TED2013
Eric Berlow and Sean Gourley: Mapping ideas worth spreading
Eric Berlow e Sean Gourley: Representación de ideas de que vale a pena difundir.
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¿Como son 24.000 ideas xuntas? O ecoloxista Eric Berlow e o físico Sean Gourley aplican algoritmos ó arquivo enteiro de charlas de TEDx, e lévannos a unha estimulante viaxe visual para ensinarnos como as ideas se conectan globalmente.
Eric Berlow - Ecologist
TED Senior Fellow Eric Berlow studies ecology and networks, exposing the interconnectedness of our ecosystems with climate change, government, corporations and more. Full bioSean Gourley - Physicist and military theorist
Sean Gourley, trained as a physicist, has turned his scientific mind to analyzing data about a messier topic: modern war and conflict. He is a TED Fellow. Full bio
TED Senior Fellow Eric Berlow studies ecology and networks, exposing the interconnectedness of our ecosystems with climate change, government, corporations and more. Full bioSean Gourley - Physicist and military theorist
Sean Gourley, trained as a physicist, has turned his scientific mind to analyzing data about a messier topic: modern war and conflict. He is a TED Fellow. Full bio
Double-click the English transcript below to play the video.
00:12
Eric Berlow: I'm an ecologist, and Sean's a physicist,
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Eric Berlow: eu son ecoloxista, Sean é físico,
00:15
and we both study complex networks.
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e os dous estudamos mecanismos complexos.
00:17
And we met a couple years ago when we discovered
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Coñecímonos fai dous anos cando descubrimos
00:19
that we had both given a short TED Talk
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que nos deran unha pequena conferencia en TED
00:21
about the ecology of war,
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sobre a ecoloxía da guerra,
00:23
and we realized that we were connected
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e decatámonos de que estabamos unidos
00:25
by the ideas we shared before we ever met.
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polas ideas que compartiamos mesmo antes de coñecermos.
00:28
And then we thought, you know, there are thousands
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Entón pensamos, xa sabedes, hai milleiros
00:29
of other talks out there, especially TEDx Talks,
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de charlas por aí fóra, especialmente charlas de TEDx,
00:31
that are popping up all over the world.
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que están a aflorar arredor do mundo.
00:34
How are they connected,
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Como están conectadas,
00:34
and what does that global conversation look like?
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e como pinta esta conversa global?
00:36
So Sean's going to tell you a little bit about how we did that.
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Sean vai falaros un pouquiño sobre como o fixemos.
00:39
Sean Gourley: Exactly. So we took 24,000 TEDx Talks
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Sean Gourley: Exactamente. Nós collimos 24.000 conferencias de TEDx
00:43
from around the world, 147 different countries,
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de todo o mundo, 147 países distintos,
00:46
and we took these talks and we wanted to find
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e escollemos estas charlas porque queriamos atopar
00:48
the mathematical structures that underly
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as estruturas matemáticas que esconden
00:50
the ideas behind them.
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as ideas tras delas.
00:52
And we wanted to do that so we could see how
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E o queriamos facer para poder ver como
00:53
they connected with each other.
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conectan as unhas coas outras.
00:55
And so, of course, if you're going to do this kind of stuff,
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Por suposto, se ti vas facer algo coma isto,
00:57
you need a lot of data.
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precisas unha chea de datos.
00:58
So the data that you've got is a great thing called YouTube,
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A información que ti tes é unha cousa xenial chamada YouTube,
01:02
and we can go down and basically pull
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a onde nos podemos conectar e basicamente sacar
01:03
all the open information from YouTube,
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toda a información aberta,
01:06
all the comments, all the views, who's watching it,
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todos os comentarios, todas as visitas, quen o está a ver,
01:08
where are they watching it, what are they saying in the comments.
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onde o están a ver, que están a dicir nos comentarios...
01:11
But we can also pull up, using speech-to-text translation,
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Pero tamén podemos entender, usando a tradución discurso-texto,
01:14
we can pull the entire transcript,
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podemos obter a transcrición enteira,
01:16
and that works even for people with kind of funny accents like myself.
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e isto funciona incluso para xente con acentos graciosos coma o meu.
01:19
So we can take their transcript
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Polo tanto, podemos coller a transcrición
01:21
and actually do some pretty cool things.
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e facer cousas bastante molonas.
01:23
We can take natural language processing algorithms
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Podemos coller a linguaxe natural procesando algoritmos
01:25
to kind of read through with a computer, line by line,
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para facer algo como ler cun ordenador, liña por liña,
01:28
extracting key concepts from this.
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sacando conceptos clave de eles.
01:30
And we take those key concepts and they sort of form
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Despois collemos eses conceptos clave e fan algo como
01:33
this mathematical structure of an idea.
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a estrutura matemática dunha idea.
01:36
And we call that the meme-ome.
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A isto chamámoslle o meme-ome.
01:38
And the meme-ome, you know, quite simply,
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O meme-ome, xa sabedes, sinxelamente,
01:40
is the mathematics that underlies an idea,
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son as matemáticas que subxacen nunha idea,
01:43
and we can do some pretty interesting analysis with it,
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e podemos facer análisis moi interesantes con isto
01:45
which I want to share with you now.
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que quero compartir con vós agora.
01:47
So each idea has its own meme-ome,
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Polo tanto, cada idea ten o seu propio meme-ome,
01:49
and each idea is unique with that,
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e cada idea é única niso, pero
01:51
but of course, ideas, they borrow from each other,
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por suposto, as ideas empréstanse cousas unhas ás outras,
01:53
they kind of steal sometimes,
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ás veces case as rouban,
01:54
and they certainly build on each other,
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e certamente, constrúense unhas sobre outras.
01:56
and we can go through mathematically
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Podemos seguir matematicamente
01:58
and take the meme-ome from one talk
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e sacar o meme-ome dunha charla
02:00
and compare it to the meme-ome from every other talk,
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e comparalo có meme-ome de todas as outras charlas
02:02
and if there's a similarity between the two of them,
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e, se hai semellanzas entre dous deles,
02:04
we can create a link and represent that as a graph,
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podemos crear un vínculo e representalo cun gráfico,
02:07
just like Eric and I are connected.
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xusto coma Eric e eu estamos conectados.
02:10
So that's theory, that's great.
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Esta é a teoría, xenial.
02:11
Let's see how it works in actual practice.
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Imos ver como funciona na práctica.
02:14
So what we've got here now is the global footprint
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O que temos agora é a pegada global
02:17
of all the TEDx Talks over the last four years
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de todas as charlas de TEDx dos últimos catro anos
02:19
exploding out around the world
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que están a explotar ao redor do mundo,
02:20
from New York all the way down to little old New Zealand in the corner.
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dende Nova York ata a pequena e vella Nova Zelanda alá na esquina.
02:24
And what we did on this is we analyzed the top 25 percent of these,
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O que fixemos con isto foi analizar o 25 por cento,
02:28
and we started to see where the connections occurred,
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e comezamos a ver onde se daban as conexións,
02:30
where they connected with each other.
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onde conectaban unhas con outras.
02:32
Cameron Russell talking about image and beauty
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Cameron Russell falando sobre imaxe e beleza
02:33
connected over into Europe.
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conectou toda Europa.
02:35
We've got a bigger conversation about Israel and Palestine
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Temos unha conversa máis longa sobre Israel e Palestina
02:37
radiating outwards from the Middle East.
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irradiando cara afora dende Oriente Medio.
02:40
And we've got something a little broader
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Temos tamén algo máis xeral
02:41
like big data with a truly global footprint
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como unha fonte de datos cunha pegada global de verdade
02:43
reminiscent of a conversation
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que alude a unha conversa
02:45
that is happening everywhere.
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que se dá por todas partes.
02:47
So from this, we kind of run up against the limits
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Dende aquí, nós coma que corremos contra os límites
02:50
of what we can actually do with a geographic projection,
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do que actualmente podemos facer cunha proxección xeográfica,
02:52
but luckily, computer technology allows us to go out
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pero afortunadamente, a tecnoloxía dos ordenadores permítennos saír
02:54
into multidimensional space.
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ó espazo multimensional.
02:56
So we can take in our network projection
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Así que podemos coller o noso sistema de proxección,
02:58
and apply a physics engine to this,
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aplicarlle un mecanismo físico,
02:59
and the similar talks kind of smash together,
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e as charlas similares farán algo como pegarse unhas a outras,
03:01
and the different ones fly apart,
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as que sexan diferentes separaranse,
03:03
and what we're left with is something quite beautiful.
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e o resultado é algo bastante bonito.
03:05
EB: So I want to just point out here that every node is a talk,
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EB: Eu só quero destacar que cada nóduo é unha charla.
03:08
they're linked if they share similar ideas,
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Están conectadas entre elas se comparten ideas semellantes
03:11
and that comes from a machine reading
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e isto vén dado por una lectura mecanizada
03:13
of entire talk transcripts,
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das transcricións completas das charlas
03:15
and then all these topics that pop out,
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e, entón, todos os temas que saen á luz
03:17
they're not from tags and keywords.
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non veñen de etiquetas ou palabras clave.
03:19
They come from the network structure
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Veñen da rede
03:21
of interconnected ideas. Keep going.
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de ideas conectadas. Segue.
03:23
SG: Absolutely. So I got a little quick on that,
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SG: Totalmente. Pode que apure un pouco niso
03:25
but he's going to slow me down.
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pero el vai frearme.
03:26
We've got education connected to storytelling
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Temos a educación conectada á narración,
03:28
triangulated next to social media.
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triangulada de seguido cós medios sociais.
03:30
You've got, of course, the human brain right next to healthcare,
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Ti tes, por suposto, o cerebro préto da asistencia médica,
03:33
which you might expect,
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o que debes supor,
03:34
but also you've got video games, which is sort of adjacent,
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pero tamén tés videoxogos, que é algo así como adxacente,
03:36
as those two spaces interface with each other.
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xa que estes dous espazos interactúan o un có outro.
03:39
But I want to take you into one cluster
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Pero quero que formedes parte de algo
03:41
that's particularly important to me, and that's the environment.
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que é especialmente importante para min: o medio ambiente.
03:43
And I want to kind of zoom in on that
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Quero acercame a iso
03:45
and see if we can get a little more resolution.
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e ver se podemos conseguir un pouco máis de resolución.
03:47
So as we go in here, what we start to see,
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En canto nos adentramos aquí, o que comezamos a ver,
03:50
apply the physics engine again,
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aplicade o mecanismo da física outra vez,
03:51
we see what's one conversation
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vemos que unha conversa
03:53
is actually composed of many smaller ones.
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está formada realmente por moitas conversas máis pequenas.
03:55
The structure starts to emerge
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A estrutura comeza a saír
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where we see a kind of fractal behavior
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onde vemos algo parecido a un comportamento fraccional
03:59
of the words and the language that we use
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das palabras e da linguaxe que usamos
04:01
to describe the things that are important to us
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para describir as cousas que son importantes para nós
04:03
all around this world.
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por todo o mundo.
04:04
So you've got food economy and local food at the top,
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Así que temos a economía alimentaria e a comida local na cima,
04:06
you've got greenhouse gases, solar and nuclear waste.
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e tamén gases de efecto invernadoiro, e desperdicios solares e nucleares.
04:09
What you're getting is a range of smaller conversations,
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O que estás a conseguir é unha gama de consversas máis pequenas,
04:12
each connected to each other through the ideas
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cada unha conectada coa outra a través de ideas
04:14
and the language they share,
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e da linguaxe que comparten,
04:15
creating a broader concept of the environment.
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creando un concepto máis amplo do medio ambiente.
04:18
And of course, from here, we can go
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Por suposto, dende aquí podemos
04:19
and zoom in and see, well, what are young people looking at?
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fixarnos máis e ver, bueno, ¿en que se está a fixar a xente nova?
04:23
And they're looking at energy technology and nuclear fusion.
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Estanse a fixar na enerxía, na tecnoloxía e na fusión nuclear.
04:25
This is their kind of resonance
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Isto é como a repercusión
04:27
for the conversation around the environment.
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da conversa sobre o medio ambiente.
04:29
If we split along gender lines,
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Se rompemos coas liñas de xénero,
04:31
we can see females resonating heavily
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podemos ver mulleres que pisan forte
04:33
with food economy, but also out there in hope and optimism.
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no campo da economía alimentaria, pero tamén aí fóra en esperanza e optimismo.
04:37
And so there's a lot of exciting stuff we can do here,
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Hai moitas cousas interesantes que podemos facer aquí,
04:39
and I'll throw to Eric for the next part.
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e pasareille a testemuña a Eric para a seguinte parte.
04:41
EB: Yeah, I mean, just to point out here,
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EB: Si, quero dicir, só para remarcar,
04:43
you cannot get this kind of perspective
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non podes obter este tipo de perspectiva
04:44
from a simple tag search on YouTube.
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dende unha soa busca en YouTube.
04:48
Let's now zoom back out to the entire global conversation
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Imos agora volver atrás e fixarnos no total da conversa global
04:52
out of environment, and look at all the talks together.
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sobre o medio ambiente, e ver todas as charlas xuntas.
04:54
Now often, when we're faced with this amount of content,
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A miúdo, cando nos enfrontamos a tal cantidade de contido,
04:57
we do a couple of things to simplify it.
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facemos un par de cousas para facelo máis sinxelo.
05:00
We might just say, well,
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Debemos dicir, bueno,
05:01
what are the most popular talks out there?
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¿cales son as charlas máis coñecidas por aí?
05:04
And a few rise to the surface.
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E unhas poucas suben á superficie.
05:05
There's a talk about gratitude.
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Hai unha charla sobre aprecio.
05:07
There's another one about personal health and nutrition.
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Hai outra sobre saúde e nutrición.
05:10
And of course, there's got to be one about porn, right?
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E por suposto, ten que haber outra sobre porno, ¿verdade?
05:13
And so then we might say, well, gratitude, that was last year.
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E despois debemos dicir, bueno, aprecio, isto foi o ano pasado.
05:17
What's trending now? What's the popular talk now?
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¿Que se leva agora? ¿Cal é a charla máis popular agora?
05:19
And we can see that the new, emerging, top trending topic
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E vemos que o novo, emerxente tema de moda
05:22
is about digital privacy.
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é sobre privacidade dixital.
05:25
So this is great. It simplifies things.
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Isto é xenial. Isto simplicfica as cousas,
05:27
But there's so much creative content
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Pero hai demasiado contido creativo
05:29
that's just buried at the bottom.
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que simplemente foi soterrado.
05:31
And I hate that. How do we bubble stuff up to the surface
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Eu odio iso. ¿Como facemos que saia á superficie
05:34
that's maybe really creative and interesting?
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algo que pode ser realmente creativo e interesante?
05:36
Well, we can go back to the network structure of ideas
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Bueno, podemos volver á rede de estrutura das ideas
05:39
to do that.
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para iso.
05:41
Remember, it's that network structure
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Recorda, esta é a rede
05:43
that is creating these emergent topics,
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que crea os temas emerxentes.
05:45
and let's say we could take two of them,
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Digamos que podemos coller dous deles,
05:47
like cities and genetics, and say, well, are there any talks
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como cidades e xenética, e dicir ben, ¿hai aquí algunha charla
05:50
that creatively bridge these two really different disciplines.
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que una creativamente estas dúas disciplinas tan diferentes?
05:52
And that's -- Essentially, this kind of creative remix
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E isto é -- esencialmente, este tipo de remix creativo
05:54
is one of the hallmarks of innovation.
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é un selo distintivo da innovación.
05:56
Well here's one by Jessica Green
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Mirade, aquí temos un de Jessica Green
05:58
about the microbial ecology of buildings.
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sobre a ecoloxía microbiana dos edificios.
06:00
It's literally defining a new field.
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Está literalmente definindo un novo campo de traballo.
06:02
And we could go back to those topics and say, well,
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E nós poderiamos volver a eses tópicos e dicir, vale,
06:04
what talks are central to those conversations?
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que charlas son primordiais para esas conversas?
06:07
In the cities cluster, one of the most central
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No conxunto de charlas sobre cidades, unha das primordiais
06:09
was one by Mitch Joachim about ecological cities,
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era unha de Mitch Joachim sobre cidades ecolóxicas,
06:13
and in the genetics cluster,
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e das charlas sobre xenética,
06:15
we have a talk about synthetic biology by Craig Venter.
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temos unha sobre bioloxía sintética de Craig Venter.
06:18
These are talks that are linking many talks within their discipline.
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Estas son charlas que están a unir outras moitas charlas da súa disciplina.
06:21
We could go the other direction and say, well,
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Podemos ir noutra dirección e dicir está ben,
06:23
what are talks that are broadly synthesizing
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son charlas que sintetizan ampliamente
06:25
a lot of different kinds of fields.
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unha morea de campos distintos.
06:27
We used a measure of ecological diversity to get this.
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Usamos a medida de diversidade ecolóxica para conseguilo.
06:29
Like, a talk by Steven Pinker on the history of violence,
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Como por exemplo, unha charla de Steven Pinker sobre a historia da violencia,
06:32
very synthetic.
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moi sintético.
06:33
And then, of course, there are talks that are so unique
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E logo, por suposto, hai charlas que son tan únicas
06:35
they're kind of out in the stratosphere, in their own special place,
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que están como na estratosfera, no seu propio sitio especial,
06:38
and we call that the Colleen Flanagan index.
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e a iso chamámoslle a lista Colleen Flanagan.
06:41
And if you don't know Colleen, she's an artist,
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Se non coñecedes a Colleen, é unha artista,
06:44
and I asked her, "Well, what's it like out there
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e un día pregunteille, "¿como é todo ahí fóra
06:45
in the stratosphere of our idea space?"
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na estratosfera da nosa idea de espazo?"
06:47
And apparently it smells like bacon.
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E aparentemente cheira a panceta.
06:50
I wouldn't know.
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Eu non o sabería.
06:52
So we're using these network motifs
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Polo tanto, estamos a usar a idea central da rede
06:54
to find talks that are unique,
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para atopar charlas que sexan únicas,
06:56
ones that are creatively synthesizing a lot of different fields,
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unhas que sintetizan de forma creativa unha morea de campos distintos,
06:58
ones that are central to their topic,
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outras que se centran no seu tema,
07:00
and ones that are really creatively bridging disparate fields.
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e outras que abranguen campos disparatados.
07:03
Okay? We never would have found those with our obsession
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¿Vale? Xamáis os atopariamos de non ser pola nosa obsesión
07:05
with what's trending now.
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co que está de moda agora.
07:08
And all of this comes from the architecture of complexity,
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E todo isto vén dado pola arquitectura da complexidade,
07:11
or the patterns of how things are connected.
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ou polos patróns que conectan as cousas.
07:14
SG: So that's exactly right.
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SG: Isto é totalmente certo.
07:15
We've got ourselves in a world
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Metémonos nun mundo
07:18
that's massively complex,
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excesivamente complexo,
07:20
and we've been using algorithms to kind of filter it down
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e estivemos a usar algo como algoritmos para filtralo dalgunha maneira
07:23
so we can navigate through it.
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e así poder navegar nel.
07:24
And those algorithms, whilst being kind of useful,
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Estes algoritmos, aínda que útiles,
07:27
are also very, very narrow, and we can do better than that,
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tamén son moi limitados, e podemos facelo mellor
07:30
because we can realize that their complexity is not random.
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porque podemos decatarmos de que a súa complexidade non é casual.
07:33
It has mathematical structure,
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Ten unha estrutura matemática,
07:35
and we can use that mathematical structure
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e podemos usar esta estrutura
07:36
to go and explore things like the world of ideas
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para explorar cousas como o mundo das ideas
07:39
to see what's being said, to see what's not being said,
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para ver o que se está a dicir, o que non;
07:42
and to be a little bit more human
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para ser un pouquiño máis humanos
07:43
and, hopefully, a little smarter.
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e, con sorte, un pouquiño máis listos.
07:45
Thank you.
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Grazas.
07:46
(Applause)
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(Aplausos)
ABOUT THE SPEAKERS
Eric Berlow - EcologistTED Senior Fellow Eric Berlow studies ecology and networks, exposing the interconnectedness of our ecosystems with climate change, government, corporations and more.
Why you should listen
Eric Berlow is an ecologist and network scientist who specializes in not specializing. A TED Senior Fellow, Berlow is recognized for his research on food webs and ecological networks and for creative approaches to complex problems. He was the founding director of the University of California's first environmental science center inside Yosemite National Park, where he continues to develop data-driven approaches to managing natural ecosystems.
In 2012 Berlow founded Vibrant Data Labs, which builds tools to use data for social good. Berlow's current projects range from helping spark an egalitarian personal data economy to protecting endangered amphibians in Yosemite to crowd-sourcing novel insights about human creativity. Berlow holds a Ph.D. from Oregon State University in marine ecology.
Eric Berlow | Speaker | TED.com
Sean Gourley - Physicist and military theorist
Sean Gourley, trained as a physicist, has turned his scientific mind to analyzing data about a messier topic: modern war and conflict. He is a TED Fellow.
Why you should listen
Sean Gourley's twin passions are physics (working on nanoscale blue-light lasers and self-assembled quantum nanowires) and politics (he once ran for a national elected office back home in New Zealand).
A Rhodes scholar, he's spent the past five years working at Oxford on complex adaptive systems and collective intelligent systems -- basically, using data to understand the nature of human conflict. As he puts it, "This research has taken me all over the world from the Pentagon, to the House of Lords, the United Nations and most recently to Iraq". Originally from New Zealand, he now lives in San Francisco, where he is the co-founder and CTO of Quid which is building a global intelligence platform. He's a 2009 TED Fellow.
In December 2009, Gourley and his team's research was published in the scientific journal Nature. He is co-founder and CTO of Quid.
Sean Gourley | Speaker | TED.com