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

Applying for jobs online

Prevodilac: Ivana Krivokuća Lektor: Dragana Savanovic

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.

Konkurisanje za poslove onlajn

It's a terrible experience for people.

je jedno od najgorih digitalnih iskustava našeg vremena.

About 75 percent of people

A ni konkurisanje uživo zapravo nije mnogo bolje.

who applied to jobs using various methods in the past year

[Način na koji radimo]

said they never heard anything back from the employer.

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

Zapošljavanje kakvo poznajemo je manjkavo na više načina.

46 percent of people get fired or quit

To je grozno iskustvo za ljude.

within the first year of starting their jobs.

Oko 75 posto ljudi koji su se prijavljivali za poslove

It's pretty mind-blowing.

pomoću različitih metoda prošle godine

It's also bad for the economy.

For the first time in history,

reklo je da nikad nisu ništa čuli od poslodavca.

we have more open jobs than we have unemployed people,

Na nivou kompanije nije ništa bolje.

and to me that screams that we have a problem.

Četrdeset šest posto ljudi dobije ili da otkaz

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

u prvoj godini zaposlenja.

To je prilično zapanjujuće.

A résumé definitely has some useful pieces in it:

Takođe je loše za ekonomiju.

what roles people have had, computer skills,

Prvi put u istoriji,

imamo više slobodnih radnih mesta nego nezaposlenih ljudi,

what languages they speak,

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

i to po meni jasno govori da imamo problem.

Smatram da je u srži svega ovoga jedan papir: biografija.

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

Biografija definitivno sadrži neke korisne informacije:

that might require skills that nobody has,

koje poslove su ljudi obavljali, veštine na računaru, koje jezike govore,

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

ali izostavlja njihov potencijal da urade nešto

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

što možda nisu imali priliku da urade u prošlosti.

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

Sa ekonomijom koja se tako brzo menja i u kojoj se pojavljuju poslovi

You've probably seen that algorithms have gotten pretty good

koji mogu zahtevati veštine koje niko nema,

at matching people to things,

but what if we could use that same technology

ako samo gledamo šta je neko radio u prošlosti,

nećemo moći da povežemo ljude sa poslovima budućnosti.

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

Mislim da bi tu tehnologija mogla bila od velike pomoći.

But I know what you're thinking.

Algorithms picking your next job sounds a little bit scary,

Verovatno ste videli da su algoritmi postali prilično dobri

but there is one thing that has been shown

u povezivanju ljudi sa raznim stvarima,

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

ali šta ako bismo mogli da upotrebimo tu istu tehnologiju

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

da nam pomogne da nađemo poslove za koje smo zaista podesni?

Multimeasure tests really aren't anything new,

Znam šta mislite.

Zvuči pomalo zastrašujuće da algoritmi biraju vaš sledeći posao,

but they used to be really expensive

and required a PhD sitting across from you

ali postoji nešto što se pokazalo

and answering lots of questions and writing reports.

da dobro predviđa budući uspeh osobe na poslu,

Multimeasure tests are a way

a to nešto se zove test višestrukih merila.

to understand someone's inherent traits --

Testovi višestrukih merila nisu ništa novo,

your memory, your attentiveness.

ali ranije su bili jako skupi

What if we could take multimeasure tests

i zahtevali su da doktor nauka sedi naspram vas,

and make them scalable and accessible,

odgovaranje na mnogo pitanja i pisanje izveštaja.

and provide data to employers about really what the traits are

Testovi višestrukih merila su način

za razumevanje nečijih unutrašnjih osobina -

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

vašeg pamćenja, pažljivosti.

This all sounds abstract.

Let's try one of the games together.

Šta ako bismo testove višestrukih merila

You're about to see a flashing circle,

učinili prilagodljivim i pristupačnim

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

i obezbedili podatke poslodavcima o tome koje su to karakteristike

and do nothing when it's green.

osobe koja bi odgovarala nekom poslu?

[Ready?]

[Begin!]

Sve ovo zvuči apstraktno.

Hajde da probamo jednu igru zajedno.

[Green circle]

Videćete krug koji treperi

[Green circle]

i vaš zadatak će biti da udarite dlanom o dlan kada je krug crven,

[Red circle]

[Green circle]

a ne uradite ništa kada je zelen.

[Red circle]

[Spremni?]

Maybe you're the type of person

[Počnite!]

who claps the millisecond after a red circle appears.

[Zeleni krug]

Or maybe you're the type of person

[Zeleni krug]

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

[Crveni krug]

[Zeleni krug]

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

[Crveni krug]

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

Možda ste tip osobe

koja pljesne milisekundu nakon što se crveni krug pojavi.

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

Instead it's about understanding the fit between your characteristics

Ili ste možda tip osobe

koja čeka malo više da bi bila 100 posto sigurna.

and what would make you good a certain job.

Ili možda tapšete na zeleno iako ne bi trebalo.

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

Ovde je zanimljivo da to nije kao standardizovan test

you might be high in attentiveness and high in restraint.

gde su neki ljudi podobni za zaposlenje, a neki nisu.

Umesto toga, radi se o razumevanju uklapanja vaših karakteristika

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

i onog zbog čega biste bili dobri na izvesnom poslu.

great at project management or accounting.

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

Otkrili smo da, ako pljesnete kasno na crveno i ne pljesnete na zeleno,

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

možete biti veoma pažljivi i uzdržani.

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

Ljudi u tom kvadrantu su često dobri učenici, dobro prolaze na testovima,

The way we actually use this in hiring

odlični u upravljanju projektima ili u računovodstvu.

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

Ali ako odmah pljesnete na crveno i ponekad na zeleno,

like this one.

to može značiti da ste više impulsivni i kreativni,

Then we develop an algorithm

that understands what makes those top performers unique.

i otkrili smo da vrhunski prodavci često poseduju ove osobine.

And then when people apply to the job,

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

Ovo koristimo u zapošljavanju

tako što ljude koji su se istakli na poslu podvrgnemo neuronaučnim vežbama

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

kao što je ova.

The work world today is not the most diverse

Zatim razvijemo algoritam

koji razume šta te odlične radnike čini jedinstvenim.

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

A onda, kada ljudi konkurišu za posao,

how do we make sure

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

možemo da iznedrimo kandidate

koji bi mogli biti najpogodniji za taj posao.

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

Možda mislite da se u ovome krije opasnost.

Svet rada danas nije baš najraznovrsniji

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

i ako ćemo stvarati algoritme na osnovu trenutno najboljih radnika,

you would actually find

kako da budemo sigurni

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

da time nećemo samo održavati predrasude koje već postoje?

Na primer, ako pravimo algoritam zasnovan na vrhunskim direktorima

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

But technology actually poses a really interesting opportunity.

i koristimo indeks S&P 500 kao početni skup podataka,

We can create algorithms that are more equitable

otkrili bismo

and more fair than human beings have ever been.

da je verovatnije da ćete zaposliti belca po imenu Džon nego neku ženu.

Every algorithm that we put into production has been pretested

To je stvarna slika toga ko se sada nalazi na tim poslovima.

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

Ali tehnologija zapravo predstavlja zaista zanimljivu priliku.

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

Možemo napraviti algoritme koji su pravedniji

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

i pošteniji od ljudskih bića.

Svaki algoritam koji smo stavili u upotrebu je prethodno testiran

When we focus on the inherent characteristics

that can make somebody a good fit for a job,

da bi se osiguralo da ne favorizuje jedan pol ili etničku pripadnost.

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

A ako postoji neka populacija koja je više favorizovana,

even good schoolism.

možemo da izmenimo algoritam da više ne bude tako.

Our best technology and algorithms shouldn't just be used

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

Kada se fokusiramo na unutrašnje osobine

zbog kojih je neko dobra osoba za neki posao,

Imagine if we could harness the power of technology

možemo prevazići rasizam, klasizam, seksizam, starosnu diskriminaciju -

to get real guidance on what we should be doing

čak i obrazovnu diskriminaciju.

based on who we are at a deeper level.

Naša najbolja tehnologija i algoritmi ne bi trebalo da se samo koriste

za pomoć u pronalaženju narednog filma ili nove omiljene pesme Džastina Bibera.

Zamislite ako bismo iskoristili moć tehnologije

da dobijemo stvarne smernice za ono što treba da radimo

na osnovu onoga što jesmo na dubljem nivou.