Our emotions influence every aspect of our lives, from our health and how we learn, to how we do business and make decisions, big ones and small. Our emotions also influence how we connect with one another. We've evolved to live in a world like this, but instead, we're living more and more of our lives like this -- this is the text message from my daughter last night -- in a world that's devoid of emotion. So I'm on a mission to change that. I want to bring emotions back into our digital experiences.
Naše emocije utiču na svaki aspekt naših života, od našeg zdravlja i načina učenja do načina obavljanja posla i donošenja odluka, bile one velike ili male. Naše emocije takođe utiču na to kako se povezujemo jedni sa drugima. Razvili smo se za život u svetu kao što je ovaj, ali umesto toga, živimo sve više naše živote ovako - ovo je SMS poruka koju mi je ćerka poslala sinoć - u svetu koji je lišen emocija. Tako sam na misiji to da promenim. Želim da vratim emocije u naše digitalno iskustvo.
I started on this path 15 years ago. I was a computer scientist in Egypt, and I had just gotten accepted to a Ph.D. program at Cambridge University. So I did something quite unusual for a young newlywed Muslim Egyptian wife: With the support of my husband, who had to stay in Egypt, I packed my bags and I moved to England. At Cambridge, thousands of miles away from home, I realized I was spending more hours with my laptop than I did with any other human. Yet despite this intimacy, my laptop had absolutely no idea how I was feeling. It had no idea if I was happy, having a bad day, or stressed, confused, and so that got frustrating. Even worse, as I communicated online with my family back home, I felt that all my emotions disappeared in cyberspace. I was homesick, I was lonely, and on some days I was actually crying, but all I had to communicate these emotions was this. (Laughter) Today's technology has lots of I.Q., but no E.Q.; lots of cognitive intelligence, but no emotional intelligence. So that got me thinking, what if our technology could sense our emotions? What if our devices could sense how we felt and reacted accordingly, just the way an emotionally intelligent friend would? Those questions led me and my team to create technologies that can read and respond to our emotions, and our starting point was the human face.
Krenula sam ovim putem pre 15 godina. Bila sam kompjuterski naučnik u Egiptu i samo što su me primili na doktorski program na univerzitetu u Kembridžu. Tako sam uradila nešto prilično neobično za jednu mladu, tek venčanu ženu koja je muslimanska Egipćanka: (Smeh) uz podršku mog muža koji je morao da ostane u Egiptu, spakovala sam kofere i preselila se u Englesku. Na Kembridžu, kilometrima daleko od kuće, shvatila sam da više vremena provodim sa laptopom nego sa bilo kojim drugim ljudskim bićem. Ipak, i pored ove prisnosti, moj laptop nije imao pojma kako se osećam. Nije imao pojma da li sam srećna, da li sam imala loš dan, da li sam pod stresom, zbunjena, tako da je to postalo frustrirajuće. Još gore, dok sam komunicirala sa porodicom kod kuće preko mreže, osećala sam da sve moje emocije nestaju u sajber prostoru. Nedostajala mi je kuća, bila sam usamljena i nekih dana sam zapravo i plakala, ali sve što sam imala da iskažem ove emocije bilo je ovo. (Smeh) Današnja tehnologija ima mnogo IQ-a, ali nema EQ; mnogo kognitivne inteligencije, ali nimalo emocionalne inteligencije, te me je to nagnalo na razmišljanje. Šta ako bi naša tehnologija mogla da oseti naše emocije? Šta ako bi uređaji mogli da prepoznaju i reaguju na naša osećanja, baš kao što bi reagovao i emocionalno inteligentan prijatelj? Ta pitanja su navela mene i moj tim da napravimo tehnologiju koja može da čita i reaguje na naše emocije, a naša početna tačka bilo je ljudsko lice.
So our human face happens to be one of the most powerful channels that we all use to communicate social and emotional states, everything from enjoyment, surprise, empathy and curiosity. In emotion science, we call each facial muscle movement an action unit. So for example, action unit 12, it's not a Hollywood blockbuster, it is actually a lip corner pull, which is the main component of a smile. Try it everybody. Let's get some smiles going on. Another example is action unit 4. It's the brow furrow. It's when you draw your eyebrows together and you create all these textures and wrinkles. We don't like them, but it's a strong indicator of a negative emotion. So we have about 45 of these action units, and they combine to express hundreds of emotions.
Dakle, ljudsko lice je jedno od najmoćnijih kanala koje koristimo da prenesemo društvena i emocionalna stanja, sve od zadovoljstva, iznenađenja, empatije do radoznalosti. U nauci o emocijama, sve pokrete facijalnih mišića nazivamo akcijskim jedinicama. Tako, na primer, akcijska jedinica 12 nije holivudski blokbaster, nego se radi o podizanju ugla usana, što je glavna komponenta osmeha. Probajte to. Hajde da svi nabacimo osmehe. Još jedan primer je akcijska jedinica 4. To je boranje obrve. To je kada skupite obrve i stvorite sve ove teksture i bore. Ne volimo ih, ali one su jasan pokazatelj neke negativne emocije. Tako imamo oko 45 ovih akcijskih jedinica i one se kombinuju da izraze stotine emocija. Podučavanje kompjutera da čita ove facijalne emocije je teško
Teaching a computer to read these facial emotions is hard, because these action units, they can be fast, they're subtle, and they combine in many different ways. So take, for example, the smile and the smirk. They look somewhat similar, but they mean very different things. (Laughter) So the smile is positive, a smirk is often negative. Sometimes a smirk can make you become famous. But seriously, it's important for a computer to be able to tell the difference between the two expressions.
zato što ove akcijske jedinice mogu biti brze, suptilne i kombinuju se na mnogo različitih načina. Uzmite tako, na primer, osmeh i zloban osmeh. Izgledaju pomalo slično ali imaju veoma različita značenja. (Smeh) Dakle, osmeh je pozitivan, a zloban osmeh je često negativan. Ponekad jedan zloban osmeh može da vas napravi poznatim. Ozbiljno, važno je da kompjuter bude u stanju da prepozna razliku između ova dva izraza. Dakle, kako to postižemo?
So how do we do that? We give our algorithms tens of thousands of examples of people we know to be smiling, from different ethnicities, ages, genders, and we do the same for smirks. And then, using deep learning, the algorithm looks for all these textures and wrinkles and shape changes on our face, and basically learns that all smiles have common characteristics, all smirks have subtly different characteristics. And the next time it sees a new face, it essentially learns that this face has the same characteristics of a smile, and it says, "Aha, I recognize this. This is a smile expression."
Obezbeđujemo svojim algoritmima desetine hiljada primera ljudi za koje znamo da se osmehuju, ljudi različitih etničkih pripadnosti, godina, različitog pola, a to isto činimo za podsmehe. Onda, uz dubinski pristup učenju, algoritam traži sve ove teksture i bore i promene oblika na našim licima, i u suštini uči da svi osmesi imaju zajedničke osobine, da se svi zlobni osmesi suptilno razlikuju od osmeha po osobinama. I sledeći put kada vidi novo lice, u suštini uči da ovo lice ima iste osobine osmeha i kaže „Aha, prepoznajem ovo. Ovo je izraz osmeha.”
So the best way to demonstrate how this technology works is to try a live demo, so I need a volunteer, preferably somebody with a face. (Laughter) Cloe's going to be our volunteer today.
Najbolji način da pokažemo kako ova tehnologija funkcioniše jeste da probamo demo-verziju uživo, tako da mi treba dobrovoljac. Poželjno je da taj neko ima lice. (Smeh) Kloi će nam danas biti dobrovoljac.
So over the past five years, we've moved from being a research project at MIT to a company, where my team has worked really hard to make this technology work, as we like to say, in the wild. And we've also shrunk it so that the core emotion engine works on any mobile device with a camera, like this iPad. So let's give this a try.
Dakle, u zadnjih pet godina, od istraživačkog projekta na MIT-u postali smo kompanija, u kojoj je moj tim vredno radio da ova tehnologija uspe, kako mi volimo da kažemo, u divljini. Takođe smo je smanjili tako da osnovni emotivni motor radi na bilo kom mobilnom uređaju koji ima kameru, kao što je ovaj Ajped. Dakle, hajde da probamo.
As you can see, the algorithm has essentially found Cloe's face, so it's this white bounding box, and it's tracking the main feature points on her face, so her eyebrows, her eyes, her mouth and her nose. The question is, can it recognize her expression? So we're going to test the machine. So first of all, give me your poker face. Yep, awesome. (Laughter) And then as she smiles, this is a genuine smile, it's great. So you can see the green bar go up as she smiles. Now that was a big smile. Can you try a subtle smile to see if the computer can recognize? It does recognize subtle smiles as well. We've worked really hard to make that happen. And then eyebrow raised, indicator of surprise. Brow furrow, which is an indicator of confusion. Frown. Yes, perfect. So these are all the different action units. There's many more of them. This is just a slimmed-down demo. But we call each reading an emotion data point, and then they can fire together to portray different emotions. So on the right side of the demo -- look like you're happy. So that's joy. Joy fires up. And then give me a disgust face. Try to remember what it was like when Zayn left One Direction. (Laughter) Yeah, wrinkle your nose. Awesome. And the valence is actually quite negative, so you must have been a big fan. So valence is how positive or negative an experience is, and engagement is how expressive she is as well. So imagine if Cloe had access to this real-time emotion stream, and she could share it with anybody she wanted to. Thank you. (Applause)
Kao što možete da vidite, algoritam je pronašao Kloino lice. To je ovaj beli granični okvir, koji prati glavne tačke odlika na njenom licu, dakle, njene obrve, njene oči, njena usta i njen nos. Pitanje je, da li može prepoznati njen izraz lica? Dakle, testiraćemo mašinu. Pre svega, da vidimo tvoje pokeraško lice. Da, super. (Smeh) Onda, kada se osmehne, ovo je iskren osmeh, odlično. Vidite da se zelena traka puni kada se osmehuje. To je bio širok osmeh. A jedan suptilan osmeh da vidimo da li kompjuter ume da prepozna? Prepoznaje i suptilne osmehe. Vredno smo radili da ovo ostvarimo. Zatim podignute obrve, pokazatelj iznenađenja. Boranje obrva, što je pokazatelj zbunjenosti. Mrštenje. Da, savršeno. Ovo su različite akcijske jedinice. Postoji ih još mnogo više. Ovo je samo skraćena demo verzija. Svako čitanje nazivamo tačkom emotivnih podataka i one mogu zajedno da rade da iskažu različite emocije. Dakle, na desnoj strani demo verzije - izgledaj kao da si srećna. Dakle, to je radost. Radost se povećava. Sad mi pokaži izraz gađenja. Pokušaj da se setiš kako si se osećala kada je Zejn napustio „One Direction". (Smeh) Da, naboraj nos. Super. Valenca je stvarno krajnje negativna, tako da mora da si bila veliki fan. Valenca označava koliko je iskustvo pozitivno ili negativno, a angažman je taj koji označava koliko je ona ekspresivna. Zamislite da Kloi ima pristup ovom emotivnom prenosu u realnom vremenu i da može da ga podeli sa kim god želi. Hvala ti. (Aplauz)
So, so far, we have amassed 12 billion of these emotion data points. It's the largest emotion database in the world. We've collected it from 2.9 million face videos, people who have agreed to share their emotions with us, and from 75 countries around the world. It's growing every day. It blows my mind away that we can now quantify something as personal as our emotions, and we can do it at this scale.
Dakle, do sada smo nagomilali 12 milijardi ovih tačaka emotivnih podataka. To je najveća baza emocija u svetu. Sakupili smo je kroz 2,9 miliona klipova lica, ljudi koji su pristali da podele svoje emocije sa nama, a to iz 75 zemalja širom sveta. Broj svaki dan raste. Raspamećuje me to da sada možemo odrediti količinu nečega tako ličnog kao što su emocije i da to možemo obaviti na ovom nivou.
So what have we learned to date? Gender. Our data confirms something that you might suspect. Women are more expressive than men. Not only do they smile more, their smiles last longer, and we can now really quantify what it is that men and women respond to differently. Let's do culture: So in the United States, women are 40 percent more expressive than men, but curiously, we don't see any difference in the U.K. between men and women. (Laughter) Age: People who are 50 years and older are 25 percent more emotive than younger people. Women in their 20s smile a lot more than men the same age, perhaps a necessity for dating. But perhaps what surprised us the most about this data is that we happen to be expressive all the time, even when we are sitting in front of our devices alone, and it's not just when we're watching cat videos on Facebook. We are expressive when we're emailing, texting, shopping online, or even doing our taxes.
Dakle, šta smo naučili do sada? Pol. Naši podaci potvrđuju ono što možda pretpostavljate. Žene su eskpresivnije od muškaraca. Ne samo da se više osmehuju, njihovi osmesi traju duže. Sada stvarno možemo odrediti šta je to na šta muškarci i žene reaguju drugačije. Pozabavimo se kulturom. U Sjedinjenim Državama, žene su 40% ekspresivnije od muškaraca, ali neobično je to da nema razlike u UK između muškaraca i žena. (Smeh) Godine. Ljudi koji imaju 50 godina ili stariji od toga su 25% emotivniji od mlađih ljudi. Žene u dvadesetima osmehuju se mnogo više od muškaraca istih godina, što je možda neophodno pri zabavljanju. Ipak, možda najveće iznenađenje u vezi ovih podataka je to da smo stalno izražajni, čak i kada sedimo sami ispred naših uređaja, i to ne samo kada gledamo klipove sa mačkama na Fejbuku. Izražajni smo kada šaljemo i-mejlove, SMS-ove, kupujemo onlajn, čak i kada obrađujemo porez.
Where is this data used today? In understanding how we engage with media, so understanding virality and voting behavior; and also empowering or emotion-enabling technology, and I want to share some examples that are especially close to my heart. Emotion-enabled wearable glasses can help individuals who are visually impaired read the faces of others, and it can help individuals on the autism spectrum interpret emotion, something that they really struggle with. In education, imagine if your learning apps sense that you're confused and slow down, or that you're bored, so it's sped up, just like a great teacher would in a classroom. What if your wristwatch tracked your mood, or your car sensed that you're tired, or perhaps your fridge knows that you're stressed, so it auto-locks to prevent you from binge eating. (Laughter) I would like that, yeah. What if, when I was in Cambridge, I had access to my real-time emotion stream, and I could share that with my family back home in a very natural way, just like I would've if we were all in the same room together?
Gde se ovi podaci koriste danas? Kada treba da razumemo kako da se angažujemo na mrežama, da razumemo viralnost i ponašanja pri glasanju, kao i da razumemo tehnologije koje osnažuju i omogućuju emocije. Želim takođe da podelim i primere koji su mi posebno dragi. Naočare koje omogućuju emocije mogu da pomognu pojedincima koji imaju oštećen vid da čitaju lica drugih ljudi i mogu da pomognu pojedincima sa autizmom da protumače emocije, nešto sa čim stvarno imaju problema. U obrazovanju, zamislite kada bi vaše aplikacije za učenje mogle da osete kada ste zbunjeni i uspore, ili kada vam je dosadno i ubrzaju, kao što bi dobar profesor uradio u učionici. Šta bi bilo ako bi vaš ručni sat mogao da prati vaše raspoloženje, ili kada bi vaš auto mogao da oseti kada ste umorni, ili kada bi vaš frižider znao kada ste pod stresom, pa se automatski zatvori da vas spreči da se opsesivno prejedate? Da, i ja bih to volela. (Smeh) Šta bi bilo da sam na Kembridžu imala pristup svom emotivnom prenosu u realnom vremenu, da sam mogla da ga podelim to sa porodicom kod kuće na prirodan način, kao što bih uradila da smo svi u istoj sobi zajedno?
I think five years down the line, all our devices are going to have an emotion chip, and we won't remember what it was like when we couldn't just frown at our device and our device would say, "Hmm, you didn't like that, did you?" Our biggest challenge is that there are so many applications of this technology, my team and I realize that we can't build them all ourselves, so we've made this technology available so that other developers can get building and get creative. We recognize that there are potential risks and potential for abuse, but personally, having spent many years doing this, I believe that the benefits to humanity from having emotionally intelligent technology far outweigh the potential for misuse. And I invite you all to be part of the conversation. The more people who know about this technology, the more we can all have a voice in how it's being used. So as more and more of our lives become digital, we are fighting a losing battle trying to curb our usage of devices in order to reclaim our emotions. So what I'm trying to do instead is to bring emotions into our technology and make our technologies more responsive. So I want those devices that have separated us to bring us back together. And by humanizing technology, we have this golden opportunity to reimagine how we connect with machines, and therefore, how we, as human beings, connect with one another.
Mislim da će kroz pet godina, svi naši uređaji imati emotivni čip i nećemo se sećati kako je bilo kada nismo mogli samo da se namrštimo uređajima, a da oni ne kažu: „Hmm, to ti se nije baš svidelo, zar ne?” Naš najveći izazov je veliki broj korisnika ove tehnologije. Moj tim i ja smo shvatili da je ne možemo napraviti sami, pa smo ovu tehnologiju učinili dostupnom tako da i drugi programeri mogu da počnu sa građenjem i iskažu kreativnost. Razumemo da su mogući i rizici i da je moguća zloupotreba, ali, budući da sam mnogo godina provela u radu na ovome, verujem da su prednosti čovečanstva sa emocionalno inteligentnom tehnologijom važnije od moguće zloupotrebe. Pozivam vas sve da budete deo te rasprave. Što više ljudi zna za ovu tehnologiju, to će više nas imati pravo da odlučuje kako će se ona koristiti. Dakle, kako naši životi postaju sve više i više digitalni, sve više gubimo bitku u pokušaju da smanjimo korišćenje ovih uređaja da bismo povratili naše emocije. Dakle, ono što ja pokušavam umesto toga je da uvedem emocije u našu tehnologiju da bi tehnologija bila prijemčivija. Dakle, želim da nas ovi uređaji koji su nas rastavili ponovo spoje. Kada damo ljudska svojstva tehnologiji, dobijamo zlatnu priliku da obnovimo način na koji se povezujemo sa mašinama i stoga, kako se mi, kao ljudska bića, povezujemo jedni sa drugima.
Thank you.
Hvala vam.
(Applause)
(Aplauz)