How to make AI a force for good in climate | Amen Ra Mashariki and Manoush Zomorodi

Summary

Podcast Summary: How to Make AI a Force for Good in Climate

Podcast: TED Talks Daily
Host: Manoush Zomorodi (TED Radio Hour)
Guest: Amen Ra Mashariki (Director, AI at Bezos Earth Fund)
Date: December 19, 2025
Duration (approx. content): 04:02 - 14:54

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Overview:

This TED Talks Daily episode features an engaging interview between Manoush Zomorodi and Amen Ra Mashariki, director of AI for the Bezos Earth Fund. Together, they explore how artificial intelligence can become a transformative force in addressing climate and nature challenges. Mashariki shares insights on the Fund’s approach to leveraging AI for climate solutions, discusses real-world examples and future milestones, and directly addresses concerns about AI’s environmental impact.

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Key Discussion Points & Insights

1. Mashariki’s Journey and Approach at the Bezos Earth Fund

• Background: Mashariki describes his path from dedicated computer science researcher to someone driven by a desire for impact, focusing on real-world problem solving.
  • “I was one of those computer scientists that believed in computer science, you know, algorithm optimization. Through a couple of personal things that took place, I realized that that was only a mechanism by which I could do other things which is have an impact.” (04:21)
• Problem-first Mindset: At the Bezos Earth Fund, the team starts with understanding the climate problem first, then seeks out AI-enabled solutions – as opposed to being “AI in search of a problem.”
  • “At the Bezos Earth Fund, we think about starting with the problem first and understanding that problem and then looking for ways to use modern AI in order to scale solutions in that space.” (05:11)

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2. Inventions vs. Discoveries: The Fund's Mental Model

• Inventions vs. Discoveries: Mashariki outlines a framework where inventions are tools (e.g., a telescope), while discoveries are the breakthroughs enabled by those tools (e.g., seeing Jupiter’s moons).
  • “A telescope is an invention. Looking through the telescope to notice that Jupiter has moons is the discovery.” (05:48)
• Strategy: They fund projects that combine groundbreaking inventions (“grand innovations”) that then lead to transformative discoveries in climate and nature.

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3. State of AI in Climate Solutions

• Current Capabilities vs. Aspirations:
  • Today’s AI often provides “an average of reality”—it synthesizes known data well but rarely invents truly novel ideas.
  • Cites AlphaGo’s “Move 37” as a symbol of counterintuitive, creative AI:
    • “Move 37 was this view into how AI can be creative and actually come up with a move that no one has ever thought of.” (07:18)
• Aspirational Goal: Achieve “Move 37” moments in climate science, where AI proposes restoration solutions that even leading experts have not considered.

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4. Real-World Example: Meta, Dyno V3, and WRI Partnership

• Project Highlighted:
  • Meta’s Dyno V3 (a computer vision AI) + WRI’s restoration work has enabled tracking of tree growth via satellite with 80% accuracy of expensive field surveys, but at just 3% of the cost.
    • “You could actually track the growth of trees to an 80% accuracy of field surveys at 3% of the cost... you can actually unlock performance based financing with this technology.” (08:26)
• Impact: Technology unlocks new financial models for large-scale, data-driven restoration efforts.

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5. Trust, Accessibility, and Timeline

• Milestones for Widespread Adoption:
  • Experts and the public must both trust and be able to use new AI tools.
  • There’s no firm timeline: “Anyone who gives you an exact number, doesn’t know the number, how long it’s going to take, but that’s where we have to get to...” (09:56)

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6. Addressing AI’s Environmental Costs and Potential Greenwashing

• Acknowledgement of Dual Impact:
  • Mashariki is candid that AI can contribute to environmental problems, but maintains a belief that “on balance, AI is going to be a tool and a force for good and a tool and a force for saving the planet.” (10:51)
  • The Fund supports solutions to mitigate AI’s environmental costs, working with a broad coalition of companies, NGOs, academia, and governments.

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7. Concrete Environmental Milestones and Solutions

• Transparency & Measurement:
  • Need for accurate, universally agreed data on AI’s actual environmental impact (e.g., energy and water use):
    • “We need to begin to do is to have precise accuracy and understanding of exactly the impact that AI is having on our environment and a shared understanding across the board...” (12:06)
• Technological Response:
  • The industry is shifting towards more efficient hardware—cooling at the chip level to reduce water waste is cited as a key example.

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8. Hope and Urgency: The “Consequential Meets Decisive Decade”

• Sense of Purpose: Mashariki articulates the present as a unique convergence of technological innovation and urgent climate action:
  • “We believe that we are in a space where the consequential decade meets the decisive decade... These are the things that are going to decide what impact AI has on the global community.” (13:45)
  • He calls for “all hands on deck,” positioning the Bezos Earth Fund as a leader bridging AI and climate communities.

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Memorable Quotes

• On AI’s Tipping Point:
  • “We really want to get to a place where in climate and nature, AI is actually offering solutions, creative solutions that even the world’s greatest experts find counterintuitive, but are actually really powerful.” — Amen Ra Mashariki (07:25)
• On Building Trust & Access:
  • “There has to be a mechanism by which everyday people who are living their lives, who are living in these regions that we’re concerned about, who are doing the work on the ground, can trust and use these tools as well.” — Amen Ra Mashariki (09:58)
• On Environmental Impact Transparency:
  • “Precise accuracy and understanding of exactly the impact that AI is having on our environment and a shared understanding across the board...” — Amen Ra Mashariki (12:06)
• On Urgency:
  • “We are in a space where the consequential decade meets the decisive decade. It has to be all hands on deck...” — Amen Ra Mashariki (13:45)

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Important Timestamps

• Amen Ra Mashariki’s path to the Bezos Earth Fund: 04:09 - 05:27
• Inventions vs. Discoveries mental model: 05:39 - 06:22
• Current state and future aspiration for AI (“Move 37” analogy): 06:39 - 08:03
• Meta/WRI AI restoration project: 08:08 - 09:46
• Building trust in AI for climate: 09:46 - 10:30
• AI’s dual environmental impact and greenwashing concerns: 10:30 - 11:37
• Environmental milestones, need for measurement: 11:49 - 13:26
• Mashariki’s hope and the gravity of the present moment: 13:42 - 14:49

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Conclusion

Amen Ra Mashariki and Manoush Zomorodi deliver a nuanced, forward-looking conversation about making AI a genuine force for good amid the climate crisis. Highlighting a problem-first approach, a strategic framework for funding, and concrete milestones for trust, measurement, and innovation, Mashariki remains realistic yet optimistic about both the challenges and opportunities ahead. His conviction that this is where the “consequential” and “decisive” decades merge drives home the urgency—and the promise—of using AI wisely in service of the planet.

Transcript

[Elise Hu]

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[Elise Hu]

This episode is brought to you by Cargurus. You know, sometimes I think about how good design solves real problems. And car shopping? That's a problem that desperately needs better design. The uncertainty of buying a car can be exhausting. Is this price fair? Is there a better deal two clicks away? You shouldn't need a detective's intuition to feel confident about a major purchase. That's where Cargurus comes in. They've redesigned the entire experience, ensuring a transparent and hassle free buying process with more car listings than any other major online automotive marketplace in the US you can actually compare and find the best deal. Real data driven ratings, price drop alerts, verified dealers. It removes the confusion from the equation. It's no wonder similar web estimated traffic data shows Cargurus is the number one most visited car shopping site. Buy or sell your next car today with [e-mail] Go to CarGurus.com to make sure your big deal is the best deal. That's C-A R G U R U S.com CarGurus.com. You're listening to TED Talks Daily where we bring you new ideas to spark your curiosity every day. I'm your host Elise Hu. I'm still amazed by the ridiculously fast pace at which technology and AI is growing. But what are some ways that AI might be used for climate and nature solutions? Today, Manouch Zomorodi, who hosts the TED Radio Hour, sits down with AI changemaker Amen Ra Mashariki to discuss what he thinks truly game changing climate ideas might look like and how a guy is playing an increasingly large role in that space. Space.

[Manouch Zomorodi]

Okay, so tell us the story of how you got to be working with Bezos, your sort of trajectory to being here.

[Amen Ra Mashariki]

Yeah, it's really interesting that you asked that question because sort of my pathway to the Bezos Earth Fund is almost polar opposite to how we think about our pathway to adopting and using AI to accelerate climate and nature solutions. And I'll explain why, really, really, in some quick points. I undergrad, master's doctorate, computer science, computer scientists, research labs, did the whole thing. I was one of those computer scientists that believed in computer science, you know, algorithm optimization. Through a couple of personal things that took place, I realized that that was only a mechanism by which I could do other things which is have an impact. So then I began to chase problems you mentioned here. I was the Chief Analytics Officer for the City of New York. How do we solve problems here? And then coming to the Basel Earth Fund, how do we use AI computer science to solve climate and nature problems? I was AI in search of a problem at the Bezos Earth Fund. We think about starting with the problem first and understanding that problem and then looking for ways to use modern AI in order to scale solutions in that space.

[Manouch Zomorodi]

Okay, so let's go deeper into that. How are you looking at different projects that are out there? What are sort of the big ideas that you're using to sort of lead you to find what you want to fund?

[Amen Ra Mashariki]

Yeah, so internally we have a mental Model that we use to really get there. We think about this difference between inventions and discoveries. Right. And the way you want to think about that is a telescope is an invention. Looking through the telescope to notice that Jupiter has moons is the discovery. Right. And so for us, when we look at it, it's how do we identify big, big innovations, grand innovations that have an impact such that you can have discoveries that then have an impact in climate and nature. And so we look for projects and efforts that sort of go across that, that mental model.

[Manouch Zomorodi]

Okay, so before we get into the discovery part, let's talk about the tool. Where are we when it comes to AI? I mean, I know there are some people who might think, what do you mean? We're at ChatGPT 5. But like from your perspective, much different. Where do you think we are?

[Amen Ra Mashariki]

Yeah. So I could, I could, I could spend hours talking about digital twins, earth observation models, edge AI and all of those things. But one of the things that have resonated with me is this concept called move 37. So move 37 was this move that AlphaGo, when playing against Go Champion early on in the game, in his 37th move, did a move that was counterintuitive to all experts. It made no sense to anyone GO Expert. But it was the move that ultimately won the game. And so where AI is is these two places. Right now it's at a place where it answers questions based on what it knows. Right? It answers, it takes an average of reality and then gives you answers. Move 37 was this view into how AI can be creative and actually come up with a move that no one has ever thought of. And it was counterintuitive to use. And so we really want to get to a place where in climate and nature, AI is actually offering solutions, creative solutions that even the world's greatest experts find counterintuitive, but are actually really powerful.

[Manouch Zomorodi]

Do you have an example of something that's maybe happening already that demonstrates that, that.

[Amen Ra Mashariki]

Well, one of the projects that really goes across this mental model that I Talked about is Meta, really came up with this AI innovation invention called Dyno V3, which is a computer vision model, very powerful computer vision model. Then they matched it with satellite data and it's really powerful brand innovation. But what they did was partner with WRI in its restoration efforts, such that you could actually track the growth of trees to an 80% accuracy of field surveys at 3% of the cost. Right. And so now you can actually unlock performance based financing with this technology. So it's. It followed that mental model of grand innovation and invention and ultimately a discovery that leads to an impact. The move. 37. The whole thing about that is we haven't gotten there yet. And that's where we should be going, which is there are restoration solutions that people are using. And if you ask AI, tell me some of the best ways to do restoration in this particular area, what it's going to do is identify an average or interpolation of the existing good solutions. What we want is AI to come up with something that no one in the room can come up with when it comes to restoration. And that's the trajectory.

[Manouch Zomorodi]

What's the timeline look for that? How will we know when we have sort of hit that tipping point?

[Amen Ra Mashariki]

One, there has to be trust by the experts, and the experts are using it. But then also there has to be a mechanism by which everyday people who are living their lives, who are living in these regions that we're concerned about, who are doing the work on the ground, can trust and use these tools as well. There is anyone who gives you an exact number, doesn't know the number, how long it's going to take, but that's where we have to get to, is that level of trust and that level of use across a number of types of people.

[Manouch Zomorodi]

I want to be sure to ask you, because there are many people who say that the same tech giants who are driving AI are also responsible for a lot of the environmental harms and that their climate initiatives essentially amount to greenwashing. How do you respond to that?

[Amen Ra Mashariki]

You know, at the Bezos Earth Fund, we believe that, on balance, AI is going to be a tool and a force for good and a tool and a force for saving the planet. On balance, we have to acknowledge that AI does contribute to degradation and challenges when it comes to the environment. There are many, many solutions that a lot of these companies, a lot of NGOs, a lot of academic institutions and a lot of governments are applying in this space. And we will continue as the Bezos Hurt Fund to support those type of efforts, such that we are deliberate in meeting that broad statement that AI, on balance, will have a positive impact on the planet.

[Manouch Zomorodi]

I mean, it makes me nervous because it's like, let's hope it works a little bit. What are some of the sort of milestones that we need to be looking for as we go forward?

[Amen Ra Mashariki]

So I was listening to a panel the other day and someone said something along the lines of, every time you do a query on ChatGPT, it's like throwing away a bottle of water on the ground. As soon as they made that statement, they said, I don't know if that's true, but it sounds like it might be true. One of the things that we need to begin to do is to have precise accuracy and understanding of exactly the impact that AI is having on our environment and a shared understanding across the board, such that we can make statements that we all agree on, such that we can identify the solutions. So the first milestone, which will include a level of transparency, a lot of information and data, such that we can really get to a place of agreeing on exactly what those challenges are, the next milestone is because as we speak, companies are shifting how they build technology to support AI. For instance, cooling is no longer just cooling at the data center level has shifted to now there are mechanisms where you can cool at the chip level such that the burden on water is not so great. So these are the types of milestones that would have to be in place.

[Manouch Zomorodi]

So I guess I want to end by saying it's an exciting time, it's a scary time. What is getting you sort of what makes you most hopeful? What are you most excited about when you get up every day to go figure out how we're going to find solutions?

[Amen Ra Mashariki]

So let me say this. We believe that we are in a space where the consequential decade meets the decisive decade. And so if you've heard that term before, the consequential decade, it's what AI practitioners use to talk about. This is the time in which we have to think about ethics, policy, regulation, technology, innovation, invention, because these are the decisions that are going to decide. These are the things that are going to decide what impact AI has on the global community. And we all know here what the decisive decade is. References. And so this is a place where the consequential decade meets the decisive decade. And so it really has to be all hands on deck and a commitment from communities in the AI space and communities in the climate and nature space and the Bezos HERF Fund. We see ourselves as sitting right in the middle and being a leader in that space.

[Manouch Zomorodi]

Okay, we'll have to leave it there. Aman Ra Maharishi, thank you so much.

[Amen Ra Mashariki]

Thank you so much.

[Podcast Sponsor Announcer]

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[Elise Hu]

That was Amen Ra Mashariki in conversation with Manouch Zomorodi at a TED Countdown event in New York in partnership with the Bezos earth fund in 2025. If you're curious about Ted's curation, find out [e-mail] curationguidelines and that's it for today. TED talks Daily is part of the TED Audio Collective. This talk was fact checked by the TED Research team and produced and edited by our team, Martha Estefan, Oliver Friedman, Brian Greene, Lucy Little and Tansika Sangmarnivong. This episode was mixed by Christopher Faizy Bogan. Additional support from Emma Tobner and Daniela Balarazo. I'm Elise Hu. I'll be back tomorrow with a fresh idea for your feed. Thanks for listening. TED Talks Daily is sponsored by Capital One. In my house we subscribe to everything music, tv, even dog food. And it rocks until you have to manage it all. Which is where Capital One comes in. Capital One credit card holders can easily track, block or cancel recurring charges right from the Capital One mobile app at no additional cost. With one sign in, you can manage all your subscriptions all in one place. Learn more at CapitalOne.comscriptions Terms and Conditions apply.

[Podcast Sponsor Announcer]

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[Elise Hu]

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