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

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.

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)

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.

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.

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.

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)

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.

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.

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.

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)

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

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.