COMPLEXITY
Simon DeDeo on Good Explanations & Diseases of Epistemology
Episode guests
Podcast summary created with Snipd AI
Quick takeaways
- Conspiracy theorists struggle to maintain simplicity in their explanations, leading to convoluted and complex narratives as more elements are added to the conspiracy.
- Scientists excel at preserving simplicity in their explanations by connecting concepts and correlating complex phenomena in elegant and unified ways.
- The ability to simplify explanations and connect concepts is a fundamental aspect of scientific progress, fostering the discovery of new correlations and advancing knowledge in various fields.
Deep dives
Conspiracy Theories and the Lack of Simplicity
Conspiracy theories often arise from the lack of a razor module, which allows for simple explanations. While the correlation of different properties is observed, conspiracy theorists struggle to preserve simplicity in their explanations. For instance, they may attribute a complex event to a single cause, like government agents orchestrating a terrorist attack. However, their explanations become convoluted as more elements are added to the conspiracy, undermining the initial simplicity. In contrast, scientists aim to correlate phenomena using simple explanations, like the connection between electricity and magnetism in physics.
Flow, Gestalt Perception, and Simplifying Correlations
Flow, a state of deep engagement, relies on the correlation of various properties within a task. Similarly, gestalt perception involves perceiving invisible objects that provide simple explanations for complex perceptions. In both cases, the brain seeks to simplify correlations to make sense of the world. These phenomena connect to the history of science, where scientists discovered reliable connections between concepts and began linking them together. Concepts like electricity and magnetism became correlated before the explicit development of the theory of electromagnetism.
The History of Science and Simplifying Explanations
The history of science reveals patterns in linking concepts over time. Scientists increasingly associated ideas before their explicit theories were developed. For example, the correlation between electricity and magnetism emerged in scientific literature years before the theory of electromagnetism. This pattern demonstrates scientists' tendency to simplify explanations by connecting related concepts. Understanding this history allows for a deeper appreciation of how simplicity drives scientific progress and the discovery of fundamental connections in various fields of study.
Connecting Concepts and the Value of Simplicity
Scientists and conspiracy theorists both attempt to correlate different phenomena. However, scientists excel at preserving simplicity by explaining complex correlations in elegant and unified ways. On the contrary, conspiracy theorists struggle to maintain simplicity, resulting in convoluted explanations as more elements are added to the conspiracy. The ability to simplify explanations and connect concepts is a fundamental aspect of scientific progress, fostering the discovery of new correlations and advancing knowledge in various fields.
The Power of Reliably Associating Patterns
The podcast explores the idea that one of the reasons for the success of science is the ability to reliably associate patterns. By connecting concepts and linking them together, science achieves great success in understanding the world. This is evidenced by the way people distinguish correlations between different topics, such as acidity and blood circulation. Science's reliance on associating patterns and making deeper cognitive connections has led to significant scientific achievements over the past two centuries.
Collapse as a Catalyst for Creativity and Opportunity
The podcast emphasizes the notion that the current period of instability and collapse can offer great opportunities for creativity and positive change. It highlights the breaking apart of traditional institutions and the rise of alternative systems for knowledge creation and sharing, such as Wikipedia and independent learning communities. The collapse of old systems allows for the emergence of new ideas and the testing and retesting of concepts, leading to greater innovation. While instability and uncertainty can be frightening, they also open the doorway for comedy, creativity, and the exploration of new possibilities.
What makes a satisfying explanation? Understanding and prediction are two different goals at odds with one another — think fundamental physics versus artificial neural networks — and even what defines a “simple” explanation varies from one person to another. Held in a kind of ecosystemic balance, these diverse approaches to seeking knowledge keep each other honest…but the use of one kind of knowledge to the exclusion of all others leads to disastrous results. And in the 21st Century, the difference between good and bad explanations determines how society adapts as rapid change transforms the world most people took for granted — and sends humankind into the epistemic wilds to find new stories that will help us navigate this brave new world.
This week we dive deep with SFI External Professor Simon DeDeo at Carnegie Mellon University to explore his research into intelligence and the search for understanding, bringing computational techniques to bear on the history of science, information processing at the scale of society, and how digital technologies and the coronavirus pandemic challenge humankind to think more carefully about the meaning that we seek, here on the edge of chaos…
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Works Discussed:
“From Probability to Consilience: How Explanatory Values Implement Bayesian Reasoning”
Zachary Wojtowicz & Simon DeDeo (+ SFI press release on this paper)
“Supertheories and Consilience from Alchemy to Electromagnetism”
Simon DeDeo (SFI lecture video)
“From equality to hierarchy”
Simon DeDeo & Elizabeth Hobson
The Complex Alternative: Complexity Scientists on the COVID-19 Pandemic
SFI Press (with “From Virus to Symptom” by Simon DeDeo)
“Boredom and Flow: An Opportunity Cost Theory of Attention-Directing Motivational States”
Zachary Wojtowicz, Nick Chater, & George Loewenstein
“Scale and information-processing thresholds in Holocene social evolution”
Jaeweon Shin, Michael Holton Price, David H. Wolpert, Hajime Shimao, Brendan Tracey, & Timothy A. Kohler
“Slowed canonical progress in large fields of science”
Johan Chu and James Evans
“Will A Large Complex System Be Stable?”
Robert May
Related Podcast Episodes:
• Andy Dobson on Disease Ecology & Conservation Strategy
• Nicole Creanza on Cultural Evolution in Humans & Songbirds
• On Coronavirus, Crisis, and Creative Opportunity with David Krakauer
• Carl Bergstrom & Jevin West on Calling Bullshit: The Art of Skepticism in a Data-Driven World
• Vicky Yang & Henrik Olsson on Political Polling & Polarization: How We Make Decisions & Identities
• David Wolpert on The No Free Lunch Theorems and Why They Undermine The Scientific Method
• Science in The Time of COVID: Michael Lachmann & Sam Scarpino on Lessons from The Pandemic
• Jonas Dalege on The Physics of Attitudes & Beliefs
• Tyler Marghetis on Breakdowns & Breakthroughs: Critical Transitions in Jazz & Mathematics
Mentioned:
David Spergel, Zachary Wojtowicz, Stuart Kauffman, Jessica Flack, Thomas Bayes, Claude Shannon, Sean M. Carroll, Dan Sperber, David Krakauer, Marten Scheffer, David Deutsch, Jaewon Shin, Stuart Firestein, Bob May, Peter Turchin, David Hume, Jimmy Wales, Tyler Marghetis
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