+ la
+
+ SABIDURIA + y/o la + LOCURA +
+ de las +
+ MASAS +
+
+ + SABIDURIA + y/o la + LOCURA +
+ de las +
+ MASAS +
+
+
+
+ por nicky case • traducido por Gilberto Guerra • original en Inglés
+
+
++ + Sir Isaac Newton estaba bastante seguro de que era +
+ una persona muy lista. Quiero decir, después de inventar el cálculo y +
+ una teoría de la gravedad, él debería de ser lo suficientemente listo como para hacer +
+ algunas inversiones financieras, ¿cierto? Sin embargo, en resúmen, él +
+ perdió $4,600,000 dólares (dólares actuales) en el frenesí especulativo +
+ nacional conocido como la burbuja de los Mares del Sur, en 1720. + +
+ + Es por esto que Newton dijo: “Puedo calcular el movimiento de los +
+ cuerpos celestes, pero no la locura de la gente.” + +
+ ocasión en la que mercados, instituciones, +
+ o democracias enteras se volvieron locas — la locura de las +
+ multitudes. Pero aún así, justo cuando pierdes la fé en la humanidad, +
+ vez a ciudadanos coordinandose para rescatar a sus prójimos en +
+ huracanes, comunidades creando soluciones a problemas, +
+ gente luchando por un mundo mejor — ¡la sabiduría de las masas! + + + + Pero ¿por qué algunas multitudes recurren a la locura, o a la sabiduría? No existe una teoría +
+ que pueda explicar todo, pero creo que un nuevo campo de estudio, +
+ análisis de redes, puede guiarnos! Su idea principal es esta: para +
+ entender a las masas, en lugar de observar a las personas de forma +
+ individual, deberíamos observar... + +
+ opcional ¡notas extras! ↑
+
+
+ ↓ enlaces y referencias
+
++ Por ejemplo, un estudio de 1991 mostró que + “virtualmente, todos los estudiantes [de universidad] reportaron que sus amigos consumían más alcohol que ellos.” + ¡Pero eso es imposible! + ¿Cómo puede suceder eso? + Pues, estás a punto de descubrir la respuesta, creando una red. + Es tiempo de... + +
+ Engaña a todos haciéndoles creer + que la mayoría de sus amigos (al menos el 50%) son bebedores impulsivos
+ + Start the simulation! + (p.s: you can't draw while the sim's running) + +
+ Draw a network & run the simulation, + so that everyone gets infected with the "contagion". +
+ (new rule: you can't cut the thick connections) +
+ However: this simulation is wrong. + Most ideas don't spread like viruses. + For many beliefs and behaviors, you need to be "exposed" to the contagion more than just once + in order to be "infected". + So, network scientists have come up with a new, better way to + describe how ideas/behaviors spread, and they call it... +
+ + Now, let's simulate what happens if people start drinking + when 50%+ of their friends do! + Before you start the sim, ask yourself what you think should happen. + +
+ + Now, run the sim, and see what actually happens! + +
+ + ← Get everyone "infected" with the good vibes! + +
+ Try to "infect" everyone with complex wisdom! +
+ Too many connections, and you get groupthink. +
+ Build a bridge, to "infect" everyone with complex wisdom: +
+ Draw connections within groups (bonding) and between groups (bridging) + to spread wisdom to the whole crowd: + +
+ No matter how it's phrased, + people across times and cultures often arrive at the same piece of wisdom: + + a healthy society needs a sweet spot of bonds within groups + and bridges between groups. + + That is: + +
+ (because ideas can't spread) +
+ (because you'll get groupthink) +
+ [Space]: Drag [Backspace]: Delete +
+ IN CONCLUSION: it's all about...
+
+
+ Contagions & Connections
+
+
+
+ Contagions:
+ Like how neurons pass signals in a brain,
+ people pass beliefs & behaviors in a society.
+ Not only do we influence our friends,
+ we also influence our friends' friends, and even our friends' friends' friends!
+ (“be the change you wanna see in the world” etc etc)
+ But, like neurons, it's not just signals that matter, it's also...
+
+
+
+ Connections:
+ Too few connections and complex ideas can't spread.
+ Too many connections and complex ideas get crushed by groupthink.
+ The trick is to build a small world network, the optimal mix of
+ bonding and bridging: e pluribus unum.
+
+
+
+ (wanna make your own simulations?
+ check out Sandbox Mode, by clicking the (★) button below!)
+
+
+
+ So, what about our question from the very beginning?
+ Why do some crowds turn to...
+
+
+ ...wisdom and/or madness?
+
+
++ network science, we've covered a lot here +
+ today. Long story short, the madness of crowds +
+ is not necessarily due to the individual people, but due +
+ to how we're trapped in a network's sticky web. + + + + That does NOT mean abandoning personal responsibility, for +
+ we're also the weavers of that web. So, improve your contagions: +
+ be skeptical of ideas that flatter you, spend time understanding +
+ complex ideas. And, improve your connections: bond with similar +
+ folk, but also build bridges across cultural/political divides. + + + + We can weave a wise web. Sure, it's harder than doodling +
+ lines on a screen... + +
+ ~ Neil Gaiman & Terry Pratchett + +
+
+
+ created by
+
+ + + lots of love and thanks to +
+ + help me make more like this! <3 + +
+ + + ♫ music is + + "Friends 2018" and "Friends 2068" + by Komiku +
+ </> Crowds is + + fully open source + + +
+ +
+
+
+ NICKY CASE
+
+ play my other shtuff ·
+
+ follow my tweeter
+
+ + + + lots of love and thanks to +
+ MY PATREON SUPPORTERS
+
+ see names & drawings of supporters ·
+
+ see playtesters
+ + + help me make more like this! <3 + +
+ + + ♫ music is + + "Friends 2018" and "Friends 2068" + by Komiku +
+ </> Crowds is + + fully open source + + +
+ +
+ A quick response to James Surowiecki's The Wisdom of Crowds +
+ +
+
+ 
+
+ First off, I'm not dissing
+
+ this book.
+ It's a good book, and Surowiecki was trying to tackle the same question I am:
+ “why do some crowds turn to madness, or wisdom?”
+
+
+ + Surowiecki's answer: crowds make good decisions when everybody is as independent as possible. + He gives the story of a county fair, + where the townsfolk were invited to guess the weight of an ox. + Surprisingly, the average of all their guesses was better than any one guess. + But, here's the rub: the people have to guess independently of each other. + Otherwise, + they'd be influenced by earlier incorrect guesses, + and the average answer would be highly skewed. + +
+ + But... I don't think "make everyone as independent as possible" is the full answer. + Even geniuses, who we mischaracterize as the most independent thinkers, + are deeply influenced by others. As Sir Isaac Newton said, + “If I have seen further, it is by standing on the sholders of Giants.” + +
+ + So, which idea is correct? + Does wisdom come from thinking for yourself, or thinking with others? + The answer is: "yes". + +
+ + So that's what I'll try to explain in this explorable explanation: + how to get that sweet spot between independence and interdependence — + that is, how to get a wise crowd. + +
+
+
+
+ First off, I'm not dissing
+
+ this book.
+ It's a good book, and Surowiecki was trying to tackle the same question I am:
+ “why do some crowds turn to madness, or wisdom?”
+
+ + + Surowiecki's answer: crowds make good decisions when everybody is as independent as possible. + He gives the story of a county fair, + where the townsfolk were invited to guess the weight of an ox. + Surprisingly, the average of all their guesses was better than any one guess. + But, here's the rub: the people have to guess independently of each other. + Otherwise, + they'd be influenced by earlier incorrect guesses, + and the average answer would be highly skewed. + +
+ + But... I don't think "make everyone as independent as possible" is the full answer. + Even geniuses, who we mischaracterize as the most independent thinkers, + are deeply influenced by others. As Sir Isaac Newton said, + “If I have seen further, it is by standing on the sholders of Giants.” + +
+ + So, which idea is correct? + Does wisdom come from thinking for yourself, or thinking with others? + The answer is: "yes". + +
+ + So that's what I'll try to explain in this explorable explanation: + how to get that sweet spot between independence and interdependence — + that is, how to get a wise crowd. + +
+ What other kinds of connections are there? +
+ +
+
+ For the sake of simplicity,
+ my simulations pretend that people can only be connected through friendships,
+ and that all friendships are equal.
+ But network scientists do consider other ways we can be connected, such as:
+
+
+
+ +
+ Directional connections. Alice is the boss of Bob, but Bob is not the boss of Alice.
+ Carol is the parent of Dave, but Dave is not the parent of Carol.
+ "Boss" & "parent" are directional relationships:
+ the relationship only goes one way.
+ In contrast, "friends" is a bidirectional relationship:
+ the relationship goes both ways. (well, hopefully)
+
+
+
+ +
+ Weighted connections. Elinor and Frankie are mere acquaintances.
+ George and Harry are Best Friends Forever.
+ Even though there's a "friendship" connection in both cases, the second one is stronger.
+ We say that these two connections have different "weights".
+
+
+
+ +
+ Just remember: all these simulations are wrong. The same way any map is "wrong".
+ You see the map on the left? Buildings aren't gray featureless blocks!
+ Words don't float above the city! However, maps are useful not despite being simplified,
+ but because they're simplified. Same goes for simulations, or any scientific theory.
+ Of course they're "wrong" — that's what makes them useful.
+
+
+
++ +
+ Directional connections. Alice is the boss of Bob, but Bob is not the boss of Alice.
+ Carol is the parent of Dave, but Dave is not the parent of Carol.
+ "Boss" & "parent" are directional relationships:
+ the relationship only goes one way.
+ In contrast, "friends" is a bidirectional relationship:
+ the relationship goes both ways. (well, hopefully)
+
+
+ + +
+ Weighted connections. Elinor and Frankie are mere acquaintances.
+ George and Harry are Best Friends Forever.
+ Even though there's a "friendship" connection in both cases, the second one is stronger.
+ We say that these two connections have different "weights".
+
+
+ + +
+ Just remember: all these simulations are wrong. The same way any map is "wrong".
+ You see the map on the left? Buildings aren't gray featureless blocks!
+ Words don't float above the city! However, maps are useful not despite being simplified,
+ but because they're simplified. Same goes for simulations, or any scientific theory.
+ Of course they're "wrong" — that's what makes them useful.
+
+ + What other kinds of contagions are there? +
+ +
+
+ There are so, so many ways that network scientists can simulate "contagions"!
+ I picked the simplest one, for educational purposes.
+ But here's other ways you could do it:
+
+
+
+ +
+ Contagions with Randomness.
+ Being "exposed" to a contagion doesn't guarantee you'll be infected,
+ it only makes it more likely.
+
+
+
+ +
+ People have different contagion thresholds.
+ My simulations pretend that everyone has the same threshold for binge-drinking (50%) or
+ volunteering (25%) or misinformation (0%).
+ Of course, that's not true in real life, and you could make your sim reflect that.
+
+
+
+ +
+ An ecology of contagions.
+ What if there were multiple contagions, with different thresholds?
+ For example, a simple "madness" contagion and a complex "wisdom" contagion.
+ If someone's infected with madness, can they still be infected with wisdom?
+ Or vice versa?
+ Can someone be infected with both?
+
+
+
+ +
+ Contagions that mutate and evolve.
+ Ideas don't pass perfectly from one person to another the way a virus does.
+ Like a game of Telephone, the message gets mutated with each re-telling —
+ and sometimes the mutant will be more infectious than the original!
+ So, over time, ideas "evolve" to be more catchy, copy-able, contagious.
+
+
+
+
+
++ +
+ Contagions with Randomness.
+ Being "exposed" to a contagion doesn't guarantee you'll be infected,
+ it only makes it more likely.
+
+
+ + +
+ People have different contagion thresholds.
+ My simulations pretend that everyone has the same threshold for binge-drinking (50%) or
+ volunteering (25%) or misinformation (0%).
+ Of course, that's not true in real life, and you could make your sim reflect that.
+
+
+ + +
+ An ecology of contagions.
+ What if there were multiple contagions, with different thresholds?
+ For example, a simple "madness" contagion and a complex "wisdom" contagion.
+ If someone's infected with madness, can they still be infected with wisdom?
+ Or vice versa?
+ Can someone be infected with both?
+
+
+ + +
+ Contagions that mutate and evolve.
+ Ideas don't pass perfectly from one person to another the way a virus does.
+ Like a game of Telephone, the message gets mutated with each re-telling —
+ and sometimes the mutant will be more infectious than the original!
+ So, over time, ideas "evolve" to be more catchy, copy-able, contagious.
+
+
+
+ + I wanna learn more! What else can I read and/or play? +
+ +
+
+ This explorable explanation was just a springboard for your curiosity,
+ so you can dive deeper into a vast pool of knowledge!
+ Here's more stuff on networks or social systems:
+
+
+ +
+ Book:
+
+ Connected
+ by Nicholas Christakis and James Fowler (2009).
+ An accessible tour of how our networks affect our lives, for good or ill.
+
+ Here's an excerpt: Preface & Chapter 1
+
+
+
+
+ +
+ Interactive:
+
+ The Evolution of Trust by Nicky Case (me) (2017).
+ A game about the game theory of how cooperation is built... or destroyed.
+
+
+
+ +
+ Interactive:
+
+ Parable of the Polygons by Vi Hart and Nicky Case (also me) (2014).
+ A story about how harmless choices can create a harmful world.
+
+
+
+ +
+ Or, if you just want to see a whole gallery of interactive edu-things, here's
+
+ Explorable Explanations,
+ a hub for learning through play!
+
+
+
+
+
++ +
+ Book:
+
+ Connected
+ by Nicholas Christakis and James Fowler (2009).
+ An accessible tour of how our networks affect our lives, for good or ill.
+
+ Here's an excerpt: Preface & Chapter 1
+
+
+
+ + +
+ Interactive:
+
+ The Evolution of Trust by Nicky Case (me) (2017).
+ A game about the game theory of how cooperation is built... or destroyed.
+
+
+ + +
+ Interactive:
+
+ Parable of the Polygons by Vi Hart and Nicky Case (also me) (2014).
+ A story about how harmless choices can create a harmful world.
+
+
+ + +
+ Or, if you just want to see a whole gallery of interactive edu-things, here's
+
+ Explorable Explanations,
+ a hub for learning through play!
+
+
+
+ + “virtually all [college] students reported that their friends drank more than they did.” +
+ +
+
+ “Biases in the perception of drinking norms among college students” by Baer et al (1991)
+
+
++ “The Majority Illusion” +
+ +
+
+ “The Majority Illusion in Social Networks” by Lerman et al (2016).
+
+ Related: + The Friendship Paradox. +
++ Related: + The Friendship Paradox. +
+ “strong statistical evidence that + smoking, health, happiness, voting patterns, and cooperation levels + are all contagious” +
+ +
+
+ From Nicholas Christakis and James Fowler's
+ wonderfully-written, layperson-accessible book,
+
+ Connected (2009).
+
+
++ “some evidence that suicides are [contagious], too” +
+ +
+
+ “Suicide Contagion and the Reporting of Suicide: Recommendations from a National Workshop”
+ by O'Carroll et al (1994), endorsed by the frickin' Centers for Disease Control & Prevention (CDC).
+
+
++ “some evidence that mass shootings are [contagious], too” +
+ +
+
+
+ “Contagion in Mass Killings and School Shootings” by Towers et al (2015).
+
+
+ + Also see: the + + Don't Name Them campaign, + which urges that news outlets DO NOT air mass murderers' names, manifestos, and social media feeds. + This spreads the contagion. + Instead, news outlets should focus on the victims, first responders, civilian heroes, + and the grieving, healing community. + +
+
++ + Also see: the + + Don't Name Them campaign, + which urges that news outlets DO NOT air mass murderers' names, manifestos, and social media feeds. + This spreads the contagion. + Instead, news outlets should focus on the victims, first responders, civilian heroes, + and the grieving, healing community. + +
+ “The world's financial institutions fell for such a cascade in 2008.” +
+ +
+
+ “Lemmings of Wall Street” by Cass Sunstein, is a quick, non-technical read.
+ Published in Oct 2008, right in the wake of the crash.
+
+
++ “the complex contagion theory.” +
+ +
+
+
+ “Threshold Models of Collective Behavior” by Granovetter (1978)
+ was the first time, as far as I know, anyone described a "complex contagion" model.
+ (although he didn't use that specific name)
+
+
+ + + “Evidence for complex contagion models of social contagion from observational data” + by Sprague & House (2017) + shows that complex contagions do, in fact, exist. (at least, in the social media data they looked at) + +
+ + Finally, + + “Universal behavior in a generalized model of contagion” by Dodds & Watts (2004) + proposes a model that unifies all kinds of contagions: + simple and complex, biological and social! + +
+
++ + + “Evidence for complex contagion models of social contagion from observational data” + by Sprague & House (2017) + shows that complex contagions do, in fact, exist. (at least, in the social media data they looked at) + +
+ + Finally, + + “Universal behavior in a generalized model of contagion” by Dodds & Watts (2004) + proposes a model that unifies all kinds of contagions: + simple and complex, biological and social! + +
+ “the possum has 13 nipples” +
+
+ arranged in a ring of 12 nipples, plus one in the middle
+
++ “groupthink” +
+ +
+ This Orwell-inspired phrase was coined by Irving L. Janis in 1971.
+
+ In his original article,
+ Janis investigates cases of groupthink, lists its causes, and — thankfully —
+ some possible remedies.
+
+
++ “bonding and bridging social capital” +
+ +
+ These two types of social capital — "bonding" and "bridging" —
+ were named by Robert Putnam in his insightful 2000 book,
+
+ Bowling Alone. His discovery:
+ across almost all empircal measures of social connectiveness,
+ Americans are more alone than ever.
+ Golly.
+
+
++ “bridging social capital has a sweet spot” +
+ +
+
+ “The Strength of Weak Ties” by Granovetter (1973)
+ showed that connections across groups helps spread simple contagions (like information),
+ but
+
+ “Complex Contagions and the Weakness of Long Ties” by Centola & Macy (2007)
+ showed that connections across groups may not help complex contagions,
+ and it fact, can hurt their spread!
+
+
++ “the small world network” +
+ +
+
+ The idea of the "small world" was popularized by
+ Travers & Milgram's 1969 experiment,
+ which showed that, on average, any two random people in the United States
+ were just six friendships apart — "six degrees of separation"!
+
+
+ + The small-world network got more mathematical meat on its bones with + + “Collective dynamics of small-world networks” by Watts & Strogatz (1998), + which proposed an algorithm for creating networks + with both low average path length (low degree of separation) + and high clustering (friends have lots of mutual friends) — + that is, a network that hits the sweet spot! + +
+ + You can also play with + + the visual, interactive adaptation of that paper by Bret Victor (2011). + +
+
++ + The small-world network got more mathematical meat on its bones with + + “Collective dynamics of small-world networks” by Watts & Strogatz (1998), + which proposed an algorithm for creating networks + with both low average path length (low degree of separation) + and high clustering (friends have lots of mutual friends) — + that is, a network that hits the sweet spot! + +
+ + You can also play with + + the visual, interactive adaptation of that paper by Bret Victor (2011). + +
+ “[small world networks] describe how our neurons are connected” +
+ +
+
+ “Small-world brain networks” by Bassett & Bullmore (2006).
+
+
++ “[small world networks] give rise to collective creativity” +
+ +
+
+
+ “Collaboration and Creativity: The Small World Problem” by Uzzi & Spiro (2005).
+ This paper analyzed the social network of the Broadway scene over time,
+ and discovered that, yup, the network's most creative when it's a "small world" network!
+
+
+
++ “[small world networks] give rise to collective problem-solving” +
+ +
+ See
+
+ “Social Physics” by MIT Professor Alex "Sandy" Pentland (2014)
+ for a data-based approach to collective intelligence.
+
+
++ “[small world networks] helped John F. Kennedy (barely) avoid nuclear war!” +
+ +
+
+ Besides the NASA Challenger explosion, the most notorious example of groupthink
+ was the Bay of Pigs fiasco.
+ In 1961, US President John F. Kennedy and his team of advisors thought
+ — for some reason —
+ it would be a good idea to secretly invade Cuba and overthrow Fidel Castro.
+ They failed.
+ Actually, worse than failed: it led to the Cuban Missile Crisis of 1962,
+ the closest the world had ever been to full-scale nuclear war.
+
+
+ + Yup, JFK really screwed up on that one. + +
+ + But, having learnt some hard lessons from the Bay of Pigs fiasco, + JFK re-organized his team to avoid groupthink. + Among many things, he: + 1) actively encouraged people to voice criticism, + thus lowering the "contagion threshold" for alternate ideas. + And + 2) he broke his team up into sub-groups before reconvening, + which gave their group a "small world network"-like design! + Together, this arrangement allowed for a healthy diversity of opinion, + but without being too fractured — a wisdom of crowds. + +
+ + And so, with the same individuals who decided the Bay of Pigs, + but re-arranged collectively to decide on the Cuban Missile Crisis... + JFK's team was able to reach a peaceful agreement with Soviet leader Nikita Khrushchev. + The Soviets would remove their missiles from Cuba, and in return, + the US would promise not to invade Cuba again. + (and also agreed, in secret, to remove the US missiles from Turkey) + +
+ + And that's the story of how all of humanity almost died. + But a small world network saved the day! Sort of. + +
+ + You can read more about this + + on Harvard Business Review, + or from + + the original article on groupthink. + +
+
++ + Yup, JFK really screwed up on that one. + +
+ + But, having learnt some hard lessons from the Bay of Pigs fiasco, + JFK re-organized his team to avoid groupthink. + Among many things, he: + 1) actively encouraged people to voice criticism, + thus lowering the "contagion threshold" for alternate ideas. + And + 2) he broke his team up into sub-groups before reconvening, + which gave their group a "small world network"-like design! + Together, this arrangement allowed for a healthy diversity of opinion, + but without being too fractured — a wisdom of crowds. + +
+ + And so, with the same individuals who decided the Bay of Pigs, + but re-arranged collectively to decide on the Cuban Missile Crisis... + JFK's team was able to reach a peaceful agreement with Soviet leader Nikita Khrushchev. + The Soviets would remove their missiles from Cuba, and in return, + the US would promise not to invade Cuba again. + (and also agreed, in secret, to remove the US missiles from Turkey) + +
+ + And that's the story of how all of humanity almost died. + But a small world network saved the day! Sort of. + +
+ + You can read more about this + + on Harvard Business Review, + or from + + the original article on groupthink. + +
+ “we influence [...] our friends' friends' friends!” +
+ +
+ Again, from Nicholas Christakis and James Fowler's
+ wonderful book,
+
+ Connected (2009).
+
+
++ “be skeptical of ideas that flatter you” +
+
+ yes, including the ideas in this explorable explanation.
+
++ ★ Sandbox Mode ★ +
+ +
+ The keyboard shortcuts (1, 2, space, backspace)
+ work in all the puzzles, not just Sandbox Mode!
+ Seriously, you can go back to a different chapter,
+ and edit the simulation right there.
+ In fact, that's how I created all these puzzles. Have fun!
+
+
+
+ To
+ my supporters on Patreon:
+ I'm deeply grateful.
+ Your generosity literally feeds me and pays my rent,
+ and grants me the creative freedom to make these weird math/social-science games.
+ From the bottom of my heart, thank you!
+
+
+
+ Thank you, everyone who playtested Crowds
+ during its many stages of life!
+
+
+ The Prototype: +
+ Maria · + Monica Srivastava + +
+ The Alpha: +
+ Glen Chiacchieri · + Kalli Repzeti · + Mali Akmanalp · + Toph Tucker + +
+ The Beta: +
+ Alex Dytrych · + Amit Patel · + Cassandra McClure · + Catherine Ray · + Josh Comeau · + Kayle Sawyer · + Matthew Conlen · + Srini Kadamati · + Vanessa Shen · + Wick Perry + +
++ The Prototype: +
+ Maria · + Monica Srivastava + +
+ The Alpha: +
+ Glen Chiacchieri · + Kalli Repzeti · + Mali Akmanalp · + Toph Tucker + +
+ The Beta: +
+ Alex Dytrych · + Amit Patel · + Cassandra McClure · + Catherine Ray · + Josh Comeau · + Kayle Sawyer · + Matthew Conlen · + Srini Kadamati · + Vanessa Shen · + Wick Perry + +