I work on helping computers communicate about the world around us. There are a lot of ways to do this, and I like to focus on helping computers to talk about what they see and understand. Given a scene like this, a modern computer-vision algorithm can tell you that there's a woman and there's a dog. It can tell you that the woman is smiling. It might even be able to tell you that the dog is incredibly cute. I work on this problem thinking about how humans understand and process the world. The thoughts, memories and stories that a scene like this might evoke for humans. All the interconnections of related situations. Maybe you've seen a dog like this one before, or you've spent time running on a beach like this one, and that further evokes thoughts and memories of a past vacation, past times to the beach, times spent running around with other dogs. One of my guiding principles is that by helping computers to understand what it's like to have these experiences, to understand what we share and believe and feel, then we're in a great position to start evolving computer technology in a way that's complementary with our own experiences.
Ja pomažem da računari saopštavaju informacije o svetu oko nas. Postoji mnogo načina da se to uradi, i ja volim da se fokusiram na pomaganje da računari pričaju o tome šta vide i razumeju. Na slici kao što je ova, savremeni algoritmi za prepoznavanje oblika će videti da su tu žena i pas. Prepoznaće da se žena smeje. Može čak proceniti da je pas neverovatno sladak. Ja radim na ovom problemu razmišljajući kako ljudi razumeju svet i razmišljaju o njemu. Misli, sećanja i priče koje slika kao što je ova mogu izazvati kod ljudi. Sve međuzavisnosti povezanih situacija. Možda ste već videli psa kao što je ovaj, ili ste provodili vreme u trčanju na plaži kao što je ova, a to dalje podstiče misli i sećanja na odmor iz prošlosti, vreme provedeno na plaži i u trčanju sa drugim psima. Jedan od mojih vodećih principa je da pomaganjem računarima da shvate šta znači imati ovakva iskustva, da shvate šta mi imamo zajedničko, u šta verujemo i šta osećamo, dolazimo do odlične pozicije za početak razvoja računarske tehnologije tako da dopunjava naša sopstvena iskustva.
So, digging more deeply into this, a few years ago I began working on helping computers to generate human-like stories from sequences of images. So, one day, I was working with my computer to ask it what it thought about a trip to Australia. It took a look at the pictures, and it saw a koala. It didn't know what the koala was, but it said it thought it was an interesting-looking creature. Then I shared with it a sequence of images about a house burning down. It took a look at the images and it said, "This is an amazing view! This is spectacular!" It sent chills down my spine. It saw a horrible, life-changing and life-destroying event and thought it was something positive. I realized that it recognized the contrast, the reds, the yellows, and thought it was something worth remarking on positively. And part of why it was doing this was because most of the images I had given it were positive images. That's because people tend to share positive images when they talk about their experiences. When was the last time you saw a selfie at a funeral?
Ako uđemo malo dublje u temu, pre par godina sam počela rad na pomaganju računarima da stvaraju priče na osnovu niza slika. Jednog dana sam radila na računaru i pitala ga šta misli o putovanju u Australiju. Pogledao je slike i video je koalu. Nije znao šta je koala, ali je rekao da misli da to biće izgleda zanimljivo. Zatim sam sa njim podelila niz slika kuća u plamenu. Pogledao je slike i rekao: „Ovo izgleda sjajno! Ovo je spektakularno!“ Niz kičmu su mi prošli žmarci. Video je užasan događaj koji menja i uništava živote ljudi i mislio je da je to nešto pozitivno. Shvatila sam da je prepoznao kontrast, crvene i žute boje, i da je mislio da je to nešto što treba označiti kao pozitivno. Delimično je razlog tome to što je većina slika koje sam mu davala bila pozitivna. To je zbog toga što su ljudi skloni da dele pozitivne slike kada pričaju o svojim iskustvima. Kada ste poslednji put videli selfi sa sahrane?
I realized that, as I worked on improving AI task by task, dataset by dataset, that I was creating massive gaps, holes and blind spots in what it could understand. And while doing so, I was encoding all kinds of biases. Biases that reflect a limited viewpoint, limited to a single dataset -- biases that can reflect human biases found in the data, such as prejudice and stereotyping. I thought back to the evolution of the technology that brought me to where I was that day -- how the first color images were calibrated against a white woman's skin, meaning that color photography was biased against black faces. And that same bias, that same blind spot continued well into the '90s. And the same blind spot continues even today in how well we can recognize different people's faces in facial recognition technology. I though about the state of the art in research today, where we tend to limit our thinking to one dataset and one problem. And that in doing so, we were creating more blind spots and biases that the AI could further amplify.
Shvatila sam da, dok sam radila na unapređenju veštačke inteligencije zadatak po zadatak, bazu po bazu, da sam u stvari stvarala velike pukotine, rupe i „mrtve uglove“ u onome što može da razume. Time sam sam ubacivala različite pristrasnosti. Pristrasnosti koje odražavaju ograničeno gledište, ograničeno na samo jedan skup podataka - pristrasnosti koje odražavaju ljudske pristrasnosti pronađene u podacima kao što su predrasude i stereotipi. Razmislila sam o evoluciji tehnologije koja me je dovela tu gde sam bila u tom trenutku - kako su prve slike u boji bile podešene prema boji kože belih žena, što znači da je fotografija u boji bila naklonjena protiv crnih lica. Ta ista naklonjenost, isti „mrtav ugao“ se nastavio duboko u '90-im godinama. Isti „mrtav ugao“ traje čak i danas u tome koliko dobro možemo prepoznati lica različitih ljudi u tehnologiji za prepoznavanje lica. Razmišljala sam o najnaprednijim istraživanjima danas, gde pokušavamo da ograničimo svoje razmišljanje na jedan skup podataka i jedan problem. A čineći to, stvaramo još više „mrtvih uglova“ i predrasuda koje veštačka inteligencija može još više da pojača.
I realized then that we had to think deeply about how the technology we work on today looks in five years, in 10 years. Humans evolve slowly, with time to correct for issues in the interaction of humans and their environment. In contrast, artificial intelligence is evolving at an incredibly fast rate. And that means that it really matters that we think about this carefully right now -- that we reflect on our own blind spots, our own biases, and think about how that's informing the technology we're creating and discuss what the technology of today will mean for tomorrow.
Tada sam shvatila da moramo da dobro razmislimo o tome kako će tehnologija na kojoj danas radimo da izgleda za pet ili 10 godina. Ljudi evoluiraju polako, imaju vremena da isprave greške u interakciji sa ljudima i okruženjem. Za razliku od njih, veštačka inteligencija se razvija neverovatnom brzinom. To znači da je zaista bitno da o ovome pažljivo razmislimo sada - da razmislimo o svojim „mrtvim uglovima“, o sopstvenim predrasudama, i da razmislimo o tome kako to utiče na tehnologiju koju stvaramo i da razmotrimo šta će značiti tehnologija današnjice za sutrašnjicu.
CEOs and scientists have weighed in on what they think the artificial intelligence technology of the future will be. Stephen Hawking warns that "Artificial intelligence could end mankind." Elon Musk warns that it's an existential risk and one of the greatest risks that we face as a civilization. Bill Gates has made the point, "I don't understand why people aren't more concerned." But these views -- they're part of the story. The math, the models, the basic building blocks of artificial intelligence are something that we call access and all work with. We have open-source tools for machine learning and intelligence that we can contribute to. And beyond that, we can share our experience. We can share our experiences with technology and how it concerns us and how it excites us. We can discuss what we love. We can communicate with foresight about the aspects of technology that could be more beneficial or could be more problematic over time.
Direktori i naučnici raspravljaju o tome kakva će biti veštačka inteligencija u budućnosti. Stiven Hoking upozorava da „Veštačka inteligencija može uništiti čovečanstvo.“ Ilon Mask upozorava da je to rizik za preživljavanje i jedan od najvećih rizika sa kojima se susrećemo kao civilizacija. Bil Gejts je izneo stav: „Ne razumem zašto ljudi nisu više zabrinuti.“ Ali ova mišljenja su deo priče. Matematika, modeli, osnovni sastavni delovi veštačke inteligencije su nešto čemu svi možemo da pristupimo i da radimo sa time. Imamo alate otvorenog koda za mašinsko učenje i inteligenciju kojima možemo da doprinesemo. Osim toga, možemo da delimo naše iskustvo. Možemo da delimo naša iskustva sa tehnologijom, kako nas brine i kako nas uzbuđuje. Možemo da razmatramo šta volimo. Možemo da govorimo o budućim aspektima tehnologije koji bi bili delotvorniji ili problematičniji tokom vremena.
If we all focus on opening up the discussion on AI with foresight towards the future, this will help create a general conversation and awareness about what AI is now, what it can become and all the things that we need to do in order to enable that outcome that best suits us. We already see and know this in the technology that we use today. We use smart phones and digital assistants and Roombas. Are they evil? Maybe sometimes. Are they beneficial? Yes, they're that, too. And they're not all the same. And there you already see a light shining on what the future holds. The future continues on from what we build and create right now. We set into motion that domino effect that carves out AI's evolutionary path.
Ako se svi fokusiramo na otvaranje diskusije o veštačkoj inteligenciji sa pogledom na budućnost, to će pomoći kreiranju uopštenih razgovora i svesti o tome šta je veštačka inteligencija sada, šta može da postane i sve stvari koje treba da uradimo da ostvarimo rezultat koji bi nam najbolje služio. Već vidimo i znamo to iz tehnologije koju danas koristimo. Koristimo pametne telefone, digitalne pomoćnike i robotske usisivače. Da li su zli? Možda ponekad. Da li su korisni? Jesu i to. I nisu svi isti. Već možemo da vidimo da je budućnost svetla. Budućnost nastaje iz onoga što kreiramo upravo sada. Mi pokrećemo taj domino efekat koji kreira evolucioni put veštačke inteligencije.
In our time right now, we shape the AI of tomorrow. Technology that immerses us in augmented realities bringing to life past worlds. Technology that helps people to share their experiences when they have difficulty communicating. Technology built on understanding the streaming visual worlds used as technology for self-driving cars. Technology built on understanding images and generating language, evolving into technology that helps people who are visually impaired be better able to access the visual world. And we also see how technology can lead to problems. We have technology today that analyzes physical characteristics we're born with -- such as the color of our skin or the look of our face -- in order to determine whether or not we might be criminals or terrorists. We have technology that crunches through our data, even data relating to our gender or our race, in order to determine whether or not we might get a loan. All that we see now is a snapshot in the evolution of artificial intelligence. Because where we are right now, is within a moment of that evolution. That means that what we do now will affect what happens down the line and in the future.
U svom vremenu sada, mi oblikujemo veštačku inteligenciju sutrašnjice. Tehnologiju koja nas uvodi u izmenjenu stvarnost oživljavajući prošlost. Tehnologiju koja pomaže ljudima da dele svoja iskustva kada imaju problem da komuniciraju. Tehnologiju zasnovanu na prenosu sadržaja vizuelnog sveta, korišćenu kao tehnologiju za samovozeće automobile. Tehnologiju zasnovanu na razumevanju slika i generisanju jezika, koja evoluira u tehnologiju koja pomaže ljudima sa oštećenim vidom da imaju bolji pristup vizuelnom svetu. Takođe vidimo kako tehnologija može da dovede do problema. Danas imamo tehnologiju koja analizira fizičke karakteristike sa kojima smo rođeni - kao što je boja kože ili izgled lica - kako bi odredila da li smo možda kriminalci ili teroristi. Imamo tehnologiju koja pretražuje naše podatke, čak i podatke o našem polu ili rasi, da bi odredila da li možemo da dobijemo kredit. Sve što sada vidimo je trenutna slika u evoluciji veštačke inteligencije. Zato što je ovo gde smo sada samo trenutak u toj evoluciji. To znači da će ono što sada radimo uticati na to šta se dešava u budućnosti.
If we want AI to evolve in a way that helps humans, then we need to define the goals and strategies that enable that path now. What I'd like to see is something that fits well with humans, with our culture and with the environment. Technology that aids and assists those of us with neurological conditions or other disabilities in order to make life equally challenging for everyone. Technology that works regardless of your demographics or the color of your skin. And so today, what I focus on is the technology for tomorrow and for 10 years from now.
Ukoliko želimo da pomognemo da se veštačka inteligencija razvije tako da pomogne ljudima, onda moramo da definišemo ciljeve i strategije koje će omogućiti taj put sada. Ono što bih želela da vidim je nešto što će se uklopiti sa ljudima, sa našom kulturom i okruženjem. Tehnologiju koja pomaže onima sa neurološkim problemima ili drugim vidovima invaliditeta kako bi život bio podjednako izazovan za svakoga. Tehnologiju koja radi bez obzira na poreklo ili boju kože. Tako da ono na šta se danas fokusiram je tehnologija sutrašnjice i 10 godina od danas.
AI can turn out in many different ways. But in this case, it isn't a self-driving car without any destination. This is the car that we are driving. We choose when to speed up and when to slow down. We choose if we need to make a turn. We choose what the AI of the future will be. There's a vast playing field of all the things that artificial intelligence can become. It will become many things. And it's up to us now, in order to figure out what we need to put in place to make sure the outcomes of artificial intelligence are the ones that will be better for all of us.
Veštačka inteligencija može da krene različitim putevima. Ali u ovom slučaju, to nije samovozeći automobil bez cilja. To je automobil koji mi vozimo. Mi biramo kada da ubrzamo i kada da usporimo. Mi biramo da li treba da skrenemo. Mi biramo šta će veštačka inteligencija budućnosti zapravo biti. Veliki je broj mogućnosti šta veštačka inteligencija može postati. I postaće dosta toga. Sada je na nama da smislimo šta treba da uradimo da bismo bili sigurni da rezultati veštačke inteligencije budu oni koji su dobri za sve nas.
Thank you.
Hvala.
(Applause)
(Aplauz)