TED@IBM
Susan Etlinger: What do we do with all this big data?
Suzan Etlindžer (Susan Etlinger): Šta radimo sa ovim velikim podacima?
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Da li jedna količina podataka čini da se osećate ugodnije? Uspešnije? Ukoliko je odgovor da, vaša interpretacija tih podataka je verovatno pogrešna. U iznenađujuće dirljivom govoru, Suzan Etlindžer objašnjava zašto, dok prikupljamo sve više i više podataka, moramo da ojačamo i umeće kritičkog mišljenja. Jer teško je preći sa pukog brojanja stvari na njihovo razumevanje.
Susan Etlinger - Data analyst
Susan Etlinger promotes the smart, well-considered and ethical use of data. Full bio
Susan Etlinger promotes the smart, well-considered and ethical use of data. Full bio
Double-click the English transcript below to play the video.
00:13
Technology has brought us so much:
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Tehnologija nam je donela puno toga:
00:16
the moon landing, the Internet,
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sletanje na Mesec, internet,
00:18
the ability to sequence the human genome.
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mogućnost da sekvenciramo
ljudski genom.
ljudski genom.
00:21
But it also taps into a lot of our deepest fears,
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Ali je i dotakla mnogo naših
najdubljih strahova,
najdubljih strahova,
00:24
and about 30 years ago,
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i pre oko 30 godina,
00:26
the culture critic Neil Postman wrote a book
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kritičar kulture Nil Postman
napisao je knjigu
napisao je knjigu
00:29
called "Amusing Ourselves to Death,"
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po imenu "Zabavljamo se na mrtvo",
00:31
which lays this out really brilliantly.
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koja to pokazuje na briljantan način.
00:34
And here's what he said,
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I evo šta je on rekao,
00:35
comparing the dystopian visions
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upoređujući distopijske vizije
00:38
of George Orwell and Aldous Huxley.
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Džordža Orvela i Oldosa Hakslija.
00:41
He said, Orwell feared we would become
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Rekao je: "Orvel se plašio
da ćemo postati
da ćemo postati
00:44
a captive culture.
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zatočena kultura.
00:47
Huxley feared we would become a trivial culture.
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Haksli se plašio da ćemo postati
beznačajna kultura.
beznačajna kultura.
00:50
Orwell feared the truth would be
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Orvel se plašio da će istina
00:52
concealed from us,
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biti sakrivena od nas,
00:54
and Huxley feared we would be drowned
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a Haksli se plašio da ćemo
se udaviti
se udaviti
00:57
in a sea of irrelevance.
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u moru nebitnih stvari".
00:59
In a nutshell, it's a choice between
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Ukratko, izbor se svodi na
01:01
Big Brother watching you
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Velikog Brata koji posmatra tebe
01:04
and you watching Big Brother.
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i tebe koji posmatraš "Velikog brata".
01:06
(Laughter)
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(Smeh)
01:08
But it doesn't have to be this way.
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Ali ne mora da bude tako.
01:10
We are not passive consumers
of data and technology.
of data and technology.
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Mi nismo pasivni potrošači
podataka i tehnologije.
podataka i tehnologije.
01:13
We shape the role it plays in our lives
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Mi oblikujemo ulogu koju
oni igraju u našim životima
oni igraju u našim životima
01:16
and the way we make meaning from it,
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i način na koji ih shvatamo,
01:18
but to do that,
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ali da bismo to uradili,
01:20
we have to pay as much attention to how we think
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moramo da obratimo onoliko
pažnje na to kako mislimo
pažnje na to kako mislimo
01:23
as how we code.
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koliko i na to kako kodiramo.
01:25
We have to ask questions, and hard questions,
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Moramo da postavljamo pitanja,
teška pitanja,
teška pitanja,
01:28
to move past counting things
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da pređemo sa brojanja stvari
01:30
to understanding them.
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na njihovo razumevanje.
01:33
We're constantly bombarded with stories
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Konstantno smo bombardovani pričama
01:35
about how much data there is in the world,
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o tome koliko podataka ima u svetu,
01:38
but when it comes to big data
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ali kada se radi
o velikoj količini podataka
o velikoj količini podataka
01:39
and the challenges of interpreting it,
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i izazovima njihovog tumačenja,
količina nije sve.
01:42
size isn't everything.
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01:44
There's also the speed at which it moves,
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Bitna je i brzina kojom se menjaju,
01:47
and the many varieties of data types,
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mnoge varijacije tipova podataka,
01:49
and here are just a few examples:
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i ovo su samo neki od primera:
01:51
images,
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fotografije,
01:53
text,
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tekst,
01:57
video,
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video,
01:59
audio.
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audio.
02:01
And what unites this disparate types of data
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I ono što ujedinjuje ove
različite tipove podataka
različite tipove podataka
02:04
is that they're created by people
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je to da su ih stvorili ljudi,
02:06
and they require context.
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a to povlači i kontekst.
02:09
Now, there's a group of data scientists
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Postoji grupa naučnika
koja se bavi podacima
koja se bavi podacima
02:12
out of the University of Illinois-Chicago,
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na Univerzitetu Ilinois u Čikagu,
02:14
and they're called the Health Media Collaboratory,
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zovu ih Health Media Collaboratory,
02:16
and they've been working with
the Centers for Disease Control
the Centers for Disease Control
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i oni sarađuju
sa Centrom za kontrolu bolesti
sa Centrom za kontrolu bolesti
02:19
to better understand
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da bi bolje razumeli
02:21
how people talk about quitting smoking,
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kako ljudi pričaju
kako će da prestanu da puše,
kako će da prestanu da puše,
02:23
how they talk about electronic cigarettes,
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kako pričaju o elektronskim cigaretama,
02:26
and what they can do collectively
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i šta oni mogu da urade kao kolektiv
02:28
to help them quit.
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da im pomognu da prestanu.
02:30
The interesting thing is, if you want to understand
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Interesantna stvar je da,
ako hoćete da razumete
ako hoćete da razumete
02:32
how people talk about smoking,
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kako ljudi pričaju o pušenju,
02:34
first you have to understand
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prvo morate da razumete
02:36
what they mean when they say "smoking."
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na šta misle kada kažu "pušenje".
02:39
And on Twitter, there are four main categories:
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Na Tviteru, postoje
četiri glavne kategorije:
četiri glavne kategorije:
02:43
number one, smoking cigarettes;
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broj jedan, pušenje cigareta;
02:46
number two, smoking marijuana;
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broj dva, pušenje marihuane;
02:48
number three, smoking ribs;
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broj tri, dimljena rebarca,
02:51
and number four, smoking hot women.
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i broj četiri, zgodne žene.
02:55
(Laughter)
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(Smeh)
02:58
So then you have to think about, well,
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Onda morate da razmislite,
03:00
how do people talk about electronic cigarettes?
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kako ljudi pričaju
o elektronskim cigaretama?
o elektronskim cigaretama?
03:02
And there are so many different ways
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Postoji toliko različitih načina
03:04
that people do this, and you can see from the slide
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na koji ljudi to rade,
i kao što vidite sa slajda,
i kao što vidite sa slajda,
03:07
it's a complex kind of a query.
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to je kompleksno pitanje.
03:09
And what it reminds us is that
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I ono nas podseća na to
03:13
language is created by people,
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da jezik stvaraju ljudi,
03:15
and people are messy and we're complex
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a ljudi su zbrkani i kompleksni
03:17
and we use metaphors and slang and jargon
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i koristimo metafore i sleng i žargon
03:20
and we do this 24/7 in many, many languages,
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i radimo to non-stop
na mnogo, mnogo jezika,
na mnogo, mnogo jezika,
03:23
and then as soon as we figure it out, we change it up.
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i taman kada se stvari slegnu,
mi sve promenimo.
mi sve promenimo.
03:27
So did these ads that the CDC put on,
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Dakle, da li su ove reklame
koje je CDC napravio,
koje je CDC napravio,
03:32
these television ads that featured a woman
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ove televizijske reklame
koje su imale ženu
koje su imale ženu
03:34
with a hole in her throat and that were very graphic
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sa rupom u grlu i koje su
bile vrlo snažne
bile vrlo snažne
03:36
and very disturbing,
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i vrlo uznemirujuće,
03:38
did they actually have an impact
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da li su one zapravo imale uticaja
03:40
on whether people quit?
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da ljudi ostave pušenje?
03:43
And the Health Media Collaboratory
respected the limits of their data,
respected the limits of their data,
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Health Media Collaboratory je
bila svesna ograničenosti podataka,
bila svesna ograničenosti podataka,
03:46
but they were able to conclude
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ali bili su u mogućnosti da zaključe
03:48
that those advertisements —
and you may have seen them —
and you may have seen them —
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da te reklame - i možda ste ih videli -
03:51
that they had the effect of jolting people
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da su imale efekat da trgnu ljude
03:54
into a thought process
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da uđu u proces razmišljanja
03:56
that may have an impact on future behavior.
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koji će možda imati uticaj
na buduće ponašanje.
na buduće ponašanje.
03:59
And what I admire and
appreciate about this project,
appreciate about this project,
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Ono čemu se divim i što poštujem
kod ovog projekta,
kod ovog projekta,
04:03
aside from the fact, including the fact
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pored činjenice,
uključujući činjenicu
uključujući činjenicu
04:05
that it's based on real human need,
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da je baziran
na realnoj ljudskoj potrebi,
na realnoj ljudskoj potrebi,
04:09
is that it's a fantastic example of courage
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je da je sjajan primer hrabrosti
04:12
in the face of a sea of irrelevance.
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uprkos moru irelevantnih stvari.
04:16
And so it's not just big data that causes
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I nije samo velika količina podataka
ta koja prouzrokuje
ta koja prouzrokuje
04:19
challenges of interpretation, because let's face it,
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probleme u interpretaciji jer,
budimo realni,
budimo realni,
04:22
we human beings have a very rich history
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mi ljudi imamo veoma bogatu istoriju
04:25
of taking any amount of data, no matter how small,
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da od bilo koje količine podataka,
ma koliko male,
ma koliko male,
04:27
and screwing it up.
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izvedemo loše zaključke.
04:29
So many years ago, you may remember
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Pre mnogo godina, možda se sećate,
04:33
that former President Ronald Reagan
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bivšeg predsednika Ronalda Regana
04:35
was very criticized for making a statement
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snažno su kritikovali zbog izjave
04:37
that facts are stupid things.
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da su činjenice glupost.
04:40
And it was a slip of the tongue, let's be fair.
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Bio je to lapsus, budimo pošteni.
04:43
He actually meant to quote John Adams' defense
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On je zapravo želeo da citira Džona Adamsa
04:45
of British soldiers in the Boston Massacre trials
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i njegovu odbranu britanskih vojnika
u suđenju za Bostonski masakr
u suđenju za Bostonski masakr
04:48
that facts are stubborn things.
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koji kaže da su činjenice neumoljive.
04:51
But I actually think there's
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Ono što ja zapravo mislim je da
04:54
a bit of accidental wisdom in what he said,
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u onome što je on rekao postoji
i delić slučajne mudrosti,
i delić slučajne mudrosti,
04:57
because facts are stubborn things,
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jer činjenice jesu neumoljive,
05:00
but sometimes they're stupid, too.
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ali su nekada i glupe.
05:03
I want to tell you a personal story
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Hoću da vam ispričam ličnu priču
05:05
about why this matters a lot to me.
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o tome zašto sve ovo meni
mnogo znači.
mnogo znači.
05:08
I need to take a breath.
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Moram da udahnem.
05:11
My son Isaac, when he was two,
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Mom sinu Isaku, kada je imao dve godine,
05:13
was diagnosed with autism,
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dijagnostikovan je autizam,
05:16
and he was this happy, hilarious,
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a on je bio srećan, razdragan,
05:18
loving, affectionate little guy,
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pun ljubavi, srdačan mali momak,
05:20
but the metrics on his developmental evaluations,
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ali pokazatelji njegove
razvojne evaluacije,
razvojne evaluacije,
05:23
which looked at things like
the number of words —
the number of words —
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koji su gledali na stvari kao što su
broj reči -
broj reči -
05:25
at that point, none —
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u tom trenutku, nijedna -
05:29
communicative gestures and minimal eye contact,
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gestikuliranje i minimalni kontakt očima,
05:33
put his developmental level
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rangirali su njegov razvojni nivo
05:35
at that of a nine-month-old baby.
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na nivo devetomesečne bebe.
05:39
And the diagnosis was factually correct,
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Dijagnoza je činjenično bila tačna,
05:42
but it didn't tell the whole story.
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ali nije pričala celu priču.
05:45
And about a year and a half later,
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Oko godinu i po dana kasnije,
05:46
when he was almost four,
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kada mu je bilo skoro četiri godine,
05:48
I found him in front of the computer one day
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zatekla sam ga za kompjuterom jednog dana
05:51
running a Google image search on women,
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kako pretražuje Gugl za slikama žena,
05:56
spelled "w-i-m-e-n."
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tražeći "žne".
06:00
And I did what any obsessed parent would do,
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I ja sam uradila isto što i svaki
opsednuti roditelj -
opsednuti roditelj -
06:02
which is immediately started
hitting the "back" button
hitting the "back" button
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odmah sam počela
da pritiskam dugme "nazad"
da pritiskam dugme "nazad"
06:04
to see what else he'd been searching for.
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kako bih videla šta je još pretraživao.
06:08
And they were, in order: men,
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Pretrage su bile: muškarci,
06:10
school, bus and computer.
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škola, autobus i kompjuter.
06:17
And I was stunned,
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Bila sam zatečena,
06:19
because we didn't know that he could spell,
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jer nismo znali da on ume da sriče,
06:21
much less read, and so I asked him,
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kamoli da čita, i pitala sam ga:
06:23
"Isaac, how did you do this?"
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"Isače, kako si ovo uradio?"
06:25
And he looked at me very seriously and said,
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Pogledao me je veoma ozbiljno
i rekao:
i rekao:
06:28
"Typed in the box."
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"Kucao sam u polje za tekst."
06:31
He was teaching himself to communicate,
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On je učio sebe da komunicira,
06:35
but we were looking in the wrong place,
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ali mi smo gledali na pogrešnom mestu,
06:38
and this is what happens when assessments
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i to je ono što se desi kad procene
06:40
and analytics overvalue one metric —
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i analize daju previše značaja
jednom pokazatelju -
jednom pokazatelju -
06:43
in this case, verbal communication —
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u ovom slučaju, verbalnoj komunikaciji -
06:45
and undervalue others, such
as creative problem-solving.
as creative problem-solving.
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a premalo značaja drugim, kao što je
kreativno rešavanje problema.
kreativno rešavanje problema.
06:51
Communication was hard for Isaac,
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Komunikacija je bila teška za Isaka,
06:53
and so he found a workaround
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pa je on našao drugi put
06:55
to find out what he needed to know.
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kako bi došao do onoga što ga zanima.
06:58
And when you think about it, it makes a lot of sense,
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I kada razmislite o tome,
to ima smisla,
to ima smisla,
07:00
because forming a question
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jer formiranje pitanja
07:02
is a really complex process,
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je veoma složen proces,
07:05
but he could get himself a lot of the way there
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ali je on mogao dosta toga da postigne
07:07
by putting a word in a search box.
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upisujući reč u polje za pretraživanje.
07:11
And so this little moment
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I tako je taj momenat
07:14
had a really profound impact on me
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imao veoma jak uticaj na mene
07:17
and our family
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i našu porodicu
07:18
because it helped us change our frame of reference
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jer nam je pomogao da promenimo fokus
07:21
for what was going on with him,
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u vezi sa onim što se dešavalo sa njim
07:24
and worry a little bit less and appreciate
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i da brinemo malo manje, a da više cenimo
07:27
his resourcefulness more.
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njegovu snalažljivost.
07:29
Facts are stupid things.
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Činjenice su glupost.
07:32
And they're vulnerable to misuse,
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I lako ih je pogrešno protumačiti,
07:34
willful or otherwise.
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svesno ili ne.
07:36
I have a friend, Emily Willingham, who's a scientist,
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Ja imam prijateljicu, Emili Vilingem,
koja je naučnik,
koja je naučnik,
07:39
and she wrote a piece for Forbes not long ago
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i ona je nedavno napisala članak za Forbs
07:42
entitled "The 10 Weirdest Things
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pod imenom "10 najčudnijih stvari
07:44
Ever Linked to Autism."
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ikada vezanih za autizam".
07:45
It's quite a list.
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Jako zanimljiva lista.
07:48
The Internet, blamed for everything, right?
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Internet, krivac za sve, je l' da?
07:52
And of course mothers, because.
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I naravno majke, jer eto.
07:56
And actually, wait, there's more,
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I zapravo, čekajte, ima još,
07:57
there's a whole bunch in
the "mother" category here.
the "mother" category here.
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postoji čitava gomila
u kategoriji "majka".
u kategoriji "majka".
08:01
And you can see it's a pretty
rich and interesting list.
rich and interesting list.
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I možete da vidite da je prilično bogata
i zanimljiva lista.
i zanimljiva lista.
08:05
I'm a big fan of
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Ja sam veliki fan stavke
"trudnoća blizu autoputa".
08:08
being pregnant near freeways, personally.
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Poslednji je interesantan,
08:11
The final one is interesting,
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08:13
because the term "refrigerator mother"
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jer je termin "frižider majka"
zapravo bio originalna hipoteza
08:16
was actually the original hypothesis
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za uzrok autizma,
08:19
for the cause of autism,
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i opisuje nekoga
ko je hladan i bez ljubavi.
ko je hladan i bez ljubavi.
08:20
and that meant somebody
who was cold and unloving.
who was cold and unloving.
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08:23
And at this point, you might be thinking,
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U ovom trenutku, možda mislite,
08:24
"Okay, Susan, we get it,
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"U redu, Suzan, razumemo,
08:26
you can take data, you can
make it mean anything."
make it mean anything."
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moguće je uzeti podatke
i napraviti od njih bilo šta."
i napraviti od njih bilo šta."
08:28
And this is true, it's absolutely true,
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I to je tačno, to je apsolutno tačno,
08:32
but the challenge is that
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ali izazov je da
08:38
we have this opportunity
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imamo ovu priliku
da sami pokušamo da shvatimo smisao,
08:40
to try to make meaning out of it ourselves,
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jer iskreno, podaci ne stvaraju smisao.
Mi ga stvaramo.
Mi ga stvaramo.
08:43
because frankly, data doesn't
create meaning. We do.
create meaning. We do.
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08:48
So as businesspeople, as consumers,
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Pa kao poslovni ljudi, kao potrošači,
08:51
as patients, as citizens,
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kao pacijenti, kao građani,
mi imamo odgovornost, po mom mišljenju,
08:54
we have a responsibility, I think,
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08:56
to spend more time
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da provodimo više vremena
08:58
focusing on our critical thinking skills.
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fokusirajući se na
veštinu kritičkog razmišljanja.
veštinu kritičkog razmišljanja.
Zašto?
09:01
Why?
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09:02
Because at this point in our history, as we've heard
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Zato što u ovom trenutku
naše istorije, kao što smo čuli
naše istorije, kao što smo čuli
mnogo puta do sad,
09:06
many times over,
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09:07
we can process exabytes of data
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mi možemo da obradimo
eksabajte podataka
eksabajte podataka
09:09
at lightning speed,
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brzinom svetlosti,
09:11
and we have the potential to make bad decisions
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pa imamo potencijal da donosimo
loše odluke
loše odluke
mnogo brže, efikasnije
09:15
far more quickly, efficiently,
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i sa većim posledicama nego ikada pre.
09:17
and with far greater impact than we did in the past.
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09:22
Great, right?
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Sjajno, zar ne?
09:23
And so what we need to do instead
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Ono što treba da uradimo
umesto toga
umesto toga
09:26
is spend a little bit more time
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je da potrošimo malo više vremena
09:29
on things like the humanities
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na stvari poput humanističkih nauka
09:31
and sociology, and the social sciences,
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i sociologije, i društvenih nauka,
09:35
rhetoric, philosophy, ethics,
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retorike, filozofije, etike
jer one pružaju kontekst
koji je tako bitan
koji je tako bitan
09:37
because they give us context that is so important
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09:40
for big data, and because
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za velike količine podataka,
jer nam one pomažu da budemo
bolji u kritičkom mišljenju.
bolji u kritičkom mišljenju.
09:42
they help us become better critical thinkers.
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09:45
Because after all, if I can spot
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Jer na kraju svega,
ako ja mogu da primetim
ako ja mogu da primetim
09:49
a problem in an argument, it doesn't much matter
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problem u nekom argumentu,
nije mnogo bitno
nije mnogo bitno
09:52
whether it's expressed in words or in numbers.
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da li je on izražen
u rečima ili brojevima.
u rečima ili brojevima.
09:54
And this means
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A to zahteva
09:57
teaching ourselves to find
those confirmation biases
those confirmation biases
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da naučimo sebe da prepoznajemo
pristrasnost u zaključcima
pristrasnost u zaključcima
i lažne korelacije
10:02
and false correlations
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i da možemo da primetimo
čistu emotivnu manipulaciju
čistu emotivnu manipulaciju
10:03
and being able to spot a naked emotional appeal
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10:05
from 30 yards,
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sa 30 metara,
10:07
because something that happens after something
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jer ako se nešto desilo posle nečega,
10:10
doesn't mean it happened
because of it, necessarily,
because of it, necessarily,
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ne znači da se nužno desilo
baš zbog toga,
baš zbog toga,
i ako mi dozvolite da budem štreber
na sekund,
na sekund,
10:13
and if you'll let me geek out on you for a second,
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10:15
the Romans called this
"post hoc ergo propter hoc,"
"post hoc ergo propter hoc,"
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Rimljani su ovo zvali
"Post hoc ergo propter hoc",
"Post hoc ergo propter hoc",
10:19
after which therefore because of which.
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"Posle toga, dakle zbog toga".
To znači i preispitivanje
disciplina kao što je demografija.
disciplina kao što je demografija.
10:22
And it means questioning
disciplines like demographics.
disciplines like demographics.
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Zašto? Zato što su takve discipline
zasnovane na pretpostavkama
zasnovane na pretpostavkama
10:26
Why? Because they're based on assumptions
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10:29
about who we all are based on our gender
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o tome ko smo mi na osnovu
našeg pola
našeg pola
10:31
and our age and where we live
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i naših godina i gde živimo
10:32
as opposed to data on what
we actually think and do.
we actually think and do.
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umesto na osnovu toga
šta mislimo i radimo.
šta mislimo i radimo.
10:36
And since we have this data,
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Pošto imamo tu veliku
količinu podataka,
količinu podataka,
10:38
we need to treat it with appropriate privacy controls
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moramo da je tretiramo sa
prikladnom kontrolom privatnosti
prikladnom kontrolom privatnosti
10:41
and consumer opt-in,
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i pristankom potrošača,
10:44
and beyond that, we need to be clear
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i pored toga, moramo biti jasni
kada su u pitanju naše hipoteze,
10:47
about our hypotheses,
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10:49
the methodologies that we use,
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metodologije koje koristimo,
10:52
and our confidence in the result.
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i naša uverenost u rezultat.
10:55
As my high school algebra teacher used to say,
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Kao što je moj učitelj algebre
iz srednje škole umeo da kaže:
iz srednje škole umeo da kaže:
10:57
show your math,
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"Pokaži proces,
10:59
because if I don't know what steps you took,
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jer ako ne znam koje si korake napravila,
11:02
I don't know what steps you didn't take,
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ne znam ni koje korake nisi napravila,
11:04
and if I don't know what questions you asked,
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i ako ne znam koja pitanja si postavila,
11:07
I don't know what questions you didn't ask.
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ne znam ni koja pitanja nisi postavila".
11:10
And it means asking ourselves, really,
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I to znači zapitati se, zapravo,
11:11
the hardest question of all:
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najteže pitanje od svih:
11:13
Did the data really show us this,
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"Da li su nam podaci ovo pokazali,
11:16
or does the result make us feel
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ili da li rezultat čini da se osećamo
11:19
more successful and more comfortable?
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uspešnije i zadovoljnije?"
11:23
So the Health Media Collaboratory,
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Health Media Collaboratory,
11:25
at the end of their project, they were able
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na kraju svog projekta, pokazala je
11:27
to find that 87 percent of tweets
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da je 87 procenata tvitova
11:30
about those very graphic and disturbing
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baš o onim snažnim i uznemirujućim
11:32
anti-smoking ads expressed fear,
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antipušačkim reklamama izražavalo strah,
11:36
but did they conclude
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ali da li su zaključili
11:38
that they actually made people stop smoking?
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da su zapravo učinili
da ljudi prestanu da puše?
da ljudi prestanu da puše?
11:41
No. It's science, not magic.
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Ne. To je nauka, a ne magija.
11:44
So if we are to unlock
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Ako želimo da otključamo
11:47
the power of data,
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moć podataka,
11:50
we don't have to go blindly into
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ne moramo slepo da pratimo
11:54
Orwell's vision of a totalitarian future,
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Orvelovu viziju totalitarne budućnosti,
11:57
or Huxley's vision of a trivial one,
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ili Hakslijevu viziju trivijalne,
12:00
or some horrible cocktail of both.
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ili neki užasavajući koktel obe.
12:03
What we have to do
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Ono što moramo da uradimo
12:05
is treat critical thinking with respect
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je da tretiramo kritičko mišljenje
sa poštovanjem
sa poštovanjem
12:08
and be inspired by examples
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i da budemo inspirisani primerima
12:10
like the Health Media Collaboratory,
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kao što je Health Media Collaboratory,
12:13
and as they say in the superhero movies,
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i kao što kažu
u filmovima o superherojima,
u filmovima o superherojima,
hajde da koristimo naše moći
da činimo dobro.
da činimo dobro.
12:15
let's use our powers for good.
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12:17
Thank you.
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Hvala vam.
(Aplauz)
12:19
(Applause)
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ABOUT THE SPEAKER
Susan Etlinger - Data analystSusan Etlinger promotes the smart, well-considered and ethical use of data.
Why you should listen
Susan Etlinger is an industry analyst with Altimeter Group, where she focuses on data and analytics. She conducts independent research and has authored two intriguing reports: “The Social Media ROI Cookbook” and “A Framework for Social Analytics.” She also advises global clients on how to work measurement into their organizational structure and how to extract insights from the social web which can lead to tangible actions. In addition, she works with technology innovators to help them refine their roadmaps and strategies.
Etlinger is on the board of The Big Boulder Initiative, an industry organization dedicated to promoting the successful and ethical use of social data. She is regularly interviewed and asked to speak on data strategy and best practices, and has been quoted in media outlets like The Wall Street Journal, The New York Times, and the BBC.
Susan Etlinger | Speaker | TED.com