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Doyne Farmer

Professor at Oxford University, complexity scientist, and former physicist. Author of "Making Sense of Chaos: A Better Economics for a Better World."

Top 5 podcasts with Doyne Farmer

Ranked by the Snipd community
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38 snips
Oct 21, 2024 • 1h 11min

293 | Doyne Farmer on Chaos, Crashes, and Economic Complexity

Doyne Farmer, Director of the Complexity Economics program at Oxford, dives into the chaotic nature of economies and the inadequacies of traditional economic models. He highlights how chaos theory can reshape our understanding of financial systems and promote more accurate predictions. Farmer critiques the reliance on equilibrium, advocating for models that embrace dynamic interactions and real-world complexities. He also draws fascinating parallels between economic systems and ecological dynamics, exploring how innovation intertwines with complexity in markets.
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20 snips
Sep 28, 2022 • 1h 4min

Learning curves will lead to extremely cheap clean energy

A newly published research paper out of Oxford suggests that a rapid energy transition will not "cost" anything -- it will save nearly a trillion dollars relative to the no-transition case. And the faster we move, the more money we save. I talk with complex-systems scientist and co-author Doyne Farmer about his optimistic projections. This is a public episode. If you’d like to discuss this with other subscribers or get access to bonus episodes, visit www.volts.wtf/subscribe
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16 snips
Mar 27, 2024 • 46min

A conversation with Dr Doyne Farmer about complexity theory, energy transition

Dr. Doyne Farmer, Baillie Gifford Professor of Complex Systems Science at Oxford University, dives into complexity theory and its impact on energy systems. He explains how simple interactions can lead to significant outcomes in our energy transition. The conversation highlights technological advancements in solar and battery innovations, how hydrocarbons can transform the oil and gas industry, and the potential of renewable systems for rural communities. Farmer also discusses consumer behavior in embracing electric vehicles and the need for innovative economic solutions in the energy sector.
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9 snips
Jan 13, 2023 • 44min

Which technologies get cheaper over time, and why?

In 2021, a group of Scholars at Oxford University published a paper that made big waves in the energy world. It argued that key clean energy technologies — wind, solar, batteries, and electrolyzers — are on learning curves which guarantee that, if they are deployed at the scale required to reach zero carbon, they will get extremely cheap.This is, as they say, big if true. In September, I had one of the lead authors, Doyne Farmer, on Volts to discuss the paper in-depth. He made a convincing case for the paper’s thesis, but when I asked him why these technologies were on learning curves and others weren't, he could only speculate.That's the question that's been on my mind ever since. Why are some clean-energy technologies getting rapidly cheaper while others aren't? What is it about particular technologies that make them amenable to learning curves?I cast that question to the academic gods, and lo, they returned with a paper, and that paper is what we’re here to discuss today. It’s called “Accelerating Low-Carbon Innovation,” by Abhishek Malhotra of the School of Public Policy at the Indian Institute of Technology in New Delhi, India, and Tobias Schmidt of the Swiss Federal Institute of Technology in Zurich, Switzerland.It sets out to chart technologies against two basic axes: design complexity and need for customization. That creates a schema that can help illuminate why some technologies developed quicker than others.I don't want to say much more than that, since I have my Malhotra and Schmidt here with me to help explain. This is a public episode. If you’d like to discuss this with other subscribers or get access to bonus episodes, visit www.volts.wtf/subscribe
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Apr 29, 2024 • 39min

Making sense of chaos with Doyne Farmer

Doyne Farmer, a prominent figure in complexity economics, discusses his journey from chaos theory to economics. He emphasizes the importance of multidisciplinary work and applying complexity science to climate change. The conversation delves into the development of agent-based models for the economy and the challenges in predicting economic impacts, such as during the COVID pandemic.