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 utječu na svako područje naših života, od zdravlja i načina na koji učimo do toga kako radimo i donosimo odluke, bile one velike ili male. Naše emocije također utječu na način na koji se povezujemo s drugima. Razvili smo se za život u ovakvom svijetu, no umjesto toga sve više i više živimo ovako - ovo je sinoćnji SMS moje kćeri - u svijetu lišenom emocija. Ja to želim promijeniti. Želim vratiti emocije u digitalni svijet.
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.
U to sam se upustila prije 15 godina. Bila sam računalna znanstvenica u Egiptu i bila sam primljena na doktorski studij na sveučilištu u Cambridgeu. Učinila sam nešto prilično neuobičajeno za egipatsku muslimansku mladenku: uz potporu supruga koji je ostao u Egiptu, spakirala sam kofere i preselila u Englesku. Na Cambridgeu, kilometrima daleko od kuće, shvatila sam da više vremena provodim s laptopom nego s bilo kojim drugim ljudskim bićem. Unatoč ovoj intimnosti moj laptop nije imao pojma kako se ja osjećam. Nije znao jesam li sretna, tužna, pod stresom, zbunjena, što je postalo frustrirajuće. Tim više, dok sam online kontaktirala s obitelji, osjećala sam kako sve moje emocije nestaju u cyber-prostoru. Nedostajala mi je kuća, bila sam usamljena, a nekada sam znala čak i zaplakati, ali svoje sam emocije mogla prenijeti samo ovako. (Smijeh) Suvremena tehnologija ima puno IQ-a, a ništa EQ-a, puno kognitivne inteligencije, ništa emocionalne inteligencije, što mi je dalo na razmišljanje - što kad bi naša tehnologija mogla osjetiti naše emocije? Što kad bi sve naprave mogle osjetiti naše raspoloženje i reagirati na njih onako kako bi to napravio emocionalno inteligentan prijatelj. Ta su pitanja mene i moj tim naveli na razvijanje tehnologije koja očitava i odgovara na naše emocije, a početna točka bilo nam 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.
Ljudsko lice jedno je od najmoćnijih kanala za prijenos društvenih i emocionalnih stanja, sve od užitka, iznenađenja, empatije i znatiželje. U znanosti emocija svaki je pokret facijalnih mišića akcijska jedinica. Npr. akcijska jedinica 12, nije to holivudski blockbuster, nego se radi o podizanju kuta usnice, što je osnovna sastavnica osmijeha. Probajte. Da vidimo te osmijehe. Drugi je primjer akcijska jedinica 4: boranje obrva. To je kada skupite obrve čime stvarate ovakve teksture i bore. Ne volimo ih, ali snažan su pokazatelj negativnih emocija. Imamo oko 45 ovakvih akcijskih jedinica koje se kombiniraju kako bi izrazile stotine emocija.
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.
Teško je naučiti računalo da ih očitava jer mogu biti brze, suptilne su i mogu se kombinirati na različite načine. Npr. smijeh i podsmijeh. Izgledaju koliko-toliko slično, ali znače različite stvari. (Smijeh) Osmijeh je pozitivan, a podsmijeh negativan. Nekad vas podsmijeh može proslaviti. No ozbiljno, za računalo je važno da može razlikovati ova dva izraza.
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."
Kako da to izvedemo? Tako da algoritmima damo desetke tisuća primjera osmijeha ljudi različitih nacionalnosti, dobi, spolova, a isto to učinimo i za podsmijehe. Zatim koristeći dubinsko učenje, algoritam traži sve te teksture i bore i promjene oblika lica te nauči da svi osmjesi imaju zajedničke karakteristike, a svi podsmjesi neznatno različite karakteristike. Sljedeći put kad ugleda novo lice, nauči da to lice ima iste karakteristike osmijeha pa kaže: "Aha, znam što je to - osmijeh."
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 demonstracije funkcioniranja ove tehnologije jest demonstracija uživo. Trebat će mi dobrovoljac, po mogućnosti netko s licem. (Smijeh) Cloe će biti naša dobrovoljka.
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.
Tijekom zadnjih pet godina iz istraživačkog projekta na MIT-u prerasli smo u tvrtku koja naporno radi da omogući funkcioniranje ove tehnologije, kako mi to nazivamo, u divljini. Smanjili smo je tako da ključni motor za emocije radi na bilo kakvom uređaju s kamerom, poput ovog iPada. Isprobajmo ga.
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 vidjeti, algoritam je prepoznao Chloeino lice vidljivo u ovoj bijeloj kutijici i prati njezine glavne crte lica, dakle obrve, oči, usta i nos. Pitanje glasi: prepoznaje li izraz lica? Testirat ćemo uređaj. Prvo mi pokaži pokerašku facu. Odlično. (Smijeh) I onda kako se smije, ovo je iskren osmijeh, sjajno. Zelena se pokazatelj povećava kako se smije. To je bio veliki osmijeh. Sad probaj nešto manje očito da vidimo hoće li ga prepoznati. Prepoznaje i manje očite osmjehe. Naporno smo radili da to postignemo. Zatim podignute obrve, pokazatelj iznenađenja. Naborane obrve, pokazatelj zbunjenosti. Namrgodi se. Tako, savršeno. To su sve različite akcijske jedinice, a ima ih još jako puno. Ovo je samo osnovna demonstracija. Svako očitanje nazivamo točkom emocionalnih podataka i zajedno mogu izraziti različite emocije. Na desnoj strani izgledaj sretno. To je sreća, povećava se. Sad nam pokaži gađenje. Sjeti se kako si se osjećala kad je Zayn napustio One Direction. (Smijeh) Da, naboraj nos. Odlično. Valencija je prilično negativna, mora da si bila njegov veliki fan. Valencija pokazuje pozitivnost, tj. negativnost iskustva, a angažman pokazuje koliko je ekspresivna. Zamislite da Cloe ima pristup ovom emocionalnom prijenosu uživo i da ga može podijeliti s bilo kime s kime želi. Hvala. (Pljesak)
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.
Dosad smo prikupili 12 milijardi ovih jedinica emocionalnih podataka. To je najveća baza podataka za emocije u svijetu. Prikupili smo ih iz 2,9 milijuna snimaka lica ljudi koji su pristali podijeliti svoje emocije s nama iz 75 zemalja diljem svijeta. Svakim je danom sve veća. Svakim me danom sve više oduševljava kako možemo kvantificirati nešto tako osobno poput emocija, i to možemo prikazati na ovoj skali.
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.
Što smo dosad naučili? Spol. Prikupljeni podatci potvrđuju nešto na što ste vjerojatno sumnjali. Žene su ekspresivnije od muškaraca. Žene se više smiješe, a i osmjesi im dulje traju te sada možemo zaista kvantificirati na što to muškarci i žene drugačije reagiraju. Prijeđimo na kulturu. U SAD-u žene su 40% eskspresivnije od muškaraca, ali zanimljivo je da tu razliku ne vidlmo u UK-u između muškaraca i žena. (Smijeh) Dob: ljudi od pedeset godina i više 25% su emotivniji od mlađih ljudi. Žene u dvadesetima smiju se više nego muškarci iste dobi, što je vjerojatno nužno za romantične veze. Vjerojatno najnevjerojatnija spoznaja jest da da smo ekspresivni cijelo vrijeme, čak i kad sami sjedimo ispred uređaja, a ne samo kad gledamo snimke mačaka na Facebooku. Ekspresivni smo dok pišemo mejlove, poruke, kupujemo online ili pak računamo 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?
Gdje se ovi podatci danas koriste? U razumijevanju toga kako funkcioniramo s medijima, dakle razumijevanje marketinga i glasačkog ponašanja, ali i u osnaživanju ili tehnologiji u službi emocija. Željela bih vam pokazati neke meni drage primjere. Naočale za očitavanje emocija pomažu osobama oštećenog vida da čitaju emocije drugih, a mogu pomoći i autistima da prepoznaju emocije, nešto što je njima zaista teško. Zamislite kad bi aplikacije za učenje u obrazovanju mogle osjetiti da ste zbunjeni i usporiti ili da vam je dosadno, pa ubrzati, baš poput odličnog učitelja u učionici. Što kad bi vam ručni sat mogao pratiti raspoloženje ili kad bi automobil osjetio da ste umorni ili da hladnjak zna da ste pod stresom, pa se automatski zaključa da se ne bi prejedali. (Smijeh) Meni bi to bilo super. Što da sam, dok sam bila na Cambridgeu, imala pristup emocionalnom prijenosu uživo i da sam to mogla podijeliti sa svojom obitelji na prirodan način, kao što bih to učinila da smo zajedno u istoj prostoriji?
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 za pet godina svi naši uređaji imati emocionalni čip i bit će nam teško zamisliti kako je bilo kad se nismo mogli samo namrštiti uređaju, a da nam on ne kaže: "Hmm, to ti se nije svidjelo, zar ne?" Izazov je u tome što ovu tehnologiju možemo primijeniti na razne načine, a moj tim i ja shvaćamo da ne možemo sve to napraviti sami. Stoga smo tu tehnologiju podijelili s drugim razvojnim inženjerima da je nastave razvijati i biti kreativni. Shvaćamo potencijalne rizike, kao i potencijal za zloupotrebu, ali osobno, nakon što sam tolike godine provela radeći na tome, vjerujem da su koristi za čovječanstvo od emocionalno inteligentne tehnologije puno veće od potencijalne zloupotrebe. Sve vas pozivam da budete dio rasprave. Što je više ljudi upoznato s tom tehnologijom, to će više nas imati pravo izabrati kako će se koristiti. Što se naši životi sve više digitaliziraju, to smo više osuđeni na propast u pokušaju da smanjimo upotrebu uređaja kako bismo povratili emocije. Ono što ja želim napraviti jest donijeti emocije u tehnologiju te je učiniti osjetljivijom na nas. Želim da nas ti uređaji koji su nas razdvajali ponovno spoje. Humaniziranjem tehnologije dobivamo jedinstvenu priliku ponovnog interpretiranja načina na koji se povezujemo sa strojevima te samim time i kako se mi kao ljudska bića povezujemo jedni s drugima.
Thank you.
Hvala vam.
(Applause)
(Pljesak)