Carbon Chemist

Category: Science & Tech

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  • The AI lab waging a guerrilla war over exploitative AI

    The AI lab waging a guerrilla war over exploitative AI

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    Yet it is “simplistic to think that if you have a real security problem in the wild and you’re trying to design a protection tool, the answer should be it either works perfectly or don’t deploy it,” Zhao says, citing spam filters and firewalls as examples. Defense is a constant cat-and-mouse game. And he believes most artists are savvy enough to understand the risk. 

    Offering hope

    The fight between creators and AI companies is fierce. The current paradigm in AI is to build bigger and bigger models, and there is, at least currently, no getting around the fact that they require vast data sets hoovered from the internet to train on. Tech companies argue that anything on the public internet is fair game, and that it is “impossible” to build advanced AI tools without copyrighted material; many artists argue that tech companies have stolen their intellectual property and violated copyright law, and that they need ways to keep their individual works out of the models—or at least receive proper credit and compensation for their use. 

    So far, the creatives aren’t exactly winning. A number of companies have already replaced designers, copywriters, and illustrators with AI systems. In one high-profile case, Marvel Studios used AI-generated imagery instead of human-created art in the title sequence of its 2023 TV series Secret Invasion. In another, a radio station fired its human presenters and replaced them with AI. The technology has become a major bone of contention between unions and film, TV, and creative studios, most recently leading to a strike by video-game performers. There are numerous ongoing lawsuits by artists, writers, publishers, and record labels against AI companies. It will likely take years until there is a clear-cut legal resolution. But even a court ruling won’t necessarily untangle the difficult ethical questions created by generative AI. Any future government regulation is not likely to either, if it ever materializes. 

    That’s why Zhao and Zheng see Glaze and Nightshade as necessary interventions—tools to defend original work, attack those who would help themselves to it, and, at the very least, buy artists some time. Having a perfect solution is not really the point. The researchers need to offer something now because the AI sector moves at breakneck speed, Zheng says, means that companies are ignoring very real harms to humans. “This is probably the first time in our entire technology careers that we actually see this much conflict,” she adds.

    On a much grander scale, she and Zhao tell me they hope that Glaze and Nightshade will eventually have the power to overhaul how AI companies use art and how their products produce it. It is eye-wateringly expensive to train AI models, and it’s extremely laborious for engineers to find and purge poisoned samples in a data set of billions of images. Theoretically, if there are enough Nightshaded images on the internet and tech companies see their models breaking as a result, it could push developers to the negotiating table to bargain over licensing and fair compensation. 

    That’s, of course, still a big “if.” MIT Technology Review reached out to several AI companies, such as Midjourney and Stability AI, which did not reply to requests for comment. A spokesperson for OpenAI, meanwhile, did not confirm any details about encountering data poison but said the company takes the safety of its products seriously and is continually improving its safety measures: “We are always working on how we can make our systems more robust against this type of abuse.”

    In the meantime, the SAND Lab is moving ahead and looking into funding from foundations and nonprofits to keep the project going. They also say there has also been interest from major companies looking to protect their intellectual property (though they decline to say which), and Zhao and Zheng are exploring how the tools could be applied in other industries, such as gaming, videos, or music. In the meantime, they plan to keep updating Glaze and Nightshade to be as robust as possible, working closely with the students in the Chicago lab—where, on another wall, hangs Toorenent’s Belladonna. The painting has a heart-shaped note stuck to the bottom right corner: “Thank you! You have given hope to us artists.”

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  • The Download: Parkour for robot dogs, and Africa’s AI ambitions

    The Download: Parkour for robot dogs, and Africa’s AI ambitions

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    Teaching robots to navigate new environments is tough. You can train them on physical, real-world data taken from recordings made by humans, but that’s scarce, and expensive to collect. Digital simulations are a rapid, scalable way to teach them to do new things, but the robots often fail when they’re pulled out of virtual worlds and asked to do the same tasks in the real one. 

    Now, there’s potentially a better option: a new system that uses generative AI models in conjunction with a physics simulator to develop virtual training grounds that more accurately mirror the physical world. Robots trained using this method worked with a higher success rate than those trained using more traditional techniques during real-world tests.

    Researchers used the system, called LucidSim, to train a robot dog in parkour, getting it to scramble over a box and climb stairs, despite never seeing any real world data. The approach demonstrates how helpful generative AI could be when it comes to teaching robots to do challenging tasks. It also raises the possibility that we could ultimately train them in entirely virtual worlds. Read the full story.

    —Rhiannon Williams

    Africa’s AI researchers are ready for takeoff

    When we talk about the global race for AI dominance, the conversation often focuses on tensions between the US and China, and European efforts at regulating the technology. But it’s high time we talk about another player: Africa.

    African AI researchers are forging their own path, developing tools that answer the needs of Africans, in their own languages. Their story is not only one of persistence and innovation, but of preserving cultures and fighting to shape how AI technologies are used on their own continent. However, they face many barriers. Read the full story.

    —Melissa Heikkilä

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  • Africa’s AI researchers are ready for takeoff

    Africa’s AI researchers are ready for takeoff

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    Tech companies have been funneling billions of dollars into quantum computers for years. The hope is that they’ll be a game changer for fields as diverse as finance, drug discovery, and logistics. Those expectations have been especially high in physics and chemistry, where the weird effects of quantum mechanics come into play. In theory, this is where quantum computers could have a huge advantage over conventional machines.

    Enter AI: But while the field struggles with the realities of tricky quantum hardware, another challenger is making headway in some of these most promising use cases. AI is now being applied to fundamental physics, chemistry, and materials science in a way that suggests quantum computing’s purported home turf might not be so safe after all. 

    Given the pace of recent advances, a growing number of researchers are now asking whether AI could solve a substantial chunk of the most interesting problems in chemistry and materials science before large-scale quantum computers become a reality. Read more from Edd Gent here. 

    Bits and Bytes

    The Saudis are planning a $100 billion AI powerhouse 
    Speaking of the race for AI dominance, this piece looks at how Saudi Arabia wants in on AI action. And it’s putting its money where its mouth is. The country is investing a massive sum to develop a tech hub that it hopes will rival the neighboring United Arab Emirates. (Bloomberg)

    AI is making it harder to believe what is real and what is not
    Two recent examples show just how influential AI slop can be in warping our sense of reality. In Dublin, crowds gathered in the city center to wait for a Halloween parade to take place. There was no parade planned, but the listing was created by AI and then picked up by social media users and local media. By way of contrast, some social media users dismissed shocking images of the devastating recent floods in Spain as AI-generated, despite them being entirely real. 

    AI companies are getting comfortable offering their technology to the military
    Militaries around the world have been pouring money into new technologies, including AI. Meta and Anthropic are the latest tech companies to start courting them, joining the likes of Google and OpenAI. (The Washington Post) 

    OpenAI is shifting its strategy as the improvement in its AI tools slows down
    The current paradigm in AI development is to make things bigger to make them better. But OpenAI’s new model, code-named Orion, only performs slightly better than its predecessors. Instead, OpenAI is shifting to improving models after their initial training. (The Information) 

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  • Generative AI taught a robot dog to scramble around a new environment

    Generative AI taught a robot dog to scramble around a new environment

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    Researchers used the system, called LucidSim, to train a robot dog in parkour, getting it to scramble over a box and climb stairs, despite never seeing any real world data. The approach demonstrates how helpful generative AI could be when it comes to teaching robots to do challenging tasks. It also raises the possibility that we could ultimately train them in entirely virtual worlds. The research was presented at the Conference on Robot Learning (CoRL) last week.

    “We’re in the middle of an industrial revolution for robotics,” says Ge Yang, a postdoc scholar at MIT CSAIL who worked on the project. “This is our attempt at understanding the impact of these [generative AI] models outside of their original intended purposes, with the hope that it will lead us to the next generation of tools and models.” 

    LucidSim uses a combination of generative AI models to create the visual training data. Firstly, the researchers generated thousands of prompts for ChatGPT, getting it to create descriptions of a range of environments that represent the conditions the robot will encounter in the real world, including different types of weather, times of day, and lighting conditions. For example, these included ‘an ancient alley lined with tea houses and small, quaint shops, each displaying traditional ornaments and calligraphy’ and ‘the sun illuminates a somewhat unkempt lawn dotted with dry patches.’   

    These descriptions were fed into a system which maps 3D geometry and physics data onto AI-generated images, creating short videos mapping the trajectory the robot will follow. The robot draws on this information to work out the height, width and depth of the things it has to navigate—a box or a set of stairs, for example.

    The researchers tested LucidSim by instructing a four-legged robot equipped with a webcam to complete several tasks, including locating a traffic cone or soccer ball, climbing over a box and walking up and down stairs. The robot performed consistently better than when it ran a system trained on traditional simulations. Out of 20 trials to locate the cone, LucidSim had a 100% success rate, compared to 70% for systems trained on standard simulations. Similarly, LucidSim reached the soccer ball in another 20 trials 85% of the time, compared to just 35% for the other system. 

    Finally, when the robot was running LucidSim, it successfully completed all 10 stair-climbing trials, compared to just 50% for the other system.

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    From left to right: Phillip Isola, Ge Yang and Alan Yu

    COURTESY OF MIT CSAIL

    These results are likely to improve even further in the future if LucidSim draws directly from sophisticated generative video models rather than a rigged-together combination of language, image and physics models, says Phillip Isola, an associate professor at MIT who worked on the research.

    The researchers’ approach to using generative AI is a novel one that will pave the way for more interesting new research, says Mahi Shafiullah, a PhD student at New York University who is using AI models to train robots, and did not work on the project. 

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  • The Download: AI in Africa, and reporting in the age of Trump

    The Download: AI in Africa, and reporting in the age of Trump

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    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 Africa needs to do to become a major AI player

    Africa is still early in the process of adopting AI technologies. But researchers say the continent is uniquely hospitable to it for several reasons, including a relatively young and increasingly well-educated population, a rapidly growing ecosystem of AI startups, and lots of potential consumers. 

    However, ambitious efforts to develop AI tools that answer the needs of Africans face numerous hurdles. The biggest are inadequate funding and poor infrastructure. Limited internet access and a scarcity of domestic data centers also mean that developers might not be able to deploy cutting-edge AI capabilities. Complicating this further is a lack of overarching policies or strategies for harnessing AI’s immense benefits—and regulating its downsides.

    Taken together, researchers worry, these issues will hold Africa’s AI sector back and hamper its efforts to pave its own pathway in the global AI race. Read the full story.

    —Abdullahi Tsanni

    Science and technology stories in the age of Trump

    —Mat Honan

    I’ve spent most of this year being pretty convinced that Donald Trump would be the 47th president of the United States. Even so, like most people, I was completely surprised by the scope of his victory. This level of victory will certainly provide the political capital to usher in a broad sweep of policy changes.

    Some of these changes will be well outside our lane as a publication. But very many of President-elect Trump’s stated policy goals will have direct impacts on science and technology. 

    So I thought I would share some of my remarks from our edit meeting on Wednesday morning, when we woke up to find out that the world had indeed changed. Read the full story.

    This story is from The Debrief, the weekly newsletter from our editor in chief Mat Honan. Sign up 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 Canada has recorded its first known bird flu case in a human 
    Officials are investigating how the teenager was exposed to the virus. (NPR)
    + Canada insists that the risk to the public remains low. (Reuters)
    + Why virologists are getting increasingly nervous about bird flu. (MIT Technology Review)

    2 How MAGA became a rallying call for young men
    The Republicans’ online strategy tapped into the desires of disillusioned Gen Z men. (WP $)
    + Elon Musk is assembling a list of favorable would-be Trump advisors. (FT $)

    3 Trump’s victory is a win for the US defense industry
    Palmer Luckey’s Anduril is anticipating a lucrative next four years. (Insider $)
    + Here’s what Luckey has to say about the Pentagon’s future of mixed reality. (MIT Technology Review)
    + Traditional weapons are being given AI upgrades. (Wired $)

    4 This year is highly likely to be the hottest on record
    This week’s Cop29 climate summit will thrash out future policies. (The Guardian)
    + A little-understood contributor to the weather? Microplastics. (Wired $)
    + Trump’s win is a tragic loss for climate progress. (MIT Technology Review)

    5 Ukraine is scrambling to repair its power stations
    Workers are dismantling plants to repair other stations hit by Russian attacks. (WSJ $)
    + Meet the radio-obsessed civilian shaping Ukraine’s drone defense. (MIT Technology Review)

    6 We need better ways to evaluate LLMs
    Tech giants are coming up with better methods of measuring these systems. (FT $)
    + The improvements in the tech behind ChatGPT appear to be slowing. (The Information $)
    + AI hype is built on high test scores. Those tests are flawed. (MIT Technology Review)

    7 FTX is suing crypto exchange Binance
    It claims Sam Bankman-Fried fraudulently transferred close to $1.8 billion to Binance in 2021. (Bloomberg $)
    + Meanwhile, bitcoin is surging to new record heights. (Reuters)

    8 What we know about tech and loneliness
    While there’s little evidence tech directly makes us lonely, there’s a strong correlation between the two. (NYT $)

    9 What’s next for space policy in the US
    If one person’s interested in the cosmos, it’s Elon Musk. (Ars Technica)

    10 Could you save the Earth from a killer asteroid?
    It’s a game that’s part strategy, part luck. (New Scientist $)
    + Earth is probably safe from a killer asteroid for 1,000 years. (MIT Technology Review)

    Quote of the day

    “‘Conflict of interest’ seems rather quaint.”

    —Gita Johar, a professor at Columbia Business School, tells the Guardian about Donald Trump and Elon Musk’s openly transactional relationship.

    The big story

    Quartz, cobalt, and the waste we leave behind

    May 2024

    It is easy to convince ourselves that we now live in a dematerialized ethereal world, ruled by digital startups, artificial intelligence, and financial services.

    Yet there is little evidence that we have decoupled our economy from its churning hunger for resources. We are still reliant on the products of geological processes like coal and quartz, a mineral that’s a rich source of the silicon used to build computer chips, to power our world.

    Three recent books aim to reconnect readers with the physical reality that underpins the global economy. Each one fills in dark secrets about the places, processes, and lived realities that make the economy tick, and reveals just how tragic a toll the materials we rely on take for humans and the environment. Read the full story.

    —Matthew Ponsford

    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 tweet ’em at me.)

    + Oscars buzz has already begun, and this year’s early contenders are an interesting bunch.
    + This sweet art project shows how toys age with love ❤
    + Who doesn’t love pretzels? Here’s how to make sure they end up with the perfect fluffy interior and a glossy, chewy crust.
    + These images of plankton are really quite something.



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  • Science and technology stories in the age of Trump

    Science and technology stories in the age of Trump

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    Some of these changes will be well outside our lane as a publication. But very many of President-elect Trump’s stated policy goals will have direct impacts on science and technology. Some of the proposed changes would have profound effects on the industries and innovations we’ve covered regularly, and for years. When he talks about his intention to end EV subsidies, hit the brakes on FTC enforcement actions on Big Tech, ease the rules on crypto, or impose a 60 percent tariff on goods from China, these are squarely in our strike zone and we would be remiss not to explore the policies and their impact in detail. 

    And so I thought I would share some of my remarks from our edit meeting on Wednesday morning, when we woke up to find out that the world had indeed changed. I think it’s helpful for our audience if we are transparent and upfront about how we intend to operate, especially over the next several months that will likely be, well, chaotic. 

    This is a moment when our jobs are more important than ever. There will be so much noise and heat out there in the coming weeks and months, and maybe even years. The next six months in particular will be a confusing time for a lot of people. We should strive to be the signal in that noise. 

    We have extremely important stories to write about the role of science and technology in the new administration. There are obvious stories for us to take on in regards to climate, energy, vaccines, women’s health, IVF, food safety, chips, China, and I’m sure a lot more, that people are going to have all sorts of questions about. Let’s start by making a list of questions we have ourselves. Some of the people and technologies we cover will be ascendant in all sorts of ways. We should interrogate that power.  It’s important that we take care in those stories not to be speculative or presumptive. To always have the facts buttoned up. To speak the truth and be unassailable in doing so.

    Do we drop everything and only cover this? No. But it will certainly be a massive story that affects nearly all others.

    This election will be a transformative moment for society and the world. Trump didn’t just win, he won a mandate. And he’s going to change the country and the global order as a result.  The next few weeks will see so much speculation as to what it all means. So much fear, uncertainty, and doubt. There is an enormous amount of bullshit headed down the line. People will be hungry for sources they can trust. We should be there for that. Let’s leverage our credibility, not squander it. 

    We are not the resistance. We just want to tell the truth. So let’s take a breath, and then go out there and do our jobs.

    I like to tell our reporters and editors that our coverage should be free from either hype or cynicism. I think that’s especially true now. 

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  • A bold AI movement is underway in Africa—but it’s being held up

    A bold AI movement is underway in Africa—but it’s being held up

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    It’s unclear what’s behind the second strategy, but Seydina Ndiaye, a program director at the Cheikh Hamidou Kane Digital University in Dakar who helped draft the development agency’s white paper, claims it was drafted by a tech lobbyist from Switzerland. The commission’s strategy calls for African Union member states to declare AI a national priority, promote AI startups, and develop regulatory frameworks to address safety and security challenges. But Ndiaye expressed concerns that the document does not reflect the perspectives, aspirations, knowledge, and work of grassroots African AI communities. “It’s a copy-paste of what’s going on outside the continent,” he says.               

    Vukosi Marivate, a computer scientist at the University of Pretoria in South Africa who helped found the Deep Learning Indaba and is known as an advocate for the African machine-learning movement, expressed fury over this turn of events at the conference. “These are things we shouldn’t accept,” he declared. The room full of data wonks, linguists, and international funders brimmed with frustration. But Marivate encouraged the group to forge ahead with building AI that benefits Africans: “We don’t have to wait for the rules to act right,” he said.  

    Barbara Glover, a program manager for the African Union Development Agency, acknowledges that AI researchers are angry and frustrated. There’s been a push to harmonize the two continental AI strategies, but she says the process has been fractious: “That engagement didn’t go as envisioned.” Her agency plans to keep its own version of the continental AI strategy, Glover says, adding that it was developed by African experts rather than outsiders. “We are capable, as Africans, of driving our own AI agenda,” she says.       

    crowd of attendees mingle around display booths at Deep Learning Indaba 2024. Booth signs for Mila, Meta and OpenAI can be seen in the frame.

    DEEP LEARNING INDABA 2024

    This all speaks to a broader tension over foreign influence in the African AI scene, one that goes beyond any single strategic document. Mirroring the skepticism toward the African Union Commission strategy, critics say the Deep Learning Indaba is tainted by its reliance on funding from big foreign tech companies; roughly 50% of its $500,000 annual budget comes from international donors and the rest from corporations like Google DeepMind, Apple, Open AI, and Meta. They argue that this cash could pollute the Indaba’s activities and influence the topics and speakers chosen for discussion. 

    But Mohamed, the Indaba cofounder who is a researcher at Google DeepMind, says that “almost all that goes back to our beneficiaries across the continent,” and the organization helps connect them to training opportunities in tech companies. He says it benefits from some of its cofounders’ ties with these companies but that they do not set the agenda.

    Ndiaye says that the funding is necessary to keep the conference going. “But we need to have more African governments involved,” he says.     

    To Timnit Gebru, founder and executive director at the nonprofit Distributed AI Research Institute (DAIR), which supports equitable AI research in Africa, the angst about foreign funding for AI development comes down to skepticism of exploitative, profit-driven international tech companies. “Africans [need] to do something different and not replicate the same issues we’re fighting against,” Gebru says. She warns about the pressure to adopt “AI for everything in Africa,” adding that there’s “a lot of push from international development organizations” to use AI as an “antidote” for all Africa’s challenges.       

    Siminyu, who is also a researcher at DAIR, agrees with that view. She hopes that African governments will fund and work with people in Africa to build AI tools that reach underrepresented communities—tools that can be used in positive ways and in a context that works for Africans. “We should be afforded the dignity of having AI tools in a way that others do,” she says.     

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  • What’s next for reproductive rights in the US

    What’s next for reproductive rights in the US

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    Two years ago, the US Supreme Court overturned Roe v. Wade, a legal decision that protected the right to abortion. Since then, abortion bans have been enacted in multiple states, and millions of people in the US have lost access to local clinics.

    Now, some states are voting to extend and protect access to abortion. This week, seven states voted in support of such measures. And voters in Missouri, a state that has long restricted access, have voted to overturn its ban.

    It’s not all good news for proponents of reproductive rights—some states voted against abortion access. And questions remain over the impact of a second term under former president Donald Trump, who is set to return to the post in January.

    Roe v. Wade, the legal decision that enshrined a constitutional right to abortion in the US in 1973, guaranteed the right to an abortion up to the point of fetal viability, which is generally considered to be around 24 weeks of pregnancy. It was overturned by the US Supreme Court in the summer of 2022.

    Within 100 days of the decision, 13 states had enacted total bans on abortion from the moment of conception. Clinics in these states could no longer offer abortions. Other states also restricted abortion access. In that 100-day period, 66 of the 79 clinics across 15 states stopped offering abortion services, and 26 closed completely, according to research by the Guttmacher Institute.

    The political backlash to the decision was intense. This week, abortion was on the ballot in 10 states: Arizona, Colorado, Florida, Maryland, Missouri, Montana, Nebraska, Nevada, New York, and South Dakota. And seven of them voted in support of abortion access.

    The impact of these votes will vary by state. Abortion was already legal in Maryland, for example. But the new measures should make it more difficult for lawmakers to restrict reproductive rights in the future. In Arizona, abortions after 15 weeks had been banned since 2022. There, voters approved an amendment to the state constitution that will guarantee access to abortion until fetal viability.

    Missouri was the first state to enact an abortion ban once Roe v. Wade was overturned. The state’s current Right to Life of the Unborn Child Act prohibits doctors from performing abortions unless there is a medical emergency. It has no exceptions for rape or incest. This week, the state voted to overturn that ban and protect access to abortion up to fetal viability. 

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  • Why AI could eat quantum computing’s lunch

    Why AI could eat quantum computing’s lunch

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    There is a caveat: Because the ground states are effectively found through trial and error rather than explicit calculations, they are only approximations. But this is also why the approach could make progress on what has looked like an intractable problem, says Juan Carrasquilla, a researcher at ETH Zurich, and another coauthor on the Science benchmarking paper.

    If you want to precisely track all the interactions in a strongly correlated system, the number of calculations you need to do rises exponentially with the system’s size. But if you’re happy with an answer that is just good enough, there’s plenty of scope for taking shortcuts. 

    “Perhaps there’s no hope to capture it exactly,” says Carrasquilla. “But there’s hope to capture enough information that we capture all the aspects that physicists care about. And if we do that, it’s basically indistinguishable from a true solution.”

    And while strongly correlated systems are generally too hard to simulate classically, there are notable instances where this isn’t the case. That includes some systems that are relevant for modeling high-temperature superconductors, according to a 2023 paper in Nature Communications.

    “Because of the exponential complexity, you can always find problems for which you can’t find a shortcut,” says Frank Noe, research manager at Microsoft Research, who has led much of the company’s work in this area. “But I think the number of systems for which you can’t find a good shortcut will just become much smaller.”

    No magic bullets

    However, Stefanie Czischek, an assistant professor of physics at the University of Ottawa, says it can be hard to predict what problems neural networks can feasibly solve. For some complex systems they do incredibly well, but then on other seemingly simple ones, computational costs balloon unexpectedly. “We don’t really know their limitations,” she says. “No one really knows yet what are the conditions that make it hard to represent systems using these neural networks.”

    Meanwhile, there have also been significant advances in other classical quantum simulation techniques, says Antoine Georges, director of the Center for Computational Quantum Physics at the Flatiron Institute in New York, who also contributed to the recent Science benchmarking paper. “They are all successful in their own right, and they are also very complementary,” he says. “So I don’t think these machine-learning methods are just going to completely put all the other methods out of business.”

    Quantum computers will also have their niche, says Martin Roetteler, senior director of quantum solutions at IonQ, which is developing quantum computers built from trapped ions. While he agrees that classical approaches will likely be sufficient for simulating weakly correlated systems, he’s confident that some large, strongly correlated systems will be beyond their reach. “The exponential is going to bite you,” he says. “There are cases with strongly correlated systems that we cannot treat classically. I’m strongly convinced that that’s the case.”

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  • The Download: What Trump’s victory means for the climate

    The Download: What Trump’s victory means for the climate

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    —James Temple

    Donald Trump’s decisive victory is a stunning setback for the fight against climate change.

    The Republican president-elect’s return to the White House means the US is going to squander precious momentum, unraveling hard-won policy progress that was just beginning to pay off, all for the second time in less than a decade. 

    It comes at a moment when the world can’t afford to waste time, with nations far off track from any emissions trajectories that would keep our ecosystems stable and our communities safe. 

    Trump could push the globe into even more dangerous terrain, by defanging President Joe Biden’s signature climate laws, exacerbating the dangers of heat waves, floods, wildfires, droughts, and famine and increase deaths and disease from air pollution. And this time round, I fear it will be far worse. Read the full story.

    The US is about to make a sharp turn on climate policy

    The past four years have seen the US take climate action seriously, working with the international community and pumping money into solutions. Now, we’re facing a period where things are going to be very different. This is what the next four years will mean for the climate fight. Read the full story.

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