TEDSalon NY2013
Amy Webb: How I hacked online dating
Sådan hackede jeg onlinedating
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Readability: 3.7
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Amy Webb havde ikke noget held med onlinedating. De dates, hun kunne lide, skrev ikke tilbage, og hendes egen profil tiltrak kun fårekyllinger (og det, der var værre). Men som enhver datafan ville gøre, begyndte hun at opstille et regneark. Hør hendes historie om, hvordan hun gik fra at hacke sit online-datingliv -- med frustrerende, sjove og livsændrende resultater.
Amy Webb - Founder and CEO, Future Today Institute
Amy Webb is a futurist and founder of the Future Today Institute, and is the award-winning author of three books, including “Data: A Love Story” and “The Signals Are Talking: Why Today’s Fringe Is Tomorrow’s Mainstream.” Full bio
Amy Webb is a futurist and founder of the Future Today Institute, and is the award-winning author of three books, including “Data: A Love Story” and “The Signals Are Talking: Why Today’s Fringe Is Tomorrow’s Mainstream.” Full bio
Double-click the English transcript below to play the video.
00:12
So my name is Amy Webb,
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Mit navn er Amy Webb,
00:15
and a few years ago I found myself at the end
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og for et par år siden stod jeg i slutningen af
00:17
of yet another fantastic relationship
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endnu et fantastisk forhold
00:20
that came burning down in a spectacular fashion.
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der sluttede i spektakulære flammer.
00:23
And I thought, you know, what's wrong with me?
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Og jeg tænkte: "Hvad er der galt med mig?
00:26
I don't understand why this keeps happening.
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Jeg forstår ikke, hvorfor dette bliver ved med at ske."
00:28
So I asked everybody in my life
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Så jeg spurgte alle i mit liv om,
00:30
what they thought.
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hvad de tænkte.
00:32
I turned to my grandmother,
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Jeg spurgte min bedstemor,
00:33
who always had plenty of advice,
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der altid har masser af råd,
00:36
and she said, "Stop being so picky.
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og hun sagde, "Lad være med at være så kræsen.
00:39
You've got to date around.
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Du er nødt til at gå på dates.
00:40
And most importantly,
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Og allervigtigst,
00:42
true love will find you when you least expect it."
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den ægte kærlighed finder dig, når du mindst venter det."
00:46
Now as it turns out,
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Det viser sig,
00:48
I'm somebody who thinks a lot about data,
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at jeg er en person, der tænker meget på data,
00:50
as you'll soon find.
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som I snart finder ud af.
00:52
I am constantly swimming in numbers
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Jeg svømmer konstant i tal,
00:55
and formulas and charts.
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formler og diagrammer.
00:56
I also have a very tight-knit family,
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Jeg har også en meget fast sammentømret familie,
00:59
and I'm very, very close with my sister,
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jeg har et meget, meget nært forhold til min søster,
01:01
and as a result, I wanted to have
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og derfor ønskede jeg også
01:02
the same type of family when I grew up.
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den samme form for familie, når jeg blev voksen.
01:04
So I'm at the end of this bad breakup,
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Jeg er altså i slutningen af dette slemme brud,
01:06
I'm 30 years old,
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jeg er 30 år gammel,
01:08
I figure I'm probably going to have
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jeg tror, at jeg skal date nogen i
01:09
to date somebody for about six months
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omkring et halvt års tid,
01:11
before I'm ready to get monogamous
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før jeg er klar til at blive monogam
01:13
and before we can sort of cohabitate,
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før vi mere eller mindre kan leve sammen,
01:15
and we have to have that happen for a while before we can get engaged.
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og det skal ske i noget tid, inden vi bliver forlovede.
01:18
And if I want to start having children by the time I'm 35,
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Og hvis jeg vil til at have børn, inden jeg er 35,
01:21
that meant that I would have had to have been
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betød det, at jeg skulle have været
01:23
on my way to marriage five years ago.
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på vej ind i ægteskabet for fem år siden.
01:26
So that wasn't going to work.
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Så det skulle ikke være sådan.
01:27
If my strategy was to least-expect my way
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Hvis min strategi var at mindst forvente mig
01:30
into true love, then the variable that I had
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til ægte kærlighed, så skulle jeg tage højde for
01:32
to deal with was serendipity.
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den variabel, der hedder lykketræf.
01:34
In short, I was trying to figure out, well,
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Kort sagt prøvede jeg at regne ud,
01:36
what's the probability of my finding Mr. Right?
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hvad sandsynligheden var for, at jeg kunne finde
ridderen på den hvide hest?
ridderen på den hvide hest?
01:40
Well, at the time I was living in the city of Philadelphia,
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På det tidspunkt boede jeg i Philadelphia,
01:42
and it's a big city, and I figured,
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og det er en stor by, så jeg tænkte,
01:45
in this entire place, there are lots of possibilities.
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at på hele dette område er der masser af muligheder.
01:48
So again, I started doing some math.
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Jeg begyndte igen med nogle udregninger.
01:50
Population of Philadelphia: It has 1.5 million people.
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Indbyggertallet i Philadelphia: der er 1,5 million mennesker.
01:54
I figure about half of that are men,
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Jeg går ud fra, at cirka halvdelen er mænd,
01:55
so that takes the number down to 750,000.
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så det halverer tallet til 750.000.
01:58
I'm looking for a guy between the ages of 30 and 36,
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Jeg leder efter en fyr, der er mellem 30 og 36 år,
02:01
which was only four percent of the population,
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hvilket kun var 4 procent af indbyggertallet,
02:04
so now I'm dealing with the possibility of 30,000 men.
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så nu har jeg at gøre med 30.000 mulige mænd.
02:07
I was looking for somebody who was Jewish,
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Jeg ledte efter en, der var jødisk,
02:08
because that's what I am and that was important to me.
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for det er jeg, og det var vigtigt for mig.
02:11
That's only 2.3 percent of the population.
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Det er kun 2,3 procent af indbyggertallet.
02:13
I figure I'm attracted to maybe one out of 10
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Jeg antager, at jeg kun tiltrækkes af én ud af ti
02:15
of those men,
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af de mænd,
02:18
and there was no way I was going
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og jeg skulle på ingen måde
02:20
to deal with somebody who was an avid golfer.
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have med nogen at gøre, der var ivrige golfspillere.
02:22
So that basically meant there were 35 men for me
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Så det betød dybest set, at der var 35 mænd til mig,
02:25
that I could possibly date
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som jeg på nogen måde kunne få lyst til at date
02:28
in the entire city of Philadelphia.
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i hele Philadelphia.
02:32
In the meantime, my very large Jewish family
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I mellemtiden var hele min meget store, jødiske familie
02:35
was already all married and well on their way
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allerede gift og godt i gang med
02:38
to having lots and lots of children,
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at få masser og masser af børn,
02:40
and I felt like I was under tremendous peer pressure
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så jeg følte, at jeg var under et enormt gruppepres
02:42
to get my life going already.
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for at få gang i mit liv.
02:44
So if I have two possible strategies at this point
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Jeg har nærmest kun to mulige strategier
på dette tidspunkt,
på dette tidspunkt,
02:46
I'm sort of figuring out.
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som jeg prøver at regne ud.
02:47
One, I can take my grandmother's advice
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Som det første kan jeg følge min bedstemors råd
02:50
and sort of least-expect my way
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og på en eller anden måde mindst-forvente
02:52
into maybe bumping into the one
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at jeg støder ind i den eneste ene
02:55
out of 35 possible men in the entire
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ud af de 35 mulige mænd i hele
02:57
1.5 million-person city of Philadelphia,
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byen Philadelphia med 1,5 millioner indbyggere
03:01
or I could try online dating.
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eller jeg kunne prøve online-dating.
03:04
Now, I like the idea of online dating,
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Jeg kan faktisk godt lide ideen om online-dating,
03:06
because it's predicated on an algorithm,
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fordi det er baseret på en algoritme,
03:08
and that's really just a simple way of saying
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og det er i virkeligheden en simpel måde at sige
03:10
I've got a problem, I'm going to use some data,
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at man har et problem, man vil anvende nogle data,
03:12
run it through a system
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køre det gennem et system
03:13
and get to a solution.
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og finde frem til en løsning.
03:16
So online dating is the second most popular way
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Online-dating er den næstmest populære måde
03:18
that people now meet each other,
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for mennesker at møde hinanden på,
03:20
but as it turns out, algorithms have been around
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men det viser sig, at de algoritmer har været anvendt
03:22
for thousands of years in almost every culture.
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i tusindvis af år i næsten alle kulturer.
03:25
In fact, in Judaism, there were matchmakers
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Faktisk var der i jødedommen "Kirsten Gifteknive"
03:28
a long time ago, and though
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allerede for lang tid siden, og selvom
03:29
they didn't have an explicit algorithm per se,
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de ikke nødvendigvis havde en algoritme som sådan,
03:32
they definitely were running through formulas in their heads,
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så gennemgik de bestemt nogle formler i tankerne,
03:34
like, is the girl going to like the boy?
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f.eks. vil pigen kunne lide drengen?
03:36
Are the families going to get along?
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Vil familierne finde ud af det med hinanden?
03:38
What's the rabbi going to say?
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Hvad vil rabbineren sige?
03:39
Are they going to start having children right away?
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Begynder de at få børn med det samme?
03:42
And the matchmaker would sort of think through all of this,
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Og giftekniven vil overveje alle disse ting,
03:45
put two people together, and that would be the end of it.
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sætte to mennesker sammen, og det vil så være det.
03:47
So in my case, I thought,
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Men i mit tilfælde,
03:49
well, will data and an algorithm
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kunne data og algoritmer
03:52
lead me to my Prince Charming?
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så føre mig til min ridder på den hvide hest?
03:54
So I decided to sign on.
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Jeg besluttede mig for at melde mig ind.
03:56
Now, there was one small catch.
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Der var dog en lille hage.
03:57
As I'm signing on to the various dating websites,
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Mens jeg meldte mig til de forskellige datingsider,
04:00
as it happens, I was really, really busy.
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havde jeg faktisk meget, meget travlt.
04:02
But that actually wasn't the biggest problem.
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Men det var faktisk ikke det største problem.
04:05
The biggest problem is that I hate
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Det største problem er, at jeg hader
04:07
filling out questionnaires of any kind,
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at udfylde nogen form for spørgeskemaer,
04:09
and I certainly don't like questionnaires
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og jeg kan bestemt ikke lide spørgeskemaer
04:11
that are like Cosmo quizzes.
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der er ligesom Cosmo-quizzer.
04:13
So I just copied and pasted from my résumé.
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Så jeg tog mit cv og kopierede ind fra dét.
04:16
(Laughter)
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(Latter)
04:21
So in the descriptive part up top,
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I den beskrivende del øverst
04:24
I said that I was an award-winning journalist
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skrev jeg, at jeg var en prisvindende journalist
04:26
and a future thinker.
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og en fremtidstænker.
04:28
When I was asked about fun activities and
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Da jeg blev spurgt om sjove aktiviteter og
04:30
my ideal date, I said monetization
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min ideelle date, skrev jeg møntning
04:33
and fluency in Japanese.
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og at kunne flydende japansk.
04:36
I talked a lot about JavaScript.
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Jeg skrev meget om JavaScript.
04:38
So obviously this was not the best way
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Så dette var åbenlyst ikke den bedste måde
04:42
to put my most sexy foot forward.
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at vise mig fra min sexede side.
04:45
But the real failure was that
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Men den helt store fejl var,
04:47
there were plenty of men for me to date.
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at der var masser af mænd, jeg kunne date.
04:50
These algorithms had a sea full of men
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Disse algoritmer fremkaldte et hav af mænd,
04:52
that wanted to take me out on lots of dates --
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der ville invitere mig på masser af dates --
04:55
what turned out to be truly awful dates.
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hvad der viste sig at være forfærdelige dates.
04:59
There was this guy Steve, the I.T. guy.
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Der var f.eks. Steve, it-fyren.
05:01
The algorithm matched us up
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Algoritmen satte os sammen,
05:03
because we share a love of gadgets,
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fordi vi deler en forkærlighed for gadgets,
05:05
we share a love of math and data and '80s music,
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vi deler en forkærlighed for matematik, data og 80'er-musik,
05:09
and so I agreed to go out with him.
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så jeg lod ham invitere mig ud.
05:11
So Steve the I.T. guy invited me out
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It-fyren Steve inviterede mig ud
05:13
to one of Philadelphia's white-table-cloth,
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på en af Philadelphias fine,
05:15
extremely expensive restaurants.
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ekstremt dyre restauranter.
05:17
And we went in, and right off the bat,
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Vi gik ind, og lige fra starten
05:19
our conversation really wasn't taking flight,
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kom vores samtale ikke rigtigt i gang,
05:22
but he was ordering a lot of food.
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men han bestilte en masse mad.
05:24
In fact, he didn't even bother looking at the menu.
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Han så faktisk slet ikke på menukortet.
05:26
He was ordering multiple appetizers,
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Han bestilte flere forretter,
05:28
multiple entrées, for me as well,
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flere hovedretter, også til mig,
05:31
and suddenly there are piles and piles of food on our table,
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og pludselig var der bunker og bunker af mad på vores bord,
05:33
also lots and lots of bottles of wine.
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også en hel masse flasker vin.
05:36
So we're nearing the end of our conversation
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Vi nærmer os enden på vores samtale
05:38
and the end of dinner, and I've decided
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og middagens slutning, og jeg har besluttet
05:39
Steve the I.T. guy and I are really just not meant for each other,
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at it-fyren Steve og jeg ikke hører sammen,
05:42
but we'll part ways as friends,
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men at vi deles som venner,
05:44
when he gets up to go to the bathroom,
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og så rejser han sig for at gå på toilet.
05:47
and in the meantime the bill comes to our table.
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I mellemtiden kommer regningen til vores bord.
05:50
And listen, I'm a modern woman.
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Og hør engang, jeg er en moderne kvinde.
05:53
I am totally down with splitting the bill.
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Jeg har det fint med at dele regningen.
05:56
But then Steve the I.T. guy didn't come back. (Gasping)
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Men it-fyren Steve kom ikke tilbage. (Gisp)
06:00
And that was my entire month's rent.
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Og det var altså en hel måneds husleje.
06:04
So needless to say, I was not having a good night.
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Jeg behøver nok ikke fortælle,
at jeg ikke havde en god aften.
at jeg ikke havde en god aften.
06:08
So I run home, I call my mother, I call my sister,
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Jeg løber så hjem, ringer til min mor, ringer til min søster,
06:11
and as I do, at the end of each one of these
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og mens jeg gør det, efter hver af disse
06:14
terrible, terrible dates,
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forfærdelige, forfærdelige dates,
06:16
I regale them with the details.
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underholder jeg dem med detaljerne.
06:18
And they say to me,
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De siger til mig,
06:20
"Stop complaining."
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"Hold op med at brokke dig."
06:22
(Laughter)
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(Latter)
06:23
"You're just being too picky."
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"Du er bare for kræsen."
06:26
So I said, fine, from here on out
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Så jeg sagde; "Fint, fra nu af
06:28
I'm only going on dates where I know
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tager jeg kun på dates, hvor jeg ved,
06:29
that there's wi-fi, and I'm bringing my laptop.
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at der er wifi, og jeg tager min laptop med.
06:31
I'm going to shove it into my bag,
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Jeg putter den i min taske,
06:33
and I'm going to have this email template,
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og så har jeg en email-skabelon,
06:35
and I'm going to fill it out and collect information
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som jeg udfylder for at indsamle oplysninger
06:37
on all these different data points during the date
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på en masse forskellige datapunkter i løbet af daten
06:40
to prove to everybody that empirically,
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for at bevise for alle, at empirisk set
06:42
these dates really are terrible. (Laughter)
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er alle disse dates virkelig forfærdelige. (Latter)
06:44
So I started tracking things like
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Så jeg begyndte at holde styr på ting som
06:46
really stupid, awkward, sexual remarks;
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virkelig dumme, akavede, seksuelle bemærkninger;
06:49
bad vocabulary;
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dårligt ordforråd;
06:51
the number of times a man forced me to high-five him.
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antallet af gange, en mand tvang mig til at give ham high-five.
06:54
(Laughter)
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(Latter)
06:56
So I started to crunch some numbers,
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Jeg begyndte også at kigge på nogle tal,
07:00
and that allowed me to make some correlations.
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og derudfra kunne jeg beregne nogle sammenfald.
07:03
So as it turns out,
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Det viser sig
07:06
for some reason, men who drink Scotch
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af en eller anden grund, at mænd, der drikker whisky
07:09
reference kinky sex immediately.
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hænger sammen med fræk sex fra starten.
07:11
(Laughter)
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(Latter)
07:13
Well, it turns out that these
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Det viser sig, at de
07:16
probably weren't bad guys.
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sikkert ikke var dårlige fyre.
07:17
There were just bad for me.
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De var bare dårlige til mig.
07:19
And as it happens, the algorithms that were setting us up,
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Algoritmerne, der satte os sammen,
07:23
they weren't bad either.
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var heller ikke dårlige.
07:24
These algorithms were doing exactly
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Disse algoritmer gjorde præcis det,
07:26
what they were designed to do,
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de var designet til at gøre,
07:27
which was to take our user-generated information,
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nemlig at tage vores brugerskabte oplysninger,
07:30
in my case, my résumé,
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i mit tilfælde, mit cv,
07:32
and match it up with other people's information.
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og matche dem med andre menneskers oplysninger.
07:35
See, the real problem here is that,
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Det virkelige problem her er,
07:36
while the algorithms work just fine,
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at mens algoritmerne fungerer helt fint,
07:38
you and I don't, when confronted
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gør du og jeg det ikke, når vi står over for
07:40
with blank windows where we're supposed
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tomme felter, som vi skal
07:42
to input our information online.
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udfylde med vores oplysninger.
07:44
Very few of us have the ability
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Meget få af os har evnen
07:46
to be totally and brutally honest with ourselves.
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til at være totalt og hudløst ærlige over for os selv.
07:50
The other problem is that these websites are asking us
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Det andet problem er, at disse hjemmesider stiller os
07:52
questions like, are you a dog person or a cat person?
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spørgsmål som: er man et hundemenneske
eller et kattemenneske?
eller et kattemenneske?
07:55
Do you like horror films or romance films?
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Kan man lide gyserfilm eller romantiske film?
07:58
I'm not looking for a pen pal.
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Jeg leder ikke efter en penneven.
08:00
I'm looking for a husband. Right?
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Jeg leder efter en mand. Okay?
08:02
So there's a certain amount of superficiality in that data.
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Der er altså en vis mængde overfladiskhed i de data.
08:05
So I said fine, I've got a new plan.
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Jeg fik så en ny plan.
08:08
I'm going to keep using these online dating sites,
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1998
Jeg vil blive ved med at bruge disse online-datingsider,
08:10
but I'm going to treat them as databases,
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men jeg vil behandle dem som databaser,
08:12
and rather than waiting for an algorithm to set me up,
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og i stedet for at vente på en algoritme,
der sætter os sammen,
der sætter os sammen,
08:15
I think I'm going to try reverse-engineering this entire system.
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vil jeg prøve at vende hele systemet om.
08:19
So knowing that there was superficial data
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Med den viden, at der blev brugt overfladiske data
08:22
that was being used to match me up with other people,
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til at sætte mig sammen med andre mennesker,
08:24
I decided instead to ask my own questions.
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besluttede jeg mig i stedet for at stille mine egne spørgsmål.
08:27
What was every single possible thing
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1638
Hvad var hver eneste mulige ting,
08:28
that I could think of that I was looking for in a mate?
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2903
som jeg kunne komme på,
at jeg ledte efter hos en partner?
at jeg ledte efter hos en partner?
08:31
So I started writing and writing and writing,
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Jeg begyndte at skrive og skrive og skrive,
08:36
and at the end, I had amassed
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og til slut havde jeg akkumuleret
08:38
72 different data points.
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2581
72 forskellige datapunkter.
08:41
I wanted somebody was Jew...ish,
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Jeg ville have en, der var jøde…isk,
08:43
so I was looking for somebody who had the same
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511579
1697
så jeg ledte efter nogen, der havde samme
08:45
background and thoughts on our culture,
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2561
baggrund og tanker omkring vores kultur,
08:47
but wasn't going to force me to go to shul
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1573
men som ikke ville tvinge mig til at gå til shul
08:49
every Friday and Saturday.
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517410
2333
hver fredag og lørdag.
08:51
I wanted somebody who worked hard,
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519743
1590
Jeg ville have en, der arbejdede hårdt,
08:53
because work for me is extremely important,
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1884
fordi arbejde er ekstremt vigtigt for mig,
08:55
but not too hard.
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1618
men ikke for hårdt.
08:56
For me, the hobbies that I have
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524835
1680
For mig er mine hobbyer
08:58
are really just new work projects that I've launched.
220
526515
2836
i virkeligheden bare nye arbejdsprojekter,
jeg har sat i gang.
jeg har sat i gang.
09:01
I also wanted somebody who not only wanted two children,
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529351
3165
Jeg ville også have en, der ikke kun ville have to børn,
09:04
but was going to have the same attitude toward parenting that I do,
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2895
men som havde samme indstilling til opdragelse som jeg,
09:07
so somebody who was going to be totally okay
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1931
med andre ord en, der ville have det helt fint med
09:09
with forcing our child to start taking piano lessons at age three,
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537342
3535
at tvinge vores børn til at begynde med klaverundervisning i treårsalderen,
09:12
and also maybe computer science classes
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3656
og måske også computerundervisning,
09:16
if we could wrangle it.
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544533
1904
hvis vi kunne få det til at fungere.
09:18
So things like that, but I also wanted somebody
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546437
1732
Ting som det, men jeg ville også finde en,
09:20
who would go to far-flung, exotic places,
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2063
der ville tage til fjerne, eksotiske steder med mif,
09:22
like Petra, Jordan.
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1628
f.eks. Petra i Jordan.
09:23
I also wanted somebody who would weigh
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1505
Jeg ville også have en, der altid ville veje
09:25
20 pounds more than me at all times,
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553365
1928
9 kilo mere end mig,
09:27
regardless of what I weighed.
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1370
uanset hvad jeg selv vejer.
09:28
(Laughter)
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2402
(Latter)
09:31
So I now have these 72 different data points,
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559065
3074
Så nu har jeg 72 forskellige datapunkter,
09:34
which, to be fair, is a lot.
235
562139
2046
som ærlig talt er ret mange.
09:36
So what I did was, I went through
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564185
1382
Jeg gennemgik dem derfor
09:37
and I prioritized that list.
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1822
og prioriterede den liste.
09:39
I broke it into a top tier and a second tier of points,
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3953
Jeg inddelte den i to lag med punkter,
09:43
and I ranked everything starting at 100
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3225
hvor jeg rangerede alt begyndende med 100
09:46
and going all the way down to 91,
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574567
1980
og helt ned til 91,
09:48
and listing things like I was looking for somebody who was really smart,
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576547
3240
og opstillede ting som, at jeg leder efter en meget klog mand,
09:51
who would challenge and stimulate me,
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579787
1712
som kan udfordre og stimulere mig,
09:53
and balancing that with a second tier
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2256
og balancerede det med det andet lag
09:55
and a second set of points.
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2025
og et andet sæt punkter.
09:57
These things were also important to me
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585780
1405
Disse ting var også vigtige for mig,
09:59
but not necessarily deal-breakers.
246
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4816
men ikke nødvendigvis nok til at bryde kontrakten.
10:04
So once I had all this done,
247
592001
1421
Da jeg havde gjort alt dette,
10:05
I then built a scoring system,
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593422
1809
lavede jeg et scoringssystem,
10:07
because what I wanted to do
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595231
2623
fordi jeg ønskede at
10:09
was to sort of mathematically calculate
250
597854
1850
lave en matematisk udregning på,
10:11
whether or not I thought the guy that I found online
251
599704
2506
om jeg mente, at fyren, som jeg havde fundet online,
10:14
would be a match with me.
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1447
ville passe til mig.
10:15
I figured there would be a minimum of 700 points
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603657
2443
Jeg tænkte, at det krævede mindst 700 point,
10:18
before I would agree to email somebody
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606100
1546
før jeg ville gå med til at send emails til nogen
10:19
or respond to an email message.
255
607646
2166
eller svare på en email.
10:21
For 900 points, I'd agree to go out on a date,
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609812
2002
Ved 900 point ville jeg gå med på en date,
10:23
and I wouldn't even consider any kind of relationship
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611814
2681
og jeg ville slet ikke så meget som overveje
nogen form for forhold
nogen form for forhold
10:26
before somebody had crossed the 1,500 point threshold.
258
614495
4188
før nogen havde krydset 1.500 point-tærsklen.
10:30
Well, as it turns out, this worked pretty well.
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2872
Det viste sig, at det fungerede ret godt.
10:33
So I go back online now.
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621555
1809
Jeg gik igen online.
10:35
I found Jewishdoc57
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623364
2755
Jeg fandt Jewishdoc57,
10:38
who's incredibly good-looking, incredibly well-spoken,
262
626119
2937
der så virkelig godt ud, utrolig veltalende,
10:41
he had hiked Mt. Fuji,
263
629056
1718
han havde besteget Fujiyama,
10:42
he had walked along the Great Wall.
264
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1742
han havde gået på Den kinesiske mur.
10:44
He likes to travel as long as it doesn't involve a cruise ship.
265
632516
3116
Han kunne lide at rejse, bare det ikke var på et krydstogtskib.
10:47
And I thought, I've done it!
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2738
Så jeg tænkte, jeg har gjort det!
10:50
I've cracked the code.
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2064
Jeg har brudt koden.
10:52
I have just found the Jewish Prince Charming
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640434
3770
Jeg har lige fundet den jødiske ridder på den hvide hest,
10:56
of my family's dreams.
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644204
2218
som min familie drømmer om.
10:58
There was only one problem:
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2156
Der var bare et problem:
11:00
He didn't like me back.
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3309
Han kunne ikke lide mig.
11:03
And I guess the one variable that I haven't considered
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3086
Det var nok den eneste variabel, jeg ikke havde overvejet
11:06
is the competition.
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1893
nemlig rivaliseringen.
11:08
Who are all of the other women
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1488
Hvem er alle de andre kvinder
11:10
on these dating sites?
275
658354
2445
på disse datingsider?
11:12
I found SmileyGirl1978.
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660799
3704
Jeg fandt SmileyGirl1978.
11:16
She said she was a "fun girl who is Happy and Outgoing."
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664503
2829
Hun skrev, hun var en "sjov pige, der er Glad og Udadvendt."
11:19
She listed her job as teacher.
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667332
1442
Hun skrev, at hun var lærer.
11:20
She said she is "silly, nice and friendly."
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668774
2606
Hun skrev, at hun var "fjollet, sød og venlig."
11:23
She likes to make people laugh "alot."
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2449
Hun kunne godt lide at få folk til at grine "meget."
11:25
At this moment I knew, clicking after profile
281
673829
2442
På dette tidspunkt vidste jeg, efter at have klikket på profil
11:28
after profile after profile that looked like this,
282
676271
2051
efter profil efter profil, der så sådan her ud,
11:30
that I needed to do some market research.
283
678322
2176
at jeg skulle lave nogle markedsundersøgelser.
11:32
So I created 10 fake male profiles.
284
680498
3280
Så jeg skabte 10 falske mandlige profiler.
11:35
Now, before I lose all of you --
285
683778
2944
Nuvel, inden jeg mister jer alle sammen --
11:38
(Laughter) --
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686722
1753
(Latter) --
11:40
understand that I did this
287
688475
3588
må I forstå, at jeg gjorde det
11:44
strictly to gather data
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2137
udelukkende for at indsamle data
11:46
about everybody else in the system.
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1748
om alle andre i systemet.
11:47
I didn't carry on crazy Catfish-style relationships with anybody.
290
695948
4195
Jeg havde ikke nogen skøre Catfish-agtige forhold med nogen.
11:52
I really was just scraping their data.
291
700143
2013
Jeg indsamlede bare deres data.
11:54
But I didn't want everybody's data.
292
702156
1968
Men jeg ville ikke have alles data.
11:56
I only wanted data on the women
293
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1883
Jeg ville kun have data fra de kvinder,
11:58
who were going to be attracted
294
706007
1564
der kunne blive tiltrukket
11:59
to the type of man that I really, really wanted to marry. (Laughter)
295
707571
3234
af den slags mand, jeg virkelig, virkelig gerne ville giftes med. (Latter)
12:02
When I released these men into the wild,
296
710805
3595
Når jeg slap disse mænd løs i naturen,
12:06
I did follow some rules.
297
714400
1302
fulgte jeg nogle strenge regler.
12:07
So I didn't reach out to any woman first.
298
715702
2140
Jeg kontaktede ikke selv kvinder.
12:09
I just waited to see who these profiles were going to attract,
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717842
2921
Jeg ventede bare på at se, hvem disse profiler ville tiltrække,
12:12
and mainly what I was looking at was two different data sets.
300
720763
3371
og jeg ledte hovedsageligt efter to forskellige datasæt.
12:16
So I was looking at qualitative data,
301
724134
1538
Jeg ledte efter kvalitative data,
12:17
so what was the humor, the tone,
302
725672
1949
hvordan var humoren, tonen,
12:19
the voice, the communication style
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727621
1562
stemmen, kommunikationsformen
12:21
that these women shared in common?
304
729183
1850
som disse kvinder havde til fælles.
12:23
And also quantitative data,
305
731033
1283
Og også kvantitative data,
12:24
so what was the average length of their profile,
306
732316
2338
hvad var den gennemsnitlige længde på deres profil,
12:26
how much time was spent between messages?
307
734654
2235
hvor meget tid gik der mellem beskederne?
12:28
What I was trying to get at here was
308
736889
1681
Det jeg prøvede på at opnå her, var,
12:30
that I figured in person,
309
738570
1925
at jeg som person
12:32
I would be just as competitive
310
740495
1410
ville være lige så konkurrerende
12:33
as a SmileyGirl1978.
311
741905
2065
som SmileyGirl1978.
12:35
I wanted to figure out how to maximize
312
743970
1900
Jeg ville regne ud, hvordan jeg maksimerede
12:37
my own profile online.
313
745870
2940
min egen profil online.
12:40
Well, one month later,
314
748810
1727
En måneds tid senere
12:42
I had a lot of data, and I was able to do another analysis.
315
750537
3753
havde jeg masser af data, og jeg var i stand til at lave endnu en analyse.
12:46
And as it turns out, content matters a lot.
316
754290
2880
Det viser sig, at indhold betyder meget.
12:49
So smart people tend to write a lot --
317
757170
2706
Kloge mennesker har en tendens til at skrive meget --
12:51
3,000, 4,000,
318
759876
1875
3.000, 4.000,
12:53
5,000 words about themselves,
319
761751
1743
5.000 ord om sig selv,
12:55
which may all be very, very interesting.
320
763494
2146
hvilket alt sammen muligvis er meget, meget interessant.
12:57
The challenge here, though, is that
321
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1352
Udfordringen her er dog,
12:58
the popular men and women
322
766992
1182
at de populære mænd og kvinder
13:00
are sticking to 97 words on average
323
768174
3772
holder sig til 97 ord i gennemsnit
13:03
that are written very, very well,
324
771946
1722
der er rigtig, rigtig godt skrevet,
13:05
even though it may not seem like it all the time.
325
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2890
også selvom det ikke altid virker sådan.
13:08
The other sort of hallmark of the people who do this well
326
776558
2149
Det andet kendetegn ved mennesker, der gør det godt,
13:10
is that they're using non-specific language.
327
778707
2153
er, at de bruger et uspecifikt sprog.
13:12
So in my case, you know,
328
780860
1290
I mit eget tilfælde er
13:14
"The English Patient" is my most favorite movie ever,
329
782150
3198
"Den Engelske Patient" min absolutte yndlingsfilm,
13:17
but it doesn't work to use that in a profile,
330
785348
3809
men det fungerer ikke at bruge det i en profil,
13:21
because that's a superficial data point,
331
789157
1741
fordi det er et overfladisk datapunkt,
13:22
and somebody may disagree with me
332
790914
1542
og nogen er måske uenige med mig
13:24
and decide they don't want to go out with me
333
792456
1215
og beslutter, at de ikke vil på date med mig
13:25
because they didn't like sitting through the three-hour movie.
334
793671
2699
fordi de ikke kan lide at se en tre timer lang film.
13:28
Also, optimistic language matters a lot.
335
796370
2240
Og optimistisk sprog betyder meget.
13:30
So this is a word cloud
336
798610
1436
Dette er en ordsky,
13:32
highlighting the most popular words that were used
337
800046
2460
der fremhæver de vigtigste ord, der blev brugt
13:34
by the most popular women,
338
802506
1632
af de mest populære kvinder,
13:36
words like "fun" and "girl" and "love."
339
804138
2575
ord som "sjov" og "pige" og "kærlighed."
13:38
And what I realized was not that I had
340
806713
2111
Jeg blev klar over, at jeg ikke skulle
13:40
to dumb down my own profile.
341
808824
1568
gøre min egen profil dummere.
13:42
Remember, I'm somebody who said
342
810392
1532
Husk på, at jeg selv skrev,
13:43
that I speak fluent Japanese and I know JavaScript
343
811924
3043
at jeg taler flydende japansk og kender JavaScript,
13:46
and I was okay with that.
344
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1594
og det havde jeg det fint med.
13:48
The difference is that it's about being more approachable
345
816561
2717
Forskellen er, at det handler om at være mere tilgængelig
13:51
and helping people understand
346
819278
2155
og hjælpe folk med at forstå,
13:53
the best way to reach out to you.
347
821433
1612
hvordan de bedst kan nå ind til en.
13:55
And as it turns out, timing is also really, really important.
348
823045
2922
Det viser sig, at timing også er virkelig, virkelig vigtigt.
13:57
Just because you have access
349
825967
1650
Blot fordi man har adgang
13:59
to somebody's mobile phone number
350
827617
1744
til nogens mobilnummer
14:01
or their instant message account
351
829361
1756
eller deres instant message-profil,
14:03
and it's 2 o'clock in the morning and you happen to be awake,
352
831117
2407
og klokken er to om natten, og man tilfældigvis er vågen,
14:05
doesn't mean that that's a good time to communicate with those people.
353
833524
3189
så betyder det ikke, at det er et godt tidspunkt at kommunikere med de mennesker.
14:08
The popular women on these online sites
354
836713
2649
De populære kvinder på disse onlinesider
14:11
spend an average of 23 hours
355
839362
1838
venter gennemsnitligt 23 timer
14:13
in between each communication.
356
841200
2376
mellem hver kommunikation.
14:15
And that's what we would normally do
357
843576
1931
Det er det, vi normalvis ville gøre
14:17
in the usual process of courtship.
358
845507
2064
i den almindelige kurtiseringsproces.
14:19
And finally, there were the photos.
359
847571
3405
Der var også billederne.
14:22
All of the women who were popular
360
850976
1833
Alle de populære kvinder
14:24
showed some skin.
361
852809
1625
viste hud.
14:26
They all looked really great,
362
854434
2012
De så alle sammen godt ud,
14:28
which turned out to be in sharp contrast
363
856446
2778
hvilket viste sig at være en skarp kontrast
14:31
to what I had uploaded.
364
859224
3293
til det, jeg selv havde uploadet.
14:34
Once I had all of this information,
365
862517
1640
Da jeg havde alle disse oplysninger,
14:36
I was able to create a super profile,
366
864157
2344
var jeg i stand til at skabe en superprofil,
14:38
so it was still me,
367
866501
1874
som stadig var mig,
14:40
but it was me optimized now for this ecosystem.
368
868375
3909
men jeg var nu optimeret til dette økosystem.
14:44
And as it turns out, I did a really good job.
369
872284
4850
Det viser sig, at jeg gjorde et virkelig godt stykke arbejde.
14:49
I was the most popular person online.
370
877134
3056
Jeg var den mest populære person online.
14:52
(Laughter)
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2519
(Latter)
14:54
(Applause)
372
882709
4214
(Bifald)
14:58
And as it turns out, lots and lots of men wanted to date me.
373
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3487
Det viste sig, at rigtigt mange mænd ville på date med mig.
15:02
So I call my mom, I call my sister, I call my grandmother.
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Så jeg ringer til min mor, jeg ringer til min søster, jeg ringer til min bedstemor.
15:04
I'm telling them about this fabulous news,
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Jeg fortæller dem disse fantastiske nyheder,
15:06
and they say, "This is wonderful!
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og de siger, "Det er vidunderligt!
15:08
How soon are you going out?"
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Hvornår går du på date med ham?"
15:10
And I said, "Well, actually, I'm not going to go out with anybody."
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Og jeg sagde, "Jamen, faktisk går jeg ikke på date med nogen."
15:13
Because remember, in my scoring system,
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Husk på, at i mit scoringssystem
15:15
they have to reach a minimum threshold of 700 points,
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skal de nå en minimumsgrænse på 700 point,
15:17
and none of them have done that.
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og det gjorde ingen af dem.
15:19
They said, "What? You're still being too damn picky."
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De sagde, "Hvad? Du er stadig at for kræsen."
15:22
Well, not too long after that,
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Men ikke længe efter det
15:24
I found this guy, Thevenin,
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fandt jeg denne fyr, Thevenin,
15:26
and he said that he was culturally Jewish,
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og han skrev at han kulturelt set var jødisk,
15:28
he said that his job was an arctic baby seal hunter,
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han skrev, at hans job var arktisk babysæljæger,
15:31
which I thought was very clever.
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hvilket jeg syntes var ret kvikt.
15:34
He talked in detail about travel.
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Han skrev detaljeret om at rejse.
15:37
He made a lot of really interesting cultural references.
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Han lavede mange interessante kulturelle referencer.
15:39
He looked and talked exactly like what I wanted,
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Han lignede og skrev præcis som det, jeg ville have,
15:42
and immediately, he scored 850 points.
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så han scorede øjeblikkeligt 850 point.
15:45
It was enough for a date.
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Det var nok til en date.
15:47
Three weeks later, we met up in person
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Tre uger senere mødtes vi ansigt til ansigt
15:49
for what turned out to be a 14-hour-long conversation
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til det, der viste sig at blive en 14-timer lang samtale,
15:52
that went from coffee shop to restaurant
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der gik fra en cafe til en restaurant
15:55
to another coffee shop to another restaurant,
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til endnu en cafe til endnu en restaurant,
15:57
and when he dropped me back off at my house that night
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og da han satte mig af ved mit hus den aften,
15:59
I re-scored him --
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testede jeg ham igen --
16:00
[1,050 points!] --
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[1.050 point!] --
16:02
thought, you know what,
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jeg tænkte, ved I hvad,
16:03
this entire time I haven't been picky enough.
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i al den tid har jeg ikke været kræsen nok.
16:06
Well, a year and a half after that,
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Halvandet år efter det
16:08
we were non-cruise ship traveling
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var vi ude at rejse, ikke med krydstogtskib,
16:11
through Petra, Jordan,
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gennem Petra i Jordan,
16:13
when he got down on his knee and proposed.
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hvor han gik på knæ og friede.
16:16
A year after that, we were married,
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Et år senere var vi gift,
16:19
and about a year and a half after that, our daughter,
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og omkring halvandet år efter det blev vores datter,
16:21
Petra, was born.
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Petra, født.
16:23
(Applause)
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(Bifald)
16:30
Obviously, I'm having a fabulous life, so --
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Jeg har tydeligvis et fantastisk liv, så --
16:33
(Laughter) --
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(Latter) --
16:34
the question is, what does all of this mean for you?
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spørgsmålet er, hvad alt dette betyder for en?
16:37
Well, as it turns out, there is an algorithm for love.
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Det viser sig, at der findes en algoritme for kærlighed.
16:40
It's just not the ones that we're being presented with online.
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Det er ikke kun dem, vi bliver præsenteret for online.
16:44
In fact, it's something that you write yourself.
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Faktisk er det noget, man selv skriver.
16:46
So whether you're looking for a husband or a wife
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Så hvadenten man leder efter en mand eller en kone,
16:49
or you're trying to find your passion
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om man prøver at finde sin passion
16:51
or you're trying to start a business,
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eller prøver at starte et firma,
16:52
all you have to really do is figure out your own framework
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så skal man blot finde sin egen ramme
16:55
and play by your own rules,
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og spille efter egne regler,
16:57
and feel free to be as picky as you want.
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føle sig fri til at være så kræsen, som man ønsker.
17:00
Well, on my wedding day,
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På min bryllupsdag
17:01
I had a conversation again with my grandmother,
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havde jeg igen en samtale med min farmor,
17:03
and she said, "All right, maybe I was wrong.
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og hun sagde, "Godt, måske tog jeg fejl.
17:06
It looks like you did come up with
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Det ser ud til, at du fandt på et
17:07
a really, really great system.
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virkelig, virkelig fantatisk system.
17:09
Now, your matzoh balls.
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Men, dine matzoh-kugler.
17:12
They should be fluffy, not hard."
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De skal være luftige, ikke hårde."
17:15
And I'll take her advice on that.
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Og dér følger jeg hendes råd.
17:17
(Applause)
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(Bifald)
ABOUT THE SPEAKER
Amy Webb - Founder and CEO, Future Today InstituteAmy Webb is a futurist and founder of the Future Today Institute, and is the award-winning author of three books, including “Data: A Love Story” and “The Signals Are Talking: Why Today’s Fringe Is Tomorrow’s Mainstream.”
Why you should listen
Amy Webb uses data to understand the present and future of humanity, a practice she first developed as a journalist for the Wall Street Journal and Newsweek and has continued as a futurist. She is the head of the Future Today Institute, which researches collisions between technology, society and business — and maps scenarios that are on the horizon. She was named to the Thinkers50 Radar list of the 30 management thinkers most likely to shape the future of how organizations are managed and led.
Webb is on the adjunct faculty at the NYU Stern School of Business, where she teaches a popular MBA-level course on futures forecasting. She is the author of The Signals Are Talking, Why Today’s Fringe Is Tomorrow’s Mainstream, which has become the standard text on futures forecasting and explains how to predict and manage technological change. Her book Data: A Love Story tells the tale of how she gamed the online dating system to figure out how to find the love of her life.
Amy Webb | Speaker | TED.com