How to make applying for jobs less painful | The Way We Work, a TED series

Applying for jobs online

Translator: Lars Hansen Reviewer: Jette Thrane

is one of the worst digital experiences of our time.

And applying for jobs in person really isn't much better.

[The Way We Work]

Hiring as we know it is broken on many fronts.

Jobsøgning på nettet

It's a terrible experience for people.

er en af de værste digitale oplevelser i vor tid.

About 75 percent of people

Og personlig jobsøgning er ikke meget bedre.

who applied to jobs using various methods in the past year

[Måden vi arbejder på]

said they never heard anything back from the employer.

And at the company level it's not much better.

Ansættelse som vi kender det, fungerer ikke

46 percent of people get fired or quit

Det er en dårlig oplevelse.

within the first year of starting their jobs.

Omtrent 75% af de

der søgte job det seneste år

It's pretty mind-blowing.

It's also bad for the economy.

For the first time in history,

fortæller at de aldrig hørte noget fra arbejdsgiveren.

we have more open jobs than we have unemployed people,

I virksomhederne er det ikke meget bedre

and to me that screams that we have a problem.

46% af de ansatte bliver fyret eller siger op

I believe that at the crux of all of this is a single piece of paper: the résumé.

indenfor det første år af deres ansættelse.

Det er chokerende tal.

A résumé definitely has some useful pieces in it:

Og skidt for økonomien.

what roles people have had, computer skills,

For første gang i historien

har vi flere ledige jobs end arbejdsløse i USA,

what languages they speak,

but what it misses is what they have the potential to do

og det viser et tydeligt problem

Jeg tror sagens kerne er et enkelt stykke papir: CV'et.

that they might not have had the opportunity to do in the past.

And with such a quickly changing economy where jobs are coming online

Et CV indeholder utvivlsomt vigtig information:

that might require skills that nobody has,

tidligere ansættelser, IT-evner,

if we only look at what someone has done in the past,

hvilke sprog de taler,

men sjældent noget om de potentialer

we're not going to be able to match people to the jobs of the future.

der måske ikke tidligere er blevet udlevet

So this is where I think technology can be really helpful.

Og med en økonomi i forandring, hvor de job der opslås på nettet

You've probably seen that algorithms have gotten pretty good

måske kræver evner som ingen har ...

at matching people to things,

but what if we could use that same technology

hvis vi kun kigger på hvad folk har lavet tidligere,

vil vi ikke kunne matche folk til de rette jobs i fremtiden.

to actually help us find jobs that we're really well-suited for?

But I know what you're thinking.

Det er her teknologien kan være til stor hjælp

Algorithms picking your next job sounds a little bit scary,

Algoritmer er gode til

but there is one thing that has been shown

at matche folk med ting,

to be really predictive of someone's future success in a job,

men måske kan vi anvende denne teknologi

and that's what's called a multimeasure test.

til at finde jobs vi matcher godt?

Multimeasure tests really aren't anything new,

Men jeg ved hvad I tænker.

but they used to be really expensive

Algoritmer der vælger dit næste job, lyder lidt skræmmende,

and required a PhD sitting across from you

and answering lots of questions and writing reports.

men der er en faktor som påviseligt er

en stærk indikator for en kandidats fremtidige jobsucces

Multimeasure tests are a way

to understand someone's inherent traits --

og det er en såkaldt multifaktortest.

your memory, your attentiveness.

Multifaktortests er egentlig ikke nye,

men de plejede at være meget dyre

What if we could take multimeasure tests

og krævede at en PhD sad sammen med dig

and make them scalable and accessible,

og svar på en masse spørgsmål og rapportskrivning.

and provide data to employers about really what the traits are

Multifaktortests er en måde

at afdække folks naturlige talenter -

of someone who can make them a good fit for a job?

deres hukommelse, deres opmærksomhed.

This all sounds abstract.

Let's try one of the games together.

Hvad hvis vi kunne gøre multifaktortests

You're about to see a flashing circle,

tilgængelige i stor skala

and your job is going to be to clap when the circle is red

og levere data til arbejdsgivere om hvilke egenskaber den bedste ansøger

and do nothing when it's green.

til jobbet bør have.

[Ready?]

[Begin!]

Det kan lyde abstrakt.

Lad os prøve en af testene sammen.

[Green circle]

Snart vil I se en blinkende cirkel,

[Green circle]

og jeres opgave er at klappe, når cirklen er rød

[Red circle]

[Green circle]

og ingenting, når den er grøn.

[Red circle]

[Klar?]

Maybe you're the type of person

[Start!]

who claps the millisecond after a red circle appears.

[Grøn cirkel]

Or maybe you're the type of person

[Grøn cirkel]

who takes just a little bit longer to be 100 percent sure.

[Rød cirkel]

[Grøn cirkel]

Or maybe you clap on green even though you're not supposed to.

[Rød cirkel]

The cool thing here is that this isn't like a standardized test

Måske er du typen

der klapper øjeblikkeligt, når en rød cirkel vises.

where some people are employable and some people aren't.

Instead it's about understanding the fit between your characteristics

Eller måske er du typen,

der lige tager sig tid til at være 100% sikker.

and what would make you good a certain job.

Eller måske klapper du på grøn, selvom det ikke er meningen.

We found that if you clap late on red and you never clap on the green,

Det fede her er, at det ikke er som en standardiseret test,

you might be high in attentiveness and high in restraint.

hvor nogle kan bruges og andre ikke kan.

People in that quadrant tend to be great students, great test-takers,

I stedet handler det om at forstå matchet mellem dine talenter

great at project management or accounting.

og hvad der gør dig egnet til et givent job

But if you clap immediately on red and sometimes clap on green,

Vi har opdaget, at hvis du klapper sent på rød og aldrig på grøn,

that might mean that you're more impulsive and creative,

så scorer du nok højt i opmærksomhed og højt i tilbageholdenhed.

and we've found that top-performing salespeople often embody these traits.

Folk i den kvadrant er ofte gode til at studere og tage tests,

The way we actually use this in hiring

gode til projektledelse eller bogføring.

is we have top performers in a role go through neuroscience exercises

Men hvis du klapper øjeblikkeligt på rød og nogle gange på grøn,

like this one.

kan det betyde, at du er mere impulsiv og kreativ

Then we develop an algorithm

that understands what makes those top performers unique.

Og vi ser at de bedste sælgere ofte besidder disse talenter.

And then when people apply to the job,

we're able to surface the candidates who might be best suited for that job.

Vi bruger dette i ansættelser

ved at lade de dygtigste udføre neurovidenskabelige øvelser

So you might be thinking there's a danger in this.

som denne.

The work world today is not the most diverse

Så udvikler vi en algoritme,

der kan udpege, hvad der gør dem i toppen unikke.

and if we're building algorithms based on current top performers,

Og når folk så søger jobbet,

how do we make sure

that we're not just perpetuating the biases that already exist?

kan vi udpege de kandidater, der sandsynligvis er bedst.

For example, if we were building an algorithm based on top performing CEOs

Du fornemmer måske en risiko

Arbejdsmarkedet i dag er ikke så alsidigt,

and use the S&P 500 as a training set,

og hvis vi laver algoritmer baseret på de dygtigste i job,

you would actually find

that you're more likely to hire a white man named John than any woman.

hvordan sikrer vi så

at vi ikke gror fast i gamle mønstre?

And that's the reality of who's in those roles right now.

F.eks. hvis algoritmen baseres på de dygtigste topchefer

But technology actually poses a really interesting opportunity.

og fodres med data fra S&P 500 (de største amerikanske virksomheder)

We can create algorithms that are more equitable

ville du opdage at

and more fair than human beings have ever been.

flere hvide mænd hedder John end der totalt set er kvinder.

Every algorithm that we put into production has been pretested

Sådan er sammensætningen af dem, der har disse jobs nu.

to ensure that it doesn't favor any gender or ethnicity.

Men teknologien giver os en interessant mulighed.

And if there's any population that's being overfavored,

Vi kan lave algoritmer, der er mere retfærdige

we can actually alter the algorithm until that's no longer true.

og mere fair end mennesker nogensinde har været.

Alle vores algoritmer er testet

When we focus on the inherent characteristics

that can make somebody a good fit for a job,

for favorisering af køn og etnicitet

we can transcend racism, classism, sexism, ageism --

Og hvis en bestemt gruppe favoriseres,

even good schoolism.

så kan vi ændre algoritmen så dette ikke sker.

Our best technology and algorithms shouldn't just be used

for helping us find our next movie binge or new favorite Justin Bieber song.

Når vi fokuserer på de naturlige talenter,

der er basis for et et godt match,

Imagine if we could harness the power of technology

kan vi undgå diskrimination på race, køn, klasse og alder -

to get real guidance on what we should be doing

sågar uddannelsesniveau.

based on who we are at a deeper level.

Vores bedste teknologi og algoritmer skal ikke bare bruges

til at finde den næste film eller favoritsang med Justin Bieber.

Vi kan udnytte teknologiens kraft

til at få reel vejledning i hvad vi burde lave

baseret på hvem vi er inderst inde.