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Russia has attempted to fully block WhatsApp in the country, the company said, the latest move in an ongoing government effort to tighten control over the internet.A WhatsApp spokesperson said late Wednesday that the Russian authorities’ action was intended to “drive users to a state-owned surveillance app,” a reference to Russia’s own state-supported MAX messaging app that’s seen by critics as a surveillance tool.“Trying to isolate over 100 million people from private and secure communication is a backwards step and can only lead to less safety for people in Russia,” the WhatsApp spokesperson said. “We continue to do everything we can to keep people connected.”Russia’s government has already blocked major social media like Twitter, Facebook, and Instagram, and ramped up other online restrictions since Russia’s full-scale invasion of Ukraine in 2022.Kremlin spokesman Dmitry Peskov said WhatsApp owner Meta Platforms should comply with Russian law to see it unblocked, according to the state Tass news agency.Earlier this week, Russian communications watchdog Roskomnadzor said it will introduce new restrictions on the Telegram messaging app after accusing it of refusing to abide by the law. The move triggered widespread criticism from military bloggers, who warned that Telegram was widely used by Russian troops fighting in Ukraine and its throttling would derail military communications.Despite the announcement, Telegram has largely been working normally. Some experts say it’s a more difficult target, compared with WhatsApp. Some Russian experts said that blocking WhatsApp would free up technological resources and allow authorities to fully focus on Telegram, their priority target.Authorities had previously restricted access to WhatsApp before moving to finally ban it Wednesday.Under President Vladimir Putin, authorities have engaged in deliberate and multipronged efforts to rein in the internet. They have adopted restrictive laws and banned websites and platforms that don’t comply, and focused on improving technology to monitor and manipulate online traffic.Russian authorities have throttled YouTube and methodically ramped up restrictions against popular messaging platforms, blocking Signal and Viber and banning online calls on WhatsApp and Telegram. In December, they imposed restrictions on Apple’s video calling service FaceTime.While it’s still possible to circumvent some of the restrictions by using virtual private network services, many of them are routinely blocked, too.At the same time, authorities actively promoted the “national” messaging app called MAX, which critics say could be used for surveillance. The platform, touted by developers and officials as a one-stop shop for messaging, online government services, making payments and more, openly declares it will share user data with authorities upon request. Experts also say it doesn’t use end-to-end encryption. Associated Press
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E-Commerce
Daniel Kokotajlo predicted the end of the world would happen in April 2027. In AI 2027 a document outlining the impending impacts of AI, published in April 2025 the former OpenAI employee and several peers announced that by April 2027, unchecked AI development would lead to superintelligence and consequently destroy humanity. The authors, however are going back on their predictions. Now, Kokotajlo forecasts superintelligence will land in 2034, but he doesnt know if and when AI will destroy humanity. In AI 2027, Kokotajlo argued that superintelligence will emerge through fully autonomous coding, enabling AI systems to drive their own development. The release of ChatGPT in 2022 accelerated predictions around artificial general intelligence, with some forecasting its arrival within years rather than decades. These predictions accrued widespread attention. Notably, JD Vance, U.S. vice president, reportedly read AI 2027 and later urged Pope Leo XIV who underscored AI as a main challenge facing humanity to provide international leadership to avoid outcomes listed in the document. On the other hand, people like Gary Marcus, emeritus professor of neuroscience at New York University, disregarded AI 2027 as a work of fiction, even calling various predictions pure science fiction mumbo jumbo. As researchers and the public alike begin to reckon with how jagged AI performance is, AGI timelines are starting to stretch again, according to Malcolm Murray, an AI risk management expert and one of the authors of the International AI Safety Report. For a scenario like AI 2027 to happen, [AI] would need a lot of more practical skills that are useful in real-world complexities, Murray said. Still, developing AI models that can train themselves remains a steady goal for leading AI companies. Sam Altman, OpenAI CEO, set internal goals for a true automated AI researcher by March of 2028. However, hes not entirely confident in the companys capabilities to develop superintelligence. We may totally fail at this goal, he admitted on X, but given the extraordinary potential impacts we think it is in the public interest to be transparent about this. And so, superintelligence may still be possible, but when it arrives and what it will be capable of remains far murkier than AI 2027 once suggested. Leila Sheridan This article originally appeared on Fast Company‘s sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
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E-Commerce
For most of modern finance, one number has quietly dictated who gets ahead and who gets left out: the credit score. It was a breakthrough when it arrived in the 1950s, becoming an elegant shortcut for a complex decision. But shortcuts age. And in a world driven by data, digital behavior, and real-time signals, the score is increasingly misaligned with how people actually live and manage money. Were now at a turning point. A foundational system, long considered untouchable, is finally being reconstructed by using AIspecifically, advanced machine learning models built for risk predictionto extract more intelligence from existing data. These are rigorously tested, well-governed systems that help lenders see risk with greater nuance and clarity. And the results are reshaping core economics for lenders. THE CREDIT SCORE WASNT BUILT FOR MODERN CONSUMERS Legacy credit scores rely on a narrow slice of information updated at a pace that reflects the black-and-white television era. A single late payment can overshadow years of financial discipline. Data updates lag behind real behavior. And lenders are forced to make million-dollar decisions using a tool that cant see volatility, nuance, or context. A single, generic credit score is a compromise by design. National credit scores are designed to work reasonably well across thousands of institutions, but not optimally for any specific one. That becomes clear when you compare regional differences. A lender in an agricultural region may see very different income seasonality and cash-flow patterns than a lender in a major metro areadifferences that a universal score was never designed to capture. Financial institutions need models built around their actual membership that can adjust to different financial histories and behaviors. That rigidity has created the gap were now seeing across the economy. Consumers feel squeezed, lenders feel exposed, and businesses struggle to grow in a risk environment that looks nothing like the one their scoring tools were built for. Modern machine-learning models give lenders something the score never coulda panoramic view instead of a narrow window. HOW AI CHANGES THE GAME The data in credit files has long been there. Whats changed is the modelingmodern machine learning systems that can finally make full use of those signals. These models can evaluate thousands of factors inside bureau files, not just the static inputs, but the patterns behind them: How payment behavior changes over time Which fluctuations are warning signs versus temporary noise How multiple variables interact in ways a traditional score cant measure This lets lenders differentiate between someone who is truly risky and someone who is momentarily out of rhythm. The impact is profound: more approvals without more losses, stronger compliance without more overhead, and decisions that align with how people actually manage their finances today. For leadership teams, this also means making intentional choices about who to serve and how to allocate capital. Tailored models let institutions focus their resources on the customers they actually want to reach, rather than relying on a one-size-fits-all score. AI FIXES SOMETHING WE DONT TALK ABOUT ENOUGH There’s widespread concern about AI bias, and rightly so. When algorithms aren’t trained on a representative set of data or arent monitored after deployment, this can create biased results. In lending, these models arent deployed on faith; theyre validated, back-tested, and monitored over time, with clear documentation of the factors driving each decision. Modern explainability techniques, now well-established in credit risk, can give regulators and consumers a clearer view into how and why decisions are made. Business leaders should also consider that there is bias embedded in manual underwriting. Human decisionsespecially in high-volume, time-pressured environmentsvary from reviewer to reviewer, case to case, hour to hour. Machine learning models that use representative data, are regularly monitored, and make explainable, transparent decisions, giving humans a dependable baseline. This allows them to focus on exceptions, tough cases, and strategy. THE NEW ADVANTAGE FOR BUSINESS LEADERS The next era of lending will be defined by companies that operationalize AI with discipline, building in strong governance, clear guardrails, and transparency. Those who do will see higher approval rates, lower losses, faster decisions with fewer manual bottlenecks, and fairer outcomes that reflect real behavior, not outdated shortcuts. For the first time in 70 years, were able to bring real, impactful change to one of the most influential drivers in the economy. THE FUTURE ISNT A SCORE, ITS UNDERSTANDING If the last century of lending was defined by a single, blunt number, the next century will be defined by intelligence. By the ability to interpret risk with nuance, adapt to fast-moving economic signals, and extend opportunity to people who have long been underestimated by the system. AI wont make lending flawless. But it gives us the clearest path weve ever had toward a credit ecosystem that is more accurate, more resilient, and far fairer than the one we inherited. And for leaders focused on growth, innovation, and long-term competitiveness, that shift is transformational. Sean Kamkar is CTO of Zest AI.
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E-Commerce
Perusing the grocery aisle in the Westside Market on 23rd Street in Manhattan, you might not even notice the screens. They look just like paper price labels and, alongside a bar code, use a handwriting-style font weve come to associate with a certain merchant folksiness. Theyre not particularly bright or showy. The only clues that theyre not ordinary sticky shelf labels are a barely distinguishable light bulb and, on some, a small QR code. These are electronic shelf labels, chip-enabled screens that some stores are now using to display product prices. Unlike their paper predecessors, the prices arent printed in ink but rendered in pixels, and they can change instantaneously, at any time. The labels also come with additional features. An LED light can switch on to flag something, perhaps a product that needs restocking, explains Vusion, the company that made the labels Westside Market is now using. The QR codes are designed to help customers find more information about a product, or integrate with a personalized shopping list someone might have. Of course, these labels arent just labels, but end-points of a much larger effort to digitize every way we now interface with products. You have a network in the store. You send the information that you want to transmit to the labels, and there you go, says Finn Wikander, the chief product officer at Pricer, another company thats manufacturing ESLs with the hope of making them a fixture of 21st century shopping. Unsurprisingly, electronic shelf labels have become a flashpoint for consumer anxiety. The companies selling the devices, and the stores buying them, say the technology isnt about screwing people over but about making their businesses easier to run. Automating price changes eliminates hours spent replacing labels. It also makes it simpler to respond to new tariffs or account for rising inflation. But in a world spooked by dynamic pricing, electronic shelf labels can look to some like a goblin of digitizationa symptom of late-stage Silicon Valley campaigns to streamline and optimize seemingly all elements of commerce. Even members of Congress have raised suspicions about the technology, arguing that it enables price gouging and discrimination, particularly as it becomes more common in the United States. “Historically, when we thought about brick and mortar stores, prices were relatively stable,” Vicki Morwitz, a Columbia Business School professor who focuses on marketing and consumer behavior, tells Fast Company. “These electronic shelf tags break that assumption which makes pricing feel less stable. Even if average prices aren’t necessarily going up, that shelf instability can become a psychological flash point.” Screenified everything A handful of companies sell this technology as part of broader enterprise software packages. Theres Pricer, a Swedish firm, and Vusion, headquartered in France. Solum operates out of South Korea, and Opticon, known for barcode scanners, is also in the mix. Electronic shelf labels can also be bought, ahem, off the shelf and integrated into a stores Bluetooth networkno enterprise startup required. The pitch for these devices is exactly what unsettles so many shoppers: Electronic shelf labels make it much easier for stores to change prices dynamically and more frequently. The companies that manufacture and deploy these tools say there are legitimate reasons to do so. For example, a store might raise prices if suppliers increase costs, or cut them quickly when a product is nearing its expiration date. ESLs also allow chains to keep prices consistent across locations and respond more quickly to competitors (especially valuable at a time when shoppers are already carrying smartphones to compare prices between stores). Most consumers today are used to either doing their own scanning or use ChatGPT or Gemini to find the best offer or use price comparison sites, says Pricer’s Wikander. Then theres labor. Employees might spend hours replacing labels for a price surge or sale. The idea is to liberate people from very tedious tasks in a store. Changing prices could be one. Launching promotions could be one, argues Loc Oumier, a marketing executive with Vusion. There are also regulatory considerations: France, for instance, passed a law mandating that prices at checkout match advertised prices on aisles, which pushed stores in that country to adopt the technology, says Wikander. They are now rolling out more broadly in the United States, especially at large chains. Vusion says its labels are in use at Fresh Market, Mattress Firm, and Leons in Canada. Walmart, which declined to comment for this story, announced in 2024 that it would begin installing electronic shelf labels, with plans to bring Vusions technology to more than 2,000 stores by the end of 2026. Tests or deployments have appeared in Whole Foods, Schnucks, and even smaller retailers like Westside Market. The reception can be frosty. While there are some scenarios, like from Uber rides and airline tickets, where consumers have come to accept rapidly changing costs, the practice often feels jarring. That tension was evident in 2024, when Wendys faced backlash after announcing plans to install digital menu boards and later promised it wouldn’t introduce surge pricing for burgers. Shoppers also worry about price gouging, where retailers spike prices during emergencies. Exploiting consumers when they have no real alternatives or limited alternatives, says Columbia’s Morwitz. The problem is consumers may feel exploited long before an economist would say they are. There is also the understandable anxiety that the technology is designed to cut jobs. Some workers, as reported in The Nation, say the labels do not simplify their work but replace one kind of labor with another form of algorithmic babysitting. Unlike paper tags, screens can break, and computer programs fall victim to bugs and internet outages. Employees at one chain store operated by Kroger, which has also deployed the tech, have apparently complained that the labels heat up stores. (Kroger did not respond to Fast Company‘s request for comment.) Concerns reach D.C. Lawmakers have taken notice. Democratic Senators Elizabeth Warren of Massachusetts and Bob Casey of Pennsylvania wrote to Kroger after the company announced it would introduce the technology, amid accusations that it was using facial recognition to show different customers different prices. In a letter of response obtained by Fast Company, Kroger defended the rollout, saying ESLs helped it manage the 1.3 billion price changes it implements each year and freed up associates to assist customers. Paula Walsh,Krogers director of retail operations, denied in the letter that the company was using facial recognition or collecting personal information from customers through the tags. Kroger dodged my questions but confirmed my key concerns: Its using electronic shelf labels to change grocery prices in real-time and collect data that could be used to jack up grocery prices for Americans, Warren tells Fast Company. Ill keep pushing to make sure consumers arent being exploited while they work hard to put food on the table. Wikander, for his part, dismisses the idea that retailers would use the technology that way. Just because you have the possibility of screwing your customers doesn’t mean that retailers will do that,” he says. “I don’t think retailers would typically do it, because the consumers are smarter than that. Wikander says it takes a typical business around a year or two and that, while the investment upfront is big, the labels last for many years. Indeed, for all the eeriness surrounding the labels, research shows that it might not be much of a change, price wise, for either consumers or businesses. Ioannis Stamatopoulos, a business professor at the University of Texas at Austin, says there is little evidence that digital shelf labels lead to significant price swings. He pointed to a 2025 study involving an American grocery store that found no evidence of the practice, and another involving an international grocery store that showed that prices tended to decline, particularly for items with short shelf lives. Much of his research, at least, suggests that the labels are most effective at stopping food waste, since it makes it easier for stores to offer sales on products like bananas and strawberries when theyre about to go bad. For now, the future of grocery shopping may look almost exactly like the pastexcept the price tag is oh-so-faintly glowing.
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E-Commerce
James Van Der Beek was one of the biggest stars of the late 1990s and early 2000s. His family still couldn’t afford the cost of cancer. The actor, 48, best known for his portrayal of Dawson Leery in the 90s hit Dawson’s Creek, died Wednesday. Van Der Beek’s passing comes a little more than a year after he announced on social media that he was battling colorectal cancer, which he was diagnosed with in 2023. And while the actor and father’s untimely death is undeniably tragic, there’s another heartbreaking piece of the story to be told. His family was desperately struggling to afford the cost of his cancer treatment. Despite having enjoyed a successful careerwhich included hits like Varsity Blues (1999) and The Rules of Attraction (2002), as well as playing the lead role in a popular TV drama for six seasonsthe actor still spent the final years of his life struggling financially. Last year, Van Der Beek teamed up with the auction house Propstore to sell his personal collection of memorabilia, wardrobe items, and set pieces from Dawson’s Creek and his most notable films to raise money for his treatment. “I’ve been storing these treasures for years, waiting for the right time to do something with them. And with all of the recent unexpected twists and turns life has presented recently, it’s clear that the time is now,” Van Der Beek told People magazine at the time. According to The Hollywood Reporter, the auction raised around $47,000. His plight begs the question: If one of the most successful actors of the late 1990s and early 2000s can’t afford cancer treatment in the United States, who can? According to a 2022 survey from the American Cancer Society Cancer Action Network (ACS CAN), not many. Per the survey, more than 70% of respondents said they made significant lifestyle changes in order to afford their care. And more than half (51%) went into medical debt due to treatment. The statistics were worse for certain groups, with women more likely to report medical debt than men (57% versus 36%), and Black Americans more likely to go into debt than white Americans (62% versus 52%). Likewise, states with fewer people enrolled in Medicaid had higher rates of medical debt due to cancer (58% compared with 49% in states with expanded Medicaid offerings). But overall, almost three-quarters of the cancer patients surveyed were worried about being able to afford the cost of their current care, as well as costs that may stack up in the future (73%). On Wednesday, amid the tributes and heartfelt words, a GoFundMe page dedicated to the actor’s family also showed up online. The page, which GoFundMe told Fast Company has been verified, explained that the family has been under “significant financial strain” due to Van Der Beek’s medical expenses. “In the wake of this loss, Kimberly and the children are facing an uncertain future,” it said. “The costs of Jamess medical care and the extended fight against cancer have left the family out of funds. They are working hard to stay in their home and to ensure the children can continue their education and maintain some stability during this incredibly difficult time.” At present, the page has raised over $1.4 million for his wife and six kids. The efforts being made for the actor’s family may be touching. They are happening, in part, because the actor was well loved. Shortly after his death was made public, the tributes from friends and colleagues began pouring in. One belief, which seemed to be shared by those who knew him, was how deeply genuine and kind he was, with many describing him as the antithesis of everything Hollywood actors are known to be. “There are people in this industry who are talented. Some who are charismatic. A few who are generous,” wrote actress Alyssa Milano. “And then there were the rare onesthe truly kind and thoughtful. James was the rare kind. He showed up for his people. He listened. He cared.” She went on to call him a “unicorn of a man.” The sentiments were echoed by many other actors he grew up alongside, including Katie Holmes and Melissa Joan Hart. In the end, the outpouring of love for Van Der Beek underscores both how deeply he was valued and how precarious illness remains in the United States, even for those who seem outwardly successful. That his family needed to rely on auctions and crowdfunding to survive a cancer diagnosis is not an anomaly, but a reflection of a system where serious illness often comes with financial ruin attached.
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E-Commerce
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