Podcast appearances and mentions of Duncan J Watts

How much blame should we put on social media for polarizing our society? Perhaps not as much as we tend to do. Joshua A Tucker joins Vasant Dhar in episode 82 of Brave New World to discuss his studies on the effects of social media -- and the algorithms that run them.    Useful resources: 1. Joshua Tucker at NYU, Twitter and Google Scholar. 2. Online searches to evaluate misinformation can increase its perceived veracity -- Kevin Aslett, Zeve Sanderson, William Godel, Nathaniel Persily, Jonathan Nagler & Joshua A Tucker. 3. Less than you think: Prevalence and predictors of fake news dissemination on Facebook -- Andrew Guess, Jonathan Nagler and Joshua A Tucker. 4. Breaking the Social Media Prism: How to Make Our Platforms Less Polarizing -- Chris Bail. 5. Chris Bail on How to Fight Polarization -- Episode 34 of Brave New World. 6. The Social Media Industrial Complex -- Episode 3 of Brave New World (w Sinan Aral). 7. How Social Media Threatens Society -- Episode 8 of Brave New World (w Jonathan Haidt). 8. Quantifying the Impact of Misinformation and Vaccine-Skeptical Content on Facebook -- Jennifer Nancy Lee Allen, Duncan J Watts, and David Rand. Check out Vasant Dhar's newsletter on Substack. Subscription is free!

How can you find objects that are hard to see in the depths of space? There is plenty of gas in a galaxy, but trying to see a cloud amongst all those starts is not easy. The further back in time you look in the history of the universe, the colder and darker it gets. How do you figure out the structure of the earliest galaxies and their cold gas? A black hole roaming across a galaxy sounds like bad sci fi horror, but may have been found. How can you spot a black hole without any frame of reference? Detecting a roaming black hole is tricky but not impossible. Kieran A. Cleary, Jowita Borowska, Patrick C. Breysse, Morgan Catha, Dongwoo T. Chung, Sarah E. Church, Clive Dickinson, Hans Kristian Eriksen, Marie Kristine Foss, Joshua Ott Gundersen, Stuart E. Harper, Andrew I. Harris, Richard Hobbs, Håvard T. Ihle, Junhan Kim, Jonathon Kocz, James W. Lamb, Jonas G. S. Lunde, Hamsa Padmanabhan, Timothy J. Pearson, Liju Philip, Travis W. Powell, Maren Rasmussen, Anthony C. S. Readhead, Thomas J. Rennie, Marta B. Silva, Nils-Ole Stutzer, Bade D. Uzgil, Duncan J. Watts, Ingunn Kathrine Wehus, David P. Woody, Lilian Basoalto, J. Richard Bond, Delaney A. Dunne, Todd Gaier, Brandon Hensley, Laura C. Keating, Charles R. Lawrence, Norman Murray, Roberta Paladini, Rodrigo Reeves, Marco P. Viero, Risa H. Wechsler. COMAP Early Science. I. Overview. The Astrophysical Journal, 2022; 933 (2): 182 DOI: 10.3847/1538-4357/ac63cc Casey Y. Lam, Jessica R. Lu, Andrzej Udalski, Ian Bond, David P. Bennett, Jan Skowron, Przemek Mroz, Radek Poleski, Takahiro Sumi, Michal K. Szymanski, Szymon Kozlowski, Pawel Pietrukowicz, Igor Soszynski, Krzysztof Ulaczyk, Lukasz Wyrzykowski, Shota Miyazaki, Daisuke Suzuki, Naoki Koshimoto, Nicholas J. Rattenbury, Matthew W. Hosek Jr., Fumio Abe, Richard Barry, Aparna Bhattacharya, Akihiko Fukui, Hirosane Fujii, Yuki Hirao, Yoshitaka Itow, Rintaro Kirikawa, Iona Kondo, Yutaka Matsubara, Sho Matsumoto, Yasushi Muraki, Greg Olmschenk, Clement Ranc, Arisa Okamura, Yuki Satoh, Stela Ishitani Silva, Taiga Toda, Paul J. Tristram, Aikaterini Vandorou, Hibiki Yama, Natasha S. Abrams, Shrihan Agarwal, Sam Rose, Sean K. Terry. An isolated mass gap black hole or neutron star detected with astrometric microlensing. Accepted to APJ Letters, 2022 [abstract] Kailash C. Sahu, Jay Anderson, Stefano Casertano, Howard E. Bond, Andrzej Udalski, Martin Dominik, Annalisa Calamida, Andrea Bellini, Thomas M. Brown, Marina Rejkuba, Varun Bajaj, Noe Kains, Henry C. Ferguson, Chris L. Fryer, Philip Yock, Przemek Mroz, Szymon Kozlowski, Pawel Pietrukowicz, Radek Poleski, Jan Skowron, Igor Soszynski, Michael K. Szymanski, Krzysztof Ulaczyk, Lukasz Wyrzykowski, Richard Barry, David P. Bennett, Ian A. Bond, Yuki Hirao, Stela Ishitani Silva, Iona Kondo, Naoki Koshimoto, Clement Ranc, Nicholas J. Rattenbury, Takahiro Sumi, Daisuke Suzuki, Paul J. Tristram, Aikaterini Vandorou, Jean-Philippe Beaulieu, Jean-Baptiste Marquette, Andrew Cole, Pascal Fouque, Kym Hill, Stefan Dieters, Christian Coutures, Dijana Dominis-Prester, Clara Bennett, Etienne Bachelet, John Menzies, Michael Alb-row, Karen Pollard, Andrew Gould, Jennifer Yee, William Allen, Leonardo Andrade de Almeida, Grant Christie, John Drummond, Avishay Gal-Yam, Evgeny Gorbikov, Francisco Jablonski, Chung-Uk Lee, Dan Maoz, Ilan Manulis, Jennie McCormick, Tim Natusch, Richard W. Pogge, Yossi Shvartzvald, Uffe G. Jorgensen, Khalid A. Alsubai, Michael I. Andersen, Valerio Bozza, Sebastiano Calchi Novati, Martin Burgdorf, Tobias C. Hinse, Markus Hundertmark, Tim-Oliver Husser, Eamonn Kerins, Penelope Longa-Pena, Luigi Mancini, Matthew Penny, Sohrab Rahvar, Davide Ricci, Sedighe Sajadian, Jesper Skottfelt, Colin Snodgrass, John Southworth, Jeremy Tregloan-Reed, Joachim Wambsganss, Olivier Wertz, Yiannis Tsapras, Rachel A. Street, Daniel M. Bramich, Keith Horne, Iain A. Steele. An Isolated Stellar-Mass Black Hole Detected Through Astrometric Microlensing. Accepted to APJ, 2022 [abstract]  

In dieser Episode ist wieder Dr. Lukas Lang zu Gast. Wir sprechen über Data Science und Machine Learninig (auch »artificial intelligence« genannt). Das ist ein Themenbereich, der sehr viel Potential für unsere Zukunft hat, aber wie alle diese Themenbereiche auch eine Menge an Gefahren, Herausforderungen und Hypes generiert. Lukas ist ein perfekter Gesprächspartner für dieses Thema, weil er sowohl in der Spitzenforschung tätig war als auch in der industriellen Praxis mit diesen Themen beschäftigt ist. Diese Mischung scheint mir bei komplexen technischen Fragestellungen und Problemen sehr nützlich zu sein. Lukas hat nach seinem Studium der Informatik eine Promotion im Spezialgebiet Computational Science gemacht. Anschließend war er mehrere Jahre in der universitären Forschung im Bereich der mathematischen Bild- und Datenanalyse tätig, zuletzt an der Universität Cambridge. Seine Arbeit hat Anwendungen in der medizinischen Bildgebung, in der Molekular- und Zellbiologie, und in der Computer Vision. Derzeit leitet er den Geschäftsbereich »Data Science and AI« eines Spin-Offs des internationalen Industriekonzerns Voestalpine. Sein Team arbeitet an der Umsetzung von Daten-Projekten in der Erzeugung und Verarbeitung von Spezialmetallen, und am Aufbau eines globalen Data Science Programms für die Produktionsstandorte. Wir haben dieses umfangreiche Thema in zwei Episoden aufgeteilt: In der ersten Episode beginnen wir das Thema Data Science einzuführen, auch anhand einiger Beispiele, beginnend mit historischen Beispielen sowie Anwendungsfällen der heutigen Zeit. Wir spannen dabei den Bogen von Tycho Brahe und Florence Nightingale bis zu modernen Sprachassistenten und Entscheidungsunterstützung im Militär und zivilen Bereich. Dann gibt Lukas einen Überblick über wesentliche Prinzipien und Begriffe, die in diesem Zusammenhang immer wieder auftreten, wie Datascience, die Rolle der klassischen Statistik, Modellierung, Visualisierung, EDA, AI, KI, machine learning, multivariate statistik, Datenqualität und vieles mehr.  Wir sprechen dann über die These die seit einiger Zeit im Raum steht, dass man dank Daten und »AI« ja keine Modelle, keine Theorie mehr benötigt — The End of Theory —, sondern einfach aus Daten lernt und das wäre hinreichend für die wissenschaftliche Betrachtung der Welt. Wir diskutieren dann Möglichkeiten, Geschäftsmodelle und Grenzen von Machine Learning und Data Science. Wer trifft heute überhaupt Entscheidungen und was ist die Rolle und Funktion eines Data Scientists? Sollten Menschen immer das letzt Wort bei wesentlichen Entscheidungen haben? Ist das überhaupt (noch) realistisch? Welche Rolle spielen regulatorische Maßnahmen wie das aktuelle EU-Framework? In der zweiten Episode werden wir darauf aufbauend die Frage stellen, wie viel der aktuellen Behauptungen in diesem Feld Realität und wie viel Hype ist. Was können wir in der Zukunft zu erwarten — sowohl im positiven wie auch im negativen? Was sind dominierende Forschungsfragen und wo Grenzen liegen, unerwartete Effekte auftreten, und welche ethischen Fragen durch diese neuen Möglichkeiten zu diskutieren. xkcd Cartoon Konkret gibt es das Spannungsfeld zwischen Datensparsamkeit und der Idee alles zu sammeln, weil wir das irgendwie in der Zukunft für uns nutzen können. Aber will der Data Scientists überhaupt in Daten untergehen? Führen mehr Daten zu besseren Entscheidungen? Wir diskutieren wieder anhand konkreter Beispiele für gute und problematische Anwendungen wie predictiver Policing, Mapping und »KI« für militärische Dronenpiloten. Welche individuelle Verantwortung leiten wir daraus für Techniker ab? Wie geht Lukas selbst mit diesen Herausforderungen um?  Referenzen Lukas Lang Persönliche Webseite von Lukas Andere Episoden Episode 40: Software Nachhaltigkeit, ein Gespräch mit Philipp Reisinger Episode 37: Probleme und Lösungen Episode 32: Überleben in der Datenflut – oder: warum das Buch wichtiger ist als je zuvor Episode 31: Software in der modernen Gesellschaft – Gespräch mit Tom Konrad Episode 25:Entscheiden unter Unsicherheit Episode 19: Offene Systeme – Teil 1 und Episode 20, Teil 2 Episode 6: Messen, was messbar ist? Fachliche Referenzen Adhikari, DeNero, Jordan, Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans (2020) Michael I. Jordan, The revolution hasn't happened yet Hannah Fry, What data can't do Peter Coy, Goodhart's Law Rules the Modern World. Here Are Nine Examples  Roberts et al., Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans  Antun et al., On instabilities of deep learning in image reconstruction and the potential costs of AI Use of AI in breast cancer detection: 94% of AI systems evaluated in these studies were less accurate than a single radiologist, and all were less accurate than consensus of two or more radiologists Lukas Lang, What is Data Science? Seth Stephens-Davidowitz, Everybody Lies Evgeny Morozov, To Save Everything, Click here (2014) Meredith Broussard, Artificial Unintelligence (2018) Cathy O‘Neill, Weapons of Maths destruction (2017) Richard David Precht, Künstliche Intelligenz und der Sinn des Lebens (2020) Jerry Z Muller, The Tyrrany of Metrics (2018) Joseph Weizenbaum, Computermacht und Gesellschaft (2001) Margaret Heffernan, Uncharted: How to Map the Future (2021) Edward Snowden, Permanent Record (2019) Shoshanna Zuboff, Surveillance Capitalism (2019) Hartmut Rosa, Unverfügbarkeit (2020) Duncan J Watts, Everything is obvious, once you know the answer (2011) Gerd Gigerenzer, Klick: Wie wir in einer digitalen Welt die Kontrolle behalten und die richtigen Entscheidungen treffen - Vom Autor des Bestsellers »Bauchentscheidungen« (2021) Byung-Chul Han, Im Schwarm, Ansichten des Digitalen (2015) Marinanne Bellotti, A.I. is solving the wrong problem Hannah Fry, Hello World: How to be Human in the Age of Algorithms (2018) Hannah Fry, What Statistics Can and Can't Tell Us About Ourselves, The New Yorker (2019) David Spiegelhalter, The Art of Statistics: Learning from Statistics (2020) James, Witten, Hastie & Tibshirani. Introduction to Statistical Learning (2021) The end of theory: The data deluge makes the scientific method obsolete. Wired 6/2008 Rutherford and Fry on Living with AI: The Biggest Event in Human History Deep Mind, The Podcast David Donoho, 50 Years of Data Science, Journal of Computational and Graphical Statistics (2017) Stuart Russel and Peter Norving, Artificial Intelligence, A Modern Approach, Berkely Textbook (2021) Michael Roberts et al, Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans, Nature Machine Intelligence (2021) Neil Thompson, Deep Learning's Diminishing Returns, The Cost of Improvement Is Becoming Unsustainable, IEEE Spectrum (2021)

Luisteraars! Vol verwachting klopte ons hart voor het nieuwe regeerakkoord, maar die kwam te laat voor deze podcast. Dus de powerduiding is voor de volgende keer. Dit keer: een schraappodcast over van alles en nog wat. Zoals: winst bij de Raad voor de Journalistiek voor Jesse. Ik was door de eigenaar van gastouderbureau Dadim gedaagd vanwege mijn boek Zo hadden we het niet bedoeld. Mij werd verweten journalistiek onzorgvuldig, tendentieus en feitelijke onjuist te berichten over zijn gastouderbureau. De Raad oordeelde van niet. Het is aanleiding voor een korte rant van mij over wat zich voor en na de publicatie van mijn boek allemaal heeft voltrokken, want dat was toch wel hoogst merkwaardig. Voor de rest: Rutger was op tournee in de Verenigde Staten en heeft daar enkele loeiend rechtse boekjes gelezen. Het eerste boek is Nassim Nicholas Talebs Skin in the Game. Taleb brengt een lofzang aan mensen die de de consequenties dragen van hun acties. Best een interessante bril om de wereld door te bekijken: hoe serieus moet je iemand nemen als die niks heeft te verliezen als die het mis heeft? Denk bijvoorbeeld aan van die podcasts met overmoedige jongemannen die over van alles en nog wat een mening hebben, maar verder toch geen wezenlijke verantwoordelijkheid voor wat dan ook dragen. Geweldig boek, aldus Rutger. En dan: Peter Thiels boek From Zero to One. Een boek over hoe je een start-up groot maakt. Peter Thiel is een enge kapitalist die op Trump stemt, dus het is een beetje a-typische lectuur, maar Rutger adviseert: lees nou gewoon eens zo'n boek. Het zijn praktische wijsheden die niet alleen leerzaam zijn voor ondernemers, maar ook voor wereldverbeteraars. Tot slot: nog wat smakelijke parlementaire anekdotiek uit het boek Macht der Gewoonte van Carla Hoetink. Wist u bijvoorbeeld dat je in de jaren vijftig en zestig geen Kamervragen mocht stellen op grond van slechts berichten uit de krant? Nou, bij deze! Leesvoer bij deze aflevering: · Jesse Frederik, 'Hoe de compensatieregeling van de toeslagenaffaire gierend uit de hand loopt' (https://bit.ly/3yxrH9i) · Rutgers vijf sterren gingen uiteindelijk naar het boek Skin in the Game van Nassim Nicholas Taleb (https://bit.ly/3IXP1Se) · Derek Thompson, Hit Makers: How to Succeed in an Age of Distraction (https://bit.ly/3dYFmNc) · Duncan J. Watts, Everything is Obvious: How Common Sense Fails Us (https://bit.ly/3dUySPs) · David Graeber en David Wengrow, The Dawn of Everything: A New History of Humanity (https://bit.ly/3IU1Ugg) · Julia Galef, The Scout Mindset: See Things Clearly and Make Smarter Decisions (https://bit.ly/3GQEYfY) · Adam Hochschild, Bury the Chains: The British Struggle to Abolish Slavery (https://bit.ly/3F3NKa6) · Saul Alinsky, Rules for Radicals: A Pragmatic Primer for Realistic Radicals (https://bit.ly/33BSbes) · Peter Thiel, Zero To One: Notes on Startups, or How To Build the Future (https://bit.ly/3F4V2u6) · Carla Hoetink, Macht der gewoonte: Regels en rituelen in de Tweede Kamer na 1945 (https://bit.ly/3oZI0IH) · En Jesses reconstructie van de toeslagenaffaire, Zo hadden we het niet bedoeld (https://bit.ly/3q1auRQ)

Luisteraars! Vol verwachting klopte ons hart voor het nieuwe regeerakkoord, maar die kwam te laat voor deze podcast. Dus de powerduiding is voor de volgende keer. Dit keer: een schraappodcast over van alles en nog wat. Zoals: winst bij de Raad voor de Journalistiek voor Jesse. Ik was door de eigenaar van gastouderbureau Dadim gedaagd vanwege mijn boek Zo hadden we het niet bedoeld. Mij werd verweten journalistiek onzorgvuldig, tendentieus en feitelijke onjuist te berichten over zijn gastouderbureau. De Raad oordeelde van niet. Het is aanleiding voor een korte rant van mij over wat zich voor en na de publicatie van mijn boek allemaal heeft voltrokken, want dat was toch wel hoogst merkwaardig. Voor de rest: Rutger was op tournee in de Verenigde Staten en heeft daar enkele loeiend rechtse boekjes gelezen. Het eerste boek is Nassim Nicholas Talebs Skin in the Game. Taleb brengt een lofzang aan mensen die de de consequenties dragen van hun acties. Best een interessante bril om de wereld door te bekijken: hoe serieus moet je iemand nemen als die niks heeft te verliezen als die het mis heeft? Denk bijvoorbeeld aan van die podcasts met overmoedige jongemannen die over van alles en nog wat een mening hebben, maar verder toch geen wezenlijke verantwoordelijkheid voor wat dan ook dragen. Geweldig boek, aldus Rutger. En dan: Peter Thiels boek From Zero to One. Een boek over hoe je een start-up groot maakt. Peter Thiel is een enge kapitalist die op Trump stemt, dus het is een beetje a-typische lectuur, maar Rutger adviseert: lees nou gewoon eens zo'n boek. Het zijn praktische wijsheden die niet alleen leerzaam zijn voor ondernemers, maar ook voor wereldverbeteraars. Tot slot: nog wat smakelijke parlementaire anekdotiek uit het boek Macht der Gewoonte van Carla Hoetink. Wist u bijvoorbeeld dat je in de jaren vijftig en zestig geen Kamervragen mocht stellen op grond van slechts berichten uit de krant? Nou, bij deze! Leesvoer bij deze aflevering: · Jesse Frederik, 'Hoe de compensatieregeling van de toeslagenaffaire gierend uit de hand loopt' (https://bit.ly/3yxrH9i) · Rutgers vijf sterren gingen uiteindelijk naar het boek Skin in the Game van Nassim Nicholas Taleb (https://bit.ly/3IXP1Se) · Derek Thompson, Hit Makers: How to Succeed in an Age of Distraction (https://bit.ly/3dYFmNc) · Duncan J. Watts, Everything is Obvious: How Common Sense Fails Us (https://bit.ly/3dUySPs) · David Graeber en David Wengrow, The Dawn of Everything: A New History of Humanity (https://bit.ly/3IU1Ugg) · Julia Galef, The Scout Mindset: See Things Clearly and Make Smarter Decisions (https://bit.ly/3GQEYfY) · Adam Hochschild, Bury the Chains: The British Struggle to Abolish Slavery (https://bit.ly/3F3NKa6) · Saul Alinsky, Rules for Radicals: A Pragmatic Primer for Realistic Radicals (https://bit.ly/33BSbes) · Peter Thiel, Zero To One: Notes on Startups, or How To Build the Future (https://bit.ly/3F4V2u6) · Carla Hoetink, Macht der gewoonte: Regels en rituelen in de Tweede Kamer na 1945 (https://bit.ly/3oZI0IH) · En Jesses reconstructie van de toeslagenaffaire, Zo hadden we het niet bedoeld (https://bit.ly/3q1auRQ)

In this episode of Partnering Leadership, Greg Satell, writer, speaker, innovation advisor, an expert on transformational change, and author of Cascades, shares lessons on how leaders can lead transformation in their organizations and the community.  Greg Satell shares lessons learned from past transformations and how leaders can help lead change in organizations, especially through ongoing disruption.Some highlights:-Why Greg Satell moved to Poland and what it was like living in a post-communist country-How the Orange Revolution transformed Greg Satell's perspective on change-‘Viral cascades' and how leaders can use the understanding to drive transformational change in organizations-Greg Satell on the value of shared Purpose and Shared Values-How to best deal with fierce oppositions when driving change-How to empower people to succeed on their own terms-Gregg Satell on why Blockbuster failed to adapt and change and lessons for leaders of transformationMentioned in this episode:Duncan J. Watts, sociologist Steven Strogatz, mathematicianAlbert-László Barabási, physicistReimagining Capitalism in a World on Fire by Rebecca M. HendersonProsperity: Better Business Makes the Greater Good by Colin MayerLouis V. Gerstner Jr., former chairman of the board and chief executive officer of IBMImmanuel Kant, philosopherTeam of Teams: New Rules of Engagement for a Complex World by Stanley A. McChrystal and Chris FussellOne Mission: How Leaders Build a Team of Teams by Charles Goodyear and Chris FussellJohn F. Antioco, former CEO of Blockbuster and chairman of Red MangoCarl Icahn, former CEO of Blockbuster and founder and controlling shareholder of Icahn EnterprisesMapping Innovation: A Playbook for Navigating a Disruptive Age by Greg SatellAdversaries Into Allies: Win People Over Without Manipulation Or Coercion by Bob BurgThe Halo Effect by Phil Rosenzweig. . . . .Connect with Greg Satell:Cascades on AmazonGreg Satell's WebsiteDigital Tonto WebsiteGreg Satell on LinkedInGreg Satell on Clubhouse. . . . .Connect with Mahan Tavakoli:MahanTavakoli.comMore information and resources available at the Partnering Leadership Podcast website:PartneringLeadership.com

For most of his life, Wayne Hsiung was a typical overachiever. He attended the University of Chicago, started his PhD in Economics, became a law professor at Northwestern, was mentored by Cass Sunstein. But then, something snapped. In the midst of a deep, overwhelming depression, Hsiung visited a slaughterhouse and was radicalized by the immense suffering he saw. He now faces decades in prison for rescuing sick, injured animals from slaughterhouses. Hsiung is the founder of Direct Action Everywhere, an organization best known for conducting public, open rescues of animals too sick for slaughter. These rescues are, in many cases, illegal, and Hsiung and his fellow activists are risking years of imprisonment. But the sacrifice is the point: Hsiung and his colleagues are trying to highlight the sickness of a society that criminalizes doing what any child would recognize as the right thing to do. In our conversation, I wanted to understand a simple question: How did he get here? What leads someone with a safe, comfortable life to risk everything for a cause? What does society look like to him now, knowing what he faces? And the big question: Is Hsiung the weird one? Or is it all of us — who see so much suffering and injustice and simply go about our lives — who have lost our way? References: New York Times story on a DxE rescue mission Video of the mission to save Lily the piglet Book recommendations: Everything is Obvious by Duncan J. Watts  The Brothers Karamazov by Fyodor Dostoevsky Grit by Angela Duckworth My book is available for pre-order! You can find it at www.EzraKlein.com. Want to contact the show? Reach out at ezrakleinshow@vox.com You can subscribe to Ezra's new podcast Impeachment, explained on Apple Podcasts, Spotify, Stitcher, Overcast, Pocket Casts, or your favorite podcast app. Credits: Producer and Editor - Jeff Geld Researcher - Roge Karma Engineer - Jeremy Dalmas Learn more about your ad choices. Visit megaphone.fm/adchoices

A happy birthday to Curiosity, a stellar job opportunity, and a deep dive into Nicky Case’s game of trust, compassion and resilient cooperation—just don’t tailgate Tom. Discuss the podcast on Reddit. Support the podcast on Patreon. Warming up with Space [00:00] Curiosity sings like that NASA’s Planetary Protection wants you! The main event: playing with Trust [05:45] The Evolution of Trust (Nicky Case) Game Theory 101: The Prisoner’s Dilemma explained The WWI Christmas Truce TBG Ep. 11: Creating trust in a campaign (13:16) The Adventure Zone’s Suffering Game arc Resilient Cooperation is where it’s at (Andrew Mao, Lili Dworkin, Siddharth Suri & Duncan J. Watts) TBG Ep. 7: Tom forgives the highway cheaters (38:03) The Simple Solution to Traffic (CGP Grey) Ped’s interpretation of Utilitarianism makes him not like it at all Forbidden Island: a pretty cool non-zero-sum board game 12.5 years of Diplomacy - nice! Music by Lee Rosevere (CC by 4.0)

Your brain can easily be manipulated. Be careful. Science says you are more likely to buy German wine when German music is playing at the store in the background, and French wine when French music is playing. You are more likely to name Gatorade when you are given a green pen in order to fill out the survey of your favorite sports drink. You are more likely to buy an an expensive couch from a website with a background of fluffy white clouds.    A bit sad (haha) but research shows this is how simple our brains can be when it comes to decision making.   For today's Book-Of-The-Day I was just reading, "Everything is Obvious – How Common Sense Fails Us" by Duncan J. Watts.   The author makes a good point. You can't always just rely on common sense.   The world is too complex.    Too many factors are involved.    "Common sense is bad at dealing with complex social phenomena like political conflicts, healthcare economics, or marketing campaigns..."   Our inborn common sense only works some of the time.    Watts explains, “Urban planners in the United States have repeatedly set out to 'solve' the problem of urban poverty and have repeatedly failed. There is a wistful myth that if only we had enough money to spend—the figure is usually put at a hundred billion dollars—we could wipe out all our slums in ten years.… But look what we have built with the first several billions: Low-income projects that have become worse centers of delinquency, vandalism and general social hopelessness than the slums they were supposed to replace..."   Why did those housing experts with good intentions make such stupid mistakes?   It's the effects of the cognitive biases.    “Psychologists have identified so many of these effects—priming, framing, anchoring, availability, motivated reasoning, loss aversion, and so on..."   I would add to this book's list all of the other 25 cognitive biases and 100+ logical fallacies.    If your whole life strategy is to just trust your common sense, you are probably headed for a disaster.    “Bad things happen not because we forget to use our common sense, but rather because the incredible effectiveness of common sense in solving the problems of everyday life causes us to put more faith in it than it can bear."   Common sense is best kept for simple stuff like not petting a growling Rottweiler.   Don't over use it.    It won't work on some of the most important areas of your life   It won't work on your diet. When you eat junk food your bodies "common sense" meter will tell you that it must be good for you because it tastes good.    Wrong.   If you're driving fast and you hit a water puddle and start spinning out of control, common sense will tell you to slam on the brakes.    Wrong.   The list could go on and on.   Learn when to use common sense and when to use higher thinking.   Higher thinking comes only through training.   The world is full of people going to the gym for their body.    But hardly anyone's going to the bookstore to "workout" their brain.   One of the main reasons I created the 67 steps program was to show how you can invert the problem and reverse engineer your own brain.    Put in the work.    Use your common sense for common things and your "trained" brain for the harder things in life.    What's an example of an area in your life where you overused common sense?Learn more about your ad choices. Visit megaphone.fm/adchoices