This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What it’s like to be in the middle of a conspiracy theory (according to a conspiracy theory expert) —Mike Rothschild is a journalist and an expert on the growth and impact of conspiracy theories and disinformation.It’s something of a familiar cycle by now: Tragedy hits; rampant misinformation and conspiracy theories follow. It’s often even more acute in the case of a natural disaster, when conspiracy theories about what “really” caused the calamity run right into culture-war-driven climate change denialism. Put together, these theories obscure real causes while elevating fake ones.I’ve studied these ideas extensively, having spent the last 10 years writing about conspiracy theories and disinformation as a journalist and researcher. I’ve covered everything from the rise of QAnon to whether Donald Trump faked his assassination attempt. I’ve written three books, testified to Congress, and even written a report for the January 6th Committee.  Still, I’d never lived it. Not until my house in Altadena, California, burned down. Read the full story.
This story is part of MIT Technology Review’s series “The New Conspiracy Age,” on how the present boom in conspiracy theories is reshaping science and technology. Check out the rest of the series here. It’s also featured in this week’s MIT Technology Review Narrated podcast, which we publish each week on Spotify and Apple Podcasts.  If you’d like to hear more from Mike, he’ll be joining our features editor Amanda Silverman and executive editor Niall Firth for a subscriber-exclusive Roundtable conversation exploring how we can survive in the age of conspiracies. It’s at 1pm ET on Thursday November 20—register now to join us!
This startup thinks slime mold can help us design better cities It is a yellow blob with no brain, yet some researchers believe a curious organism known as slime mold could help us build more resilient cities.Humans have been building cities for 6,000 years, but slime mold has been around for 600 million. The team behind a new startup called Mireta wants to translate the organism’s biological superpowers into algorithms that might help improve transit times, alleviate congestion, and minimize climate-related disruptions in cities worldwide. Read the full story. —Elissaveta M. Brandon This story is from the latest print issue of MIT Technology Review magazine, which is full of fascinating stories about our bodies. If you haven’t already, subscribe now to receive future issues once they land. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 US government officials are skipping COP30And American corporate executives are following their lead. (NYT $)+ Protestors stormed the climate talks in Brazil. (The Guardian)+ Gavin Newsom took aim at Donald Trump’s climate policies onstage. (FT $) 2 The UK may assess AI models for their ability to generate CSAMIts government has suggested amending a legal bill to enable the tests. (BBC)+ US investigators are using AI to detect child abuse images made by AI. (MIT Technology Review) 3 Google is suing a group of Chinese hackersIt claims they’re selling software to enable criminal scams. (FT $)+ The group allegedly sends colossal text message phishing attacks. (CBS News)4 A major ‘cryptoqueen’ criminal has been jailedQian Zhimin used money stolen from Chinese pensioners to buy cryptocurrency now worth billions. (BBC)+ She defrauded her victims through an elaborate ponzi scheme. (CNN) 5 Carbon capture’s creators fear it’s being misusedOverreliance on the method could breed overconfidence and cause countries to delay reducing emissions. (Bloomberg $)+ Big Tech’s big bet on a controversial carbon removal tactic. (MIT Technology Review) 6 The UK will use AI to phase out animal testing3D bioprinted human tissues could also help to speed up the process. (The Guardian)+ But the AI boom is looking increasingly precarious. (WSJ $) 7 Louisiana is dealing with a whooping cough outbreakTwo infants have died to date from the wholly preventative disease. (Undark) 8 Here’s how ordinary people use ChatGPTEmotional support and discussions crop up regularly.(WP $)+ It’s surprisingly easy to stumble into a relationship with an AI chatbot. (MIT Technology Review) 9 Inside the search for lost continentsA newly-discovered mechanism is shedding light on why they may have vanished. (404 Media)+ How environmental DNA is giving scientists a new way to understand our world. (MIT Technology Review)
10 AI is taking Gen Z’s entry-level jobsEspecially in traditionally graduate-friendly consultancies. (NY Mag $)+ What the Industrial Revolution can teach us about how to handle AI. (Knowable Magazine)+ America’s corporate boards are stumbling in the dark. (WSJ $)
Quote of the day “We can’t eat money.” —Nato, an Indigenous leader from the Tupinamba community, tells Reuters why they are protesting at the COP30 climate summit in Brazil against any potential sale of their land. One more thing How K-pop fans are shaping elections around the globeBack in the early ‘90s, Korean pop music, known as K-pop, was largely conserved to its native South Korea. It’s since exploded around the globe into an international phenomenon, emphasizing choreography and elaborate performance.It’s made bands like Girls Generation, EXO, BTS, and Blackpink into household names, and inspired a special brand of particularly fierce devotion in their fans.Now, those same fandoms have learned how to use their digital skills to advocate for social change and pursue political goals—organizing acts of civil resistance, donating generously to charity, and even foiling white supremacist attempts to spread hate speech. Read the full story.—Soo Youn
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 skeet ’em at me.) + These sucker fish are having the time of their lives hitching a ride on a whale.+ Next time you fly, ditch the WiFi. I know I will.+ I love this colossal interactive gif.+ The hottest scent in perfumery right now? Smelling like a robot, apparently.

In partnership withEPAM For years, many chief information officers (CIOs) looked at VMware-to-cloud migrations with a wary pragmatism. Manually mapping dependencies and rewriting legacy apps mid-flight was not an enticing, low-lift proposition for enterprise IT teams. But the calculus for such decisions has changed dramatically in a short period of time. Following recent VMware licensing changes, organizations are seeing greater uncertainty around the platform’s future. At the same time, cloud-native innovation is accelerating. According to the CNCF’s 2024 Annual Survey, 89% of organizations have already adopted at least some cloud-native techniques, and the share of companies reporting nearly all development and deployment as cloud-native grew sharply from 2023 to 2024 (20% to 24%). And market research firm IDC reports that cloud providers have become top strategic partners for generative AI initiatives. This is all happening amid escalating pressure to innovate faster and more cost-effectively to meet the demands of an AI-first future. As enterprises prepare for that inevitability, they are facing compute demands that are difficult, if not prohibitively expensive, to maintain exclusively on-premises. Download the full article.
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 content was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The quest to find out how our bodies react to extreme temperatures Climate change is subjecting vulnerable people to temperatures that push their limits. In 2023, about 47,000 heat-related deaths are believed to have occurred in Europe. Researchers estimate that climate change could add an extra 2.3 million European heat deaths this century. That’s heightened the stakes for solving the mystery of just what happens to bodies in extreme conditions.While we broadly know how people thermoregulate, the science of keeping warm or cool is mottled with blind spots. Researchers around the world are revising rules about when extremes veer from uncomfortable to deadly. Their findings change how we should think about the limits of hot and cold—and how to survive in a new world. Read the full story. —Max G.Levy
This story is from the latest print issue of MIT Technology Review magazine, which is full of fascinating stories about the body. If you haven’t already, subscribe now to receive future issues once they land.
Whales are dying. Don’t blame wind turbines. Whale deaths have become a political flashpoint. There are currently three active mortality events for whales in the Atlantic, meaning clusters of deaths that experts consider unusual. And Republican lawmakers, conservative think tanks, and—most notably—President Donald Trump (a longtime enemy of wind power) are making dubious claims that offshore wind farms are responsible.But any finger-pointing at wind turbines for whale deaths ignores the fact that whales have been washing up on beaches since long before the giant machines were rooted in the ocean floor. This is something that has always happened. And the scientific consensus is clear: There’s no evidence that wind farms are the cause of recent increases in whale deaths. Read the full story. —Casey Crownhart This story is part of MIT Technology Review’s series “The New Conspiracy Age,” on how the present boom in conspiracy theories is reshaping science and technology. Check out the rest of the series here. The State of AI: Energy is king, and the US is falling behind In the age of AI, the biggest barrier to progress isn’t money but energy. That should be particularly worrying in the US, where massive data centers are waiting to come online. It doesn’t look as if the country will build the steady power supply or infrastructure needed to serve them all.It wasn’t always like this. For about a decade before 2020, data centers were able to offset increased demand with efficiency improvements. Now, though, electricity demand is ticking up in the US, with billions of queries to popular AI models each day—and efficiency gains aren’t keeping pace.If we want AI to have the chance to deliver on big promises without driving electricity prices sky-high for the rest of us, the US needs to learn some lessons from the rest of the world on energy abundance. Just look at China. Read the full story. —Casey Crownhart & Pilita Clark

This is from The State of AI, our subscriber-only collaboration between the Financial Times & MIT Technology Review examining the ways in which AI is reshaping global power.Every Monday for the next four weeks, writers from both publications will debate one aspect of the generative AI revolution reshaping global power. While subscribers to The Algorithm, our weekly AI newsletter, get access to an extended excerpt, subscribers to the magazine are able to read the whole thing. Sign up here to receive future editions every Monday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 How China narrowed its AI divide with the USAmerica still has a clear lead—but for how long? (WSJ $)+ The AI boom won’t offset tariffs and America’s immigration crackdown forever. (FT $)+ How quickly is AI likely to progress really? (Economist $)+ Is China about to win the AI race? (MIT Technology Review) 2 Anthropic is due to turn a profit much faster than OpenAIThe two companies are taking very different approaches to making money. (WSJ $)+ OpenAI has lured Intel’s AI chief away. (Bloomberg $) 3 The EU is setting up a new intelligence sharing unitIt’s a bid to shore up intel in the wake of Donald Trump’s plans to reduce security support for Europe. (FT $) 4 Trump officials are poised to suggest oil drilling off the coast of CaliforniaThat’s likely to rile the state’s politicians and leaders. (WP $)+ What role should oil and gas companies play in climate tech? (MIT Technology Review)
5 America’s cyber defenses are poorRepeated cuts and mass layoffs are making it harder to protect the nation. (The Verge) 6 China is on track to hit its peak CO2 emissions target earlyAlthough it’s likely to miss its goal for cutting carbon intensity. (The Guardian)+ World leaders are heading to COP30 in Brazil this week. (New Yorker $)
7 OpenAI cannot use song lyrics without a licenseThat’s what a German court has decided, after siding with a music rights society. (Reuters)+ OpenAI is no stranger to legal proceedings. (The Atlantic $)+ AI is coming for music. (MIT Technology Review) 8 A small Michigan town is fighting a proposed AI data centerThe planned center is part of a collaboration between the University of Michigan and nuclear weapons scientists. (404 Media)+ Here’s where America’s data centers should be built instead. (Wired $)+ Communities in Latin America are pushing back, too. (The Guardian)+ Should we be moving data centers to space? (MIT Technology Review)9 AI models can’t tell the time ⏰Analog clocks leave them completely stumped. (IEEE Spectrum) 10 ChatGPT is giving daters the ickThese refuseniks don’t want anything to do with AI, or love interests who use it. (The Guardian) Quote of the day “I never imagined that making a cup of tea or obtaining water, antibiotics, or painkillers would require such tremendous effort.”
—An anonymous member of startup accelerator Gaza Sky Geeks tells Rest of World about the impact the war has had on them. One more thing How Rust went from a side project to the world’s most-loved programming languageMany software projects emerge because—somewhere out there—a programmer had a personal problem to solve.That’s more or less what happened to Graydon Hoare. In 2006, Hoare was a 29-year-old computer programmer working for Mozilla. After a software crash broke the elevator in his building, he set about designing a new computer language; one that he hoped would make it possible to write small, fast code without memory bugs.That language developed into Rust, one of the hottest new languages on the planet. But while it isn’t unusual for someone to make a new computer language, it’s incredibly rare for one to take hold and become part of the programming pantheon. How did Rust do it? Read the full story. 

In partnership withCISCO AI and quantum technologies are dramatically reconfiguring how cybersecurity functions, redefining the speed and scale with which digital defenders and their adversaries can operate. The weaponization of AI tools for cyberattacks is already proving a worthy opponent to current defenses. From reconnaissance to ransomware, cybercriminals can automate attacks faster than ever before with AI. This includes using generative AI to create social engineering attacks at scale, churning out tens of thousands of tailored phishing emails in seconds, or accessing widely available voice cloning software capable of bypassing security defenses for as little as a few dollars. And now, agentic AI raises the stakes by introducing autonomous systems that can reason, act, and adapt like human adversaries. But AI isn’t the only force shaping the threat landscape. Quantum computing has the potential to seriously undermine current encryption standards if developed unchecked. Quantum algorithms can solve the mathematical problems underlying most modern cryptography, particularly public-key systems like RSA and Elliptic Curve, widely used for secure online communication, digital signatures, and cryptocurrency. “We know quantum is coming. Once it does, it will force a change in how we secure data across everything, including governments, telecoms, and financial systems,” says Peter Bailey, senior vice president and general manager of Cisco’s security business.
“Most organizations are understandably focused on the immediacy of AI threats,” says Bailey. “Quantum might sound like science fiction, but those scenarios are coming faster than many realize. It’s critical to start investing now in defenses that can withstand both AI and quantum attacks.” Critical to this defense is a zero trust approach to cybersecurity, which assumes no user or device can be inherently trusted. By enforcing continuous verification, zero trust enables constant monitoring and ensures that any attempts to exploit vulnerabilities are quickly detected and addressed in real time. This approach is technology-agnostic and creates a resilient framework even in the face of an ever-changing threat landscape.
Putting up AI defenses  AI is lowering the barrier to entry for cyberattacks, enabling hackers even with limited skills or resources to infiltrate, manipulate, and exploit the slightest digital vulnerability. Nearly three-quarters (74%) of cybersecurity professionals say AI-enabled threats are already having a significant impact on their organization, and 90% anticipate such threats in the next one to two years.  “AI-powered adversaries have advanced techniques and operate at machine speed,” says Bailey. “The only way to keep pace is to use AI to automate response and defend at machine speed.” To do this, Bailey says, organizations must modernize systems, platforms, and security operations to automate threat detection and response—processes that have previously relied on human rule-writing and reaction times. These systems must adapt dynamically as environments evolve and criminal tactics change. At the same time, companies must strengthen the security of their AI models and data to reduce exposure to manipulation from AI-enabled malware. Such risks could include, for instance, prompt injections, where a malicious user crafts a prompt to manipulate an AI model into performing unintended actions, bypassing its original instructions and safeguards. Agentic AI further ups the ante, with hackers able to use AI agents to automate attacks and make tactical decisions without constant human oversight. “Agentic AI has the potential to collapse the cost of the kill chain,” says Bailey. “That means everyday cybercriminals could start executing campaigns that today only well-funded espionage operations can afford.” Organizations, in turn, are exploring how AI agents can help them stay ahead. Nearly 40% of companies expect agentic AI to augment or assist teams over the next 12 months, especially in cybersecurity, according to Cisco’s 2025 AI Readiness Index. Use cases include AI agents trained on telemetry, which can identify anomalies or signals from machine data too disparate and unstructured to be deciphered by humans.  Calculating the quantum threat As many cybersecurity teams focus on the very real AI-driven threat, quantum is waiting on the sidelines. Almost three-quarters (73%) of US organizations surveyed by KPMG say they believe it is only a matter of time before cybercriminals are using quantum to decrypt and disrupt today’s cybersecurity protocols. And yet, the majority (81%) also admit they could do more to ensure that their data remains secure.

Companies are right to be concerned. Threat actors are already carrying out harvest now, decrypt later attacks, stockpiling sensitive encrypted data to crack once quantum technology matures. Examples include state-sponsored actors intercepting government communications and cybercriminal networks storing encrypted internet traffic or financial records.  Large technology companies are among the first to roll out quantum defenses. For example, Apple is using cryptography protocol PQ3 to defend against harvest now, decrypt later attacks on its iMessage platform. Google is testing post-quantum cryptography (PQC)—which is resistant to attacks from both quantum and classical computers—in its Chrome browser. And Cisco “has made significant investments in quantum-proofing our software and infrastructure,” says Bailey. “You’ll see more enterprises and governments taking similar steps over the next 18 to 24 months,” he adds.  As regulations like the US Quantum Computing Cybersecurity Preparedness Act lay out requirements for mitigating against quantum threats, including standardized PQC algorithms by the National Institute of Standards and Technology, a wider range of organizations will start preparing their own quantum defenses.  For organizations beginning that journey, Bailey outlines two key actions. First, establish visibility. “Understand what data you have and where it lives,” he says. “Take inventory, assess sensitivity, and review your encryption keys, rotating out any that are weak or outdated.” Second, plan for migration. “Next, assess what it will take to support post-quantum algorithms across your infrastructure. That means addressing not just the technology, but also the process and people implications,” Bailey says. Adopting proactive defense  Ultimately, the foundation for building resilience against both AI and quantum is a zero trust approach, says Bailey. By embedding zero trust access controls across users, devices, business applications, networks, and clouds, this approach grants only the minimum access required to complete a task and enables continuous monitoring. It can also minimize the attack surface by confining a potential threat to an isolated zone, preventing it from accessing other critical systems. Into this zero trust architecture, organizations can integrate specific measures to defend against AI and quantum risks. For instance, quantum-immune cryptography and AI-powered analytics and security tools can be used to identify complex attack patterns and automate real-time responses.  “Zero trust slows down attacks and builds resilience,” Bailey says. “It ensures that even if a breach occurs, the crown jewels stay protected and operations can recover quickly.”
Ultimately, companies should not wait for threats to emerge and evolve. They must get ahead now. “This isn’t a what-if scenario; it’s a when,” says Bailey. “Organizations that invest early will be the ones setting the pace, not scrambling to catch up.” 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. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Why it’s so hard to bust the weather control conspiracy theory It was October 2024, and Hurricane Helene had just devastated the US Southeast. Representative Marjorie Taylor Greene of Georgia found an abstract target on which to pin the blame: “Yes they can control the weather,” she posted on X. “It’s ridiculous for anyone to lie and say it can’t be done.”She was repeating what’s by now a pretty familiar and popular conspiracy theory: that shadowy forces are out there, wielding technology to control the weather and wreak havoc on their enemies. This preposterous claim has grown louder and more common in recent years, especially after extreme weather strikes.But here’s the thing: While Greene and other believers are not correct, this conspiracy theory—like so many others—holds a kernel of much more modest truth. Read the full story. —Dave Levitan
This story is part of MIT Technology Review’s series “The New Conspiracy Age,” on how the present boom in conspiracy theories is reshaping science and technology. Check out the rest of the series here.
AI could predict who will have a heart attack  For all the modern marvels of cardiology, we struggle to predict who will have a heart attack. Many people never get screened at all. Now, startups are applying AI algorithms to screen millions of CT scans for early signs of heart disease.This technology could be a breakthrough for public health, applying an old tool to uncover patients whose high risk for a heart attack is hiding in plain sight. But it remains unproven at scale, while raising thorny questions about implementation and even how we define disease. Read the full story. —Vishal Khetpal This story is from the latest print issue of MIT Technology Review magazine, which is full of fascinating stories about the body. If you haven’t already, subscribe now to receive future issues once they land. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Spending on AI may be to blame for all those tech layoffsAI isn’t necessarily replacing jobs, but spending on it is gobbling up budgets. (Fast Company $)+ Junior roles are likely to be the first on the chopping block. (FT $)+ Are the crazy sums that businesses are sinking into AI sustainable? (WP $)+ People are worried that AI will take everyone’s jobs. We’ve been here before. (MIT Technology Review)

2 Anti-vaccine activists gathered in Austin over the weekendThey celebrated RFK Jr’s rise and outlined their goals—including eliminating school vaccine mandates. (WP $)+ We’re on the verge of stopping the next pandemic. But will we? (Vox)+ How conspiracy theories infiltrated the doctor’s office. (MIT Technology Review) 3 People who’ve experienced AI-induced delusions are forming a movementThey’re pushing for legal action against chatbot makers. (Bloomberg $)+ The looming crackdown on AI companionship. (MIT Technology Review) 4 AI-generated clips of women being strangled are flooding social mediaMany of them appear to have been created using OpenAI’s Sora 2. (404 Media)5 Tech leaders are obsessed with bioengineering babiesThey’re not allowed to, but they’re not letting a little thing like ethics get in the way. (WSJ $)+ The race to make the perfect baby is creating an ethical mess. (MIT Technology Review)6 Apple has removed two popular gay dating apps in China The country ordered it to take down Blued and Finka from its app. (Wired $) 7 The UK government is worried China could turn off its buses remotelyIt fears hundreds of Chinese-made electric buses on British roads could be at risk. (FT $) 8 How AI is changing the world’s newsrooms 📰It’s brilliant at analyzing large data sets—but shouldn’t be used to write stories. (NYT $) 9 How to contain an invasive speciesExperts argue that too much red tape is getting in the way. (Undark)+ The weeds are winning. (MIT Technology Review)10 The world’s largest electric ship is charging up 🚢Once it’s ready to go, it’ll serve as a ferry in 90 minute bursts. (IEEE Spectrum) Quote of the day
“We would move heaven and Earth, pun intended, to try to get to the Moon sooner.”  —Dave Limp, CEO of Blue Origin, says the company is raring to work with NASA to get humans back on the Moon, Ars Technica reports.
One more thing Design thinking was supposed to fix the world. Where did it go wrong?In the 1990s, a six-step methodology for innovation called design thinking started to grow in popularity. Key to its spread was its replicable aesthetic, represented by the Post-it note: a humble square that anyone can use in infinite ways.But in recent years, for a number of reasons, the shine of design thinking has been wearing off. Critics have argued that its short-term focus on novel and naive ideas results in unrealistic and ungrounded recommendations.Today, some groups are working to reform both design thinking’s principles and its methodologies. These new efforts seek a set of design tools capable of equitably serving diverse communities and solving diverse problems well into the future. It’s a much more daunting—and crucial—task than design thinking’s original remit. Read the full story. —Rebecca Ackermann 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 skeet ’em at me.) + These tree-dwelling toads give birth to live young—who knew?!+ Now’s the time to practice your baking skills ahead of Thanksgiving.+ Younguk Yi’s glitching paintings are a lot of fun.+ Place your bets! This fun game follows three balls in a race to the bottom, but who will win?

Welcome to The State of AI, a new collaboration between the Financial Times and MIT Technology Review. Every Monday for the next six weeks, writers from both publications will debate one aspect of the generative AI revolution reshaping global power. This week, Casey Crownhart, senior reporter for energy at MIT Technology Review and Pilita Clark, FT’s columnist, consider how China’s rapid renewables buildout could help it leapfrog on AI progress. Casey Crownhart writes: In the age of AI, the biggest barrier to progress isn’t money but energy. That should be particularly worrying here in the US, where massive data centers are waiting to come online, and it doesn’t look as if the country will build the steady power supply or infrastructure needed to serve them all.
It wasn’t always like this. For about a decade before 2020, data centers were able to offset increased demand with efficiency improvements. Now, though, electricity demand is ticking up in the US, with billions of queries to popular AI models each day—and efficiency gains aren’t keeping pace. With too little new power capacity coming online, the strain is starting to show: Electricity bills are ballooning for people who live in places where data centers place a growing load on the grid. If we want AI to have the chance to deliver on big promises without driving electricity prices sky-high for the rest of us, the US needs to learn some lessons from the rest of the world on energy abundance. Just look at China.
China installed 429 GW of new power generation capacity in 2024, more than six times the net capacity added in the US during that time. China still generates much of its electricity with coal, but that makes up a declining share of the mix. Rather, the country is focused on installing solar, wind, nuclear, and gas at record rates. The US, meanwhile, is focused on reviving its ailing coal industry. Coal-fired power plants are polluting and, crucially, expensive to run. Aging plants in the US are also less reliable than they used to be, generating electricity just 42% of the time, compared with a 61% capacity factor in 2014. It’s not a great situation. And unless the US changes something, we risk becoming consumers as opposed to innovators in both energy and AI tech. Already, China earns more from exporting renewables than the US does from oil and gas exports.  Building and permitting new renewable power plants would certainly help, since they’re currently the cheapest and fastest to bring online. But wind and solar are politically unpopular with the current administration. Natural gas is an obvious candidate, though there are concerns about delays with key equipment. One quick fix would be for data centers to be more flexible. If they agreed not to suck electricity from the grid during times of stress, new AI infrastructure might be able to come online without any new energy infrastructure. One study from Duke University found that if data centers agree to curtail their consumption just 0.25% of the time (roughly 22 hours over the course of the year), the grid could provide power for about 76 GW of new demand. That’s like adding about 5% of the entire grid’s capacity without needing to build anything new. But flexibility wouldn’t be enough to truly meet the swell in AI electricity demand. What do you think, Pilita? What would get the US out of these energy constraints? Is there anything else we should be thinking about when it comes to AI and its energy use? 

Pilita Clark responds: I agree. Data centers that can cut their power use at times of grid stress should be the norm, not the exception. Likewise, we need more deals like those giving cheaper electricity to data centers that let power utilities access their backup generators. Both reduce the need to build more power plants, which makes sense regardless of how much electricity AI ends up using. This is a critical point for countries across the world, because we still don’t know exactly how much power AI is going to consume.  Forecasts for what data centers will need in as little as five years’ time vary wildly, from less than twice today’s rates to four times as much. This is partly because there’s a lack of public data about AI systems’ energy needs. It’s also because we don’t know how much more efficient these systems will become. The US chip designer Nvidia said last year that its specialized chips had become 45,000 times more energy efficient over the previous eight years.  Moreover, we have been very wrong about tech energy needs before. At the height of the dot-com boom in 1999, it was erroneously claimed that the internet would need half the US’s electricity within a decade—necessitating a lot more coal power. Still, some countries are clearly feeling the pressure already. In Ireland, data centers chew up so much power that new connections have been restricted around Dublin to avoid straining the grid. Some regulators are eyeing new rules forcing tech companies to provide enough power generation to match their demand. I hope such efforts grow. I also hope AI itself helps boost power abundance and, crucially, accelerates the global energy transition needed to combat climate change. OpenAI’s Sam Altman said in 2023 that “once we have a really powerful super intelligence, addressing climate change will not be particularly difficult.” 
The evidence so far is not promising, especially in the US, where renewable projects are being axed. Still, the US may end up being an outlier in a world where ever cheaper renewables made up more than 90% of new power capacity added globally last year.  Europe is aiming to power one of its biggest data centers predominantly with renewables and batteries. But the country leading the green energy expansion is clearly China.
The 20th century was dominated by countries rich in the fossil fuels whose reign the US now wants to prolong. China, in contrast, may become the world’s first green electrostate. If it does this in a way that helps it win an AI race the US has so far controlled, it will mark a striking chapter in economic, technological, and geopolitical history. Casey Crownhart replies: I share your skepticism of tech executives’ claims that AI will be a groundbreaking help in the race to address climate change. To be fair, AI is progressing rapidly. But we don’t have time to wait for technologies standing on big claims with nothing to back them up.  When it comes to the grid, for example, experts say there’s potential for AI to help with planning and even operating, but these efforts are still experimental.   Meanwhile, much of the world is making measurable progress on transitioning to newer, greener forms of energy. How that will affect the AI boom remains to be seen. What is clear is that AI is changing our grid and our world, and we need to be clear-eyed about the consequences.  Further reading 
MIT Technology Review reporters did the math on the energy needs of an AI query. There are still a few reasons to be optimistic about AI’s energy demands.   The FT’s visual data team take a look inside the relentless race for AI capacity. And global FT reporters ask whether data centers can ever truly be green.