The Dirty Energy Powering AI

AI is here to stay, and as global superpowers all plow forward with its development, something has become more and more obvious... 

Powering AI takes energy. A lot of it. And at the moment, much of that energy comes from fossil fuels that create greenhouse gas emissions. 

This puts an enormous amount of pressure on electrical grids around the world and complicates the path we must take towards building cleaner and more sustainable energy systems.

I’m Gabrielle Sierra and this is Why It Matters. Today, will the emergence of AI stall the clean energy transition?

Gabrielle SIERRA: AI has been the topic of conversation for a while now, right? It's dominating discussions about the future of work, the future of creativity and writing, and even the future of the truth as we know it. So here we are, we're talking about AI and the future of our climate. How do those two things overlap?

Varun SIVARAM: Well, we're talking about an AI revolution that could transform our modern economy - and the surge of power demand from the rise of AI, this AI revolution, threatens many of our climate and clean energy goals.

This is Varun Sivaram. He is a senior fellow for energy and climate at CFR and he’s leading our new Climate Realism Initiative.

SIVARAM: AI could transform the way we drive by enabling autonomous vehicles. It could transform the way we work by automating or transforming various types of work, such as the legal profession or the medical profession. But AI also comes with a dark underbelly. In order to run the computers that power AI training, the training of these models or the use of these models, known as AI inference, you have to supply power to these computers, these servers, and that power can be very dirty.

Coal, oil, and natural gas, which have a huge carbon impact, are the primary fuel used to power AI. And currently the United States, China, India, and the EU, which account for nearly 60 percent of the world’s emissions, are the top four leaders in artificial intelligence development.

None of this is to say that ambitions about clean energy haven’t been discussed at length. But there has been limited progress on how to handle the energy transition. At last year’s annual UN Climate Summit known as COP, countries promised to move away from using fossil fuels. But this year, the world burned more than ever before.

SIERRA: In relation to all the things that are bad for our climate right now, where does this fall on the scary meter, if you will?

SIVARAM: That's such a good question. Look, I've spent my whole career the last 15 years in the energy and climate industry and in public policy trying to tackle what I fear is the existential threat from climate change. And to solve that threat, I think we'll need to bring the world to net-zero emissions. There are a lot of large and concentrated sources of emissions. These include the aviation industry, shipping, steel making, cement making, the global power sector, and many more. I am very fearful that AI, data centers broadly, but AI in particular, which have typically been off our radar because these servers and chips have become more efficient over time and therefore we've never really had to worry about them, I'm very worried that AI can become one of the largest, if not the largest, consumers of energy around the world, surpassing sectors, such as aviation and shipping and some heavy industries. If that happens, and it's not going to happen in the next five years, but it could happen in the decades to come  as AI becomes the linchpin of the modern economy, then if we don't solve AI's climate impact, we have no chance of solving the overall climate challenge.

SIERRA: I feel your answer to this question actually ties directly into how you are viewing the overall climate challenge as part of your work with us at CFR, so maybe let’s touch on that right now. Can you tell me about this idea of ‘climate realism?’

SIVARAM: I think we're long overdue for a middle of the road pragmatic, clear eyed approach to climate and the clean energy transition that advances American national interests. And I think it's as relevant now under a President Trump administration as it was under a President Biden administration. It comes from recognizing three hard realities. The hard reality number one is that climate change poses a severe and maybe existential threat to American security, and we haven't been taking it that seriously in the foreign policy establishment. 

https://www.youtube.com/watch?v=92aG0u5pMFs 

DW News: The air in much of the U.S. northeast has turned into thick red smog from hundreds of wildfires...

https://youtu.be/bmYPfZHLVmQ?feature=shared&t=135  

John Kennedy: ...And I hope they do it, okay, if it turns out that the scientists are right. I’m not saying they are or they aren't, it’s just that the whole topic has become so politicized.

https://www.youtube.com/live/GWwiU085inU?feature=shared&t=9 

Fox 26 Houston: We are watching an incredible hurricane, by the name of Milton...it is unbelievable how quickly this storm strengthened.

SIVARAM: Climate change poses as much of a risk by the end of the century to America and its existence as nuclear warfare. By the end of the century, American cities could be wiped off the map if we reach some of the catastrophic levels of sea level rise, seven feet or more, that are potentially projected. And moreover, climate change will bring an increasing and intensifying drumbeat of hurricanes, wildfires, droughts, and heat waves. We should care just as much or more about climate change affecting the American homeland and our security and our economic prosperity as we do about Russia invading Ukraine, China invading Taiwan, or war in the Middle East and nuclear proliferation in North Korea or Iran. Climate is a real foreign policy issue, and we better take it seriously. The second hard reality is recognizing that the clean energy transition poses both opportunities and risks for the United States. 

https://youtu.be/GjHKYzPNBdI?feature=shared&t=53 

CBS Evening News: In the past three years, more than $90 billion in battery investments have been announced nationwide, creating an estimated of 70,000 manufacturing jobs.

https://youtu.be/TYuiRwFzwmk?feature=shared&t=149  

CBS News: The industry is changing. And what that means is for shops like an AutoZone or an O'Reilly's, those shops may not exist anymore. They may have a lot of trouble...

SIVARAM: It may be the largest wealth creation opportunity in history rivaled only by the AI revolution that we're talking about today. It's a multi-trillion dollar wealth creation opportunity, but it carries risks. Today, China is in pole position on the clean energy transition. It leads the world in electric vehicle, solar and battery production. The United States is dangerously behind. And the United States has a lot to lose. We're the world's largest hydrocarbon producer, and we gain economic prosperity through our oil and gas industry, and we gain geopolitical leverage abroad with our partners, allies, and trading partners. Therefore, if the United States is not globally competitive in the clean energy transition, a clean energy transition could bring some climate benefits to America, but geopolitical and economic disadvantages in our competition with China. And the third hard reality is that we do need to recognize that the world is nowhere near solving climate change and reaching its climate targets. 

https://www.youtube.com/live/m4uUVWTdg3A?feature=shared&t=2181 

Simonas Gentvilas: Over the last decade, every corner of the globe has been affected by the destructive consequences of climate change, and yet today, despite all the warning signs, the global community is far from reaching the goals of the Paris Agreement.

https://youtu.be/EExG3tqiozo?si=dlIEBMixjqmKTOUX 

AP Archive: The petrostate of Azerbaijan is hosting this year's UN Climate conference, called COP29. Environmentalists say that being an oil country should disqualify it from hosting a conference focused on moving away from fossil fuels like gasoline, coal, and natural gas.

SIVARAM: I can say with virtual certainty that the world will blow past the 1.5 degree global warming threshold that we are aiming to stay below, and likely the two degree threshold. We may very well be headed for more than three degrees of global warming, and that could lead to some very difficult outcomes, catastrophic outcomes potentially. The United States, therefore, recognizing that there is inevitable and unavoidable climate change, needs to be prepared to harden our resilience at home, prepare for conflict abroad, prepare for the geopolitical shifts as, for example, sea lanes and shipping lanes in the Arctic open up, and prepare to potentially engage in, or engage with, these extreme geoengineering approaches where the United States or countries around the world will try and directly engineer the world's climate. These are serious things we need to contend with in a clear eyed and realistic way, and that's what climate realism is all about. Averting catastrophic climate change requires us to solve the AI and clean energy puzzle. 

From space mirrors that bounce sunlight back into the sky to machines that pull carbon out of the air, scientists speculate these geoengineering projects may be our best shot to mitigate the effects of global warming and climate change. It is fascinating stuff and, unfortunately, we don’t have time to get into it today but lucky for you we did a whole episode on it so, if you are interested, take a look in our feed. It’s called “Dimming the Sky.” 

SIVARAM: Right now, AI really doesn't matter that much for global emissions. Between now and 2030, just in the near term time horizon, despite AI's growth, heavy industry, electric vehicles, and space cooling—air conditioning—are all going to grow in their power demand more than AI will. But it's because AI is growing from such a small base. Beyond 2030, if AI really does take off, AI power demand globally could just begin to take over the grid. And that's already started to happen in some of the pioneer markets where data centers are particularly heavy, such as in Ireland and increasingly in the United States.

What even is a data center? Well, a data center is a physical location where a network of computing machines and their hardware are stored. And these data centers are extremely energy-intensive, consuming 10 to 50 times the power of a typical commercial office building. As of March 2024, there are more than 11,000 data centers worldwide, 45 percent of which are housed in the United States - and this has been creating some problems for American consumers.

Let’s look at one example. In Texas and Northern Virginia, for example, where electricity shortages are routine, Americans are already seeing the surging demand for power affect their wallets. Dominion Energy announced that Virginians should expect energy bills to increase 50 percent by 2039, and by that time, the state anticipates a 100 percent increase in electricity usage. 

These energy costs are also being felt around the country as tech companies like Meta, Google, Apple, Amazon, and Microsoft all hunt for new sites to build more data centers.

SIERRA: So where are we at now? How much power does AI in its data centers use now, and how much could it be taking up in, let's say, you know, the next five years as we ramp up with all this AI?

SIVARAM: Well, today in the United States, data centers, overall as a category, consume about 4 percent of American power and around the world that number is even smaller. It's between 1 and 2 percent globally. And AI is still a very small proportion of overall data center use. Data centers, the cloud, for example, are used for all kinds of operations. Your PayPal transaction runs through the cloud, but AI, which includes training these large language models, fine-tuning them, or customizing them for particular applications, and then using them or applying inference on these models, these are increasingly a large and growing source of power that the projections show could become a majority of data center use over the next couple decades. So, today, if we're at 4 percent in the United States for data centers overall, by the end of the decade, 2030—just five and a half years away—we are looking at anywhere from 10 percent to 12 percent of the American grid. And that's even as the overall American consumption grows. So AI is growing even faster. Data centers overall today account for about 25 gigawatts of demand, but as we get closer to that 10 percent or 12 percent of the American grid percentage by 2030, they could consume up to 80 gigawatts of demand.

1 gigawatt of energy is equal to approximately 2.5 million solar panels and is enough energy to power around 750,000 homes.

So, yeah, that’s a lot of power...

SIERRA: Okay, hold on. I assume that self-driving cars, there's problems there, but are you telling me that the mechanics behind AI mean like every time I ask ChatGPT a question, I'm actually, like, somehow hurting the environment?

SIVARAM: In a very small way, yes. Every time you ask ChatGPT a question, a server, somewhere in the United States likely, has to run your query, the question you've asked it, through a large language model, an LLM, and the servers that run that query are consuming electricity. Now, the difference between this sort of query and a traditional query—the ChatGPT query can use 100 times or more energy per query than the simple Google search. These are much more power intensive operations. And it's also extremely power intensive to train the ChatGPT model or any other large language model for that matter to begin with, such that that model is appropriately tuned to answer your questions in an intelligible way.

SIERRA: This seems like a pretty big problem when you're developing AI. Was this known when it was created and it just wasn't seen as an issue?

SIVARAM: For the last several decades, we have heard alarmist calls that ICT, or information and communication technologies, would consume so much electricity that they would take over the grid. And, for almost uniformly over the last several decades, this has been proven false over and over again. And the reason for this is even as the computing demands of various kinds of information, computing technologies, cellular networks, laptops, the internet, cloud computing, even as these have risen dramatically, the efficiency of the servers that process the requests in the data centers has improved over time in a corresponding way. And so for about a decade now, we've had about a flat line American consumption for data centers. Data centers have consumed the same amount of power. They've roughly been around somewhere 2 percent to 4 percent. Now, however, we've hit a wall. The reason for this, by the way, is AI uses fundamentally different hardware than traditional computing does. The most in vogue type or semiconductor chip that does these computing operations is known as a graphics processing unit, a GPU. Nvidia, which has just become the world's most valuable company, is the main producer of these GPUs. Just to give you some numbers on how power intensive AI is, typically a rack of servers, which is basically a bunch of computers stacked on top of one another, might use a power consumption level of 10 kilowatts, typically in a data center. Now, in comparison to those conventional data centers, a rack that's equipped for AI processing using these graphics processing units might use 10 times as much power, 100 or more kilowatts. That means that data centers are becoming much larger. They're no longer 10 to 40 megawatts. They can be in excess of 1 gigawatt or 1,000 megawatts. That's as large as the output of a nuclear power plant.

SIERRA: Varun, why is everything that we think is going to be good for us actually really bad for the environment?

SIVARAM: Let me be clear, I don't believe that the story is written yet on whether AI will be a net positive or net negative for the environment. First of all, I think we have a real chance of powering AI with clean energy. But second, AI could also have a transformative impact on how we tackle climate change. Thanks to AI, we may be able to develop groundbreaking new materials at a much faster pace, materials that can help us make far more efficient and cost-effective batteries, or far more efficient solar panels, or transform the way that we produce industrial materials. AI can help us to optimize our energy systems to be much more efficient, such as our electricity grids. The ultimate uses of AI may overwhelm the dirty energy that powers them. And the best of all possible outcomes is if we get the benefits of AI to enable us to tackle climate and also avoid the disadvantages of fossil fuels powering AI if we can actually use clean energy sources that are both affordable and reliable. 

Even though AI is not powered by clean energy just yet, the application of AI by certain tech companies is already helping scientists track the impacts of climate pollution and global warming around the world.

An AI model from the University of Leeds has been trained to measure changes in icebergs 10,000 times faster than humans can. Space Intelligence, a tech company based in Scotland, is mapping deforestation in more than 30 countries. And in the Netherlands, the Ocean Cleanup Project’s AI model uses currents to predict where garbage hotspots are in the Pacific, allowing for more efficient trash collection and removal. Even right here in the United States, NASA is working with IBM Research and NVIDIA to create an AI powered ‘digital twin’ of Earth that would allow for the prediction of all kinds of climate and weather events.

SIVARAM: The goal in the United States should not be to constrain economic growth, and it shouldn't be to constrain innovation. It should be to enable our consumers to achieve the maximum benefit out of a revolutionary technology. What should the government focus on therefore? It should focus on making it possible for more AI to be connected to what is abundant energy availability in the United States. It should focus on building out electricity grid infrastructure and making it easier to permit these transmission and distribution lines. And it should focus on making it much easier for clean and abundant renewable energy to be connected to the growing rise of data centers. Ideally, data centers will be powered by an all-of-the-above energy strategy, but much of it will be clean, whether renewable energy from solar, wind, and geothermal and hydro, or nuclear energy and even natural gas-powered power plants. American policymakers are thinking right now about the future trajectory that AI will take, and there is a fairly unified conclusion, and I think it's sensible. America needs to be the world leader in AI. We already are, and we need to maintain that competitive edge. And that means we need to build out AI computing resources as fast as possible. We need to do that in order to compete with China. China is building AI data centers also at a breakneck pace, and they are not limited by the available power resources. They're actually limited by the availability of high-end chips, which America has some export controls over and is considering even more export controls, for example, on NVIDIA GPUs. But the United States is not constrained as much by semiconductors and chips. We are constrained by power.

Over the past two years, China has spent over $6 billion building data centers and is on track to develop a centralized data center by 2025. This so-called ‘East-to-West’ project reflects China’s motivation to grow its AI and data processing infrastructure while at the same time equally distribute key energy resources. And, as of this year, China has invited foreign investors to operate new data centers in the country, completely reforming its closed-door industrial policy and giving it an edge in the technology competition.

SIVARAM: Today, for example, in the part of the United States with the largest concentration of data centers, right here in Northern Virginia, the power utility locally, Dominion Energy, says that it'll take more than seven years to connect the next data center of 100 megawatts or more to the grid. That's an intolerable time horizon for cloud service providers or model developers, OpenAI or lesser-known companies that are developing next-generation models. That's not tolerable for them to meet their innovation objectives, and it's not tolerable for the United States to keep our competitive edge. And that's true not just here in Northern Virginia, it's increasingly true across the country in major data center markets, whether you're in Phoenix or San Antonio or Chicago or Silicon Valley. Therefore, connecting new data centers to the grid and powering them with affordable, reliable energy is the number one policy goal. And the Trump administration and the outgoing Biden administration share this goal. The Biden administration has published documents explaining that it's both important to power AI and to make sure we do it with clean energy. The Trump administration has come out in its early cabinet appointments and made it clear that what they call the AI arms race with China is a top priority, and one of the reasons that they're creating the National Energy Council. 

https://youtu.be/xrFdHO7FH8w?feature=shared&t=2931  

Logan Paul Podcast: It’s going to happen, and if it’s going to happen, we need to take the lead over China. China is the primary threat.

SIVARAM: Now, the Trump administration has displayed absolutely no interest in making sure that the power that powers data centers is clean, but nevertheless, they're very interested in making sure that it's available, and that's what I expect the new National Energy Council to focus heavily on.

SIERRA: Why is the U.S. so caught up in the clean energy and emerging tech competition with China?

SIVARAM: China has a real advantage over the United States in that it has invested heavily in its energy infrastructure and, importantly, in its clean energy infrastructure. China, therefore, has a surfeit of power and land, and the price of power in China has been steadily approaching the rock bottom prices that American industrial producers pay for power. For decades, America has had an advantage over China. Our industrial producers in many parts of the United States have access to very cheap energy. For example, from our bounteous natural gas to our hydropower resources in parts of the United States. Increasingly, China now is using rock bottom-priced solar and wind resources alongside its large coal power plant capacity to drive down prices for industrial producers of products. As a result, China comes in with some inbuilt advantages in the AI race. It can power as many data centers as it needs to. In order to compete with China, the United States needs to find new sources of power, invest in our energy infrastructure, and make it possible to connect data centers much faster and have them powered with affordable and reliable energy.

China dominates global solar manufacturing at all stages of the process, with over 80 percent market share. Currently, China is building twice as much wind and solar as the rest of the world combined, producing panels that cost as little as $0.10 per watt, less than half the price of U.S. manufacturers.

SIVARAM: There was a potential deal where Amazon was going to use an existing nuclear power plant's output to power its data center, however, the Federal Energy Regulatory Commission ruled that this sort of arrangement would impose costs on the rest of the network because this nuclear reactor would now be taken out of commission for serving ordinary households and instead just be serving a data center, creating new costs for new supply and infrastructure for the rest of the grid. Recently, there was a $50 billion deal that was announced between Energy Capital Partners and KKR to invest in new energy supplies for data centers. Almost all of it is likely to be natural gas-based. And so therefore, it's increasingly clear that if we proceed on a business as usual trajectory, the surge in AI demand, under a very supportive Trump administration for fossil fuels, is going to be powered by sources such as natural gas. That won't be great for our efforts to tackle climate warming emissions from fossil fuels and to avert the worst effects of climate change.

SIERRA: So I wonder about our immediate future. What should we expect to see from the incoming administration?

SIVARAM: Well, look, I don't expect the Trump administration to try and solve the climate impact of data centers head-on. They've made it very clear that that's unimportant to them. But I do believe that there's a bipartisan consensus on three things. First, that America needs to compete with China, and therefore, to keep our competitive edge in AI, in which we've leap out to a lead, we will need to connect many more data centers and make sure that they're well supplied with energy. I think that that was a priority under President Biden, and that will continue to be a priority under President Trump with his new National Energy Council. The second is that there's a bipartisan consensus on bringing new technologies, innovative technologies, to the market. The Trump administration with its choice of Governor Doug Burgum to lead the National Energy Council and Energy Secretary Designate Chris Wright, is bringing on energy professionals who do have experience in innovative energy technologies, whether it's shale gas fracking technologies, or next generation geothermal, or a true appreciation for next generation nuclear. And the third area that there is a bipartisan consensus on is that we may need to reform the way that we operate our electricity grid, that we permit new transmission lines, that we ease up on environmental reviews that can be painstaking in order to bring on both oil and gas infrastructure like pipelines, but also electricity infrastructure like transmission and distribution lines. 

Many of these infrastructure updates are sorely needed for issues even beyond powering AI. 70 percent of our transmission lines are over 25 years old and approaching the end of their typical 50 to 80-year lifecycle. This has major consequences on our communities: power outages, susceptibility to cyber-attacks, and community emergencies caused by faulty grid infrastructure. 

SIVARAM: And by changing the way we operate both the electricity grid and data centers to be more flexible, we really have an ability to use our existing infrastructure, the U.S. Electric Power System, which is an engineering marvel and may be the most important invention of the 20th century, to power the surge of data centers even without building out all of these expensive and next generation technology categories.

SIERRA: So if there's a will, there's a way you're saying?

SIVARAM: I think there is a will and a way, and a bipartisan way, to make sure America remains competitive in AI. I only hope that we can do this in a way that does not torpedo our climate goals.

SIERRA: So what can we do to make the energy powering data centers clean?

SIVARAM: Look, the way data centers have historically operated is they require on-demand power, power that's available whenever they need it. If they need to ramp up a bunch of GPUs to start a training run, the power needs to be available right that second, and the grid may get a very unexpected request that it needs to provide a ton of surge capacity power. And so in order to supply this kind of power that is clean but also on-demand that, the United States could invest in next generation clean technologies, these include advanced nuclear power, advanced geothermal technologies, or even an existing technology, hydropower. Very difficult to permit, but very well understood from the technology side. The second approach is to say, "Instead of trying to power AI through the grid, let's just go off grid.” Not worry about the fact that often the grid is at capacity and it's difficult to build and permit new transmission and distribution lines. This could include a lot of batteries, a microgrid, and potentially a natural gas turbine equipped with carbon capture. Of course, making energy clean is expensive if you're going to do it in this configuration. And so CCUS, carbon capture utilization sequestration, makes that natural gas turbine even more expensive. The third thing that we can do is really invest heavily in our electricity grid. Today, our electricity grid is struggling to interconnect new data centers. But if the United States were to streamline its permitting processes, then we could build transmission lines much faster, and in doing so, make it much more feasible to connect data centers to the grid in fewer than seven years.

Demand—especially from new data centers and the proliferation of electric vehicles—is expected to require the nation’s grid to expand by anywhere from a third to more than double its current capacity in the next decade. The U.S. has put forward a few proposals to meet this demand, the largest being the Department of Energy’s Grid Resilience and Innovation Partnerships Program which allotted nearly $3.5 billion for over 55 projects across 44 states to strengthen electric grid resilience and reliability.

SIVARAM: And then the fourth strategy, which is really just emerging, but which I personally find to be the most exciting of these strategies, is something called data center flexibility. The advisory board for the U.S. Secretary of Energy released a report this summer arguing that this could be a critical way to power data centers, even with the existing limitations of the grid and our power supplies. Because the electricity grid today is only 33 percent utilized, we could better utilize that if our data centers could more controllably change the power demand that they had. In addition, a series of entities, including Nvidia, Microsoft, Google, and major power utilities in the United States, signed up with the Electric Power Research Institute recently just last month for something called the Data Center Flexibility Initiative, DCFlex. I think if data centers can develop this capability, it can really enable us to connect more data centers and use our existing infrastructure better, and also line up data center demand with renewable energy. Renewables, remember, are the cheapest and fastest growing power source in the United States and around the world. As a result, renewable energy could be the fastest and cleanest way to power data centers if we could achieve just a little bit of data center flexibility.

SIERRA: So speaking of our climate goals, a big surprise for all of our Why It Matters listeners, and a very exciting announcement that the next season of Why It Matters will actually be a series focused on our climate. Throughout the season, we will be using climate realism as a tool to explore different topics from nuclear energy, to the industrial policy war with China. I wonder, Varun, not to put you on the spot, but can you give us a rundown of maybe what you're excited to discuss in this climate-centered season of Why It Matters?

SIVARAM: I'm really excited to discuss how the United States can navigate a world that is suffering from the unavoidable, inevitable impacts of the climate change that we can't solve. That includes both the geopolitical impacts of the changing climate, increased migration flows, the opening Arctic, as well as the industrial competition between major powers on the next generation of technologies. The second key question is how America can best compete. This includes how we can compete in the technologies of the clean energy revolution with China, for example: can America invent and mass produce the next generation solid-state battery that's going to be in every electric vehicle a decade from now? Or are we going to cede the battery space and many other spaces to China, which already is dominant? And the third question is, what can America do to reduce the world's emissions, or to avert the most catastrophic impacts of climate change? Again, there's not a whole lot the United States can do at home because our emissions don't matter that much. It's a small and declining share of the world's total. But through innovation, America can develop technologies that the rest of the world can benefit from to speed up their energy transitions. And America can develop policy learnings from policies that we try out at home that an India, or an Indonesia, or a China, or a South Africa can learn from. America can begin to prepare for some of the interventions like reflecting solar radiation back into the atmosphere. Or sequestering carbon from the atmosphere within the oceans, that can help us to put an emergency brake on the most catastrophic effects of climate change. Some amount of climate change, 2, maybe 3 degrees global warming is inevitable and unavoidable, but to avert the absolute worst effects of climate change, the things that could existentially threaten America's existence. The United States will be forced to confront the need for geoengineering. Those are all topics that I'm really excited to talk about in this next season of Why It Matters.

SIERRA: I'm excited to hear all about them. 

SIVARAM: Thanks so much for having me!

The team at Why It Matters is going to start production on our climate-focused season. We’re so excited, and it’s set to launch in the new year! In the meantime, be sure to check out CFR’s other podcasts to keep you in the loop until we return. Happy holidays and thank you for continuing to tune into the show - it means so much to us. And we will see you in 2025. 

For resources used in this episode and more information, visit CFR.org/whyitmatters and take a look at the show notes. If you ever have any questions or suggestions or just want to chat with us, email at [email protected] or you can hit us up on X at @CFR_org.

Why It Matters is a production of the Council on Foreign Relations. The opinions expressed on the show are solely that of the guests, not of CFR, which takes no institutional positions on matters of policy.

This episode was produced by Molly McAnany, and me, Gabrielle Sierra. Our sound designer is Markus Zakaria. Our interns this semester are Colette Yamashita Holcomb and Emily Hu. Robert McMahon is our Managing Editor. Extra help for this episode was provided by Clara Fong and Mariel Ferragamo. Our theme music is composed by Ceiri Torjussen.

You can subscribe to the show on Apple Podcasts, Spotify, YouTube or wherever you get your audio. For Why It Matters, this is Gabrielle Sierra signing off. See you soon!