Albert Kao's guest appearances

Albert Kao

Todd Nief's Show

COMPLEXITY

Scott Young

James FitzGerald

Brad Stulberg

Stephan Guyenet

Joshua Becker

Chris Mills

Deborah Gordon

Melanie Mitchell

David Krakauer

Matthew Jackson

Katherine Collins

Mike Hranica

Olivia Judson

Ray Monk

Mike Lee

OwlTail

Albert Kao of the Santa Fe Institute has been researching collective behavior in animals — including really crazy things like using their own bodies as a bridge to invade a wasp nest. As we mention in the podcast, this absolutely needs to be made into a horror movie if it hasn't already. In addition to animal behavior, Albert has also created some really insightful models that find that smaller groups do a better job of converging on accurate information in complex environments — contrary to the well-known "wisdom of crowds" model, where more information entering the system is better. While the math in these models can be a little bit tricky, there is deep insight here into how our world is organized — from schools of fish to optimal team sizes in organizations to, of course, our current engagement with social media. Albert, along with several other scholars, has started thinking about how to apply some of the knowledge that folks studying complex systems have about network design and dynamics in order to help guide policy decisions in regulating companies like Twitter and Facebook. I think this is some of the most important work of our time, since the easy potshots on social media (distraction, vanity metrics, privacy invasion) may not be what we are grappling with — we may instead be grappling with fundamental aspects of hyperconnected networks. If you're enjoying the show, the best way to support it is by sharing with your friends. If you don't have any friends,  why not a leave a review? It makes a difference in terms of other people finding the show. You can also subscribe to receive my e-mail newsletter at www.toddnief.com. Most of my writing never makes it to the blog, so get on that list. Show Notes:  [01:04] When do we experience the “wisdom of crowds” and when do we experience the “madness of crowds”? [08:24] The bizarre collective behavior of ants [17:15] When does adding more people make collective decision-making more accurate — and when does it make collective decision-making less accurate? [25:52] Mid-sized groups seem to strike the balance between benefitting from the wisdom of crowds without being susceptible to the madness of crowds. [37:19] How are academics from the Santa Fe Institute and other areas thinking about making policy recommendations for regulation of social media and other hyperconnected networks? [49:06] What do we want our social networks to be optimizing for? Can we design the networks to encourage the behaviors that we want? [59:10] Speculation on the ability of modularity in networks to improve creativity in things like music scenes — and the sometimes positive dynamics of rivalries. [01:09:10] How to learn more from Albert  Links and Resources Mentioned  Army Ant Death Spiral How do army ants build bridges with no one in charge? Conway’s Game of Life Play John Conway’s Game of Life Condorcet’s jury theorem  Limits of information for trading and investing | overconfidence vs. accuracy “The wisdom of partisan crowds” by Joshua Becker, Ethan Porter, and Damon Centola Wu-Tang Clan Prisoner’s dilemma 

Albert Kao of the Santa Fe Institute has been researching collective behavior in animals — including really crazy things like <a href="https://www.youtube.com/watch?v=bUNKQqCRFuQ" rel="nofollow" target="_blank">using their own bodies as a bridge to invade a wasp nest</a>. As we mention in the podcast, this absolutely needs to be made into a horror movie if it hasn't already. In addition to animal behavior, Albert has also created some really insightful models that find that smaller groups do a better job of converging on accurate information in complex environments — contrary to the well-known "wisdom of crowds" model, where more information entering the system is better. While the math in these models can be a little bit tricky, there is deep insight here into how our world is organized — from schools of fish to optimal team sizes in organizations to, of course, our current engagement with social media. Albert, along with several other scholars, has started thinking about how to apply some of the knowledge that folks studying complex systems have about network design and dynamics in order to help guide policy decisions in regulating companies like Twitter and Facebook. I think this is some of the most important work of our time, since the easy potshots on social media (distraction, vanity metrics, privacy invasion) may not be what we are grappling with — we may instead be grappling with fundamental aspects of hyperconnected networks. If you're enjoying the show, the best way to support it is by sharing with your friends. If you don't have any friends, <a href="https://itunes.apple.com/us/podcast/todd-niefs-show/id1278759120?mt=2" rel="nofollow" target="_blank"> why not a leave a review</a>? It makes a difference in terms of other people finding the show. You can also subscribe to receive my e-mail newsletter at <a href="http://www.toddnief.com" rel="nofollow" target="_blank">www.toddnief.com</a>. Most of my writing never makes it to the blog, so get on that list. Show Notes: <ul> <li>[01:04] When do we experience the “wisdom of crowds” and when do we experience the “madness of crowds”?</li> <li>[08:24] The bizarre collective behavior of ants</li> <li>[17:15] When does adding more people make collective decision-making more accurate — and when does it make collective decision-making less accurate?</li> <li>[25:52] Mid-sized groups seem to strike the balance between benefitting from the wisdom of crowds without being susceptible to the madness of crowds.</li> <li>[37:19] How are academics from the Santa Fe Institute and other areas thinking about making policy recommendations for regulation of social media and other hyperconnected networks?</li> <li>[49:06] What do we want our social networks to be optimizing for? Can we design the networks to encourage the behaviors that we want?</li> <li>[59:10] Speculation on the ability of modularity in networks to improve creativity in things like music scenes — and the sometimes positive dynamics of rivalries.</li> <li>[01:09:10] How to learn more from Albert</li> </ul> Links and Resources Mentioned <ul> <li><a href="https://www.youtube.com/watch?v=N0HoqjxfvJ4" rel="nofollow" target="_blank">Army Ant Death Spiral</a></li> <li><a href="https://www.youtube.com/watch?v=Wp3Gau-Aljs" rel="nofollow" target="_blank">How do army ants build bridges with no one in charge?</a></li> <li><a href="https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life" rel="nofollow" target="_blank">Conway’s Game of Life</a></li> <li><a href="https://playgameoflife.com/" rel="nofollow" target="_blank">Play John Conway’s Game of Life</a></li> <li><a href="https://en.wikipedia.org/wiki/Condorcet%27s_jury_theorem" rel="nofollow" target="_blank">Condorcet’s jury theorem</a></li> <li><a href="https://7fin.org/limits-of-information-for-trading-and-investing/" rel="nofollow" target="_blank"> Limits of information for trading and investing | overconfidence vs. accuracy</a></li> <li><a href="https://www.pnas.org/content/116/22/10717" rel="nofollow" target="_blank">“The wisdom of partisan crowds” by Joshua Becker, Ethan Porter, and Damon Centola</a></li> <li><a href="https://en.wikipedia.org/wiki/Wu-Tang_Clan" rel="nofollow" target="_blank">Wu-Tang Clan</a></li> <li><a href="https://en.wikipedia.org/wiki/Prisoner%27s_dilemma" rel="nofollow" target="_blank">Prisoner’s dilemma</a></li> </ul>

Albert Kao, PhD on the Wisdom of Crowds and Hyperconnected Networks

Over one hundred years ago, Sir Francis Galton asked 787 villagers to guess an ox’s weight. None of them got it right, but averaging the answers led to a near-perfect estimate. This is a textbook case of the so-called “wisdom of crowds,” in which we’re smarter as collectives than we are as individuals. But the story of why evolution sometimes favors sociality is not so simple — everyone can call up cases in which larger groups make worse decisions. More nuanced scientific research is required for a deeper understanding of the origins and fitness benefits of collective computation — how the complexity of an environment or problem, or the structure of a group, provides the evolutionary pressures that have shaped the landscape of wild and civilized societies alike. Not every group deploys the same rules for decision-making; some decide by a majority, some by consensus. Some groups break up into smaller sub-groups and evaluate things in a hierarchy of modular decisions. Some crowds are wise and some are dumber than their parts, and understanding how and when and why the living world adopts a vast diversity of different strategies for sociality yields potent insights into how to tackle the most wicked problems of our time.This week’s guest is Albert Kao, a Baird Scholar and Omidyar Fellow here at SFI. Kao came to Santa Fe after receiving his PhD in Ecology and Evolutionary Biology at Princeton and spending three years as a James S. McDonnell fellow at Harvard. In this episode, we talk about his research into social animals and collective decision-making, just one of several reasons why a species might evolve to live in groups. What do the features of these groups, or the environments they live in, have to do with how they process information and act in the world?If you enjoy this podcast, please help us reach a wider audience by subscribing, leaving a review, and telling your friends about the show on social media.Thank you for listening!Albert’s WebsiteAlbert’s Google Scholar PageDiscussed:Quanta Magazine’s “Smarter Parts Make Collective Systems Too Stubborn”Visit our website for more information or to support our science and communication efforts.Join our Facebook discussion group to meet like minds and talk about each episode.Podcast Theme Music by Mitch Mignano.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn

Over one hundred years ago, Sir Francis Galton asked 787 villagers to guess an ox’s weight. None of them got it right, but averaging the answers led to a near-perfect estimate. This is a textbook case of the so-called “wisdom of crowds,” in which we’re smarter as collectives than we are as individuals. But the story of why evolution sometimes favors sociality is not so simple — everyone can call up cases in which larger groups make worse decisions. More nuanced scientific research is required for a deeper understanding of the origins and fitness benefits of collective computation — how the complexity of an environment or problem, or the structure of a group, provides the evolutionary pressures that have shaped the landscape of wild and civilized societies alike. Not every group deploys the same rules for decision-making; some decide by a majority, some by consensus. Some groups break up into smaller sub-groups and evaluate things in a hierarchy of modular decisions. Some crowds are wise and some are dumber than their parts, and understanding how and when and why the living world adopts a vast diversity of different strategies for sociality yields potent insights into how to tackle the most wicked problems of our time.This week’s guest is Albert Kao, a Baird Scholar and Omidyar Fellow here at SFI. Kao came to Santa Fe after receiving his PhD in Ecology and Evolutionary Biology at Princeton and spending three years as a James S. McDonnell fellow at Harvard. In this episode, we talk about his research into social animals and collective decision-making, just one of several reasons why a species might evolve to live in groups. What do the features of these groups, or the environments they live in, have to do with how they process information and act in the world?If you enjoy this podcast, please help us reach a wider audience by subscribing, leaving a review, and telling your friends about the show on social media.Thank you for listening!<a href="http://www.thekaolab.com/research.html" rel="nofollow" target="_blank">Albert’s Website</a><a href="https://scholar.google.com/citations?hl=en&amp;user=hZhwjsIAAAAJ&amp;view_op=list_works&amp;sortby=pubdate" rel="nofollow" target="_blank">Albert’s Google Scholar Page</a>Discussed: <a href="https://www.quantamagazine.org/smarter-parts-make-collective-systems-too-stubborn-20190226/" rel="nofollow" target="_blank">Quanta Magazine’s “Smarter Parts Make Collective Systems Too Stubborn”</a><a href="https://santafe.edu/podcast" rel="nofollow" target="_blank">Visit our website</a> for more information or to support our science and communication efforts.<a href="https://facebook.com/groups/santafeinstitute" rel="nofollow" target="_blank">Join our Facebook discussion group</a> to meet like minds and talk about each episode.Podcast Theme Music by <a href="https://deathlessmusic.bandcamp.com/releases" rel="nofollow" target="_blank">Mitch Mignano</a>.Follow us on social media: <a href="http://twitter.com/sfiscience" rel="nofollow" target="_blank">Twitter</a> • <a href="http://youtube.com/c/sfiscience" rel="nofollow" target="_blank">YouTube</a> • <a href="http://facebook.com/santafeinstitute" rel="nofollow" target="_blank">Facebook</a> • <a href="http://instagram.com/sfiscience" rel="nofollow" target="_blank">Instagram</a> • <a href="https://linkedin.com/company/20131/" rel="nofollow" target="_blank">LinkedIn</a>

Albert Kao on Animal Sociality & Collective Computation