This is today’s edition of , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Next slide, please: A brief history of the corporate presentation PowerPoint is everywhere. It’s used in religious sermons; by schoolchildren preparing book reports; at funerals and weddings. In 2010, Microsoft announced that PowerPoint was installed on more than a billion computers worldwide. But before PowerPoint, and long before even digital projectors, 35-millimeter film slides were king. They were the only medium for the kinds of high-impact presentations given by CEOs and top brass at annual meetings for stockholders, employees, and salespeople. Known in the business as “multi-image” shows, these presentations required a small army of producers, photographers, and live production staff to pull off. . —Claire L. Evans This story is from the next upcoming issue of our print magazine, which is all about ethics. If you don’t subscribe already, to receive a copy when it publishes. The US just invested more than $1 billion in carbon removal The news: The US Department of Energy has that it’s providing $1.2 billion to develop regional hubs that can draw down and store away at least 1 million metric tons of carbon dioxide per year as a means of combating climate change. The details: The first recipients will include Occidental Petroleum’s proposed carbon-removal project in Kleberg County, Texas, as well as a partnership between Battelle, Climeworks, and Heirloom to develop facilities in southwestern Louisiana. Billions of dollars more funding and more hubs are set to be announced further down the line. Why it matters: A growing body of research has found that, to keep climate change in check, nations may need to not only radically cut greenhouse gas emissions but also draw down billions of tons of carbon dioxide per year. This latest move represents a major step forward in the effort to establish a market for doing this. . —James Temple AI isn’t great at decoding human emotions. So why are regulators targeting the tech? Recently regulators have been ramping up warnings against : the attempt to identify a person’s feelings or state of mind using AI analysis of video, facial images, or audio recordings. The idea isn’t super complicated: the AI model may see an open mouth, squinted eyes, and contracted cheeks with a thrown-back head, for instance, and register it as a laugh, concluding that the subject is happy. But in practice, this is incredibly complex—and, some argue, a dangerous and invasive example of the sort of pseudoscience that artificial intelligence often produces. But why is this a top concern now? . This story is from The Technocrat, Tate’s weekly newsletter giving you the inside track on all things tech, policy and power. to receive it in your inbox every Friday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Survivors say there was no warning siren before the Lahaina wildfiresBut it’s unclear what went wrong. ()+ Researchers are starting to take stock of the losses in Maui. ()+ This is why the wildfires happened—and what can be done to prevent future ones. ( $)2 The clean energy transition is happening faster than you might thinkRenewables are now expected to overtake coal as the world’s largest source of electricity by 2025. ( $)+ Yes, we have enough materials to power the world with renewable energy. ()3 Regulators have approved a driverless taxi expansion in San FranciscoAutonomous cabs can now operate across the entire city 24/7. ()4 TikTok ‘dual’ videos are set to destroy our brains even further Pity our poor, over-stimulated, already-obliterated attention spans. ( $)+ People are going to extreme lengths to make the perfect TikTok clip. ( $)5 Why is it so hard to create new types of pain relievers? The field is littered with failures, but a new study offers a small glimmer of hope. () 6 Why everyone went so crazy over the LK-99 superconductorThe claims don’t seem to stand up. But the episode shows how desperate Silicon Valley is for the next big thing. ( $)+ A body of evidence has piled up that disproves the initial claims. ()7 AI means hackers can just talk computers into misbehavingTools like ChatGPT radically lower the barriers for all sorts of attacks. ( $)+ Three ways AI chatbots are a security disaster. ()8 How China is using apps to woo Taiwanese teenagersA perfect example of soft power in action. () 9 How tech is changing how we grieveWe now leave behind reams and reams of stuff online for our families to pore over when we’re gone. ( $)+ Inside the metaverse meetups that let people share on death, grief, and pain. () 10 Zuckerberg says that cage fight isn’t happeningIt seems pretty obvious that Musk has chickened out. () Quote of the day “They had an understanding that I wasn’t the best choice — I was the only choice.” —German director and actor Werner Herzog tells the why he’s voicing a new collection of AI-generated poems. The big story Tech’s new labor movement is harnessing lessons learned a century ago ANDREA DAQUINO June 2021 Back in 2020, as the world struggled to cope with the pandemic, workers at the Amazon fulfillment center in Bessemer, Alabama, were being pressed to work harder and longer. They felt dehumanized. They wanted dignity, not just higher wages. Workers pushed to join the Retail, Wholesale, and Department Store Union, but Amazon waged war on the campaign, and eventually a vote passed in favor of keeping the status quo. Elsewhere, however, other workers across the country had started agitating. Their activity reflects a new groundswell of interest in organizing among tech workers, who are up against the world’s richest companies. But for both sides in this struggle, the bottom line is not money but power. . —Sarah Jaffe We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or .) + London’s surely have to be some of the coolest people on the planet. + Let the debate commence over .+ You can learn a lot about someone from how they their money.+ Diane Morgan’s Netflix show had me in stitches last weekend. + A little bit of knowledge into thinking we know a lot more than we really do. ($)

This article is from The Technocrat, MIT Technology Review’s weekly tech policy newsletter about power, politics, and Silicon Valley. To receive it in your inbox every Friday, . Recently, I took myself to one of my favorite places in New York City, the public library, to look at some of the hundreds of original letters, writings, and musings of Charles Darwin. The famous English scientist loved to write, and his curiosity and skill at observation come alive on the pages. In addition to proposing the theory of evolution, Darwin studied the expressions and emotions of people and animals. He debated in his writing just how scientific, universal, and predictable emotions actually are, and he sketched characters with exaggerated expressions, which the library had on display. The subject rang a bell for me. Lately, as everyone has been up in arms about ChatGPT, , and the prospect of robots , I’ve noticed that regulators have been ramping up warnings against AI and emotion recognition. Emotion recognition, in this far-from-Darwin context, is the attempt to identify a person’s feelings or state of mind using AI analysis of video, facial images, or audio recordings. The idea isn’t super complicated: the AI model may see an open mouth, squinted eyes, and contracted cheeks with a thrown-back head, for instance, and register it as a laugh, concluding that the subject is happy. But in practice, this is incredibly complex—and, some argue, a dangerous and invasive example of the sort of pseudoscience that artificial intelligence often produces. Certain privacy and human rights advocates, such as and , are calling for a blanket ban on emotion recognition. And while the isn’t a total ban, it bars the use of emotion recognition in policing, border management, workplaces, and schools. Meanwhile, some US legislators have called out this particular field, and it appears to be a likely contender in any eventual AI regulation; Senator Ron Wyden, who is one of the lawmakers leading the regulatory push, recently the EU for tackling it and warned, “Your facial expressions, eye movements, tone of voice, and the way you walk are terrible ways to judge who you are or what you’ll do in the future. Yet millions and millions of dollars are being funneled into developing emotion-detection AI based on bunk science.” But why is this a top concern? How well founded are fears about emotion recognition—and could strict regulation here actually hurt positive innovation? A handful of companies are already selling this technology for a wide variety of uses, though it’s not yet widely deployed. Affectiva, for one, has been exploring how AI that analyzes people’s facial expressions might be used to determine whether a car driver is tired and to evaluate how people are reacting to a movie trailer. Others, like HireVue, have as a way to screen for the most promising job candidates (a practice that has been met with heavy criticism; you can listen to our investigative audio series on the company ). “I’m generally in favor of allowing the private sector to develop this technology. There are important applications, such as or have low vision to better understand the emotions of people around them,” Daniel Castro, vice president of the Information Technology and Innovation Foundation, a DC-based think tank, told me in an email. But other applications of the tech are more alarming. Several companies are selling software to law enforcement that tries to ascertain if someone is lying or that can flag supposedly suspicious behavior. A pilot project called iBorderCtrl, sponsored by the European Union, offers a version of emotion recognition as part of its technology stack that manages border crossings. According to its website, the Automatic Deception Detection System “quantifies the probability of deceit in interviews by analyzing interviewees’ non-verbal micro-gestures” (though it acknowledges “scientific controversy around its efficacy”). But the most high-profile use (or abuse, in this case) of emotion recognition tech is from China, and this is undoubtedly on legislators’ radars. The country has repeatedly used emotion AI for surveillance—notably in Xinjiang, according to a software engineer who claimed to have installed the systems in police stations. Emotion recognition was intended to identify a nervous or anxious “state of mind,” like a lie detector. As one human rights advocate warned the BBC, “It’s people who are in highly coercive circumstances, under enormous pressure, being understandably nervous, and that’s taken as an indication of guilt.” Some schools in the country have also used the tech on students to measure . Ella Jakubowska, a senior policy advisor at the Brussels-based organization European Digital Rights, tells me she has yet to hear of “any credible use case” for emotion recognition: “Both [facial recognition and emotion recognition] are about social control; about who watches and who gets watched; about where we see a concentration of power.” What’s more, there’s that emotion recognition models just . Emotions are complicated, and even human beings are often quite poor at identifying them in others. Even as the technology has improved in recent years, thanks to the availability of more and better data as well as increased computing power, the accuracy varies widely depending on what outcomes the system is aiming for and how good the data is going into it. “The technology is not perfect, although that probably has less to do with the limits of computer vision and more to do with the fact that human emotions are complex, vary based on culture and context, and are imprecise,” Castro told me. A composite of heliotypes taken by Oscar Gustave Rejlander, a photographer who worked with Darwin to capture human expression.STEPHANIE ARNETT/MITTR | REJLANDER/GETTY MUSEUM Which brings me back to Darwin. A fundamental tension in this field is whether science can ever determine emotions. We might see advances in as the underlying science of emotion continues to progress—or we might not. It’s a bit of a parable for this broader moment in AI. The technology is in a period of extreme hype, and the idea that artificial intelligence can make the world significantly more knowable and predictable can be appealing. That said, as AI expert Meredith Broussard , can everything be distilled into a math problem? What else I’m reading Political bias is seeping into AI language models, according to new research that this week. Some models are more right-leaning and others are more left-leaning, and a truly unbiased model might be out of reach, some researchers say. has a fascinating long read about how Sweden is thwarting targeted online information ops by the Kremlin, which are intended to sow division within the Scandinavian country as it works to join NATO. Kate Lindsay in the Atlantic about the changing nature of death in the digital age. Emails, texts, and social media posts live on long past our loved ones, changing grief and memory. (If you’re curious about this topic, a few months back I wrote about how this shift relates to by Google and Twitter.) What I learned this week A new study from researchers in Switzerland to Google Search and accounts for the majority of its revenue. The findings offer some optimism about the economics of news and publishing, especially if you, like me, care deeply about the future of journalism. Courtney Radsch in one of my favorite publications, Tech Policy Press. (On a related note, you should also read on how to fix local news from Steven Waldman in the Atlantic.)

One morning in August 2021, as she had nearly every morning for about a decade, Janice Smith opened her computer and went to Kiva.org, the website of the San Francisco–based nonprofit that helps everyday people make microloans to borrowers around the world. Smith, who lives in Elk River, Minnesota, scrolled through profiles of bakers in Mexico, tailors in Uganda, farmers in Albania. She loved the idea that, one $25 loan at a time, she could fund entrepreneurial ventures and help poor people help themselves. But on this particular morning, Smith noticed something different about Kiva’s website. It was suddenly harder to find key information, such as the estimated interest rate a borrower might be charged—information that had been easily accessible just the day before and felt essential in deciding who to lend to. She showed the page to her husband, Bill, who had also become a devoted Kiva lender. Puzzled, they reached out to other longtime lenders they knew. Together, the Kiva users combed through blog posts, press releases, and tax filings, but they couldn’t find a clear explanation of why the site looked so different. Instead, they learned about even bigger shifts—shifts that shocked them. Kiva connects people in wealthier communities with people in poorer ones through small, crowdfunded loans made to individuals through partner companies and organizations around the world. The individual Kiva lenders earn no interest; money is given to microfinance partners for free, and only the original amount is returned. Once lenders get their money back, they can choose to lend again and again. It’s a model that Kiva hopes will foster a perennial cycle of microfinance lending while requiring only a small outlay from each person. This had been the nonprofit’s bread and butter since its founding in 2005. But now, the Smiths wondered if things were starting to change. The Smiths and their fellow lenders learned that in 2019 the organization had begun charging fees to its lending partners. Kiva had long said it offered zero-interest funding to microfinance partners, but the Smiths learned that the recently instituted fees could reach 8%. They also learned about Kiva Capital, a new entity that allows large-scale investors——to make big investments in microfinance companies and receive a financial return. The Smiths found this strange: thousands of everyday lenders like them had been offering loans return free for more than a decade. Why should Google now profit off a microfinance investment? Combined, Kiva’s top 10 executives made nearly $3.5 million in 2020. In 2021, nearly half of Kiva’s revenue went to staff salaries. The Kiva users noticed that the changes happened as compensation to Kiva’s top employees increased dramatically. In 2020, the CEO took home . Combined, Kiva’s top 10 executives made nearly $3.5 million in 2020. In 2021, of Kiva’s revenue went to staff salaries. Considering all the changes, and the eye-popping executive compensation, “the word that kept coming up was ‘shady,’” Bill Smith told me. “Maybe what they did was legal,” he said, “but it doesn’t seem fully transparent.” He and Janice felt that the organization, which relied mostly on grants and donations to stay afloat, now seemed more focused on how to make money than how to create change. Kiva, on the other hand, says the changes are essential to reaching more borrowers. In an interview about these concerns, , told me, “All the decisions that Kiva has made and is now making are in support of our mission to expand financial access.” In 2021, the Smiths and nearly 200 other lenders launched a “lenders’ strike.” More than a dozen concerned lenders (as well as half a dozen Kiva staff members) spoke to me for this article. They have refused to lend another cent through Kiva, or donate to the organization’s operations, until the changes are clarified—and ideally reversed. When Kiva was , a worldwide craze for microfinance—sometimes called microcredit—was at its height. The UN had dubbed 2005 the ; a year later, in 2006, Muhammad Yunus and the Grameen Bank he had founded in the 1980s for creating, in the words of the Nobel Committee, “economic and social development from below.” On a trip to East Africa, Flannery and Jackley had a lightbulb moment: Why not expand microfinance by helping relatively wealthy individuals in places like the US and Europe lend to relatively poor businesspeople in places like Tanzania and Kenya? They didn’t think the loans Kiva facilitated should come from grants or donations: the money, they reasoned, would then be limited, and eventually run out. Instead, small loans—as little as $25—would be fully repayable to lenders. Connecting wealthier individuals to poorer ones was the “peer-to-peer” part of Kiva’s model. The second part—the idea that funding would be sourced through the internet via the Kiva.org website—took inspiration from Silicon Valley. Flannery and another Kiva cofounder, Premal Shah, both worked in tech—, . Kiva was one of the first crowdfunding platforms, launched ahead of popular sites like GoFundMe. But Kiva is less direct than other crowdfunding sites. Although lenders “choose” borrowers through the website, flipping through profiles of dairy farmers and fruit sellers, money doesn’t go straight to them. Instead, the loans that pass through Kiva are bundled together and sent to one of the partnering microfinance institutions. After someone in the US selects, say, a female borrower in Mongolia, Kiva funds a microfinance organization there, which then lends to a woman who wants to set up a business. Even though the money takes a circuitous route, the premise of lending to an individual proved immensely effective. Stories about Armenian bakers and Moroccan bricklayers helped lenders like the Smiths feel connected to something larger, something with purpose and meaning. And because they got their money back, while the feel-good rewards were high, the stakes were low. “It’s not charity,” the website still emphasizes today. “It’s a loan.” The organization covered its operating expenses with funding from the US government and private foundations and companies, as well as donations from individual lenders, who could add a tip on top of their loan to support Kiva’s costs. This sense of individual connection and the focus on facilitating loans rather than donations was what initially drew Janice Smith. She first heard of microfinance through , and then again through Oprah Winfrey—Kiva.org one of “Oprah’s Favorite Things” in 2010. Smith was particularly enticed by the idea that she could re-lend the same $25 again and again: “I loved looking through borrower profiles and feeling like I was able to help specific people. Even when I realized that the money was going to a [microfinance lender]”—not directly to a borrower—“it still gave me a feeling of a one-on-one relationship with this person.” Kiva’s easy-to-use website and focus on repayments helped further popularize the idea of small loans to the poor. For many Americans, if they’ve heard of microfinance at all, it’s because they or a friend or family member have lent through the platform. As of 2023, according to a Kiva spokesperson, 2.4 million people from more than 190 countries have done so, ultimately reaching more than 5 million borrowers in 95 countries. The spokesperson also pointed to of 18,000 microfinance customers, 88% of whom said their quality of life had improved since accessing a loan or another financial service. A quarter said the loans and other services had increased their ability to invest and grow their business. But Kiva has also long faced criticism, especially when it comes to . There was the obvious issue that the organization suggests a direct connection between Kiva.org users and individual borrowers featured on the site, a connection that . But there were also complaints that the interest rates borrowers pay were . Although Kiva initially did not charge fees to the microfinance institutions it funneled money through, the loans to the individual borrowers . The institutions Kiva partners with use that to cover operational costs and, sometimes, make a profit. Critics were concerned about this lack of disclosure given that interest rates on microfinance loans can reach far into the double digits— more than , some . (Microlenders and their funders have long are needed to make funding sustainable.) A Kiva spokesperson stressed that the website now mentions “average cost to borrower,” which is not the interest rate a borrower will pay but a rough approximation. Over the years, Kiva has focused on partnering with “impact-first” microfinance lenders—those that charge low interest rates or focus on loans for specific purposes, such as solar lights or farming. Critics also point showing that microfinance has a limited impact on poverty, despite claims that the loans can be transformative for poor people. For those who remain concerned about microfinance overall, the clean, easy narrative Kiva promotes is a problem. By suggesting that someone like Janice Smith can skeptics charge, the organization is effectively whitewashing a troubled industry that have reportedly led to suicides, , and a . Over her years of lending through Kiva.org, Smith followed some of this criticism, but she says she was “sucked in” from her first loan. She was so won over by the mission and the method that she soon became, in her words, a “Kivaholic.” Lenders can choose to join “teams” to lend together, and in 2015 she launched one, called Together for Women. Eventually, the team would include nearly 2,500 Kiva lenders—including one who, she says, put his “whole retirement” into Kiva, totaling “millions of dollars.” Smith soon developed a steady routine. She would open her computer first thing in the morning, scroll through borrowers, and post the profiles of those she considered particularly needy to her growing team, encouraging support from other lenders. In 2020, several years into her “Kivaholicism,” Kiva invited team captains like her to join regular calls with its staff, a way to disseminate information to some of the most active members. At first, these calls were cordial. But in 2021, as lenders like Smith noticed changes that concerned them, the tone of some conversations changed. Lenders wanted to know why the information on Kiva’s website seemed less accessible. And then, when they didn’t get a clear answer, they pushed on everything else, too: the fees to microfinance partners, the CEO salaries. In 2021 Smith’s husband, Bill, became captain of a new team calling itself Lenders on Strike, which soon had nearly 200 concerned members. The name sent a clear message: “We’re gonna stop lending until you guys get your act together and address the stuff.” Even though they represented a small fraction of those who had lent through Kiva, the striking members had been involved for years, collectively lending millions of dollars—enough, they thought, to get Kiva’s attention. On the captains’ calls and in letters, the strikers were clear about a top concern: the fees now charged to microfinance institutions Kiva works with. Wouldn’t the fees make the loans more expensive to the borrowers? Individual Kiva.org lenders still expected only their original money back, with no return on top. If the money wasn’t going to them, where exactly would it be going? On one call, the Smiths recall, staffers explained that the fees were a way for Kiva to expand. Revenue from the fees—potentially millions of dollars—would go into Kiva’s overall operating budget, covering everything from new programs to site visits to staff salaries.

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, . This week I’ve been thinking about America’s addiction to opioids. The statistics are staggering. Since 2010, opioid overdose deaths have nearly quadrupled. More than 80,000 people died from an opioid overdose last year. That’s one death every six and a half minutes. Opioid use disorder is a particularly difficult disease to treat. But we do have safe and effective medications. These drugs help curb withdrawal symptoms, reduce illegal opioid use, and help people stay in treatment. They also reduce the risk of death from overdose., however, shows that just one in five people with opioid use disorder receives these drugs. Clearly, we need to do better. That means improving treatment, but it also means finding alternative methods for controlling pain, a task that has proved exceedingly difficult. suggests the Boston-based biotech Vertex may be making headway with its compound VX-548, a pill that aims to relieve pain in the wake of surgery. The highest dose of the compound offered greater pain relief than a placebo after bunion removal or tummy tuck surgery. That’s good news in a space that has had more than its fair share of setbacks. Treating pain is complicated because pain itself is complicated. Doctors categorize pain by how long it lasts—acute vs. chronic—and also how it begins. Some pain starts with damage to the body—a cut, a burn, a broken arm, a tumor. Sensory nerves (neurons) in our body detect the damage and send pain signals to the brain. Some pain, such as the stinging and burning that comes with diabetic nerve damage, begins with injury to the neurons themselves. Opioids—heroin, morphine, fentanyl and all the rest—work by masking pain. They bind to receptors in the brain and spinal cord, initiating a series of reactions that help block pain signals. Prescription opioids are extremely good at pain relief in certain situations. But they don’t just block pain. Activating the opioid receptors also prompts a rush of dopamine, which makes us feel good—even euphoric. The feeling doesn’t last. And the more a person takes, the more is needed to get the same rush. That’s why these drugs are ripe for abuse. Non-opioid painkillers already exist, of course—things like ibuprofen, aspirin, acetaminophen, and naproxen sodium. You’re probably familiar with many of them because they’re available over the counter. They don’t trigger a dopamine release and aren’t addictive like opioids, but these medications come with some serious drawbacks: ulcers, bleeding, heart problems, and more. Most (with the ) belong to a class called nonsteroidal anti-inflammatory drugs, or NSAIDS for short. As the name suggests, they target inflammation in the body, blocking the production of chemicals that cause us to feel pain. But they don’t work for pain of many other types. The effort to develop new classes of pain medicines has hit many roadblocks. Just last year Regenron pulled the plug on development of a compound to treat osteoarthritis and chronic back pain; an experimental pain therapy from the Illinois-based biotech Aptinyx failed in a trial to help people with fibromyalgia; and the California company Acadia reported that its compound performed no better than a placebo in people who had undergone bunion removal surgery*. In 2021, Eli Lilly and Pfizer halted development of tanezumab, a monoclonal antibody to treat pain in people with osteoarthritis. Why each of these failures occurred isn’t entirely clear, which makes it difficult to find the best path forward. Vertex’s new compound is part of a class of drugs that target sodium channels on the pain-sensing nerves themselves. Stephen Waxman, a Yale neurologist who studies pain, describes them as “” that drive the production of nerve impulses. Some sodium channel blockers already exist—the numbing agent lidocaine, for example. But because they block all sodium channels, even crucial ones on heart cells and in the brain, they are often administered only as local anesthetics. VX-548 targets a specific channel called Nav1.8 that is found only on pain-sensing neurons. That means it can work broadly on those neurons throughout the body without blocking the function of the heart or brain. Because it doesn’t activate opioid receptors, it also doesn’t trigger a release of dopamine, giving people pain relief without an accompanying high. Phase 2 trials of the drug enrolled people with moderate to severe pain following a tummy tuck or bunion removal. Patients who requested pain medication were randomized to one of several groups. Some participants received VX-548 at one of three dosage levels, some got a placebo pill, and some took a pill that contained hydrocodone (an opioid). Those taking the highest dose of VX-548 experienced greater reductions in pain than those in the other groups. An editorial accompanying the study noted that the effect was “small.” But the results are exciting, in part because the hunt for non-opioid painkillers has had so few successes of any size. “Here we have a clinical study in humans that shows that you can target one of these peripheral sodium channels and reduce pain in human subjects without adverse side effects,” Waxman . “I see us at the first stage in humans of a new generation of pain medications.” We can hope. *You might wonder, as my editor did, why so many pain medicine trials include patients undergoing bunionectomies. It’s one of the classic surgical models of acute pain. Dental extraction is another. The more you know. Read more from Tech Review’s archive Adam Piore to develop nonaddictive painkillers way back in 2016. Could an ingestible capsule keep tabs on whether patients are taking too many prescription opioids? Emily Mullin in 2017. Neuroscientist Fan Wang is looking for the brain circuits that control pain. Georgina Gustin in 2021. Recorded brain waves can help quantify pain, which could upend some types of treatment, Rhiannon Williams . Another thing: Twenty-five years have passed since researchers isolated the first embryonic stem cells, but we’re still waiting for stem-cell therapies. Antonio Regalado looks at. Who gets access to experimental treatments—especially some of the ultra-novel treatments that are just beginning to emerge? Jessica Hamezlou dives into this in a story for MIT Technology Review’s ethics issue. From around the web: Data from a landmark study show that the obesity drug Wegovy slashed the risk of heart attacks, strokes, and cardiovascular deaths by 20%, according to the drug’s maker. () This week the FDA approved the very first therapy exclusively for postpartum depression. () The US has a new covid variant. Meet Eris. () And if you want more about the opioid crisis, the podcast Serial has a new season out called , which offers a devastating case study on how opioid abuse can affect patients. The series is about a nurse who stole fentanyl vials and replaced the contents with saline, and the women who underwent egg retrievals without fentanyl as a result. It’s horrifying, but very much worth your time.

It’s 1948, and it isn’t a great year for alcohol. Prohibition has come and gone, and booze is a buyer’s market again. That much is obvious from Seagram’s annual sales meeting, an 11-city traveling extravaganza designed to drum up nationwide sales. No expense has been spared: there’s the two-hour, professionally acted stage play about the life of a whiskey salesman. The beautiful anteroom displays. The free drinks. But the real highlight is a slideshow. To call the Seagram-Vitarama a slideshow is an understatement. It’s an experience: hundreds of images of the distilling process, set to music, projected across five 40-by-15-foot screens. “It is composed of pictures, yet it is not static,” comments one awed witness. “The overall effect is one of magnificence.” Inspired by an Eastman Kodak exhibit at the 1939 World’s Fair, the Seagram-Vitarama is the first A/V presentation ever given at a sales meeting. It will not be the last. In the late ’40s, multimedia was a novelty. But by the early 1960s, nearly all companies with national advertising budgets were using multimedia gear—16-­millimeter projectors, slide projectors, filmstrip projectors, and overheads—in their sales training and promotions, for public relations, and as part of their internal communications. Many employed in-house A/V directors, who were as much showmen as technicians. Because although presentations have a reputation for being tedious, when they’re done right, they’re theater. The business world knows it. Ever since the days of the Vitarama, companies have leveraged the dramatic power of images to sell their ideas to the world. Next slide, please The sound of slides clacking is deafening. But it doesn’t matter, because the champagne is flowing and the sound system is loud. The 2,500 dignitaries and VIPs in the audience are being treated to an hourlong operetta about luxury travel. Onstage, a massive chorus, the entire Stockholm Philharmonic, and some 50 dancers and performers are fluttering around a pair of Saab 9000CD sedans. Stunning images of chrome details, leather seats, and open roads dance across a 26-foot-tall screen behind them. The images here are all analog: nearly 7,000 film slides, carefully arranged in a grid of 80 Kodak projectors. It’s 1987, and slideshows will never get any bigger than this. Before PowerPoint, and long before digital projectors, 35-millimeter film slides were king. Bigger, clearer, and less expensive to produce than 16-millimeter film, and more colorful and higher-resolution than video, slides were the only medium for the kinds of high-impact presentations given by CEOs and top brass at annual meetings for stockholders, employees, and salespeople. Known in the business as “multi-image” shows, these presentations required a small army of producers, photographers, and live production staff to pull off. First the entire show had to be written, storyboarded, and scored. Images were selected from a library, photo shoots arranged, animations and special effects produced. A white-gloved technician developed, mounted, and dusted each slide before dropping it into the carousel. Thousands of cues were programmed into the show control computers—then tested, and tested again. Because computers crash. Projector bulbs burn out. Slide carousels get jammed. “When you think of all the machines, all the connections, all the different bits and pieces, it’s a miracle these things even played at all,” says , a commercial photographer turned slide producer whose company Incredible Slidemakers produced the 80-­projector Saab launch. Now 77 years old, he’s made a retirement project of archiving the now-forgotten slide business. Mesney pivoted to producing multi-image shows in the early 1970s after an encounter with an impressive six-screen setup at the 1972 New York Boat Show. He’d been shooting spreads for Penthouse and car magazines, occasionally lugging a Kodak projector or two to pitch meetings for advertising clients. “All of a sudden you look at six projectors and what they can do, and you go, Holy mackerel,” he remembers. “All of a sudden you look at six projectors and what they can do, and you go, Holy mackerel.” Douglas Mesney, a commercial photographer Six was just the beginning. At the height of Mesney’s career, his shows called for up to 100 projectors braced together in vertiginous rigs. With multiple projectors pointing toward the same screen, he could create seamless panoramas and complex animations, all synchronized to tape. Although the risk of disaster was always high, when he pulled it off, his shows dazzled audiences and made corporate suits look like giants. Mesney’s clients included IKEA, Saab, Kodak, and Shell; he commanded production budgets in the hundreds of thousands of dollars. And in the multi-image business, that was cheap. Larger A/V staging companies, like Carabiner International, charged up to $1 million to orchestrate corporate meetings, jazzing up their generic multi-­image “modules” with laser light shows, dance numbers, and top-shelf talent like Hall & Oates, the Allman Brothers, and even the Muppets. “I liken it to being a rock-and-roll roadie, but I never went on the tour bus,” explains Susan Buckland, a slide programmer who spent most of her career behind the screen at Carabiner. Douglas Mesney, a former commercial photographer, produced shows with production budgets in the hundreds of thousands of dollars for clients including IKEA, Saab, Kodak, and Shell. DOUGLAS MESNEY/INCREDIBLE SLIDEMAKERS From its incorporation in 1976 to the mid-1980s, the Association for Multi-Image, a trade association for slide producers, grew from zero to 5,000 members. At its peak, the multi-image business employed some 20,000 people and supported several festivals and four different trade magazines. One of these ran a glowing profile of Douglas Mesney in 1980; when asked for his prognosis about the future of slides, he replied: “We could make a fortune or be out of business in a year.” He wasn’t wrong. At the time, some 30 manufacturers of electronic slide programming devices vied for the multi-image dollar. To meet the demand for high-impact shows, the tech had quickly evolved from manual dissolve units and basic control systems—programmed with punched paper tape, and then audiocassette—to dedicated slide control computers like the AVL Eagle I, which could drive 30 projectors at once. The Eagle, which came with word processing and accounting software, was a true business computer—so much so that when Eagle spun off from its parent company, Audio Visual Labs, in the early ’80s, it became one of Silicon Valley’s most promising computer startups. Eagle went public in the summer of 1983, making its president, Dennis R. Barnhart, an instant multimillionaire. Only hours after the IPO, Barnhart plowed his brand-new cherry-red Ferrari through a guardrail near the company’s headquarters in Los Gatos, California, flipped through the air, crashed into a ravine, and died. The slide business would soon follow. Douglas Mesney likes to say that if you never saw a slide show, you never will. The machines to show them have been landfilled. The slides themselves were rarely archived. Occasionally a few boxes containing an old multi-image “module” will turn up in a storage unit, and occasionally those will even be undamaged. But with the exception of a few hobbyists and retired programmers, the know-how to restore and stage multi-image slideshows is scarce. This leaves former slide professionals at a loss. “All of us are devastated that none of the modules survived,” says Susan Buckland. “Basically, I don’t have a past, because I can’t explain it.” The entire industry, which existed at an unexpected intersection of analog and high-tech artistry, came and went in a little over 20 years. Presentations, like porn, have always pushed technology forward; in the multi-­image days, producers like Mesney took the slide as far as it could go, using every tool available to create bigger and bolder shows. Mesney claims to have set the land speed record for a slide presentation with a three-minute-long, 2,400-slide show, but even at top speed, slides are static. The computers that controlled them, however, were not—and it wasn’t long before they evolved beyond the medium. “Back then, computers were fast enough to tell slides what to do, but they weren’t fast enough to actually create the images themselves,” explains Steven Michelsen, a former slide programmer who restores and runs in his Delaware garage. “It took another 10 or 15 years until you could run a show straight from your computer and have the images look worth looking at,” he adds. The last slide projector ever made rolled off the assembly line in 2004. The inside of its casing was signed by factory workers and Kodak brass before the unit was handed over to the Smithsonian. Toasts and speeches were made, but by then they were eulogies, because PowerPoint had already eaten the world. Inventing PowerPoint The Hotel Regina is an Art Nouveau marvel overlooking the Tuileries Garden and the Louvre. But on this day in 1992, its Old World meeting rooms have been retrofitted with advanced video technology. The color projector in the back of the room, the size of a small refrigerator, cost upwards of $100,000 and takes an hour to warm up. A team of technicians has spent the better part of the last 48 hours troubleshooting to ensure that nothing goes wrong when Robert Gaskins, the fastidious architect of a new piece of software called PowerPoint 3.0, walks into the room. He’ll be carrying a laptop under his arm, and when he reaches the lectern, he’ll pick up a video cable, plug it in, and demonstrate for the first time something that has been reproduced billions of times since: a video presentation, running straight off a laptop, in full color. The audience, full of Microsoft associates from across Europe, will go bananas. They “grasped immediately what the future would bring for their own presentations,” Gaskins later wrote. “There was deafening applause.” DOUGLAS MESNEY/INCREDIBLE SLIDEMAKERS It’s hard now to imagine deafening applause for a PowerPoint—almost as hard as it is to imagine anyone but Bob Gaskins standing at this particular lectern, ushering in the PowerPoint age. Presentations are in his blood. His father ran an A/V company, and family vacations usually included a trip to the Eastman Kodak factory. During his graduate studies at Berkeley, he tinkered with machine translation and coded computer-generated haiku. He ran away to Silicon Valley to find his fortune before he could finalize his triple PhDs in English, linguistics, and computer science, but he brought with him a deep appreciation for the humanities, staffing his team with like-minded polyglots, including a disproportionately large number of women in technical roles. Because Gaskins ensured that his offices—the only Microsoft division, at the time, in Silicon Valley—housed a museum-worthy art collection, PowerPoint’s architects spent their days among works by Frank Stella, Richard Diebenkorn, and Robert Motherwell. It wasn’t long before the computers that ran the slide shows evolved beyond the medium.TOP ROW: RICHARD SHIPPS/DD&B STUDIO; DOUGLAS MESNEY/INCREDIBLE SLIDEMAKERS; WILDEN ENTERPRISES MIDDLE ROW: DOUGLAS MESNEY/INCREDIBLE SLIDEMAKERS; WILDEN ENTERPRISES; RICHARD SHIPPS/DD&B STUDIOS; BOTTOM ROW: WILDEN ENTERPRISES; RICHARD SHIPPS/DD&B STUDIOS; DOUGLAS MESNEY/INCREDIBLE SLIDEMAKERS; IMAGES COURTESY STEVEN MICHELSEN Gaskins’s for PowerPoint, written when he was VP of product development at the Sunnyvale startup Forethought, is a manifesto in bullet points. It outlines the slumbering, largely-hidden-from-view $3.5 billion business presentation industry and its enormous need for clear, effective slides. It lists technology trends—laser printers, color graphics, “WYSIWYG” software—that point to an emerging desktop presentation market. It’s a stunningly prescient document throughout. But Gaskins italicized only one bullet point in the whole thing. User benefits: Allows the content-originator to control the presentation. This is Gaskins’s key insight: a presentation’s message is inevitably diluted when its production is outsourced. In the early ’80s, he meant that literally. The first two versions of PowerPoint were created to help executives produce their own overhead transparencies and 35-millimeter slides, rather than passing the job off to their secretaries or a slide bureau. PowerPoint had become shorthand for the stupefying indignities of office life—a 2001 New Yorker profile summed it up as “software you impose on other people.” “In the ’50s, ’60s, and early ’70s, information flow was narrow,” explains Sandy Beetner, former CEO of Genigraphics, a business graphics company that was, for several decades, the industry leader in professional presentation graphics. Their clients were primarily Fortune 500 companies and government agencies with the resources to produce full-color charts, 3D renderings, and other high-tech imagery on those slides. Everyone else was limited to acetate overheads and—gasp—words. “Prior to PowerPoint,” she says, “people communicated in black and white. There was just so much missed in that environment.” Beetner oversaw Genigraphics’ national network service bureaus, which were located in every major American city and staffed 24 hours a day, 365 days a year, by graphic artists prepared to produce, polish, and print slides. The company was so vital to presentational culture that Gaskins negotiated a deal to make Genigraphics the official 35-millimeter slide production service for PowerPoint 2.0; a “Send to Genigraphics” menu command was baked into PowerPoint until 2003. This, incidentally, was around the same time that Kodak stopped making Carousel projectors. With multiple projectors pointing toward the same screen, producers could create seamless panoramas and complex animations, all synchronized to tape.WILDEN ENTERPRISES Gaskins retired from Microsoft in 1993 and moved to London. He returned to the States 10 years later, an expert in antique concertinas. By then, PowerPoint had become shorthand for the stupefying indignities of office life. A 2001 New Yorker profile summed it up as “software you impose on other people”; the statistician Edward Tufte, known for his elegant monographs about data visualization, famously blamed the 2003 Columbia shuttle disaster on a bum PowerPoint slide. Gaskins’s software, Tufte argued, produces relentlessly sequential, hierarchical, sloganeering, over-managed presentations, rife with “chartjunk” and devoid of real meaning. No wonder software corporations loved it. Robert Gaskins is remarkably sympathetic to these views, not least because Tufte’s mother, the Renaissance scholar Virginia Tufte, mentored him as an undergraduate in the English department at the University of Southern California. In a reflection written on the 20th anniversary of PowerPoint’s introduction, Gaskins acknowledged that “more business and academic talks look like poor attempts at sales presentations,” a phenomenon he blamed as much on a “mass failure of taste” as on PowerPoint itself, a tool so powerful it collapsed all preexisting contexts. Not everything’s a sales presentation; nor should it be. But PowerPoint made it easy to add multimedia effects to informal talks, empowering lay users to make stylistic decisions once reserved for professionals. To paraphrase an early PowerPoint print ad: now the person making the presentation made the presentation. That those people weren’t always particularly good at it didn’t seem to matter. What did matter was that presentations were no longer reserved for year-end meetings and big ideas worthy of the effort and expense required to prepare color slides. “The scalability of information and audience that PowerPoint brought to the party was pretty incredible,” says Beetner, whose company has survived as a ghost in the machine, in the form of PowerPoint templates and clip art. “It opened up the channels dramatically, and pretty quickly. There isn’t a student alive, at any level, that hasn’t seen a PowerPoint presentation.” Indeed, PowerPoint is used in religious sermons; by schoolchildren preparing book reports; at funerals and weddings. In 2010, Microsoft announced that PowerPoint was installed on more than a billion computers worldwide. At this scale, PowerPoint’s impact on how the world communicates has been immeasurable. But here’s something that can be measured: Microsoft grew tenfold in the years that Robert Gaskins ran its Graphics Business Unit, and it has grown 15-fold since. Technology corporations, like PowerPoint itself, have exploded. And so have their big presentations, which are no longer held behind closed doors. They’re now semi-public affairs, watched—willingly and enthusiastically—by consumers around the world. Nobody has to worry about slide carousels getting jammed anymore, but things still go haywire all the time, from buggy tech demos to poorly-thought-out theatrics. When everything works, a good presentation can drive markets and forge reputations. Of course, this particular evolution wasn’t exclusively Microsoft’s doing. Because perhaps the most memorable corporate presentation of all time—Steve Jobs’s announcement of the iPhone at Macworld 2007— wasn’t a PowerPoint at all. It was a . Claire L. Evans is a writer and musician exploring ecology, technology, and culture.

Fifty years ago, the average business transaction was pretty straightforward. Shoppers handed purchases directly to cashiers, business partners shook hands in person, and people brought malfunctioning machines to a repair shop across the street. The proximity of all participating parties meant that both customers and businesses could verify authority and authenticity with their own eyes. But the internet has changed the very nature of how we transact, and more recently the rise of remote work has added yet more complexity to the mix. Today, a customer in Texas can call a business in Prague for product support and reach a technician ten thousand miles away in a coworking space in India—all while using a communication platform on the cloud. In other words, there are many more technology layers and much greater distances involved in even basic business interactions today. As such, authentication and verification have become much more challenging. This greatly expanded attack surface can spell bad news for companies that aren’t properly equipped to defend themselves against cybersecurity threats. Globally, the average data breach costs $4.35 million. In the U.S., the figure is more than double that—around $9.44 million. And such breaches are all-too-common occurrences, with more than 1,800 data compromises reported in the U.S. in 2022. But in the same way that business has evolved for the modern era, protective cybersecurity measures are also becoming more advanced. Today, digital solutions that integrate emerging technologies like AI into human-centric workflows are helping mitigate myriad threats. What’s more, intelligent digital solutions can protect sensitive business data while simultaneously simplifying and streamlining business operations. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This is today’s edition of , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Who gets to decide who receives experimental medical treatments? There has been a trend toward lowering the bar for new medicines, and it is becoming easier for people to access treatments that might not help them—and could even harm them. Anecdotes appear to be overpowering evidence in decisions on drug approval. As a result, we’re ending up with some drugs that don’t work. We urgently need to question how these decisions are made. Who should have access to experimental therapies? And who should get to decide? Such questions are especially pressing considering how quickly biotechnology is advancing. We’re not just improving on existing classes of treatments—we’re creating entirely new ones. For many, especially those with severe diseases, an experimental treatment may be better than nothing. But if companies struggle to get funding following a bad outcome, it can delay progress in an entire research field. . —Jessica Hamzelou This story is from the next upcoming issue of our print magazine, which is all about ethics. If you don’t subscribe already, to receive a copy when it publishes. Why watermarking AI-generated content won’t guarantee trust online —Claire Leibowicz is the Head of the AI and Media Integrity Program at the Partnership on AI and a doctoral candidate at Oxford studying AI governance and synthetic media. In late May, the Pentagon appeared to be on fire. A few miles away, White House aides and reporters scrambled to figure out whether a viral online image of the exploding building was in fact real. It wasn’t. . Yet it had real impact: it not only caused panic and confusion but led to a dip in financial markets. Whether to promote election integrity, protect evidence, reduce misinformation, or preserve historical records, it’s increasingly clear that we ought to know when content has been manipulated or generated with AI. Disclosure methods like watermarks are a good start. However, they’re complicated to put into practice, and they aren’t a quick fix. . Inside MIT’s nuclear reactor laboratory Our climate and energy reporter Casey Crownhart got a chance to tour MIT’s nuclear reactor last week. It was built in the 1950s, and its purpose has shifted over the decades. At various points, it’s been used to study everything from nuclear physics to medical therapies, alongside its consistent use for teaching the next generation of nuclear scientists. Now, it’s poised to take on a new purpose: as a testbed for the growing number of startups seeking to use molten salt as an alternative to water for cooling nuclear reactors. . Casey’s story is from The Spark, her weekly newsletter explaining the tech that could combat the climate crisis. to receive it in your inbox every Wednesday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Ukraine is unleashing regular drone attacks on MoscowSome seem to have been intercepted—but not all. ( $)+ Mass-market military drones have changed the way wars are fought. () 2 Biden signed a measure limiting US investment in Chinese techThe order targets advanced semiconductors and quantum computers. ( $)+ China’s internet giants are rushing to stockpile billions of dollars worth of chips ahead of potential restrictions. ( $)+ The US-China chip war is still escalating. ()3 Inside the race to rescue the world’s DNA More than 40,000 species are categorized as threatened. The true figure will be much higher. $)4 People are using AI to give voices to dead childrenHard to see any benefit to this whatsoever, and it deeply hurts bereaved parents. ( $)+ This company is struggling to stop its deepfake tech being used for misinformation. ( $)+ Digital clones of the people we love could forever change how we grieve. ()5 Twitter is being forced to hand over Trump’s dataAfter being held in contempt of court and fined $350,000. ()+ Trump’s tweets are coming back to bite him. ( $)6 Tons of work is being plowed into hydrogen planes It’s early days, but if technical challenges can be overcome, they could be a promising part of decarbonizing aviation. ()+ Hydrogen-powered planes take off with a startup’s test flight. ()7 There’s a decent chance you’re oversharing if you’re on VenmoEveryone can see your contacts list, for example. ( $)8 How to make Slack work for youBeing driven mad by non-stop notifications? You need to read this. ( $)+ Slack is about to undergo its biggest redesign yet. () 9 Apple Maps is better than it used to beBut, I mean… Google’s already won. () 10 Heat is Enemy Number One for your smartphone’s batterySomething to bear in mind before sitting and scrolling in the blazing sunshine. ( $) Quote of the day “I don’t think the U.S. Treasury or the [Biden] administration planned it this way, but this is spectacularly bad timing for China.” —Eswar Prasad, a professor in international trade at Cornell University, tells that the latest limits on US investment in China come as the country is already grappling with low growth, deflation and other economic problems. The big story What does breaking up Big Tech really mean? ANDREA DAQUINO June 2021 For Apple, Amazon, Facebook, and Alphabet, covid-19 was an economic blessing. Even as the pandemic sent the global economy into a deep recession and cratered most companies’ profits, these companies—often referred to as the “Big Four” of technology—not only survived but thrived. Yet at the same time, they have come under unprecedented attack from politicians and government regulators in the US and Europe, in the form of new lawsuits, proposed bills, and regulations. There’s no denying that the pressure is building to rein in Big Tech’s power. But what would that entail? . —James Surowiecki We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or .) + If you struggle with sleep too, check out . TL;DR? Stop fighting.+ Eating at Gyozanomise Okei has gone straight onto my bucket list. + Still can’t get over this . + Fashions come and go, but cottage cheese will always be a . ($)

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, . Tucked away behind a brick building on MIT’s campus sits a nuclear reactor. I’ve been hearing about this facility for over a decade, and it’s taken on a somewhat mythic quality in my mind. So I was excited to finally get to see it for myself last week. MIT’s research reactor was built in the 1950s, and its purpose has shifted over the decades. At various points, it’s been used to study everything from nuclear physics to medical therapies, alongside its consistent use for teaching the next generation of nuclear scientists. But I was most excited to hear about an energy-focused project, which is aimed at bringing novel reactor technology to reality. While virtually all commercial nuclear reactors today are cooled using water, a growing number of startups are looking to molten salt as an alternative. MIT’s nuclear reactor lab is working on a new research space that could help illuminate how well alternative technologies withstand the intense conditions inside a nuclear reactor. So for the newsletter this week, come along on my tour of MIT’s nuclear reactor lab. On the way, we can get into what all the buzz is all about with molten-salt reactors. Hot topics The first stop on my tour was the front desk, where I and each member of my group picked up a personal dosimeter to track any potential radiation exposure. We then handed over our bags and phones and got stern warnings not to touch anything or wander out of our tour guide’s sight. Finally, we filed through a set of reinforced metal doors and into the lab. We passed rows of yellow lab coats as , the head of reactor experiments and our tour guide, walked us through some history and basic facts. This is the second-largest university research reactor running in the US today, producing about six megawatts of thermal power. Commercial reactors tend to have capacities hundreds of times greater than that—around 3,000 megawatts (or three gigawatts) of thermal power. (Speedy nuclear basics: nuclear reactors are powered by fission reactions, where uranium atoms break apart. These reactions produce neutrons, which are a type of ionizing radiation, as well as heat that can be harnessed and transformed into electricity.) Reactors used on the power grid generate heat in the form of steam and turn it into electricity. But for this research reactor, the heat is basically a by-product, and the focus is all on the neutrons. MIT’s reactor is better than most other university research facilities at mimicking radiation conditions in larger commercial reactors. For that reason, the facility is used today for a lot of engineering research and development, Carpenter says. Before companies use new materials or sensors inside or near nuclear reactors, they can test them at similar radiation, temperature, and pressure conditions in a controlled environment in the research reactor. Samples can either be put directly into the core or subjected to radiation that’s allowed out in controlled corridors called beam lines. Chain reactions I had the distinct feeling that I was about to get launched into space as we approached the entrance to the reactor room, though the doors were painted a surprisingly whimsical robin’s egg blue. After Carpenter went through a round of security checks, the first door swung open, revealing a small airlock chamber and a duplicate blue door. After we waited a few seconds inside the airlock, the second door swung open and we were suddenly faced with the reactor. While the core where the fuel is contained is only about two feet tall (less than a meter), the whole setup is several stories high. Carpenter walked us around the reactor, pointing out a chamber that used to be dedicated to medical neutron therapy in the early 2000s. That research has fizzled out, so now the space is getting a makeover. Its new purpose will be to test out aspects of molten-salt-cooled reactors. Molten salt was a candidate for cooling reactors as early as the 1950s. Interest slowed as water-cooled reactors started entering commercial operation, but in the early 2000s, scientists—including some at MIT—revived the work. Several startups, including and , are working to bring molten-salt reactors into commercial operation. These companies are building demonstration systems of their cooling setups and seeking licenses for test reactors. MIT’s lab won’t be operating a molten-salt reactor. Instead, it will help gather more data on how the technology will work in the real world. The space will allow companies and academic researchers to test not only small pieces of material used to build reactors and individual sensors, but a whole operating set of pumps and pipes to move hot salt around in a circuit and see how everything reacts to radiation. “Given where the new molten-salt reactor industry is today, we still need to investigate more basic functions,” Carpenter told me in an email after our tour. Data from MIT and other research facilities could help determine how molten-salt setups will handle what it’s really like inside a nuclear reactor. The facility should be fully up and running in 2024. Related reading My colleague James Temple visited the MIT Nuclear Reactor Lab in 2017. The plan for the molten-salt work has shifted a bit since then, but take a look at for more on the facility. Advanced nuclear reactors were on our 2019 list of breakthrough technologies—read more in about the potential for progress in nuclear power. While nuclear reactors can provide stable, low-carbon power for the grid, Germany shut down In addition to changing up cooling approaches, some companies are looking to change nuclear technology by shrinking it. Read more about small modular reactors in Keeping up with climate All this heat is wreaking havoc on agriculture. While the weather is affecting staple crops like wheat, the greatest challenge could be for specialty crops like peaches in Georgia and olives in Spain. () Skepticism is catching up to a US agency’s plan to push the country toward EVs. Critics argue that the new rules will be difficult to implement and might not have the promised results even if they take effect. () Planes powered by hydrogen could help cut emissions, though the technology will probably be limited to shorter flights on smaller aircraft at first. () → Read more about why hydrogen planes were the readers’ choice on our breakthrough technologies list for 2023. () New rules in Texas could force up to 50,000 megawatts of wind and solar power to disconnect from the grid. The rules aim to increase grid reliability, though critics say they could wind up harming operations. () The “chasing arrows” symbol is used to symbolize recycling in the US, but it’s been used and misused so much that one government agency wants to ditch it. () → I loved this quiz from earlier this year about how to sort recycling. () → New chemical recycling methods could cut out the need for sorting altogether. () There’s a debate swirling about how to deal with e-bikes when they’ve reached the end of their lives: to repair or to recycle? The industry opposes laws that make the bikes easier to fix, citing safety concerns. () Remember when we all freaked out about that fusion news in December? Researchers repeated the experiments and say they got even more energy back from the reaction. () → Here’s what you need to know about what these early steps mean for the prospect of fusion energy. ()

Organizations are building resilient supply chains with a “phygital” approach, a blend of digital and physical tools. In recent years, the global supply chain has been disrupted due to the covid-19 pandemic, geopolitical volatility, overwhelmed legacy systems, and labor shortages. The National Association of Manufacturers (NAM), an industrial advocacy group, warns the disruption isn’t over— found 90% of respondents saw significant (52.5%) or partial (39%) supply chain disruption during the past two years. Just 0.5% of respondents reported no disruption at all. Digitization presents an opportunity to overcome supply chain disruption by making data flow more efficiently, using technology and data standards to break barriers between disparate systems. “Phygital merges two worlds together, where standards provide an interoperable system of defined data structures,” says Melanie Nuce-Hilton, senior vice president of innovation and partnerships at GS1 US, a member of GS1, a global not-for-profit supply chain standards organization. “The approach is intended to deliver multiple benefits—improved supply chain visibility for traceability and inventory management, better customer experiences across online and offline interactions, and the potential for better circularity and waste reduction by maintaining linkages between products and their data throughout their lifecycle,” she says. Unlocking data value Phygital systems blend digital tools and data standards with physical data carriers, such as barcodes. These tie products, assets, logistics units, and locations within a supply chain to digital information for enhanced accuracy and consistency. This capability, especially with more advanced data carriers, can help automate data flows and boost supply-chain visibility. such as the increasingly common QR codes (quick-response codes) or Data Matrix barcodes (codes with a black-and-white grid pattern), store more information—up to 7,000 characters, compared to about 20 characters for conventional bar codes. The technology is growing alongside its use in the supply chain. data measured the global barcode reader market at $7.3 billion in 2022, and projects it will maintain a 7% CAGR from 2023 to 2030. By uniquely identifying products and tracking their supply chain journey with universal standards, Nuce-Hilton says, organizations can unlock extended value for the whole enterprise. This can lead to raising operational efficiencies, improving safety, attracting consumers, advancing energy efficiency, and decreasing waste. “Supply chain resilience isn’t just about the supply chain,” she says. “It’s about the whole enterprise coming together from a data, product, and execution point of view to create an immersive experience.” The best of both worlds Several industries have explored phygital connections to enhance user experience or speed up processes. There are multiple ways to connect physical objects to technology and standardized data; all can help make data accessible, sharable, and useful. These phygital connections of product data, financial facts, and information to real-world activity can lead to a more resilient supply chain, Nuce-Hilton says. For example, retailer Pacsun —Pacsun Los Angeles Tycoon—in early 2023 with platform provider Roblox. This metaverse experience uses avatars so participants can connect and play games while viewing Pacsun’s 2023 summer clothing collection, bridging physical and virtual experiences. used phygital tools in 2022 in its Cryptokicks digital sneaker campaign with Roblox. Avid sneaker collectors can buy virtual sneakers as non-fungible tokens (NFT). Each unique digital pair is one of 20,000 customizable NFTs, some of which trade for hundreds—or thousands—of dollars. Healthcare companies have invested in phygital track-and-trace technology like barcodes and RFID tags for patient safety: Global healthcare company Fresenius Kabi relies on GS1 DataMatrix, a two-dimensional barcode carrying drug information, for its product portfolio. German consultancy Roland Berger said in its that such digital health care technologies are reaching maturity, pointing to not just tracking but digital patient monitoring, early detection devices, and using data for AI for diagnostics and therapies. Phygital technology also helps the food industry keep food safer, while ensuring trading partners and consumers can get the products they want. Imagine, Nuce-Hilton says, a frozen pizza manufacturer whose products, with various expiration dates included in 2D barcodes, ship to hundreds of retailers from dozens of plants. With machine-readable expiration data, the manufacturer and retailer can know which products will expire and when, avoiding delays, inventory gaps, and empty shelves. A 2023 Zebra Technologies annual survey found nearly half of retail shoppers who left stores emptyhanded did so because their , an experience increasingly commonplace during the past two years, having increased by 26% since the 2019 survey. Examining the business benefits Phygital tools, with data standards and technology, deliver broad benefits to the enterprise, Nuce-Hilton says. These are some of the ways businesses can benefit. Supply-chain traceability:Produce grower encodes traceability data, such as which crew picked the produce, the farm location, and packaging methods, in barcodes on case labels to enhance inventory management and order optimization. The grower calculates that barcodes, digital tools, and data standards help them achieve up to 35% in time savings compared to their former system. Safety and quality assurance:Fast-food restauranteur Subway for product data, which identify product expiration dates, best-before guidelines, and sell-by data. Traceability means faster and more accurate inventory management, and cuts down on human error. Data standards and technology empower them to quickly apply safety practices to protect consumers. Improved sustainability posture:Consumers and investors increasingly want to see environmental, social, and governance (ESG) data. Companies can build trust by increasing availability of ESG data, providing accountability. Phygital ESG data can include such things has product origin, ingredients, biodegradability, production processes, and energy use. More connected consumers:When customers scan object identifiers, they establish a phygital connection. This can provide customers with information such as how an item is made, ingredients, or geographical origin. Customers are interested: McKinsey 2022 data says customers who buy using omnichannel methods (a combination of physical, digital, and other experiences) than consumers who don’t—and they also spend more. Building for phygital success Organizations can benefit—using standards, technology, and data—by putting their data to work more broadly, says Nuce-Hilton. She suggests the following: Deploy the right technology tools: Advanced data carriers hold a large amount of information, so it’s critical to use appropriate analytics tools and IT resources to analyze and convert data into business insights. Throughout the supply chain, these tools can enhance inventory management, streamline logistics, and support traceability and sustainability. Look to AI for speed: As phygital systems make it easier to collect product data, innovative technologies such as generative AI promise to up the ante by accelerating tasks, such as creating code and analyzing supply chain data to detect anomalies and recommend corrections. Shape behavior around standards and collaboration: Increasingly complex supply chain ecosystems make collaboration and communication critical. “You can deploy any technology you want and call it what you want, but until the behaviors associated between trading partners change, you won’t be successful,” says Nuce-Hilton. Processes and underlying data structures are a common language for supply-chain partners. Supply chain resilience is needed to meet fluctuating consumer demands, respond to unanticipated roadblocks, and satisfy ESG goals. Today’s business environment makes that a challenge, says Nuce-Hilton. “But we could change that, if we empower organizations with the data to make better decisions further upstream in the supply chain,” she says. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This is today’s edition of , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. After 25 years of hype, embryonic stem cells are still waiting for their moment In 1998, researchers isolated powerful stem cells from human embryos. It was a breakthrough for biology, since these cells are the starting point for human bodies and have the capacity to turn into any other type of cell—heart cells, neurons, you name it. National Geographic would later summarize the incredible promise: “the dream is to launch a medical revolution in which ailing organs and tissues might be repaired” with living replacements. It was the dawn of a new era. A holy grail. Pick your favorite cliché—they all got airtime. Yet today, more than two decades later, there are no treatments on the market based on these cells. Not one. Our biotech editor Antonio Regalado set out to investigate why, and when that might change. . China is escalating its war on kids’ screen time When it comes to controlling how minors use the internet, China is a world leader, thanks to measures like its strict three-hour-per-week limit for children playing video games. It’s now going even bigger: last week it announced a complex maze of new rules governing how children use every different type of device. For example, under 16s are limited to a maximum of an hour using any device a day. Many in the US may be jealous of this degree of control. But it taps into the same paternalistic attitude that determines what children should watch and what adults should read. How comfortable are we in pushing the balance further to the side of centralized control rather than individual decision-making? . This story is from China Report, Zeyi Yang’s weekly newsletter giving you the inside story on what’s going on in China’s tech sector. to receive it in your inbox every Tuesday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 People are keen to get excited about technology Hype around superconductors and nuclear fusion suggest we’re swinging back towards techno-utopianism. ( $)+ Are you ready to be a techno-optimist again? () 2 WeWork has warned it could go underIt’s losing customers as the co-working market gets more competitive. ( $) 3 AI could help to fuel eating disordersAwful but unsurprising—it’s been trained on online content, and there’s a lot of pro-anorexia stuff out there. ( $) + The woes for AI image-generation startup Stability AI appear to be mounting. ( $)+ Here’s how we rein in AI. ( $)+ Our quick guide to the 6 ways we can regulate AI. ()4 Why it’s so hard to forecast wildfire smoke At best, we can still only predict it a day or so ahead. ( $)+ The quest to build wildfire-resistant homes. ()+ Europe is struggling with floods, wildfires and torrential rain this week. ( $)5 China plans to restrict face recognition techNew rules are just the latest effort to impose guardrails around AI tech there. ( $)+ China isn’t waiting to set down rules on generative AI. ()6 Grimes is always excellent entertainment valueThis interview covers everything from AI art to dying on Mars to the odds on that Musk v Zuck fight happening. ( $)+ The press ought to exercise a bit more skepticism when covering Mr Musk’s antics. ()7 TMSC is going to build its first European chip plant in GermanyEurope is following the US and China’s lead and trying to reduce reliance on external suppliers. ( $)+ What’s next for the chip industry. ()8 You could take an Alzheimer’s risk test. But should you? It’s unclear what you can do if you’re at high risk, besides going crazy with worry. ( $)9 It seems serial killings are becoming rarer And it’s likely that we can at least partly thank technology. ( $) 10 TikTok is launching its first livestream music competitionMakes sense! But weirdly, it’s yet to confirm how much money winners get. () Quote of the day “Whoever’s doing this is obviously preying on writers who trust my name and think I’ve actually written these books. I have not. Most likely they’ve been generated by AI.” —Author Jane Friedman has had enough of Amazon and Goodreads hosting fraudulent AI-generated books under her name, she writes in a . The big story Gene editing has made pigs immune to a deadly epidemic SELMAN DESIGN December 2020 When covid-19 began to spread, countries closed businesses and told people to stay home. Many thought that would be enough to stop the coronavirus. If we had paid more attention to pigs, we might have known better.To prevent their animals contracting diseases, pig farmers employ measures familiar to anyone who has been avoiding covid-19, including contact tracing, disinfecting supplies, and requiring human workers to change clothes before entering a secure barn. Now the Pig Improvement Company, in Hendersonville, Tennessee, is trying something different. Instead of trying to seal animals off from the environment, it’s changing the pigs themselves. It’s using CRISPR, the revolutionary gene scissors, to make piglets immune to deadly diseases. . —Antonio Regalado We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or .) + Get out of a cooking rut with these .+ Cat lovers know… it really is just .+ If you’re a fan of word games, this devilishly difficult will keep you busy. + So much to love about these . (Thanks Stefan!)

Twenty-five years ago, in 1998, researchers in Wisconsin isolated powerful stem cells from human embryos. It was a fundamental breakthrough for biology, since these cells are the starting point for human bodies and have the capacity to turn into any other type of cell—heart cells, neurons, you name it. National Geographic would later summarize the incredible promise: “the dream is to launch a medical revolution in which ailing organs and tissues might be repaired” with living replacements. It was the dawn of a new era. A holy grail. Pick your favorite cliché—they all got airtime. Yet today, more than two decades later, there are no treatments on the market based on these cells. Not one. To find out what happened, this June I grabbed a seat in the front row at the annual International Society for Stem Cell Research meeting, in an auditorium alongside hundreds of biologists. Projected on a huge screen was a slightly intimidating black-and-white image of cells seen through a microscope, some round with groping hair-like extensions, others rectangular cross-sections filled with a mysterious substance that looked like sand. Theme music bubbled from the stage: “I Want a New Drug,” by Huey Lewis and the News. During the stem-cell meeting, I had a chance to meet old sources—some now literally so, scientists transmuted by a quarter-century and hard work into deans or wizened advisers. I asked: is 25 years and counting a normal time frame, or is something amiss with this vaunted technology? To most of the people I spoke with, the agonizing delay is no surprise. That’s how long it can take for a truly novel biotechnology to develop. The initial human test of a gene therapy occurred , but it wasn’t that the first gene fix was approved for sale in Europe. By that yardstick, stem cells are on track. Others concede that melding stem cells into medicine has proved surprisingly difficult. The basic challenge is that cells are not like aspirin or another drug that can be made by the pound. They’re living things, which can change, die, or even run out of control, causing dangers like cancer. By this account, capturing the embryonic stem cell was the easy part. It’s coaxing them to produce specialized cells—the kind with specific functions needed to treat disease—that’s been so hard. “Ideas take a long time, but it’s still the right idea,” said Matthew Porteus, a professor from Stanford University whom I peppered with questions while he was standing at a podium at the meeting. There are signs that stem-cell-based treatments are finally poised for a breakout. According to, nearly 70 new tests on volunteers got underway in the last four years—triple the previous pace. The most advanced of these early human studies is being carried out by Vertex Pharmaceuticals, which in June said two diabetes patients who received injections of lab-made pancreatic cells . Tests of manufactured cells to treat blindness and epilepsy also have early results that suggest transplanted cells are helping. “A lot of things are on the verge,” says Haifan Lin, a Harvard University professor who is the outgoing president of the ISSCR. “I don’t think it’s delayed, because stem cells are truly the most complicated of all cells.” Tabula rasa I have covered embryonic stem cells since the beginning— even a little bit before the beginning. Here at MIT Technology Review, we broke the story of the , carried out under the looming threat of opposition from anti-abortion campaigners. Our July/August 1998 cover, “,” set the mood with a picture of a petri dish gleaming in the darkness. “If awards were given for the most intriguing, controversial, and hush-hush of scientific pursuits,” I wrote, “the search for the embryonic stem cell would likely sweep the categories.” It was the search for a tabula rasa cell, we told readers—one able to give rise to any other type in the human body. The embryonic stem cell was a potential “factory in a dish” that could give scientists for the first time “the ability to grow human tissue at will.” And it was taboo because the cells existed only in early-stage human embryos, which could be obtained from IVF clinics but had to be destroyed in order to isolate the cells. A moody 1998 cover of MIT Technology Review predicted the arrival of embryonic stem cells—and of an ethical controversy.ROBERT CARDIN A few months after our report, the scientific race reached its conclusion. That November, James Thomson at the University of Wisconsin reported he’d captured stem cells from five embryos and was keeping these cells alive, and multiplying, in his lab. Thomson’s , a succinct three-pager in the journal Science, contained a sketch of how he thought stem cells would become a medical technology.Where organs or cells from cadavers are in short supply, he predicted, stem cells “will provide a potentially limitless source of cells for drug discovery and transplantation medicine,” in particular by permitting “standardized production” of specialist cell types like beating heart cells or glucose-sensing beta cells. He noted that some diseases, specifically type 1 diabetes and Parkinson’s, result from “the death or dysfunction of just one or a few cell types.” If those specific cells could be replaced, it would mean “life-long treatment.” That vision—that the mother of all cells could replace any tissue, or even regrow organs—is what electrified a generation of researchers. “That was the closest thing to magic that I have encountered. It’s a cell that keeps dividing and makes anything. If you are a cell biologist, that is the grail,” says Jeanne Loring, a professor emerita at the Scripps Research Institute and cofounder of Aspen Neuroscience, a company that plans to treat Parkinson’s disease with a transplant of dopamine-making cells. “The problem is, how do you make them into the precise cell type that you want?” What’s more, if stem cells are allowed to multiply in the lab, they can accumulate mutations, posing potential cancer risks: “That is the dark part of the magic.” Political test The stem-cell concept would shortly face a defining test—but it was political, not scientific. Because they’d been plucked from tiny, but living, IVF embryos, destroying them in the process, the discovery was met with outrage from the Catholic Church and other religious organizations in the US. Two years after Thomson’s paper, George W. Bush was elected president. Now Christian conservatives had a line into the White House, and they wanted federal funding for the research on the cells blocked. Scientists, aided by patient advocates, reacted with an overwhelming lobbying campaign. Yes to cures, they rallied. “I love stem cells,” read the bumper stickers. That equation—stem cells equals cures—made the breakthroughs seem closer than they really were. Martin Pera, editor in chief of Stem Cell Reports, an academic journal, was part of the push: in an editorial that year, for example, he wrote that treatments would be realized “soon,” if only the government and charities would fund the science. “It was all in our imagination at the time,” Pera told me when I saw him at the ISSCR meeting. “Because all we had were undifferentiated stem cells.” Timothy Caulfield, a health law professor at the University of Alberta, would later analyze news articles and determine that scientists consistently made “authoritative statements” with “unrealistic timelines” for when cures would come. “I don’t blame the researchers,” he says. “There is a microphone in front of them, and five or 10 years is close enough yet far enough away. You have to make it exciting, revolutionary. If not, the money is going somewhere else.” But the public believed these time frames—as well as the story that only a lack of funding stood in the way of cures. So after the US introduced some limits on stem-cell research (allowing research funding on only a few supplies of the cells), patient groups struck back.In California, a 2004 ballot initiative, Proposition 71, established the California Institute of Regenerative Medicine. It made stem-cell research a “constitutional right” in the state and allotted $3 billion in tax funds for research over 10 years. By that time, lobbyists predicted, the initiative would pay for itself twice over through a bonanza of jobs and cures. Just treating type 1 diabetes (“in year six,” according to a projection) would save $122 billion in insulin and other costs. stem cells would cure “a million people with Parkinson’s.” None of those cures has reached the market yet. And many of the patient advocates from those years, some of whom hoped stem cells would save them, are now dead: Jenifer Estess, David Ames, the actor Christopher Reeve, and Jordan Klein. The last was the son of Bob Klein, the California real estate entrepreneur who’d put Prop 71 into motion. After Jordan died from complications of type 1 diabetes in 2016, age 26, his father blamed political delays, according to the. “My youngest son died. If they hadn’t held it up in DC, he would be alive,” Klein told the publication. “There was this dystopian-versus-utopian view of stem cells in the early 2000s.”-Timothy Caulfield The belief in stem-cell cures had become entrenched. To people like Klein, it was political meddling that was delaying them. “There was this dystopian-versus-utopian view of stem cells in the early 2000s,” says Caulfield. “You had people saying it’s unethical or immoral or shouldn’t be allowed. The research community, and I was part of it, had to push back and say this is an exciting area and we are going to save lives. And all this language has survived.” The clearest evidence? Fly-by-night medical clinics that started cashing in on the hype, advertising stem-cell cures for autism, migraines, and multiple sclerosis—a phenomenon Caulfied calls “scienceploitation.” For many years, any Google search for stem cells would return ads from shady clinics offering to treat just about anything, usually with cells collected from blood or fat tissue. I learned how pervasive the phenomenon is this spring when an elderly acquaintance revealed she’d paid over $7,000 in cash for an injection of supposed stem cells drawn from her bones in the hopes of treating a painful knee. Of course, it likely didn’t do anything. She could have saved her money had she read a pamphlet from the ISSCR called “” Despite its title, which sounds like a product glossary, it’s a lengthy warning about scam clinics, explaining that essentially any stem-cell treatment you see advertised today is a fake. That’s because, in reality, nothing could make stem cells move faster than the speed of science. “When the promise of stem cells reached the public consciousness … there was the idea that stem cells are themselves a magic cure, even though that is ridiculous,” says Arnold Kriegstein, a professor at the University of California, San Francisco. “The true promise was not that the stem cells would do this, but that they were the starting point for the cells you wanted. And that is never simple. That is painstaking and slow. That is science—it’s laborious and takes time.” Delayed promise Stem-cell research is no longer as political as it once was. That’s partly because by 2006, scientists had determined how to convert any cell, like a bit of skin, . Such “induced” stem cells are largely identical to those from embryos, and without the ethical hangover. But whichever type of stem cell researchers choose, using them to manufacture mature, specialized cells (the kind you’d want for transplant) turned out to be more difficult than most expected. The strategy scientists have been taking to generate the cell types they want is called “directed differentiation.” You can think of directed differentiation as a cookbook approach—add this growth factor at day 2, that one on day 12, and so on—that exposes a stem cell to the same sorts of external cues it would receive if it were part of a developing baby. While the cookbook process can be successful, it is extraordinarily difficult to hit on a correct recipe. For instance, the scientist Douglas Melton, who has two children with type 1 diabetes and who developed the Vertex treatment that’s now in testing, spent close to 15 years before he was able to produce “” pancreatic cells able to respond to glucose and make insulin when transplanted into a mouse. “That problem took much longer than I expected—I told my wife it would take five years,” Melton recounted to a Harvard publication. Maturing into a wanted cell type takes stem cells about as long in a lab dish as it does during an actual pregnancy—even six or seven months. What’s more, maturing into a wanted cell type can take stem cells as long in a lab as it does during an actual pregnancy—sometimes six or seven months. That’s been a significant obstacle to trying out new ideas, since each new test means a further long delay. “I was optimistic, but when you do the experiment, it can take 200 days,” says Hanae Lahlou, a principal scientist at Mass Eye and Ear, one of Harvard’s teaching hospitals. She was part of a project that tried using transplants. They hoped the engrafted cells would grow into new auditory hairs, but they never quite did. Now Lahlou is trying speedier genetic techniques rather than cell transplants. “At some point I didn’t see it as a therapeutic tool,” she says. “If you ask patients, they want a drug.” Making cells isn’t cheap, either. Just a gram of their favorite growth factor costs $750,000. Add to that the regulatory barriers that face any untested approach, and it’s clear why biotechnology companies’ work with stem cells has been fitful. Geron, which once controlled a patent on embryonic stem cells and launched of a treatment created from them in 2010, the study a year later. Now it works on cancer drugs and no longer mentions embryonic stem cells on its website. Another stem-cell company, Sana, has seen its stock value droop since its 2021 IPO and last year trying to create heart muscle to treat cardiac disease. Early stage trials High costs and technical difficulties aren’t unusual in the biotech world, and there is still a resilient cadre of investors and scientists who believe that stem-cell therapies are worth the risk. Today, stem-cell researchers say the increasing number of new clinical trials—about 15 are launching each year—is a sign the field may be close to a turning point. Transplants of lab-made retina cells (the approach tested most often so far) can’t be said to improve eyesight yet, but there is evidence from the initial handful of patients that the cells are doing something. According to a survey , more than 3,000 patients have received transplants generated from induced or embryonic stem cells in around 90 studies, though all of these tests remain in their initial phases. “If you look around, all the trials are at an early stage. Not all are likely to produce cures, but they will give us information on how to improve and how to refine things,” says Pera. For transplanted cells, one open question that can be answered only through experiments on people is how long those cells will survive. When dopamine-making neurons are added to the brains of Parkinson’s patients, something that’s been tried a few times,. Researchers have gone back to the drawing board, trying to figure out why, and how to adjust their tactics. Maybe they just need to crank up the dose, despite possible risks—too much dopamine is almost as bad as too little, and it can cause involuntary movements. The Vertex study on diabetes, which is expected to treat 40 people, looks more promising, but there too it remains unclear how long the added cells will live. It means a very costly treatment (some estimate a cell transplant for diabetes will run at least $500,000) might not be forever. Yet Loring is hopeful that one of these tests will soon lead to striking, incontrovertible proof that treatments crafted from embryonic stem cells can cure disease. “It could be the tipping point,” she says. “And I do think we need that moment.” Epilepsy treatment During the three days I spent at the gathering of stem-cell researchers, one study stood out to me as looking like the big breakthrough this field needs. It’s a new trial being run by a biotech called Neurona Therapeutics, in San Francisco, which a year ago transplanted lab-made “inhibitory interneurons” deep into the brains of two people whose intractable epilepsy wasn’t responding to ordinary drugs. The bet is that these added cells will each form thousands of connections and quiet the malfunctioning brain networks that cause seizures. During the meeting, Neurona announced that both patients have seen a 90%-plus reduction in seizures. In the case of one 26-year-old-man, that’s down from a debilitating 32 seizures a month. If the data holds up, it could mean the cell transplant is as effective as the most drastic treatment available for epilepsy today, which is surgical removal of part of the temporal lobe. But it wouldn’t have the side effects of getting part of your brain removed, like lost memories and vision. “There’s a lot of enthusiasm. This could be the first cell therapy for epilepsy,” says Kriegstein, the professor at the University of California, San Francisco, who is also an adviser to Neurona and its cofounder. Kriegstein told me he doesn’t think 25 years is a long time for this type of therapy to emerge. Instead, he counters, it’s “actually kind of fast.” “There’s a lot of enthusiasm. This could be the first cell therapy for epilepsy.”-Arnold Kriegstein Doctors had experimented with neuron grafts before—one company tried using cells from pigs. But it was Cory Nicholas, a postdoctoral fellow in Kriegstein’s lab, who first determined, in 2013, how embryonic stem cells might be coaxed towards forming human interneurons in large quantities. What followed was what Kriegstein calls a series of “rational, systematic” steps over a decade to improve that recipe, run tests on animals, and win approval to start a human trial. Most of that work was done at Neurona, which has raised over $160 million and where Nicholas is CEO. “Obviously, this wouldn’t be possible without embryonic [or induced] stem cells,” says Kriegstein. With only two patients treated, Neurona’s results remain anecdotal. But there’s a chance it’s an actual cure. That’s because the transplanted cells are likely still forming connections, and their effect may increase with time, possibly preventing seizures altogether. “It did seem like a pipe dream at first, but being able to make these cells in unlimited numbers is what let us try. Now we have patients who’ve been helped. It’s really quite amazing when you think about it,” says Kriegstein. “We are in the clinic. Cells are in patients, and we are going to see now how well they work. We are right at the point that the clinical trials will give us some clues. Was it just hype, or is it real?”

This is today’s edition of , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. AI language models are rife with different political biases The news: AI language models contain different political biases, according to a new study. Researchers conducted tests on 14 large language models and found that OpenAI’s ChatGPT and GPT-4 were the most left-wing libertarian, while Meta’s LLaMA was the most right-wing authoritarian. How they did it: The team asked language models where they stand on various topics, such as feminism and democracy. They used the answers to plot them on a political compass, then tested whether retraining models on even more politically biased training data changed their behavior and ability to detect hate speech and misinformation (it did). Why it matters: As AI language models are rolled out into products and services used by millions, understanding their underlying political assumptions could not be more important. That’s because they have the potential to cause real harm. A chatbot offering health-care advice might refuse to offer advice on abortion or contraception, for example. . —Melissa Heikkilä Read next: AI language models have recently become mixed up in the US culture wars, with some calling for developers to create unbiased, purely fact-based AI chatbots. In her weekly newsletter all about AI, The Algorithm, Melissa delves into why it’s a nice concept—but technically impossible to build. , and if you don’t already, every Monday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 A woman was wrongfully arrested after a false face recognition matchIt’s notable that every person we know this has happened to has been Black. ( $)+ The movement to limit face recognition tech might finally get a win. ()2 AI startups are fighting dirty We’re talking fake names, competitors posing as customers, and even bombing Zoom calls. ( $)+ It’s all starting to look a lot like a bubble. ( $) 3 A vote in San Francisco could change the future of driverless cars All eyes are on whether the state board will approve a huge expansion of autonomous taxis on Thursday. ()+ Big tech companies are struggling to win over local residents and public officials. ( $)4 Is Texas’ electricity grid going to be able to handle electric vehicles?There are reasons to be optimistic, not just for that state but the US as a whole. ( $)5 Criminals are enthusiastic early adopters of AI toolsOn the dark web, they claim to have created two large language models that can assist with illegal activities. ( $)+ Criminals are also using AI-generated books to scam people. ( $)+ We are hurtling toward a glitchy, spammy, scammy, AI-powered internet. ()6 The era of plentiful cheap stuff may be coming to an end Maybe that’s not a wholly bad thing, frankly, for the sake of the planet. ( $)7 People are keen to recreate Black Twitter elsewhereThere’s been a giant exodus from the site. But where should folks go? ( $) 8 Big cities need to changeTo thrive, they need to reinvent themselves to be more than just places where people work. ()+ What cities need now. ()9 WhatsApp is working on 32-person voice chatsSounds like pure chaos! () 10 Even Zoom is making employees go back into the officeIronic, perhaps. But not that surprising. ( $) Quote of the day “Usually our technologies give with one hand and sort of slap us round the back of the head with the other.” —Charlie Brooker, the creator of Black Mirror, expresses a surprisingly even-handed view of tech development in an interview with . The big story Meet the wounded veteran who got a penis transplant October 2019 Penis transplantation is a radical frontier of modern medicine: extremely rare, expensive, and difficult to perform. Grafting a penis from a deceased donor onto a living recipient is a chaotic amalgamation that entails stitching millimeters-wide blood vessels and nerves with minuscule sutures. Ray, a military veteran, lost his genitals in a bomb blast while he was on patrol in Afghanistan—eight years before he got the call to say the hospital had a donor penis ready for him. The procedure would be the most extensive penis transplant ever performed, and the first for a military veteran anywhere in the world. . —Andrew Zaleski We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or .) + I’d like a high five from please.+ This of shows to binge-watch this summer gets my seal of approval, for what that’s worth.+ Sorry , you’ll soon be joining us millennials on the ‘deeply lame’ bench. + Glad to see I’m not the only unapologetically slow coach out there.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, . AI language models have recently become the latest frontier in the US culture wars. Right-wing commentators have accused ChatGPT of having a “woke bias,” and conservative groups have started developing their of AI chatbots. Meanwhile, Elon Musk he is working on “TruthGPT,” a “maximum truth-seeking” language model that would stand in contrast to the “politically correct” chatbots created by OpenAI and Google. An unbiased, purely fact-based AI chatbot is a cute idea, but it’s technically impossible. (Musk has yet to share any details of what his TruthGPT would entail, probably because he is too busy thinking about and with Mark Zuckerberg.) To understand why, it’s worth reading a on that sheds light on how political bias creeps into AI language systems. Researchers conducted tests on 14 large language models and found that OpenAI’s ChatGPT and GPT-4 were the most left-wing libertarian, while Meta’s LLaMA was the most right-wing authoritarian. “We believe no language model can be entirely free from political biases,” Chan Park, a PhD researcher at Carnegie Mellon University, who was part of the study, told me. One of the most pervasive is that the technology is neutral and unbiased. This is a dangerous narrative to push, and it will only exacerbate the problem of humans’ tendency to trust computers, even when the computers are wrong. In fact, AI language models reflect not only the biases in their training data, but also the biases of people who created them and trained them. And while it is well known that the data that goes into training AI models is a huge source of these biases, the research I wrote about shows how bias creeps in at virtually every stage of model development, says Soroush Vosoughi, an assistant professor of computer science at Dartmouth College, who was not part of the study. Bias in AI language models is a , because we don’t really understand how they generate the things they do, and our processes for mitigating bias are not perfect. That in turn is partly because biases are s with no easy technical fix. That’s why I’m a firm believer in honesty as the best policy. Research like this could encourage companies to track and chart the political biases in their models and be more forthright with their customers. They could, for example, explicitly state the known biases so users can take the models’ outputs with a grain of salt. In that vein, earlier this year OpenAI it is developing customized chatbots that are able to represent different politics and worldviews. One approach would be allowing people to personalize their AI chatbots. This is something Vosoughi’s research has focused on. As described in a , Vosoughi and his colleagues created a method similar to a YouTube recommendation algorithm, but for generative models. They use reinforcement learning to guide an AI language model’s outputs so as to generate certain political ideologies or remove hate speech. OpenAI uses a technique called to fine-tune its AI models before they are launched. Vosoughi’s method uses reinforcement learning to improve the model’s generated content after it has been released, too. But in an increasingly polarized world, this level of customization can lead to both good and bad outcomes. While it could be used to weed out unpleasantness or misinformation from an AI model, it could also be used to generate more misinformation. “It’s a double-edged sword,” Vosoughi admits. Deeper Learning Worldcoin just officially launched. Why is it already being investigated? OpenAI CEO Sam Altman’s new venture, Worldcoin, aims to create a global identity system called “World ID” that relies on individuals’ unique biometric data to prove that they are humans. It officially launched last week in more than 20 countries. It’s already being investigated in several of them. Privacy nightmare: To understand why, it’s worth reading an from last year, which found that Worldcoin was collecting sensitive biometric data from vulnerable people in exchange for cash. What’s more, the company was using test users’ sensitive, though anonymized, data to train artificial intelligence models, without their knowledge. In this week’s issue of The Technocrat, our weekly newsletter on tech policy, Tate Ryan-Mosley and our investigative reporter Eileen Guo look at what has changed since last year’s investigation, and how we make sense of the latest news. . Bits and Bytes This is the first known case of a woman being wrongfully arrested after a facial recognition matchLast February, Porcha Woodruff, who was eight months pregnant, was arrested over alleged robbery and carjacking and held in custody for 11 hours, only for her case to be dismissed a month later. She is the sixth person to report that she has been falsely accused of a crime because of a facial recognition match. All of the six people have been Black, and Woodruff is the first woman to report this happening to her. () What can you do when an AI system lies about you?Last summer, I about how our personal data is being scraped into vast data sets to train AI language models. This is not only a privacy nightmare; it could lead to reputational harm. When reporting the story, a researcher and I discovered that Meta’s experimental BlenderBot chatbot had called a prominent Dutch politician, Marietje Schaake, a terrorist. And, as this piece explains, at the moment there is little protection or recourse when AI chatbots spew and spread lies about you. () Every startup is an AI company now. Are we in a bubble? Following the release of ChatGPT, AI hype this year has been INTENSE. Every tech bro and his uncle seems to have founded an AI startup, it seems. But nine months after the chatbot launched, it’s still unclear how these startups and AI technology will make money, and there are reports that consumers are starting to lose interest. () Meta is creating chatbots with personas to try to retain usersHonestly, this sounds more annoying than anything else. Meta is reportedly getting ready to launch AI-powered chatbots with different personalities as soon as next month in an attempt to boost engagement and collect more data on people using its platforms. Users will be able to chat with Abraham Lincoln, or ask for travel advice from AI chatbots that write like a surfer. But it raises tricky ethical questions—how will Meta prevent its chatbots from manipulating people’s behavior and potentially making up something harmful, and how will it treat the user data it collects? ()

Should companies have social responsibilities? Or do they exist only to deliver profit to their shareholders? If you ask an AI you might get wildly different answers depending on which one you ask. While OpenAI’s older GPT-2 and GPT-3 Ada models would advance the former statement, GPT-3 Da Vinci, the company’s more capable model, would agree with the latter. That’s because AI language models contain different political biases, according to from the University of Washington, Carnegie Mellon University, and Xi’an Jiaotong University. Researchers conducted tests on 14 large language models and found that OpenAI’s ChatGPT and GPT-4 were the most left-wing libertarian, while Meta’s LLaMA was the most right-wing authoritarian. The researchers asked language models where they stand on various topics, such as feminism and democracy. They used the answers to plot them on a graph known as a political compass, and then tested whether retraining models on even more politically biased training data changed their behavior and ability to detect hate speech and misinformation (it did). The research is described in a peer-reviewed paper that won the award at the Association for Computational Linguistics conference last month. As AI language models are rolled out into products and services used by millions of people, understanding their underlying political assumptions and biases could not be more important. That’s because they have the potential to cause real harm. A chatbot offering health-care advice might refuse to offer advice on abortion or contraception, or a customer service bot might start spewing offensive nonsense. Since the success of ChatGPT, OpenAI has faced criticism from right-wing commentators who claim the chatbot reflects a more liberal worldview. However, the company insists that it’s working to address those concerns, and in a blog , it says it instructs its human reviewers, who help fine-tune AI the AI model, not to favor any political group. “Biases that nevertheless may emerge from the process described above are bugs, not features,” the post says. Chan Park, a PhD researcher at Carnegie Mellon University who was part of the study team, disagrees. “We believe no language model can be entirely free from political biases,” she says. Bias creeps in at every stage To reverse-engineer how AI language models pick up political biases, the researchers examined three stages of a model’s development. In the first step, they asked 14 language models to agree or disagree with 62 politically sensitive statements. This helped them identify the models’ underlying political leanings and plot them on a political compass. To the team’s surprise, they found that AI models have distinctly different political tendencies, Park says. The researchers found that BERT models, AI language models developed by Google, were more socially conservative than OpenAI’s GPT models. Unlike GPT models, which predict the next word in a sentence, BERT models predict parts of a sentence using the surrounding information within a piece of text. Their social conservatism might arise because older BERT models were trained on books, which tended to be more conservative, while the newer GPT models are trained on more liberal internet texts, the researchers speculate in their paper. AI models also change over time as tech companies update their data sets and training methods. GPT-2, for example, expressed support for “taxing the rich,” while OpenAI’s newer GPT-3 model did not. Google and Meta did not respond to MIT Technology Review’s request for comment in time for publication. AI language models have distinctly different political tendencies. Chart by Shangbin Feng, Chan Young Park, Yuhan Liu and Yulia Tsvetkov. The second step involved further training two AI language models, OpenAI’s GPT-2 and Meta’s RoBERTa, on data sets consisting of news media and social media data from both right- and left-leaning sources, Park says. The team wanted to see if training data influenced the political biases. It did. The team found that this process helped to reinforce models’ biases even further: left-learning models became more left-leaning, and right-leaning ones more right-leaning. In the third stage of their research, the team found striking differences in how the political leanings of AI models affect what kinds of content the models classified as hate speech and misinformation. The models that were trained with left-wing data were more sensitive to hate speech targeting ethnic, religious, and sexual minorities in the US, such as Black and LGBTQ+ people. The models that were trained on right-wing data were more sensitive to hate speech against white Christian men. Left-leaning language models were also better at identifying misinformation from right-leaning sources but less sensitive to misinformation from left-leaning sources. Right-leaning language models showed the opposite behavior. Cleaning data sets of bias is not enough Ultimately, it’s impossible for outside observers to know why different AI models have different political biases, because tech companies do not share details of the data or methods used to train them, says Park. One way researchers have tried to mitigate biases in language models is by removing biased content from data sets or filtering it out. “The big question the paper raises is: Is cleaning data [of bias] enough? And the answer is no,” says Soroush Vosoughi, an assistant professor of computer science at Dartmouth College, who was not involved in the study. It’s very difficult to completely scrub a vast database of biases, Vosoughi says, and AI models are also pretty apt to surface even low-level biases that may be present in the data. One limitation of the study was that the researchers could only conduct the second and third stage with relatively old and small models, such as GPT-2 and RoBERTa, says ​​Ruibo Liu, a research scientist at DeepMind, who has studied political biases in AI language models but was not part of the research. Liu says he’d like to see if the paper’s conclusions apply to the latest AI models. But academic researchers do not have, and are unlikely to get, access to the inner workings of state-of-the-art AI systems such as ChatGPT and GPT-4, which makes analysis harder. Another limitation is that if the AI models just made things up, as they tend to do, then a model’s responses might not be a true reflection of its “internal state,” Vosoughi says. The researchers also admit that the political compass test, while widely used, is not a perfect way to measure all the nuances around politics. As companies integrate AI models into their products and services, they should be more aware how these biases influence their models’ behavior in order to make them fairer, says Park: “There is no fairness without awareness.”

This is today’s edition of , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Worldcoin just officially launched. Why is it already being investigated? It’s possible you’ve heard the name Worldcoin recently. It’s been getting a ton of attention—some good, some … not so good. It’s a project that claims to use cryptocurrency to distribute money across the world, though its bigger ambition is to create a global identity system called “World ID” that relies on individuals’ unique biometric data to prove that they are humans. Sam Altman, the CEO of OpenAI and one of the biggest tech celebrities right now, is one of the cofounders of the project, which launched on July 24 in more than 20 countries. But it’s already being investigated in at least four jurisdictions around the world. . This story is from The Technocrat, Tate Ryan-Mosley’s weekly newsletter all about tech, policy and power. to receive it in your inbox every Friday. + If you want to learn more about Worldcoin, , based on more than 35 interviews with executives, contractors, and test users recruited primarily in developing countries. We found some vast gaps between its idealistic rhetoric and the realities on the ground, not least when it comes to handling people’s private biometric data. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Climate change is messing with your favorite foods Farmers rely on knowing what grows where, but increasingly unpredictable weather makes that very challenging. ( $)+ A group of older Swiss women are suing their government for allegedly violating their rights by failing to curb emissions. ( $)+ New AI systems could speed up our ability to create weather forecasts. ()2 Can gene therapies help to de-age us?Even if they can (big if), any eventual treatments that hit the market will cost millions. ()+ Inside the billion-dollar meeting for the mega-rich who want to live forever. ()+ Longevity enthusiasts want to create their own independent state. They’re eyeing Rhode Island. ()3 Russia’s pro-war bloggers are increasingly fighting each otherWhich is perhaps not a huge surprise, given the tensions within Russia’s military itself. ( $)4 Scientists say they’ve repeated a fusion power breakthrough This is bound to stoke a great deal of excitement, though many believe fusion power stations are decades away. ( $)+ This startup says its first fusion plant is five years away. Experts doubt it. ()5 AI chatbots are becoming our friendsLonely people are turning to them for companionship, but they could actually deepen their isolation. ( $)+ Technology that lets us “speak” to our dead relatives has arrived. Are we ready? ()6 TikTok’s algorithm will be optional in EuropeIn order to comply with EU laws which require giant platforms to let users opt out of receiving personalized content. ()+ TikTok is being fined in the EU for breaching childrens’ privacy. ()+ TikTok’s live streaming section is deeply weird. ()7 The FBI is investigating a ransomware attack on hospitals in four statesThese kinds of attacks happen all the time, but this seems to have been a particularly big one. ()8 Elon Musk has said he’ll pay problem tweeters’ legal billsHe’s yet to elaborate on how anyone takes him up on the offer, though. ()+ Twitter (sorry, X) is failing to even pay content creators as it is. ()9 How Indian women were lured into the gig economy—then forced outUrban Company promised them flexibility and empowerment. It didn’t last long. ( $)10 A Mom and daughter duo have won the chance to go into space They’ll become the first people from the Caribbean to do so. () Quote of the day “I’m ready today. I suggested August 26 when he first challenged, but he hasn’t confirmed. Not holding my breath.” —Mark Zuckerberg confirms in a yesterday that he’s still up for that cage fight for Elon Musk. The big story How mobile money supercharged Kenya’s sports betting addiction BRIAN OTIENO April 2022 Mobile money has mostly been hugely beneficial for Kenyans. But it has also turbo-charged the country’s sports betting sector. Experts and public figures across the African continent are sounding the alarm over the growth of the sector increasingly loudly. It’s produced tales of riches, but it has also broken families, consumed college tuitions, and even driven some to suicide. . —Jonathan W. Rosen We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or .) + I thoroughly enjoyed nerdy joke. + How learning to helps you learn to see.+ I can’t get over this in Manhattan, which manages to look ancient despite being completely new.+ If you’re rocking , you’re staying cool(er) this summer.

This article is from The Technocrat, MIT Technology Review’s weekly tech policy newsletter about power, politics, and Silicon Valley. To receive it in your inbox every Friday, . It’s possible you’ve heard the name Worldcoin recently. It’s been getting a ton of attention—some good, some … not so good. It’s a project that claims to use cryptocurrency to distribute money across the world, though its bigger ambition is to create a global identity system called “World ID” that relies on individuals’ unique biometric data to prove that they are humans. It officially launched on July 24 in more than 20 countries, and Sam Altman, the CEO of OpenAI and one of the biggest tech celebrities right now, is one of the cofounders of the project. The company makes big, idealistic promises: that it can deliver a form of universal basic income through technology to make the world a better and more equitable place, while offering a way to verify your humanity in a digital future filled with nonhuman intelligence, which it calls “proof of personhood.” If you’re thinking this sounds like a potential privacy nightmare, . Luckily, we have someone I’d consider the Worldcoin expert on staff here at MIT Technology Review. Last year investigative reporter Eileen Guo, with freelancer Adi Renaldi, and found that Worldcoin’s operations were far from living up to its lofty goals and that it was collecting sensitive biometric data from many vulnerable people in exchange for cash. As they wrote: “Our investigation revealed wide gaps between Worldcoin’s public messaging, which focused on protecting privacy, and what users experienced. We found that the company’s representatives used deceptive marketing practices, collected more personal data than it acknowledged, and failed to obtain meaningful informed consent.” What’s more, the company was using test users’ sensitive, but anonymized, data to train artificial intelligence models, but Eileen and Adi found that individuals did not know their data was being used that way. I highly recommend you —which builds on more than 35 interviews with Worldcoin executives, contractors, and test users recruited primarily in developing countries—to better understand how the company was handling sensitive personal data and how its idealistic rhetoric compared with the realities on the ground. Given their reporting, it’s no surprise that regulators in at least four countries have already launched investigations into the project, citing concerns with its privacy practices. The company it has already scanned nearly 2.2 million “unique humans” into its database, which was primarily built during an extended test period over the last two years. So I asked Eileen: What really has changed since her investigation? How do we make sense of the latest news? Since her story, Worldcoin CEO Alex Blania has that the company has changed many of its data collection and privacy practices, though there are reasons to be skeptical. The company hasn’t specified exactly how it’s done this, beyond saying it has stopped some of the most exploitative and deceptive recruitment tactics. In emails Eileen recently exchanged with Worldcoin, a spokesperson was vague about how the company was handling personal data, saying that “the Worldcoin Foundation complies with all laws and regulations governing the processing of personal data in the markets where Worldcoin is available, including the General Data Protection Regulation (‘GDPR’) … The project will continue to cooperate with governing bodies on requests for more information about its privacy and data protection practices.” The spokesperson added, “It is important to stress that The Worldcoin Foundation and its contributor Tools for Humanity never have and never will sell users’ personal data.” But, Eileen notes, we (again) have nothing but the company’s word that this is true. That’s one reason we should keep a close eye on what government investigators start to uncover about Worldcoin. The legality of Worldcoin’s biometric data collection is at the and a probe by a German data protection agency, which has been , according to Reuters. On July 25, the Information Commissioner’s Officer in the UK put out a statement that it will be “making enquiries” into the company. Then on August 2, Kenya’s Office of Data Protection in the country, it will investigate whether Worldcoin is in compliance with the country’s Data Protection Act. Importantly, a core objective of the Worldcoin project is to perfect its “proof of personhood” methodology, which requires a lot of data to train AI models. If its proof-of-personhood system becomes widely adopted, this could be quite lucrative for its investors, particularly during an AI gold rush like the one we’re seeing now. The company announced this week that it will to deploy its identity system. “Worldcoin’s proposed identity solution is problematic whether or not other companies and governments use it. Of course, it would be worse if it were used more broadly without so many key questions being answered,” says Eileen. “But I think at this stage, it’s clever marketing to try to convince everyone to get scanned and sign up so that they can achieve the ‘fastest’ and ‘biggest onboarding into crypto and Web3’ to date, as Blania told me last year.” Eileen points out that Worldcoin has also not yet clarified whether it still uses the biometric data it collects to train its artificial intelligence models, or whether it has deleted the biometric data it already collected from test users and was using in training, as it told MIT Technology Review it would do before launch. “I haven’t seen anything that suggests that they’ve actually stopped training their algorithms—or that they ever would,” Eileen says. “I mean, that’s the point of AI, right? that it’s supposed to get smarter.” What else I’m reading Meta’s oversight board, which issues independently drafted and binding policies, is reviewing how the company is handling misinformation about abortion. Currently, the company’s , according to this nice explainer-y piece in Slate. We should expect the board to issue new abortion-information-specific policies in the coming weeks. At the end of July, Twitter rebranded to X, in a strange, unsurprising-yet-surprising move by its new czar Elon. I loved , in which he argues that Musk’s $44 billion investment was really just a wasteful act of “cultural vandalism.” Nobel-winning economist Joseph Stiglitz is worried that AI will worsen inequality, and about how we might get off the path we seem to currently be on. Well worth a read! What I learned this week Bots on social media are likely being supercharged by ChatGPT. Researchers from Indiana University have released a that shows a Twitter botnet of over 1,000 accounts, which the researchers call fox8, “that appears to employ ChatGPT to generate human-like content.” The botnet promoted fake-news websites and stolen images, and it’s an alarming preview of a social media environment fueled by AI and machine-generated misinformation. Tech Policy Press wrote on the findings, which I’d recommend checking out. Additional reporting from Eileen Guo.

This is today’s edition of , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What’s next for China’s digital currency? China’s digital yuan was seemingly born out of a desire to centralize a tech giant-dominated payment system. According to its central bank, the digital currency, also known as the e-CNY, is both a risk-free alternative to commercial platforms and a replacement for physical cash, which is becoming obsolete. Almost three years into the pilot, though, it seems the government is still struggling to find compelling applications for it, and adoption has been minimal. Now the goal may be shifting. China appears to be charging ahead with plans to use the e-CNY outside its borders, for international trade. If it’s successful, it could challenge the US dollar’s position as the world’s dominant reserve currency—and in the process shake up the global geopolitical order. . —Mike Orcutt This story is from MIT Technology Review’s , which looks across industries, trends, and technologies to give you a first look at the future. Check out the rest of the series . The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 How the US is planning to regulate AI It’s a multi-pronged approach, but progress is grindingly slow. ()+ Our quick guide to the 6 ways we can regulate AI. ()+ Ultimately judges, not politicians, will be the first to establish guardrails for AI. ()2 Covid cases are rising again We don’t exactly know why, but infections do seem to shoot up over the summer. ( $)+ Hospitalizations are on the up, but experts expect the vast majority of infections to be mild. ()+ Covid hasn’t entirely gone away—here’s where we stand. ()3 There’s not much you can do if AI lies about youPeople are starting to sue tech companies, but legal precedent for this is basically non-existent. ( $)+ What does GPT-3 “know” about me? () 4 Apple now has over one billion paying subscribersTim Cook’s push to expand from hardware to subscription services seems to be paying off. ( $)5 Google is making it easier to remove your private info from SearchOf course, that requires you to give Google all that information, but still nifty. ()6 A French news agency is suing X for refusing to discuss paying itElon Musk called the move “bizarre”, and I’m inclined to agree. ()+ Meta’s Twitter rival, Threads, has seen its daily active users drop by 82% since launch. ()7 Pornhub has gone dark in ArkansasIn protest at a new law requiring it to verify users’ ages. ()+ Why child safety bills are popping up all over the US. ()8 Actors are heading back to Cameo To make a bit of cash on the side while the strike is on. ( $) 9 Meta’s Ray-Ban smart glasses are a flop The vast majority of people who bought them don’t use them. ( $) 10 Parents in China are on dating apps to marry off their adult childrenIf you’re reading this, Mum… don’t go getting any ideas. () Quote of the day “We’re changing the clouds.” —Duncan Watson-Parris, an atmospheric physicist, tells that measures to cut ships’ sulfur pollution may be inadvertently helping to warm oceans, by reducing cloud cover. The big story Why Generation Z falls for online misinformation GETTY June 2021 In November 2019, a TikTok video claiming that if Joe Biden is elected president of the United States, “trumpies” will commit mass murder of LGBT individuals and people of color rapidly went viral. It was viewed, shared, liked and commented on by hundreds of thousands of young people. Clearly, the claims were false. Why, then, did so many members of Generation Z—a label applied to people aged roughly 9 to 24, who are presumably more digitally savvy than their predecessors—fall for such flagrant misinformation? The answer is complex, but may partly lie in a sense of common identity with the person who shared it in the first place. . —Jennifer Neda John We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or .) + This beautiful blog post is an entreaty to treat yourself to a (ideally fiction). + Can’t help but admire , a TikTok fashionista who is unapologetically dividing the crowd. + This would be funny enough as it is, but the fact the cat’s called Susan makes it truly outstanding. + The editing of this fast and furious food review is absolutely bonkers.

MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of our series . China’s digital yuan was seemingly born out of a desire to centralize a payment system dominated by the tech companies Alibaba and Tencent. According to its central bank, the digital currency, also known as the e-CNY, is both a risk-free alternative to these commercial platforms and a replacement for physical cash, which is becoming obsolete. Almost three years into the pilot, though, it seems the government is still struggling to find compelling applications for it, and adoption has been minimal. Now the goal may be shifting, or at least broadening. China appears to be charging ahead with plans to use the e-CNY outside its borders, for international trade. If it’s successful, it could challenge the US dollar’s position as the world’s dominant reserve currency—and in the process shake up the global geopolitical order. The (public) rationale From the outside looking in, it is impossible to fully ascertain the government’s plans for the e-CNY. Though the People’s Bank of China (PBOC) has not been shy about its central bank digital currency (CBDC) project, it has revealed few specific details about how the e-CNY actually works—or how it ultimately intends to use it. One thing we do know is that it’s been a long time in the making. While Alibaba and Tencent launched their digital payment systems in 2004 and 2005 respectively, China began researching digital currency technology in 2014 and launched a research institute devoted to the concept in 2016, hoping to create a centralized alternative. Then in 2019, after Meta (then called Facebook) proposed its own global digital currency, PBOC officials expressed concern that the coin, called Libra, might undermine the monetary sovereignty of China’s currency, the yuan. The next year it started the e-CNY pilot phase, which is still ongoing. According to Mu Changchun, director general of the PBOC’s Digital Currency Institute, the e-CNY project has three main goals: to improve the efficiency of the central bank’s payment system, provide a backup for the retail payment system, and “enhance financial inclusion.” “Now we can provide 24/7 services to the general public,” he said during a talk he gave via Zoom for an event hosted last year by the Atlantic Council, a foreign policy think tank in Washington, DC. Mu added that the e-CNY will broaden access to the PBOC’s payment system—extending it to, among others, more private-sector firms, including fintech companies and telecom operators. Mu said e-CNY will also serve as a necessary backup to the popular mobile payment apps Alipay and WeChat Pay, which dominate China’s daily retail transactions. Most people in China don’t use cash or credit cards but rely on their phones to buy things, so these commercial platforms have become “significantly important financial infrastructure,” Mu said. If something ever goes wrong with them, “that will bring a very significant negative impact to the financial stability of China,” he said. On top of that, between 10% and 20% of people in China don’t have bank accounts and can’t access the commercial financial system, said Mu. Visitors to China from other countries also often have difficulty participating in the mobile-dominated payment system, where many vendors no longer take cash or even cards. They could use e-CNY instead, according to Mu. It’s possible to access e-CNY through commercial bank apps, but it’s also possible through an app run by the PBOC. The PBOC’s choice to connect directly with retail customers through its app is remarkable, because central banks typically deal only with other banks. “Managed anonymity” China is at the forefront of an increasingly global push to adopt CBDCs. around the world are exploring possible CBDC designs, and a big question they are wrestling with is how directly the central bank should be involved versus letting the currency be run by private-sector intermediaries. For example, to prevent money laundering and other financial crimes, traditional banks require users to verify their identities. Most central banks don’t want to have to do this kind of admin for millions of people, says , an associate director for digital currency research at the Atlantic Council. But the PBOC’s desire to do just that explains why some civil liberties activists oppose the idea of CBDCs. Around the world, retail transactions are going cashless, and if cash becomes obsolete, governments will use CBDCs as tools for surveillance and control, argues , chief strategy officer at the Human Rights Foundation. “The Chinese government wants more control over payments,” says Gladstein. Though it already has a firm grip on the two commercial payment giants, direct control and oversight over a digital currency would provide much better data and the power to deny people access, he says. The PBOC, on the other hand, says the e-CNY will protect people’s privacy thanks to a policy that it calls “managed anonymity.” In short, it’s possible to get an e-CNY account using only a mobile number. Balances for these accounts are capped. In his talk last year, Mu said the cap was 10,000 yuan (around $1,400 at the time of this writing) and that users of such software wallets can spend up to 2,000 yuan per transaction and 5,000 yuan per day. Mu dismissed the idea that the government could determine users’ real identities from the mobile numbers. China’s new Personal Information Protection Law will prevent telecom operators from sharing identifying information with the central bank or other e-CNY operators, he said. One particularly advanced feature of e-CNY is the ability to transfer money between two people using devices that are not connected to the internet. During the Atlantic Council talk, Mu of people using this offline payment function with smartphones as well as plastic cards with e-ink displays. Feeling around for a fit But why should people adopt the e-CNY? It seems the government is still trying to figure that out. The PBOC has been piloting the currency for almost three years, testing a wide variety of potential uses. Kumar and her colleagues have 30 different test applications, ranging from bank loans to cards that combine e-CNY wallets with other functions. Examples include an “elderly care card,” which integrates health-care information and location data with an emergency service system; a “smart student ID”; and a card that pays e-CNY rewards for using low-carbon transportation. There are also several pilots focused on online commerce in rural areas. And in April, Changshu, a city of 1.5 million people, it would start paying public employees in e-CNY. “All kinds of little nooks and crannies of the payment system are getting reached by e-CNY,” says , a professor of finance at Stanford’s graduate school of business. Still, hardly anyone is using it. Though the system has been tested in 25 cities, and 260 million unique wallets hold a total of ($1.9 billion), last year e-CNY accounted for only of the supply of central bank reserves and cash in circulation. “That’s very small after two years of piloting,” says Duffie. He says the only reason it’s still called a pilot is that it hasn’t taken off. Officials have said there is no set timetable for the formal launch of the e-CNY, and that the bank is focused on improving the user experience and testing the security and resilience of the network rather than increasing adoption. But some close observers think the government underestimated how hard it would be to create a retail payment network from scratch. “A lot of the ambition for this project has proven more difficult to achieve than they thought, and the timeline has been longer than people anticipated,” says , a senior fellow at the Peterson Institute for Economics, a think tank in DC. What’s been especially difficult, he says, has been signing up enough merchants and creating a rich enough “ecosystem” to make the e-CNY as useful as established payment methods. “The e-CNY has to be as useful as Alipay and WeChat Pay for it to actually have a user base, and right now there really is not a use case,” says Chorzempa, who has written a book about China’s payment system. “People just get a red envelope, they spend it, and they generally don’t open the e-CNY app again,” he says, referring to the electronic icon the government uses when it doles out digital money to pilot participants. Chorzempa speculates that the challenges the PBOC has had in getting traction for the e-CNY inside China may be contributing to its increased focus on international uses. And that has put the e-CNY on a collision course with the US dollar. e-CNY vs. USD Though the government may be struggling to find compelling applications in China, it may have found one elsewhere, in the form of large cross-border payments between banks. The international payment system, which consists of a network of so-called correspondent banks, can be cumbersome and slow. CBDCs could be faster and more efficient. For China, there could also be a geopolitical upside: an alternative set of international payment rails that the United States does not control. Because the dollar is the world’s dominant reserve currency, a country that wants to do business with others typically needs dollars. That means the US can effectively expel an adversary from the global financial system. For example, when Russia invaded Ukraine in early 2022, the US, with help from its allies, on Russia’s biggest banks that targeted assets and barred them from US-controlled global financial infrastructure, hampering their ability to raise capital. This geopolitical advantage could be undermined if currencies like the Chinese yuan become more prevalent in global trade, a process that the e-CNY could accelerate. That’s why an e-CNY pilot called is important, says Chorzempa. The project is a test of infrastructure for a “wholesale” CBDC led by China, which would be used for large-value cross-border transfers between banks, says Chorzempa. “That’s really where you get into actual potential competition with the US dollar,” he says. Today, banks typically execute such transactions using what’s called the correspondent banking system. A correspondent bank is a third party that serves as an intermediary between domestic banks in different countries. According to the Bank of International Settlements (BIS), however, this system “has not kept pace” with the “rapid growth in global economic integration” that has occurred in recent decades. Correspondent banks duplicate processes and steps, making cross-border payments costly, slow, and operationally complex—with “limited access and low transparency,” according to the BIS. Researchers at the BIS believe that a CBDC-based system could make this system more efficient and cheaper. That’s part of the BIS’s rationale for working with the PBOC—along with the central banks of Hong Kong, the United Arab Emirates, and Thailand—on Project mBridge. Over the course of six weeks last August and September, 20 commercial banks used a custom blockchain to settle $22 million in cross-border transactions using CBDCs. That’s only a “drop in the bucket,” acknowledges the Atlantic Council’s Kumar. Still, it’s important because it’s the first time multiple jurisdictions have settled CBDC transactions, she says: “Not can, not potential—have actually done it.” It’s also a big deal in the context of the ongoing global discussion about “de-dollarization” and the internationalization of other currencies, says Kumar. Given the “weaponization of the dollar” via sanctions, China and other countries are trying to develop new ways to settle trades, she says. For example, , Bangladesh used yuan to pay off a loan from Russian lenders, using an interbank payment system that China developed called the Cross-border Interbank Payment System, or CIPS. “It did that partly because a) its dollar reserves aren’t very high and b) it wants to actually transact with Russia,” says Kumar. Sanctioned Russian banks are blocked from using the Society for Worldwide Interbank Financial Telecommunication (SWIFT), the platform that facilitates most wholesale cross-border transactions. In Kumar’s view, however, mBridge is about more than currency: “The more important part there is about the technology that is getting internationalized and used by other countries because there’s a geopolitical motivation for them to do that.” She has that what might emerge if China is successful is “a set of technical and regulatory standards built in the image of the e-CNY.” It’s likely no coincidence that the US Federal Reserve is now researching CBDC systems for large-value cross-border transactions too. Last November, the New York Fed results from the first phase of what it calls Project Cedar: “a multiphase research effort to develop a technical framework for a theoretical wholesale central bank digital currency.” In May, it results from Phase II, a collaboration with Singapore’s central bank. According to the New York Fed, the project demonstrated that distributed ledger technology could support “enhancements to multi-currency payments and settlements.” It will be “a long, long time” before the e-CNY might become a geopolitical problem for the US, says Stanford’s Duffie, not only because the technology is complicated but also because the legal and governance issues for cross-border payments are so complex. Chorzempa agrees that it would take a long time for the e-CNY to significantly disrupt the dollar’s power, if it ever happens. China is betting that many other countries will adopt “tokenized” central bank payment systems, he says, but it’s still not clear if the technology offers advantages over conventional payment systems. Nevertheless, he says, “I would not write it off.”

This is today’s edition of , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. How hot is too hot for the human body? There’s no other way to say it: it’s hot. Temperatures this summer have yet again broken records, and around the world, climate change is pushing the limits of what we can handle. So our climate reporter Casey Crownhart asked the experts: how hot is too hot for the human body? To keep our bodies at their relatively stable core temperature of around 98.6 °F (37 °C), we constantly lose heat. It’s a process that can be sped up by sweating. But the whole balancing act can get derailed when we’re exposed to extreme heat. If your body isn’t able to cool itself down fast enough, a whole cascade of problems can start, from stressing out your heart to throwing your kidneys and liver into chaos. Sounds bad, huh? Here’s some good news: to some extent, our bodies can and do adjust slightly to the heat. But there’s only so much people can endure—that might vary by person or place, but limits exist. That’s partly why heat is an equity issue: not everyone has access to cooling, or the ability to shelter inside when temperatures rise. This story is from The Spark, Casey’s weekly newsletter keeping you up-to-date on all things to do with energy and climate change. to receive it in your inbox every Wednesday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Researchers are racing to replicate the LK-99 superconductor It seems unlikely they’ll succeed, but for now there’s still a little hope amid all the hype. ( $)+ Even if the claims aren’t backed up, they could still lead to progress. ( $)+ Either way, it’s a slow, painstaking process, so we won’t know for a while. ()2 Ocean temperatures are risingThat is every bit as bad as it sounds. ( $)+ And it’s not only disastrous for corals. It threatens the entire oceanic ecosystem. ( $)+ There are also record low levels of Antarctic sea ice this year. ( $)3 AI is shaking up YouTube’s thumbnail industryCue much consternation from designers—but it’s still unclear how much it’ll impact their jobs. ()+ Meta has released a new music AI model. ()+ AI models can get worse over time. ( $) + A top gaming YouTuber is trying to replace himself with AI. ( $)4 What we need to know about the new wave of obesity drugs They work well—but we don’t exactly know why, or who is best suited for them. ()+ When you lose weight, where does it go? ()5 Twitter Blue subscribers now have the option to hide their blue checksWhich does beg the question of what, exactly, it is that they’re left paying for. ()+ What on earth should we call Twitter now? ( $) 6 Etsy is scrambling to stop a sellers’ strikeVendors say that the platform’s policies are leaving them out of pocket. ()+ Why everyone’s going on strike this summer. ()7 Tesla is finally starting to get more competitors for EV chargingThe crucial thing will be trying to get everyone to converge on a single standard. ()+ In the clash of the EV chargers, it’s Tesla vs. everyone else. ()8 Please friends, let’s keep theaters phone-free zones Taking photos of your TV at home? Knock yourself out! At a theater? Absolutely not. ( $)9 Sick of dating apps? Try Google Docs.People are penning ‘date me docs’ in the hope it might help them find better matches. ( $) 10 A crucial metric for weather: dew point The higher it is, the more of a sweaty mess you’ll feel. () Quote of the day “Oh my God. Wow.” —Uber’s chief executive Dara Khosrowshahi’s reaction after an interviewer told him he paid $51.69 for a three-mile ride to the company’s annual product event in New York, reports. The big story The two-year fight to stop Amazon from selling face recognition to the police MS TECH | GETTY June 2020 In the summer of 2018, nearly 70 civil rights and research organizations wrote a letter to Jeff Bezos demanding that Amazon stop providing Rekognition, its face recognition technology, to governments. Despite the mounting pressure, Amazon continued pushing Rekognition as a tool for monitoring “people of interest”. But two years later, the company shocked civil rights activists and researchers when it announced that it would place a one-year moratorium on police use of the software. . —Karen Hao We can still have nice things A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or .) + A fun challenge for you: try to just do today. ($)+ These really deliver on the “wow” factor. + A question that’s surely played on all our minds… which president ? + I bet you’ll learn something new from about how inaccurate our maps of the world really are.

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, . I think I’m running out of ways to say it: it’s hot. Saturday’s heat was crushing in New York, with temperatures topping 90 °F (32 °C) and air that was absolutely sticky with humidity. While I prayed for a breeze, I found myself thinking again about on how the human body deals with extreme heat. At the time, I wrote about how climate change is pushing the limits of what we can handle. Since it’s been a while, I decided to revisit the topic and catch up with one of the researchers I spoke to for that story. So for the newsletter this week, let’s talk about just how hot is too hot. Why is heat a problem? Our bodies need to maintain a relatively stable core temperature of around 98.6 °F (37 °C). The thing is, we’re constantly making heat as our cells carry out their jobs in our bodies and burn food for energy. “It’s just a function of being a mammal,” says a physiology researcher at Indiana University Bloomington. So in order to keep a balanced temperature, we constantly lose heat. We get rid of most of it via our skin, which throws heat into the air around us. Sweating can help speed that process up. But this heat loss, and therefore the whole balancing act, can get derailed when we’re exposed to extreme heat. If your body isn’t able to cool itself down fast enough, a whole cascade of problems can start, from stressing out your heart to throwing your kidneys and liver into chaos. How hot is too hot? As with most things related to humans and bodies and health, it’s not quite as straightforward as a single number. “As much as I hate to say this, because everything is complicated … it’s complicated,” Schlader says. A whole host of factors can alter exactly how our bodies will keep the teeter-totter of our internal temperatures balanced. Age, health status, medications, and how acclimatized we are to heat (more on this later) help determine how much heat your body is able to lose. People who are very old or very young have more trouble regulating their body temperature. And activity level will determine just how much heat your body is making that it needs to get rid of. In general, though, researchers typically put the theoretical limits of the human body at 95 °F (35 °C) on a scale called wet-bulb temperature. Wet-bulb temperature is a weird metric, but basically, it’s an effort to incorporate both heat and humidity into one number. In short, it’s the measure of what a thermometer would read with a wet cloth wrapped around it. In a dry environment, water evaporating off that cloth will cool things down, lowering the temperature. But if the air is already saturated with humidity, there will be less evaporation, and therefore less cooling. Take two examples of conditions that would reach a 35 °C wet bulb temperature. With mostly dry air, temperatures have to top 130 °F (54 °C) to reach that limit. On the other hand, a temperature of 109 °F (43 °C) and a relative humidity of 50% would result in the same wet-bulb temperature. It’s a useful metric because it can give you an idea of how much your sweat will be able to cool you down. Above a wet-bulb temperature of 35 °C, your body won’t be able to lose enough heat through the evaporation of sweat. But that’s still a theoretical limit—one that hadn’t been tested much in humans until recently. Early research has found that the limit might turn out to be more varied, but lower, than theory would suggest. One found that even in healthy young adults, heat loss couldn’t keep up at lower temperatures than the theoretical limit, especially in humid environments. Bottom line: researchers are still trying to understand where our limits lie when it comes to heat, though we do know it’ll depend a lot on specific environmental and health factors. There’s also some interesting research showing that our heat tolerance can change over time—as we age, yes, but even with the amount of heat we’re exposed to. How can we handle the heat better? One thing that I found fascinating when I started looking into extreme heat a few years ago is the concept of acclimatization: our bodies can adjust to the heat. If you’re exposed to heat consistently, your body will go through a few changes, Schlader says. You will start making more plasma, basically pushing up your total volume of blood. That means your heart won’t have to work as hard to move blood around (one of the major ways we lose heat is through blood carrying it to our skin). The process of sweating also changes—you’ll be quicker to sweat, your sweat will increase in volume, and it will get more dilute, so you’ll lose fewer electrolytes. The whole thing is somewhat akin to how you can adjust to a higher altitude. There’s been a lot of this week over a that talked about this exact concept. People argued not only about whether this effect is real, but also about whether it’s a big distraction from the need to address climate change. I have two things to say after reading way too many comments and digging into this a bit more since my initial reporting two years ago. First, as Schlader pointed out, this is a real effect, and our bodies’ ability to adapt to all sorts of things is absolutely wild. Second, bodily adaptation won’t be the silver bullet that helps protect humans from heat caused by climate change. There’s a limit to how much difference these physical effects can make—over the course of a few weeks, your body might be able to adjust to handle a couple of degrees’ worth of additional heat, Schlader says. That’s not enough to keep people safe in extreme conditions, especially if they have to work in the heat. There’s only so much heat people can endure—that might vary by person or place, but the limits still exist. As temperatures continue to break records around the world, we’ll have to rely a lot more on other ways to stay safe. This includes using cooling devices like air conditioners and fans, seeking shade, or stopping physical activity when possible. That’s why heat is such an equity issue: not everyone has access to reliable cooling technology, or the ability to shelter inside when temperatures rise. For more on the limits of our bodies, Stay safe out there. Keeping up with climate I spoke with NPR’s All Things Considered about new materials called desiccants being used in air-conditioning. () → Check out my full story if you missed it last week. () There’s some interesting data in this opinion piece, where the author argues it’s “time to chill out” about AC and climate change. As he points out, today heating accounts for significantly more emissions than cooling does globally. () → If you ask me, emissions from heat don’t cancel the need to improve the efficiency of air conditioners, given how much demand is expected to grow by 2050. I’d still call AC a climate antihero, as I wrote in the newsletter last week. () Tesla has a history of overly optimistic range projections for some of its vehicles. The company reportedly put together a special team to cancel service appointments related to range concerns. () Maine is stepping up its heat pump game. The state just blew past its goal of installing 100,000 of the devices by 2025 and re-upped the target to 175,000 by 2027. () Scientists have previously shown that a major ocean current is weakening, but according to a new study, that collapse could come as soon as 2025. The risk is serious, but there are questions about this research and whether it’s overstating the near-term dangers. () → I’d highly recommend this deep dive that my colleague James Temple took into this topic in late 2021. () Companies have sold millions of dollars of credits in programs that promise to capture and store carbon in soil on farmland. But some researchers say that the benefits of new agricultural practices aren’t so clear cut. () File this under weird climate change impacts: acidifying oceans (the result of more carbon dioxide in the atmosphere) are wiping out crabs’ sense of smell. As ocean chemistry gets more wacky, it could affect how crustaceans and other creatures can sense food and predators. ()