Apple’s top series, The Telepathy Tapes, which investigates the controversial claim that some nonspeaking individuals with autism have telepathic abilities, was the leader. That podcast, hosted by Ky Dickens, has been particularly polarizing among listeners, with some listening obsessively and many calling it a grift. “An incredible and humbling honor,” the podcast team wrote on social media. “Thank you to everyone who shared, listened, and opened their minds. We are so beyond grateful for all of the listeners.” The most surprising ranking of the list, though, was likely the podcast that didn’t top the charts. Among the most listened-to podcast episodes of the year, Taylor Swift’s appearance on New Heights with Jason & Travis Kelce only ranked third, behind offerings from The Telepathy Tapes and Crime Junkie. In fairness, the Swift podcast aired in August, while The Telepathy Tapes episode that topped the list was from September 2024 and the Crime Junkie episode was from April, giving both more time to gather listeners. Here’s how the other lists ranked this year. Top new shows Good Hang with Amy Poehler Not Gonna Lie with Kylie Kelce Deadly Mirage Blink: Jake Haendels Story Murder in the Moonlight Devil in the Desert What Happened to Holly Bobo? Cold Blooded: Mystery in Alaska Unicorn Girl The Best People with Nicolle Wallace Top series The Telepathy Tapes The Binge Cases Deadly Mirage Blink: Jake Haendels Story Dateline Originals Murder in the Moonlight Serial Three Devil in the Desert CounterClock Top episodes The Telepathy Tapes: Unveiling the Hidden World of Telepathic Communication in a Silenced Community Crime Junkie: Murdered: The Feeney Family New Heights with Jason & Travis Kelce: The Taylor Swift Episode The Joe Rogan Experience: #2223 Elon Musk The Daily: Trump, Again Blink: Jake Haendels Story: Blink Deadly Mirage: Death in the High Desert SmartLess: Amy Poehler Good Hang with Amy Poehler: Tina Fey Murder in the Moonlight: In Cold Blood
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E-Commerce
If there’s an AI application in media that has had a rough road, it’s the chatbot. With the runaway success of ChatGPT, the whole idea that chat might be the next big thing in audience experiences took on new value, and several publications dove in, offering portals or widgets that enable readers to explore their content in a new way. I think it’s fair to say none of these have been home runs, but some are more promising than others. Chatbots from Skift, USA Today, and The Texas Tribune have all seen some quiet success in user engagement, and while “chat” likely won’t save the media industry, it may well play an important role. Beyond the wins of improving site search and providing unique audience data, publisher-owned AI chat experiences may chart a path to the most mythical of all beasts in the AI era: the new business model. This is where Times new AI Agent comes in. Time recently unveiled a new AI experienceyes, a chatbot, but one trained on the entirety of Times archive, about 750,000 articles going back to 1923. It has common AI-powered features like summarization, translation, and the ability to read an audio version of the article, but the main point is that the foundation of its knowledge base is a large corpus of human-verified journalism. Right now it’s deployed only on politics and entertainment stories, according to Axios. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}} Times Agent vs. Perplexity I’ve been trying out the Agent to see if it provides a better experience than a more generic AI portal like Perplexity or ChatGPTevaluating the outputs by looking at accuracy, recency, structure, and sourcing. Exploring the topic of the recent government shutdown and how it compares to other shutdowns in the past, I queried the Agent with the following prompt: Give me a briefing on the history of U.S. government shutdowns, breaking down succinctly why each happened, when they happened, how long they lasted, and which party was presumed to have “won.” It responded in six lengthy bullet points, each one summarizing the shutdown across the dimensions I asked for, along with a journalistic caveat at the end saying, “Time’s coverage emphasizes that winners are often a matter of political framing rather than an objective metric.” When I asked for the breakdown as a table, it said it wasn’t able to create one, though it created a more structured, numbered list as a consolation prize. Specific Time articles were linked in each bullet. The Agent appeared a bit challenged to bring up-to-the-minute information to the query. Absent from its summary was any mention that the shutdown was on the verge of ending (I performed these searches on November 12), and it was imprecise about the length, twice saying it had lasted 35-plus days. To be fair, that figure is probably what’s most relevant to the query, since day 35 is what made the shutdown the longest in history, and the query itself is clearly focused on historical data rather than what’s happening now. On Perplexity, the chatbot responded with a table as the primary output, plus it was more precise about the shutdown’s current length (43 days) and mentioned a tentative deal had been reached. The response had less prose overall, and it harvested the information from several different sources (the main feature of Perplexity), including Wikipedia, CBS News, ABC News, CNN, NPR, and others. The (AI) business of information Based on what I experienced, I’d probably call it a tie, so points to Time and its partners at Scale AI for creating a user experience comparable to a multibillion-dollar company. But user experience is only one dimension of why you’d turn to Times AI Agent. The real value is in: The reliability of the information. As I said at the outset, because the Agent is “grounded” on the publisher’s content, which is guided by journalistic standards, it has the advantage of not potentially being skewed by unreliable sources. That doesn’t mean it doesn’t ever hallucinate or make errors of omission, but it’s starting with verified raw material. The licensing of that information. While everyday consumers typically aren’t concerned with whether the AI chatbot they’re using respects copyright, businesses who want to build on top of AI products are. By targeting the Agent solely at its archive, Time is addressing a key fear of any partners: Will they be held liable for surfacing content that doesn’t belong to them? That provenance is especially important for compliance teams in regulated industries that want to plug an agent like this into internal research tools or customer-facing products. All this points to the deeper strategy behind just launching a new reader experience with the “agent” label. If Times archive can power an AI experience to visitors of its website, that can also be adapted to anyone who wants to pay for it. And it wouldn’t require handing over any IPonce a deal is signed, you’d need to create just a simple technical handshake, presumably via MCP (model context protocol) between a client’s front end and Times Agent. A bank, for instance, could wire the Agent into its internal policy portal so staff can query vetted news content without ever leaving the companys systems. This is conceptually similar to the licensing deals that Time and others have already signed with AI companies like OpenAI, but it’s technically different in an important way. A typical licensing agreement involves permission (often retroactive) to use the site’s content for training, plus access to the site for AI search crawlers so it can summarize news stories in response to user queries. Those searches rely greatly on metadata, the process is far from comprehensive, and there is limited visibility in how the content is used. A better system would mean the publisher owns the agent layer and interface, which is what Time has done. Once you’ve done the hard work of formatting, ingesting, and processing your archive for AI, it makes its information much more reliable and easy for systems to parse, and you can choose to license it on yor own terms. That has an effect on the overall power dynamic of any deals; the publisher now becomes a tool vendor as much as a content supplier. So new kinds of deals are possible, but the question is: Will anyone make them? Time has a big archive, but it’s still small compared to the entire news output of the media industrysomething ProRata is closer to building with its Gist search engine (which also includes Time). Then again, if buyers can get what they need from only a few specific sources, why not just pay for access to those and be done with it? This mirrors the age-old debate around cable channels: Will customers of this kind of information want to get it as a bundle, or la carte? Either way, the transformation of big archives into AI-ready corpuses, easily plugged into information portals (public or private), could end up being a large part of how media companies monetize their content in the future. Creating new business models is a phrase that gets tossed around all the time in the media, but hardly ever seen, kind of like Bigfoot. We might have just had a sighting. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}}
Category:
E-Commerce
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