Natural Reward Podcast

By: Owen Gilbert
  • Summary

  • The Natural Reward podcast will focus on questions of innovation, progress and advancement in the evolution of life. We will discuss the evolution of scientific theories, how to think critically about science, and questions of progress and advancement in technology and human culture. The Natural Reward podcast will cover the philosophy and history of science, evolutionary theory, and economic theory. Music by Christian Bjoerklund.
    © 2024 Natural Reward Podcast
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Episodes
  • Composite-trait evolution in pitcher plants: Ulrike Bauer
    Mar 1 2024

    Ulrike Bauer discusses the evolution and diversity of pitcher plants, focusing on the spring trapping mechanism found in some species. Pitcher plants are carnivorous plants that capture insects in a fluid-filled cavity. They have evolved independently multiple times and are found all over the world. The spring trapping mechanism is a composite trait that involves multiple adaptations, including a horizontal lid, a spring-like structure, and a slippery surface. The study of this mechanism involved fieldwork, experiments, and collaboration between researchers with expertise in ecology, biomechanics, and evolutionary biology. In this part of the conversation, Ulrike discusses the evolution of a composite trait and the opportunity to study how such a trait can evolve independently in different species. She explains how she came up with hypotheses and tested them to understand the evolution of the spring trapping plant. The conversation also explores the absence of transitional stages in the fossil record and the role of randomness in the emergence of complex traits. Ulrike's research challenges the traditional narrative of goal-directed evolution and highlights the importance of considering alternative mechanisms. The conversation explores the evolution of complex traits and the emergence of their functions. It discusses the stepwise process of trait evolution, such as self-incompatibility in plants and the evolution of pitcher plants. The incidental effects of complex traits on extinction rates and the maintenance of sexual reproduction are also examined. The concept of innovation in evolutionary biology is explored, highlighting the importance of variation and the role of selection in generating novelty. The challenges of studying complex trait evolution and the need for more empirical studies are discussed.

    Takeaways

    • Pitcher plants are carnivorous plants that have evolved independently multiple times and are found all over the world.
    • The spring trapping mechanism in pitcher plants is a composite trait that involves multiple adaptations.
    • The spring trapping mechanism is an example of a moving trap that employs movement to capture prey.
    • The study of the evolution of pitcher plants involved fieldwork, experiments, and collaboration between researchers with different areas of expertise.
    • Composite traits can evolve independently in different species, providing an opportunity to study the evolution of complex traits.
    • Hypotheses can be formulated and tested to understand the mechanisms behind the evolution of composite traits.
    • The absence of transitional stages in the fossil record challenges the traditional narrative of goal-directed evolution.
    • Randomness and variability play a significant role in the emergence of complex traits. Complex traits often evolve through a stepwise process, gradually building upon existing traits to create new functions.
    • Incidental effects of complex traits can have significant ecological and evolutionary consequences, such as influencing extinction rates.
    • The distinction between invention and innovation is important in understanding the origin and spread of complex traits.
    • Variation is a key factor in generating novelty and driving the evolution of complex traits.
    • Studying the origin of complex traits can provide valuable insights into the mechanisms of evolution.



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    1 hr and 48 mins
  • Using Drones and AI to Find Illegal Dumping Sites: Interview with Brian Johnson
    May 11 2023

    Illegal dumping is a widespread problem in cities throughout the world and differentially affects disadvantaged neighborhoods.  Brian Johnson is a software engineer who moved to San Francisco nearly a decade ago. At the time, Brian could afford a house only in the least-expensive neighborhood, Bayview. Despite hopes for improvement, over time Bayview declined because of an illegal dumping problem.  To protect his children, Brian started brainstorming ways to solve this problem. The problem is difficult because dumping laws are difficult to enforce and people can easily get away with the crime.  Brian's solution was to automate drones to fly in grid-like patterns, take photos of a neighborhood, instantly recognize trash heaps using artificial intelligence (AI), and automatically report the locations of the trash piles to 311.  Brian tested many different types of AI and programmed the drones to automatically report trash heaps. This resulted in major improvements in his neighborhood, recognized by neighbors and by Brian's own tests. However, Brian is still seeking to scale up his project to help other neighborhoods and cities and seeks funding for the project.  Brian, who has a law degree and specialized in intellectual property, also wrote a patent for his system, not to prevent other people from doing this, but to prevent other people from preventing him from doing it.  Brian's solution leads to more unbiased was of reporting trash piles that can yield more equitable outcomes. Otherwise, city trash collectors may be called to affluent neighborhoods more often. Brian shows a number of photos taken by his drone in the video and explains how he trains the artificial intelligence to recognize trash heaps.  Brian has applied for an NSF grant and to join Y Combinator.

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    1 hr and 15 mins
  • Supplement to "Updating the Software of Social Evolution"
    Feb 15 2023

    In this episode, Jon and I discuss some of the background to the previous episode. We discuss generalized versions of Hamilton's rule, Fisher's fundamental theorem, and Wright's fitness maximization formula. W. D. Hamilton used Sewall Wright's formula as the foundation of the theory of inclusive fitness. We discuss Wright's shifting balance theory and the role that Wright's formula played in his theory. We also discuss the difference between Wright's rendition of Fisher's fundamental  theorem and Fisher's formula. We compare the progress of social theory to a telephone game. Finally, Jon explains why we might need the equivalent of "poll requests" when it comes to debugging the software of social evolution.

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    28 mins

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