Is the Data on Climate Change More Optimistic than We Thought? With Hannah Ritchie

Summary

Intelligence Squared Podcast Summary

Episode: Is the Data on Climate Change More Optimistic than We Thought?
Guest: Hannah Ritchie
Host: Helen Czersky
Date: September 20, 2025

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Episode Overview

This episode explores whether the data around climate change might be more hopeful than generally believed. Host Helen Czersky invites data scientist and author Hannah Ritchie to discuss her new book, Clearing the Air, which seeks to debunk common climate myths and encourages a nuanced, more optimistic perspective, grounded in current and historical data.

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Key Discussion Points & Insights

1. The Importance of Data Context ([04:00]-[06:05])

• Defining a Data Scientist:
  Hannah Ritchie discusses her transition from environmental science to championing a data-centric approach to global problems.

  “I come into most of these questions… with a very, very data centered focus on like what does the data actually tell us about these problems and their solutions?” – Hannah Ritchie (04:55)

• Data Overload vs. Data Scarcity:
  Surplus of available data can overwhelm, making context essential for understanding what really matters:

  “The issue is often that there's too much data out there or people are kind of awash in numbers… What's often lacking is the context that helps people understand.” – Hannah Ritchie (05:12)

2. From Pessimism to Measured Optimism ([06:06]-[09:07])

• Personal Journey:
  Ritchie shares her original pessimism in the face of overwhelming environmental problems and how deeper data analysis showed real progress over time.
• Progress in Climate Metrics:
  Example: A decade ago, projections suggested a 3.5–4°C warming trajectory; now, it's 2.5–3°C — a shift that's slow but real.

  “…if we can do that in the last decade, why can we not shift from 2 1/2 degrees to 2 degrees?” – Hannah Ritchie (08:21)

3. How Backward-Looking Data Informs Forward Thinking ([09:08]-[11:53])

• Leading vs. Lagging Indicators:
  Developments like the falling cost of renewable energy are leading indicators of more significant future changes.

  “…Costs fall and then people start deploying clean energy and then you eventually start to see it in the CO2 emissions data.” – Hannah Ritchie (10:23)

4. The "50 Questions" Structure: Tackling Popular Myths ([11:54]-[14:06])

• Book Framing:
  Ritchie structures her book around 50 common questions, offering compact, data-driven answers to each.
• Scepticism as Questions:
  Real-life questions often mask deeper scepticism or assumptions that practical solutions are impossible.

5. Addressing Common Climate Myths ([14:07]-[16:31])

• Myth #1 “What about China?”
  UK and other small emitters often use China’s emissions as an excuse for inaction, but collectively, nations under 2% each add up to as much as China’s total.

  “If they all take this approach… then we add up to the same carbon emissions as China.” – Hannah Ritchie (15:15)

• Misconceptions about China:
  Despite building coal plants, China aggressively invests in and exports clean energy technologies.

• Counterintuitive Data:
  Many US states leading in wind energy production are Republican, disproving the assumption that climate solutions are only partisan.

6. Renewables vs Fossil Fuel Costs ([18:07]-[20:14])

• Radically Different Cost Trajectories:

  “…for fossil fuels… there's no clear trend in the cost… It's basically flat. And what we've seen from renewable energy... is very, very different.” – Hannah Ritchie (18:27) Renewables like solar drop dramatically in cost as deployed, now often cheaper than fossil fuels.

• Technological vs. Commodity Approaches:
  Renewables benefit from technological learning curves; fossil fuels are commodities with static pricing.

7. Contextualizing Environmental Risks: Wind Turbines and Birds ([20:14]-[23:22])

• Relative Risks:
  Wind turbines do kill birds, but the scale is minuscule compared to hazards like cats or cars.

  “Cats are really not good for wild birds... We're talking about hundreds, thousands of times lower than… cats.” – Hannah Ritchie (21:41)

• Actionable Responses:
  Emphasizes working to mitigate side effects while rapidly building out renewables.

8. Communicating with the Public: Beyond the Deficit Model ([23:23]-[27:21])

• Why Only Data Isn’t Enough:

  “Data is necessary but not adequate… What really doesn't work is for someone to say something and you to say, no, you're wrong—they automatically shut down.” – Hannah Ritchie (24:33) Acknowledging concerns and building narratives are crucial to changing minds.

• The Power of Storytelling and Visualization:
  Using imagery (even AI-generated) to help people visualize a positive, decarbonized future.

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Notable Quotes & Moments

• Optimism through Contextual Data:

  “We have many of the solutions we already need... but also understand the broader challenge and can ask governments, companies, financial institutions for the right things that move us forward.” – Hannah Ritchie (37:52)

• Electric Vehicle Fires—Debunking Persistent Myths ([28:23]-[30:09]):

  “Electric vehicles come out lower and much, much lower than petrol cars. So they're actually less likely to catch fire, based on the data we have, than petrol cars.” – Hannah Ritchie (29:27)

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Action, Policy, and Future Solutions ([34:36]-[37:36])

• Innovation Stagnation:
  Many companies and actors wait for others to solve hard problems (e.g., in cement, aviation) rather than proactively investing.

  “No one really wants to be the first mover… They want to wait for others to take action.” – Hannah Ritchie (35:40)

• Policy Push:
  Effective government policies (e.g., early solar subsidies in Germany and Spain) catalyze private sector innovation.

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Takeaways for Listeners ([37:36]-[41:40])

• Individual and Systemic Action:

  • Be confident about positive changes you can make (especially in the face of misinformation about EVs, renewables, etc.).
  • Advocate for necessary policies and systemic shifts.

• For Policymakers and Investors:

  • Both are often motivated but need up-to-date, trustworthy information.
  • Public acceptance is essential for policy action.

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Staying Updated & Future Work ([41:41]-[43:20])

• Dynamic Trends:
  Climate data and solutions evolve quickly—always check recency.

• Ongoing Commentary:
  Ritchie's substack “Sustainability by Numbers” provides more current, weekly analysis beyond the book.

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Memorable Quotes with Timestamps

• “The issue is often that there's too much data out there or people are kind of awash in numbers... What's often lacking is the context.” – Hannah Ritchie (05:12)
• “I think what people were often lacking is a very short, digestible answer that tries to bring in data and put context on that.” – Hannah Ritchie (12:39)
• “If you add up all of the countries that are less than 2% of global total… they make up the same amount of emissions as China combined.” – Hannah Ritchie (15:15)
• “Data is necessary but not adequate in order to do this… what really doesn't work is …you say, no, you're wrong, that they automatically shut down.” – Hannah Ritchie (24:33)
• “Electric vehicles come out lower and much, much lower than petrol cars. So they're actually less likely to catch fire…” – Hannah Ritchie (29:27)
• “I want people to actually take it and do something, and that's at an individual level and also a more systemic level.” – Hannah Ritchie (34:58)
• “I'm hoping that people generally feel more optimistic that this problem, this big problem that we're facing is solvable.” – Hannah Ritchie (37:51)

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Timestamps for Major Segments

• 04:00—Defining a data scientist & the challenge of context
• 06:06—Pessimism, optimism, and climate progress in the data
• 09:07—Using past data to project the future, leading & lagging indicators
• 11:54—Why “50 questions”? Structure of Ritchie’s new book
• 14:06—Common myths: China and the UK’s role, partisan surprises in US renewables
• 18:07—Renewable vs. fossil fuel costs, the learning curve
• 20:14—Contextualizing risks: wind turbines vs. cats/cars for birds
• 23:23—Communicating science: deficit model, narrative, and trust
• 28:23—Electric vehicles: fire risks and public perceptions
• 34:36—The importance of action: first-movers, policy, and innovation
• 37:51—How the book aims to change minds and actions
• 41:40—Keeping up with fast-moving data; Ongoing work

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Conclusion

Clearing the Air and this interview frame climate progress as a “slow but real” story of improvement that is often hidden beneath pessimistic news cycles. Ritchie urges both individuals and policymakers to act confidently, armed with accurate data, and provides a vision of hope coupled with actionable advice.

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For more, check out Hannah Ritchie’s Substack “Sustainability by Numbers” and her new book, Clearing the Air.

Transcript

[A]

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[B]

I'm NFL linebacker TJ Watt and this is my personal best. YPB by Abercrombie is the activewear I'm wearing. That's why I reached out to co design their latest drop. I worked with designers to create high performance activewear that holds up to my toughest workouts. Shop YPB by Abercrombie in store, online and in the app. Because your personal best is greater than anything. Welcome to Intelligence Squared, where great minds meet. I'm producer Mia Sorrenti. What if the real story of climate change is far more hopeful than we've been led to believe? With so much doomsday reporting and general misinformation on climate change, it can be hard to know what's true and what actually matters. In this episode, best selling author and data scientist Hannah Ritchie joins us to examine the data on the biggest questions holding us back. Is it too late? Are we too polarized? Will we run out of the resources we need? Speaking to physicist and broadcaster Helen Chersky, Hannah draws on her new book, Clearing the Air to explain that the data paints a surprisingly optimistic picture. Let's join our host Helen Czersky now with more. Welcome to Intelligence Squared I'm Helen Czersky and it's my huge pleasure to be hosting this event today. I think a lot about our planet and how humans fit in with it or don't. And so this is an especially interesting topic for me today because joining me is Hannah Ritchie, who digs into data more generally, but especially on the topics of climate and environment. And she's interested in how much progress we're really making and what we can do next. So, Hannah is a senior researcher in the Program for Global Development at the University of Oxford and deputy editor at the online publication Our World in Data. She's got all sorts of titles. You'll have seen her all over the place. Her research appears in places like the Economist, the New York Times, the Financial Times, on the BBC. And her new book, Clearing the A Hopeful Guide to Solving Climate Change, has just been published. And it's this that we are going to be talking about today. So, Hannah, welcome to Intelligence Squared.

[C]

Thanks very much for having me. It's great to be here.

[B]

Well, I know you discuss data all the time, but I'm interested in starting off with what a data scientist is. I know you have lots of titles and you're hard to label, but what is a data scientist?

[C]

My background is actually in environmental science. My background, I did a degree in environmental geoscience, carbon management. My PhD was focused on the environmental impacts of food systems. I think maybe in the past 10 years or so I've picked up the title alongside that as data scientist. I think that's because I often focus on these topics through the lens of what does the data tell us about this given issue? What does the data tell us about the scale of this problem, the scale of the solution? Would the solution work? How much would it cost? What would the carbon savings be? I come into most of these questions that people have with a very, very data centered focus on like what does the data actually tell us about these problems and their solutions?

[B]

And just, I mean, we live in a world that is saturated with data. It sometimes feels like, but just how, how hard is it to find data on some of these things? Is this data, is it all there and it's just waiting for people to look at it? Is it a bit hard to get at how available is, is the data on these kind of topics?

[C]

I think the, the issue is often that there's too much data out there or people are kind of awash in numbers. And I think the challenge for a lot of people is being able to put those numbers in context. And I think often with the problems that we're talking about, like climate change, for example, the issue we often have is that a lot of the numbers that are out there and are quoted are just big. Right? And that's because human as. As humans, anything that's in the thousands, the millions, the billions, the trillions is just ginormous. I think it's often very hard for us, even myself, to get some sense of, is that big, is that small? Does this matter? Does this matter? So I think the numbers are often out there. I think what's often lacking is the context that helps people understand. Is this expensive? Will this make a difference? And that's kind of what I often try to do, is to put the framing around it, to give comparative examples and compare to other things to help people understand a lot of the numbers that are out there.

[B]

So this book bills itself as a hopeful guide. And I think there's a. There's a really important discussion about sort of pessimism and optimism at the moment when it comes to looking at these big issues, because they can be really big and scary. But I think you started off being a bit depressed about the state of the world, right? And data has been your. Your route to some hope. Tell us a little bit about that.

[C]

Yeah. So, as I said, my background is environmental science. And I think that was always my passion as a child and growing up. And what I wanted to do was to work in this field. But I think gradually, over time, I kind of had that beaten out of me because it just felt like the scale of problems. And here we're not just talking about climate change. There's many other big environmental problems we face are so huge and so overwhelming and we're just making no progress. Was my sense that it felt almost kind of pointless and worthless to actually even work in this, but let alone in my daily life make changes to try and make a difference. And that's shifted a lot over time, I think. One that shifted, I think, for a couple of reasons. One is, as my. On my work as data data scientist and our work around data, we look, yes, at environmental problems, but we look much broader than that. We look at health and poverty and inequality and human development more broadly. And I think what you tend to see in the data there is that we actually have made a lot of progress over the past few centuries. If you look at any human development metric, we've made progress. We're not where we want to be, but we have made substantial progress. I didn't see that before. I think when I was looking at it through the lens of just everything in the world is getting worse and worse. And that's not true. But on the environmental side, things have got worse in many different ways. But I think over the last decade, what I've seen from stepping back to look at the data is that even though we're very far from where we'd want to be, we have made progress in many areas. And actually the trajectory that we might have thought we were on 10 years ago is slowly getting better. And I would highlight slowly, but it is getting better. I think it is that balance of optimism, being able to see that we're not where we want to be and we need to put a lot more work in to get there. But there is optimism there in the sense that we can do it. If we can go from. If I use the example of climate change, a decade ago, we were talking about a trajectory of 3 1/2 to 4 degrees, which is catastrophic. Where we are now is 2 1/2 to 3 degrees, which is not where we'd want to be. But we've shifted a degree in the trajectory. My framing there is, if we can do that in the last decade, why can we not shift from 2 1/2 degrees to 2 degrees? I think that's where this balance comes in, the need for action. But also being able to see that there is stuff that we can do to change this.

[B]

I think data is really clearly, really important. But it's also interesting here because for two reasons. One is we're always told correlation isn't causation. And of course you have to be very careful in that, in data. But the other thing is that data by definition tells us about the past and in some sense we want to talk about the future. So there's always this. Do you find it a weird thing to be sort of backward looking and forward looking at the same time? How do we use the backward looking data to provide optimism for the future?

[C]

It's really difficult. And I think some of this actually separates. I think some of this actually separates what you might frame as the pessimists versus the optimists. Where actually when I look at historical data, I do see that. I do, I do see progress in that data. But I think where a lot of people are today is that they look at the current situation we're in and what's happened over the last five years. So if you say over the last 10 years, global carbon emissions have continued to go up, right? They've slowed down, but they've continued to go up. When People are only looking at, through that lens, at the data, it seems very hard to be optimistic that things could be different in the future. Right. So it is that combination of being able to see past changes, but also the expectation that your future changes will be different from how they are. I think that is just a very hard balance to strike. I think sometimes where I see more optimism in the data than just these very headline numbers like the CO2 emissions is often through this lens of what I would frame as leading and lagging indicators, where stuff has to happen first and then there's a kind of chain reaction and then you see it in the final results of the carbon emissions. So we take the example of clean energy. One of the biggest and most promising changes I've seen is the reduction in the cost of clean energy, where it's now undercutting the cost of fossil fuels. And that's fantastic. And that's happened over the last decade or so. But that takes time and then it takes some time for that to filter through into deployment. So costs fall and then people start deploying clean energy and then you eventually start to see in that in the CO2 emissions data. So where I see most optimism is in these leading indicators. And then the hope is that they then filter through to the lagging indicators, but you have to wait some time to get there.

[B]

I think it's one of the biggest issues here because I find myself living in a world where when I look at the news, for example, there's lots of big negative stories and people feel very negative. And then when I look at my daily life, which admittedly it does involve interviewing a lot of people with new ideas on how to do stuff, there's all these people and there's all this enthusiasm and there's all these sort of technologies and they've not quite got there yet. And it feels like the optimistic view of we can do things and we are doing things is so hidden. And of course we're all trying to change that, but it does feel like there's this kind of hidden corner. It's like there's a cupboard under the stairs where really exciting things are happening and no one ever really looks in the cupboard under the stairs, it's quite hard to see in there, but yes. So I think I completely agree with you on the forward and backward looking things. Now, you deal with this through data. First of all, you framed this book as 50 questions. Why do it like that? You've written another book in the past that didn't have this structure. Why is 50 questions is a good way to approach this.

[C]

This book was kind of inspired from some of the conversations I had after the last book, which is. In the last book, Climate was just one chapter and I could go into some detail there, but I couldn't cover the whole topic in massive amounts of detail. And I realized when I was doing interviews like this or book talks or people on email or social media, is that people had many more questions about how we fix climate change than I could cover. And partly inspired by that. The questions I get all the time, that many, many people have very legitimate questions that people have, but questions that, although they're framed as questions, what they mostly are is skepticism, right? They're often questions like, will we have enough minerals? With the underlying assumption being, no, we won't have enough minerals to switch to clean energy. Or, or won't we won't move into clean energy, require lots more mining than we currently do today, with the underlying assumption being yes, there will be lots and lot mining more than we have today. So lots of these questions came up. And I think what people were often lacking is a very short, digestible answer that tries to bring in data and put context on that. And that's the way I frame the book, is going through 50 of the most common questions I get asked and then trying to offer a relatively short answer on a couple of pages, which was very difficult because I often wanted to go much longer in a couple of pages to give people this ring that they could pick up, go to the one question that, the burning question that they heard that day, or they heard someone say on the news, or they saw this headline about, and try to get more context on what the answer is.

[B]

It's a really. I can see it being a really useful reference book, actually, because you can read this one of two ways. Either as you say, you have a question and then you go to see if the question's answered, or you could read it straight through, but it's almost something that I can see sitting on a shelf. And when you hear, when someone hears a news story or something, they go, oh, I wonder, I wonder what the data on that is. And they can, they can go to your book and find out. I kind of feel bad asking you this because you must have been asked it a lot. But what are the most common myths? There must be things. I mean, you said you get a lot of questions, but there must be two or three or four, perhaps that you get again and again and again and again these sort of sticky ideas in people's heads. That won't shift. What are the top few out of your 50?

[C]

I think the one I probably hear the most and I live in the UK in a country like the UK is actually two in the book that are very much linked. One is what about China? And I think this stems from this notion that what we do in the UK or many other countries that are now a relatively small amount of the world's emissions, so the UK is around 1% of the world's emissions, that what we do doesn't matter. So we just shouldn't try because China just emits nearly all of the world's carbon emissions and it's completely dictated by what they're doing. And they're not interested in clean energy at all. They're just building more and more and more coal plants. I think that is, that is damaging in many ways. One, I don't actually think that's the reality of where China is headed on this and to the fact is that if countries like the UK don't decarbonize and don't play the role, then we're in a really bad position. And what I show in the book is that if you add up all of the countries that are less than 2% of global total, right? So would make this argument that what we do doesn't matter, we're a negligible emitter, they make up the same amount of emissions as China combined, right? So if they all take this approach and say no, it's not our responsibility, then we, we add up to the same carbon emissions as China. So I think that's, that's a particularly damaging one and discourages countries from taking action. And the, the related China part of this is that China is often framed as, at the moment, as this kind of climate paradox where at the same time, yes, they are building new coal plants, but they are going extremely hard on the clean energy transition. 1 In terms of domestic deployment of solar, wind, the rollout of electric vehicles there is extremely, extremely fast. But also in an international market, right? So they are seeing this energy transition as a clear opportunity, whereas in the UK we sometimes see it as this kind of sacrifice that we maybe will have to do. They are clearly saying this is an opportunity. They have huge export markets for one, electric vehicles, batteries, solar panels, one to countries in the global north like Europe or North America. But we're also starting to see is them playing a really big role in exporting solar panels to parts of Africa now where these could, they could adopt these technologies extremely quickly. So I think this notion that China's not interested in not doing anything on climate is wrong.

[B]

One of the things that I picked up that really stuck with me, actually, that. That you wrote on that, is that China might still be building coal power plants, but it's using them less. And I guess that's where a bit of nuance and context comes in, that sometimes the headline number, whatever the headline number might be, doesn't actually tell the whole story. And the things that I like most in here actually were the bits of information that were slightly counterintuitive that just showed that the simple picture is not the most obvious one. And one of them that you talk about quite early on is that the top five states in America, if you sort of list them by the amount of wind power that they use, the top five five states are all Republican, which is not what most people would think. But I find that terribly optimistic because it says that there are other. I mean, maybe they don't care about climate change, but there are clearly other reasons that are pushing them in the same direction. And so there's a richer story to tell. And I really like those bits of. Just like, you know, we all have assumptions about the world, and of course, you challenge these all the time, and they can be very sticky assumptions. Let me pick out a couple of other things that really stuck with me from what you've written here. There was one important point that comes from the data, and it's such an obvious one, that renewables are getting cheaper and fossil fuels aren't. And I thought that was really interesting because nobody ever frames it like that. You see these charts with time and you see that, you know, things are going up and down. You see trajectories, but nobody ever says everything's getting cheaper apart from fossil fuels. Could you just talk a little bit about that and the data behind it?

[C]

Yeah. So I think for me, what's really fundamental about the energy transition is cost. Right. Because as you see, if you come back to the previous point about people wanting to deploy clean energy, whether they care about climate or not, if it's cheaper, people will build it. Even in the scenario where people do care about climate, maybe countries, if it's more expensive, just cannot afford to build the clean stuff. If the fossil fuels are cheaper, at least in the short term, cost is really, really crucial. What you see when you step back and look at the data is that for fossil fuels, even if you extrapolate out a century, the cost of fossil fuels, it fluctuates a lot. Right. We get these, which is also often Quite negative. We get these really rapid spikes and falls in the price. But overall, there's no clear trend in the cost of fossil fuel energy. It's basically flat. And what we've seen from renewable energy technologies is very, very different. They have followed what we would call a learning curve. So what's happened is that as we deploy more of them, we learn how to do it cheaper. And this has this recurring cycle. So every time globally, we've doubled the capacity of solar power. The cost has dropped by around 20%. And this has been very, very consistent. And they have continued to get cheaper and cheaper and cheaper, such that they're now undercutting the cost of fossil fuels per unit of electricity. You have this really, really different trajectory where the cost of renewables has been gone down really, really strongly and fossil fuels has been flat. And now those lines have crossed. And that's a really, really exciting position for us to be in. And I think what that also, I think says really clearly about the energy transition is that this doesn't just apply to fossil fuels. I think this generally applies to stuff and commodities that we dig out the ground. It's really, really hard to get that much, much cheaper. That tends to have a relatively fixed cost. And that's what's the case with fossil fuels and other commodities. What we're moving towards with clean energy is we're moving to technologies rather than commodities. And those do follow, like digital technologies. Those follow learning curves and efficiency curves that you just don't get from digging stuff out the ground.

[B]

It is kind of amazing in so many ways that we are still digging stuff out of the ground for energy. I mean, when you think about it like that, I associate digging stuff out of the ground with what kids in the playground, you know, in the sand pit, do we do with a little spade as a primitive thing. And we're apparently still doing it. Let's just pick up on a couple more examples where the context is really important, because I think sometimes it's hard perhaps for someone reading a news article to immediately think about what the context is. And there's a really good example you provide when you're talking about whether wind turbines kill birds and the relative lethality, I guess, for birds, of wind turbines versus cats, which is not what most people might expect. Just tell us about that.

[C]

Yeah, so I think, I think often some of the issues with the way this stuff is communicated or actually sometimes how it's hard to. I guess you could frame it as a kind of debunking, but some of the challenge there is that many of these questions have some element and seed to truth to them. So it's very, very easy for people to take that one seed and run with it. I think this is a clear example where, yes, wind turbines do kill birds. When people see that, they can then extrapolate that and build it up into some scale, any scale that they would like. And it's very easy for people to believe that that might be the scale that this is happening, which is why numbers are useful to put this in perspective. So, yes, wind turbines kill birds, but if you put this into context of other hazards that wild birds face, and I use kind of approximate numbers from the U.S. it's very, very low on the list. Right top of the list by far is cats, which is sad for me to admit as a cat lover, but yet cats are really not good for wild birds and other wildlife. And here we're talking about order of magnitude difference. We're not talking about a slight 50% lower. We're talking about hundreds, thousands of times lower than the amount of birds killed by cats. Cars are also a big threat. Pesticides, power lines, buildings also kill birds at a higher magnitude than wind turbines do. I mean, that's often why the data is so important, to try to put this into context to people. I think what's also really key here, and I try to do in each of the chapters at the end, there is what we need to do about this. I think what's really key there is that many of the answers to these questions is this particular argument is not a reason for us not to do this. The fact that some birds die from wind turbines is not a reason for us not to switch from fossil fuels to wind power. But crucially, for most of these problems, then they do create problems. Is there something we can do about it to make things better? I provide a whole list of stuff that we can do to reduce the hazards from wind turbines to birds. And I think that's really, really crucial for us to focus on. We need to keep going ahead because we are on a. We're on a tight schedule here with building the stuff and making that shift. But there's tons of stuff that we can do along the way to do it in a more responsible way and to reduce some of the side effects that will come from stuff like building clean energy.

[B]

I'd like to pick up on something about the sort of approach to this because one of the things that. But I think I've certainly seen evidence on this and it was talked a lot about among the people who shared science with the public certainly 10 or 15 years ago, which is what's called the deficit model. And that was a social science term for the idea that if you just tell someone what you know, then they will agree with you. And so people were saying, oh, well, if you just give people the facts, then they're going to believe that, that vaccines are safe or whatever particular argument it is you're referring to. And we know that in general the deficit model doesn't work. Just telling people facts doesn't seem to change minds. But you are clearly doing something that does change minds, that involves telling them, giving people more information. What do you think the difference is there? I'm interested in your perspective on how you see, just giving people information doesn't work, but you're doing something different. Just elaborate for us on what that is.

[C]

Yeah, it's difficult because of, as you say, I think just giving people a ton of information doesn't shift them that dramatically. There are, I think there are a small percentage of people that are maybe very, very open and just make decisions based on data. I think they're quite rare, but I think I often use the frame that data is necessary but not adequate in order to do this. So there is, I think one, one key thing is what really doesn't work is for someone to say something and you to say, no, you're wrong, that they automatically shut down. And it's not that they are then disagreeing with what you're saying, they're just not hearing what you're saying because they're automatically in defensive mode. I think that's a really bad way of going about it if your aim is to actually change someone's mind. I think what's actually quite effective is to be very open and acknowledge the fact that I think often with these questions people are too dismissive that it would be a valid question. And to be clear, I think all of the books and all of the questions in the book that I have been asked are valid questions and people have the right to a good answer. And I think it's really, really important to acknowledge that it's not stupid to be concerned about this. Being concerned about this doesn't make you a climate denier or a bad person or you just have a valid question. I think actually just acknowledging that up front is often useful in building some level of trust with the person that's asking the question and then acknowledging this balance of like, yes, that part of the problem is correct. But let me provide more information to give context like the bird example, just saying that one turbines don't kill birds is one. It's wrong, but it just wouldn't be believable to people because they know that that's incorrect. So I think it is this balance of acknowledging the parts of the half truth that are true and then providing more context for how people should maybe think about this differently. I think the final thing on that is that even then, I don't necessarily think that just data and this type of communication is effective on its own. I think more broadly, a lot of this is about shaping narrative. So it's yes, using data to help answer people's questions. But I think what's also just really key, and I can't necessarily do this, but more broadly, what I think we need to do if we want to shift to clean energy and tackle climate change in the next few decades, is to build a better, compelling narrative to people of what the world would look like in 2050, or pick your end date and present a future that is better than it is today. I think this narrative part is actually where we're maybe not doing that well. And I actually think the other side, if there is other side, which wants to stick with the status quo, has been actually quite effective in building a narrative of keeping us there. So I think this combination of yes, answering questions with data and providing people with information, but presenting kind of inspiring narrative of where we want to go is also crucial.

[B]

I find that's one of the places where I can actually see a use for machine learning, artificial intelligence, generated images. Because I have always thought that the problem is that photographs are also always of the past. But if you could create an AI version of a city and you can put, I don't know, wind turbines in the background and cycle lanes everywhere and all that, people could actually see it, even a picture is much more convincing. And it is one of the biggest problems, I think, that we're not very good at saying that's what the world could look like. And yet we do it with sci.

[C]

Fi all the time.

[B]

And for mobile phones, it wasn't a problem. So there's, you know, it's clearly a complicated issue. Let's pick up on a couple more of sort of interesting bits and pieces. Now, this caught my eye because this is one I hear all the time. And it's about electric vehicles, which obviously have their own. They're a serious sort of subset of the myths around in this kind of world. But the most. The very persistent myth that keeps going is that electric vehicles catch fire more Often than other types of cars. Tell us why that's not right.

[C]

Yeah, it's very common that whenever there is a car fire in the news, all of the outlets rush to say it was an electric car. And usually it transpires it was not an electric car. But this is a very, very common pattern, I think, actually shapes people's perceptions quite a lot. Like it is a myth I hear a lot. And to be clear, again, this was one where I actually just didn't have a clear idea of what the answer was until I looked at the data. And it was actually quite hard to find data on this often because this technology is relatively new. So you don't have really long term data on this. But there are a few countries that have rolled out electric cars very quickly, like Norway, Sweden's doing very well, that do have relatively large data sets on this. And when you break down the data of the number of car fires per 100,000 vehicles in that category. So like petrol, hybrid and then electric vehicles, electric vehicles come out lower and much, much lower than petrol cars. So they're actually less likely to catch fire, based on the data we have, than petrol cars. And I think the perception is that it's the opposite. There are two caveats to that. And one key caveat is that the data we have on this doesn't break down vehicles by age. Right. You would ideally want to compare vehicles of a similar age because older vehicles are typically more likely to catch fire. So I would want to see much longer term data to see do old electric cars also catch fire at similar rates or higher rates? That would be useful context, but I still don't think it would change the overall conclusion that electric vehicles are actually less likely to catch fire than petrol ones. It might just shift the relative magnitude.

[B]

Slightly and it does show how much we just don't question the technologies we have today. There's all kinds of things we do today that kill lots of people, that people have almost stopped noticing and we don't. And of course, fossil fuels themselves kill lots of people. And nobody talks about that being a great, great disaster.

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[C]

Yeah, it's interesting you say that about the progression of the book. I think the way the book is formatted, and I think this is very true of what we need to do to solve climate change overall, is that the early, at least the first half our focus on solutions that we have now are good, now are cheap, now we can go for it, and there's generally very, very clear what the pathway to doing that is. So the answers can be much more concrete as you get towards the latter half of the book. There are industries, sectors, parts of the energy transition that we haven't quite worked out yet. It's still a bit up in the air of what we're going to do with aviation or cement or steel. There are potential solutions there, but there's not a clear winner that we can point to and say, this is to be what it's like in 2050. Which means I had to be much more open on there are a range of opportunities or solutions here, but I don't have the answer on what the concrete one is. So it's interesting that you picked up on this, but on this, like, action question, I think. I think this is really crucial. Like, I didn't write this book, so we can all just keep talking about what we should do. Like, I want people to actually take it and do something, and that's at an individual level and then also a more systemic level. And systemic. I mean, governments, companies, Financial institutions as well. This challenge that no one really wants to be the first mover on this. They want to wait for others to take action. I think really points to often the role and the importance of policy where once a solution has been developed, often markets are quite good at efficiently rolling that out. And I think where we are on solar, for example, I think it's really, really hard to stop solar now. It's so cheap, it's so easy to build, it's so quick that will continue going. But that's not where solar always was. Right. Like, go back 15 years. There had to be a very, very deliberate push by countries like Germany, for example. Spain came to it very early on, where they actually just offered big subsidies to begin with to push and get this technology going. And then from there the costs have dropped dramatically and it's away now. Right. And I think we're in this position with parts of the transition and the sectors that we need to tackle where we're still waiting a bit for that. Either that policy, you could call it a push or a pull, but some forcing mechanism, whether that's subsidy and support, whether that's an actual policy that says you have to do this, or limits on particular aspects that force that change. But I think that is where we are on many of these, or not many. There are a few sectors where we're still waiting for that initial and strong push like we've had for other ones. And I think this is the key matching of strong policy. We've then taken advantage of business competition and innovation and free markets. In some sense, I think that combination is crucial.

[B]

So we're getting towards the end of our time here. What do you want people to. How do you want people to think about the world once they've read this book? What are you hoping will change in people's minds after they've read this book?

[C]

I'm hoping that people generally feel more optimistic that this problem, this big problem that we're facing is solvable. We have many of the solutions we already need. The other ones are in the pipeline, but there's stuff that we can do to accelerate that. And two aspects, one in their individual lives have a better sense of what they can do. Are they doing the right thing? I think a lot of the sparks from people who actually are already making a positive choice, but because of so much noise in the media and public discussion, they're often feeling like they're not doing the right thing. The electric vehicle. There's lots of myths around electric vehicles, and many people have made a positive switch from petrol to electric cars, but they're constantly bombarded with headlines that would tell them that that's wrong choice and it's not actually better for the climate and it's actually worse for this or that. And these headlines are generally wrong. So, one, I would hope that people feel more confident in what it is that they can do to make a difference. But then they also understand the broader challenge and can ask governments, companies, financial institutions for the right things that move us forward. Many governments respond to what the public wants. And if we have a public that thinks that solar panels don't work or wind turbines are bad, then they just won't support the policies that governments would need to put in place to accelerate that. So it's making their own change in their own lives, but also having the confidence to then ask for the right things from other actors in the system that need to move forward.

[B]

And you must be at least occasionally, I guess, talking to policymakers directly about these sorts of things. This, in your previous book, do you find that, I mean, what's their reaction to this sort of information? Are they grateful? Are they surprised? Like, you know, we're talking about individuals reading a book. Of course, everyone's an individual, ultimately. But when this kind of information gets up into the corridors of power, what sort of response do you get?

[C]

So I interact with businesses quite a lot. They get in touch a lot. And then also policymakers, I would generally say, and maybe this is a kind of like behind the scenes optimism thing, as you were saying earlier. Generally I find that a lot of businesses are really motivated and want to be doing the right things, but again, are confused about what they should be doing. Often financial institutions will have money that they can allocate, but they don't know where to put it. They don't know where to put it to make a difference. What needs backing, what doesn't need backing? Is this just a nonsense solution that's not going to make a difference, or is this actually a game? So often I find financial institutions and companies are in some sense motivated, but also need information to make good decisions. And then for policymakers, again, I think they are often in a tough spot where, at least on a personal level, and maybe they could just be saying this to me because they know that I'm interested and concerned about this issue. But they generally seem to be concerned as well and want to be pushing the country in the right direction. But again, are torn because they also need to be publicly popular. That's also just part of their job is that they need to be publicly popular. And if many of the stuff and solutions we're talking about are unpopular with the public, then it's really hard for them to make that decision and invest in that in the long term because they just get constant pushback. So I think that's the general sense that I get from policymakers as well.

[B]

Well, there's lots of optimism in all of that. And just finally, can you, I mean, you are a very busy person. You're doing lots of things. Is there anything that you're working on now or that you want to work on next? Any exciting things coming up that you'd like to share with us?

[C]

I'm very. So I work at our own data, but I'm also like fairly active on substack, where my substack is sustainability by numbers, where I basically do this kind of stuff on a weekly basis. And I think what's interesting about this book, and there's always the challenge with writing books, maybe you're probably also familiar with this, is that stuff changes quickly. And especially many of the stuff that we're talking about here, like technology trends or the price of solar, changes quickly and therefore it's often quite hard to keep up. And also write a book that's for a given time because a couple of years later is out of date. So often I'm writing online on the same topics, but trying to keep up to date with what the latest thing is. And I think that's a really key thing. I also say towards in the conclusion of the book is that that for someone that's trying to see a headline or evaluate a data, a claim or a headline, it's really, really important to look at when that data or that scenario is from, because this stuff changes so quickly. Right. If you're quoting solar prices from 2020, which seems like not that long ago, you're really, really out of date. Right. If you give the example of China. So last year, more than half of of new cars in China were sold were electric. Go back a few years, it was close to zero. Right. So your perception of where China was headed and this transition to electric vehicles overall would be really, really at odds with what the latest data is saying. So I think trying to keep up with the latest data as much as possible is really, really crucial. And that's what I try to do in my broader work.

[B]

Brilliant. Thank you so much for joining us, Hannah. That was Hannah Ritchie, author of Clearing the Air, Here We Go Guide to Climate Change, which is available now both online and in physical bookshops, and I highly recommend it. It is a very optimistic read and you will use it in your discussions with your friends and family for a while to come. I'm sure it's got all kinds of useful information in it. So thank you for joining us. I'm Helen Czersky. You've been listening to Intelligence Squared. Thanks for listening to Intelligence Squared. This episode was produced produced by me, Mia Sorrenti, and it was edited by Mark Roberts.

[C]

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[A]

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Where you got them?

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[C]

Talk soon.

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