humanitarian issues in the democratic republic of the congo. that is scheduled for 11:00 a.m. eastern. following last night's phoenix rally, president trump heading to reno, nevada to address thousands of military veterans at the 99 national convention of the american legion. c-span, where history unfolds daily.

in 1970 nine, c-span was created as a public service by america's television companies and is brought to today by your cable or satellite provider. now a discussion on the future of big data analytics and analyzing peoples personality traits based on their social media activities. this is from the computer science museum in mountain view, california. we will explore one of the most important facts about our present and future. large-scale data collection and analysis has and will continue to profoundly change politics in the developing and most especially the developed world. firms arely, private assembling profiles of everyduals, for example, eligible voter in the united states with the depth of

information that would have made jn girl hoover week with envy. the use of this so-called big data and the inferences made from it has a singular purpose, to craft and deliver messaging that will shape the future behavior of an individual, from buying a particular brand of toothpaste to discouraging a citizen from voting. from choosing one ridesharing service over another to vote one way or another on profound decisions like the u.k. brexit and the u.s. presidential election. these profiles are assembled thiswhat our guests evening calls our digital footprint. the traces of our daily lives that are captured often sold and analyzed. many of us don't realize we are leaving these footprints behind through our use of credit cards, web searches, online purchases, smartphone use, but we listen to

on streaming services, and what we watch on cable tv. tonight, of stanford university will introduce us to his work making assessments of individuals from the digital rents, particularly their facebook likes and profile pictures. they will also help us to begin to grasp how assessments like these are being and could be used to shape our political and social reality. ourse join me in welcoming guest to the stage. [applause] >> hi, david. good evening, everyone. thanks for helping us. on the curtain of the use of big data and our digital rent to assess and influence each other. maybe we can begin by having you describe your work for us and

what you believe can be learned from us, from our facebook likes and profile pictures. learning about people using surveys, i would look at the digital footprint that you saw introduced before that we are all leaving behind while using .igital products and services it is a great time to be a computational psychologist. it's a great time to be me leave an enormous amount of digital footprint behind, making 2012, ibm

estimated that we are leaving 50 megabytes of digital foot rents per day per person, which is an enormous amount of data. if you wanted to back it up on paper by printing it out on paper, letter-size paper, double-sided, font size 12, and you wanted to stack it up one day worth of data, the stack of paper would be from here to the sun four times over. guys -- exactly. you are generating, we are all generating enormous amounts of information. now, this information of course contains our trail of our behavior. our thoughts, feelings, social interactions. communications, purchases.

even the things we never intended to say, like not sure if you guys realize this, if you type a message on facebook, and then you decide, it is 2:00 a.m. and maybe i drank too much wine and i should not send it, and you abandon the message, guess what. it is still being saved and analyzed. it is not just this one platform. in most cases, data is preserved even if you think you have deleted it. my main goal is to take this data and learn something new about human psychology or human behavior. one of the byproducts of doing this is i will produce models that take your jewel footprints and we will try to predict your future behavior. maybe your psychological traits, such as personality, political views, and so on.

what was shocking to me when i started working in this field, is how accurate those models are. that is one shocking thing. they are also very difficult to interpret. i know a computer can predict your future behavior. a computer can reveal or determine your psychological traits from your digital footprint. it is very difficult for a human scientist to understand how exactly the computer is doing it, which brings me to this black box problem. which basically means, it might be human psychologist, scientists, would be replaced one day by ai. in the meantime, you basically have those models we don't really actually understand very well how they do it. they are amazing at predicting your future behavior, your psychological traits, and so on.

i worked with facebook likes quite a lot, not because facebook likes are the best type of digital foot print we are leaving behind. not at all. facebook likes are not so revealing. why? because liking happens in a public space. when you like something on facebook, you probably realize now your friends will see what you have liked. you wouldn't like anything really embarrassing or maybe something really boring, something you want to hide from your friends. but now, when you use your web browser or you search for something on google, or you go and buy something, you have much less choice. you will search for things he would never like on facebook. you would visit websites you would never like on facebook. you would buy stuff you would never like on facebook, like you

would buy medicine that is very revealing of your health. most of us do not like the medicine we are taking on facebook. which basically means if someone can get access to your data, credit card data, your search data, records from your mobile phone, this digital footprint will be way more revealing than whatever i can do using facebook likes. whatever findings i am coming up with, they are just conservative estimates of what can be done more revealing data. you can see the entire industry, the entire industries, not just one industry -- they are moving towards building their business models on top of the data we are producing. my favorite example is a credit card.

how many of you guys have actually paid for the credit card recently? we have a few people that maybe didn't do their research online properly, or are so fancy, they pay for their credit card. most of us, including me, we do not pay for credit cards. if you are not paying for something, and thick about it -- a credit card is an amazing, magical thing that allows you to pay for stuff without carrying cash. there is a complicated network behind it. computers crunching data and so on. we are not paying for it. why? we are the products of the credit card company. you can go to the website of visa or mastercard, or any other credit card operator, and you will see they see themselves not as a financial company. they started as a financial company, helping to channel

payments. now they see themselves as a consumer insights company. by observing the things you are buying and when you are buying them. how much you are spending on the individual level. they can learn a lot about you, but they can also extract information on a broader level. when they see recently people in san francisco started buying certain things or going to a certain restaurant. this is a very valuable information that can be sold. basically, if you are not paying for something, you most likely are a product. think about your web browser that you probably didn't pay for. your facebook accounts. your web search mechanism. one of the gazillions of apps you have on your phone. think about how much data you are sharing with the others. david: is your use of facebook

-- originally as a graduate student at cambridge, i believe. at the time, i believe facebook likes were public. anybody could see them. did that make that kind of data sets available to you since it was just public on facebook? is that what led you to use the data? michal: yes, you are just pointing out, another reason why i'm using facebook likes. i was lucky to have a huge data set of volunteers that donated their facebook likes to me as well as political views. personality and other psychological scores. basically other parts of their facebook profiles. in 2006 or 2007, my friend, he

started this online personality questionnaire. where you could take a standard personality test, and then he would receive feedback on your scores. it went viral. we had more than 6 million people that took the test. half of them generously gave us access to their facebook profiles. when you finish your test, it would ask you, if you would be willing in return for us offering you this interesting thing, if you would be willing to give us access to your facebook profile. which we would later use for scientific research. more than 6 million people took the test. we got around 3 million profiles, facebook profiles. at the beginning, in fact, people like to say, when i graduated from high school, i

already planned to run this research 20 years later. it was not the case. in my case, i kind of stumbled by accident, kind of got into this research by accident. i was developing traditional personality questionnaires. they are composed of, i am always on time at work. i like poetry. i don't care about abstract ideas. i had this data set of facebook likes where basically people who like poetry or -- i don't like abstract ideas, i don't like to read. what would strike me, why would we even asked people these questions if we can just go to their facebook profile, look at their likes, and fill in the questionnaire for them. i started running those simple

machine learning models that would take your facebook likes and try to predict what would be your personality score. this worked really well, which actually was pretty disappointing for me. i spent so much time developing those questionnaires. now a computer can do the same thing in a fraction of a second. we had other data in our data set. ok, we can predict personality. i wonder if we can predict political views. religion, sexual orientation, whether your parents were divorced or not. each time we asked the question, the computer would think and said, of course we can predict this. it is amazing. we were pretty suspicious in the beginning. we would rerun the models with independent data, thinking i must be doing something wrong.

given a computer can look at your facebook likes and predict with very high accuracy, close to perfect, whether you are gay or not. people don't like anything obviously gay on facebook. they do but it is a small fraction. for most of the users running those predictions, it was based on the movies they watched, books they read. it looks very counterintuitive to me at the time you could do it. now, as i got older, i spent more time running the models, it is pretty obvious. let me illustrate it for you guys, maybe let me try to offer you a short introduction to how those models work. it is actually pretty intuitive. if i told you there is an anonymous person and they like hello kitty. it is a brand, i am told. [laughter] you would probably be able to figure out, if you know what hello kitty is, that this person

is most likely female, young. an iphone user. you could probably go from there and make other inferences about her. you would be very correct. 99% of people who like hello kitty are women. you don't need computer scientists to make inferences of this kind. most of your likes, purchases on amazon, locations that you visited with your phone recording it, most of the search queries you put in google are not so strongly revealing about your intimate traits. it is not mean they are not revealing at all. they are revealing. the fact that you listen to lady gaga 30 times yesterday. it is not only weird, it shows

you something about your musical taste. it also probably -- it for sure reveals some tiny little extent, your sexual orientation, political views, intelligence, and virtually any other psychological trait we would like to predict. it is just that the amount of information there is really tiny. for a human being, this is useless. with a computer algorithm, it can get this tiny bit of information and aggregate it over thousands of digital footprints you are leaving behind to arrive at an accurate prediction of what your profile is. this is the paper i published in 2013. i was very excited about the promises of this technology. i'm still excited about the promises.

it is used to improve our lives in many ways and we don't realize how. if you don't believe me, think about netflix or spotify. facebook newsfeed. which is so engaging, people spend two hours a day on average looking at it. they don't look at it because it is boring and not wasn't to do it. they look at it because the ai made an accurate prediction about what your character is. it adjusted the message to make it engaging. there are also downsides, as i am sure we will be talking more about today. this was basically the paper i published in 2013. it got quite some press coverage. most of the coverage was like, this is so cool. we can predict whether somebody is a republican from their

facebook likes. nice, shiny gadget. i said, no, you have to realize, there are tremendous consequences for the future of our society. no, it is just so cool. this is as far as we go. interestingly, this is how the general public treated the results. policymakers and companies took notice. two weeks after the results were published, facebook changed privacy policies in such a way facebook likes were no longer public. before 2013, march when we publish the paper, before that, likes were public for everyone to see. i didn't even have to be your friend on facebook to see everything you liked. now our paper, our work showed by seeing what you like, i can also determine your sexual

orientation, political views, all those other intimate traits. i think it was a great thing facebook took notice and to preserve your privacy, switched that off. you also had u.s. governments and eu governments that took notice. they started working on changing the legislation to protect their citizens from some of the shortcomings of this phenomena. david: let's talk about some of the political uses of this work. i want to hear about how private firms are using big data analytics akin to your work to shift voting results in one way or another by micro-targeting messaging that is defined by its intended persuasion rather than accuracy.

one of these firms is cambridge analytical, part of a network of interconnected privately held firms that were involved in both the u.k. brexit vote and trunk campaign. because much of what we know about this story is due to recent investigative journalism. especially by the guardian newspaper. i thought i could provide the audience with a quick review of the story. cambridge analytical is a u.s. firm. mostly owned by robert mercer. until august, 2016, had steve bannon as the vice president. mercer is one of the most successful quantitative hedge fund managers. a major owner of breitbart news. a major financial supporter of the trunk campaign. steve bannon left his executive positions when he became manager

of the trunk campaign. of course, he is now the chief strategist to president trump. cambridge analytical employ data mining as well as government records, data sold by corporations to develop a dossier on every u.s. voter, which was first used by the ted cruz campaign and later the trump campaign to micro-target their messaging and direct their advised to influence voters. firm has, a canadian been a central consultant for this kind of thing with the various u.k. organizations that pushed for the brexit vote. cambridge analytica appears to be the owner. i should note, time magazine reported yesterday congressional investigators are looking at cambridge analytical in the context of their exploration of

russian activities. the u.s. presidential election as well, which may have included russian elements using techniques like those used by cambridge analytica. can you tell us about how your work relates to this whole thing? how we should think about the claims about the effectiveness of their work for the trunk campaign? michal: those are very good questions. there was a lot there. first of all, we don't really know how effective they were. interestingly, when you listen, they started by saying how amazingly efficient they were. when they realized governments were getting interested, some

things they have done became public, were not entirely legal, they suddenly changed theirs feel. now they say, it did not work at all. we are just making stuff up. which obviously means they are lying now or they were lying then. what i can tell you for sure, first of all, we have a lot of evidence that we produce and in academia showing such approaches work really well. we also see, it is not only the trunk campaign or the brexit campaign, but all the serious politicians employing messages like this in their campaigns. in fact, barack obama was the first politician to do it on a

massive scale. i don't remember any outrage, especially on the left side of the political spectrum. hillary clinton as well. she not only spent three times more money than donald trump doing personalized targeting on social media, also hired away smarter people in my opinion. yes, she lost, but she didn't lose because trump was using some kind of magical methods. the difference was caused by something else. when people ask me, can did analytics and personalized marketing win an election, the answer is, yes and no. it is a fact of life when you are running a political campaign. like tv spots and writing

articles, putting ads in the papers. but because everyone is using it, it is not giving anyone and unfair advantage. the only advantage here is barack obama was the first one to use it on a massive scale so it must have given him an unfair advantage. also, we as humans, we like to focus on the negative. it is great we focus on the negative. this is clearly a great psychological trait because it allows us to be successful as a species. probably even to successful to some degree. but, let's put aside focusing on the negative and risky. let's think about advantages of politicians being able to personalize their message.

there are a few interesting outcomes people seem not to notice. if i can talk to you one on one, that is what i can do. i can use algorithms to help me to talk to you one-on-one about things most relevant to you. they ran those algorithms to try to understand your character, your interest, your dreams. to make the message more interesting and relevant. which, first of all, has one outcome. messages became more important. in the past, i could say, yes we can. spend money showing it on every station and be successful. moreover, i could not do anything else because i lack the ability to communicate with people one on one. i had to settle down on a message that was a common denominator.

a message that would reach the broadest range of the population, yet was not particularly aimed at anyone. now, i can talk to you about things that are relevant to you. and someone else with something relevant to them. which means the content of the political program became more important. this, in turn, has two w important outcomes. if i make a message more relevant to you, you became more engaged in politics. this is great when we have more voters interested in the messaging they are getting. this is just great. makes of all, it also politicians think, what is important for you, david. in the past i could say yes, we can. now i had to hard about what is important to you and taking

about it would make me update my belief about what my political agenda should be. specifically when it comes to minorities, if i can broadcast my message on a tv, i focus on the majority interest because this is the logical broadcasting. if i can talk to people one on one, i can develop interest as a politician in what they have to say and what their interest and in. more engagement and more overtance of the message emotional slogan. the second change -- we have seen it in the recent election, politicians like donald trump bringingbernie sanders in people into the political process that traditionally were not so interested, disengagement politics because they thought there was nothing in it for them. i believe he even if you disagree with those new people

that were brought to the stillcal process, you recognize it's great for democracy when people are engaged in politics. the other outcome of personalized marketing is that if i can talk to you about things that are relevant to you, i don't need to show you this slogan 20 times, i can just have one conversation with you through social media. i'm exaggerating now but what i'm saying is i don't need to spend so much money on communicating because i can communicate with you using more relevant messages, which is another great outcome for democracy, which is decreasing the entry cost into politics. we have seen it in american elections, we have seen with donald trump and bernie sanders, who were not establishment candidates. they didn't have much money compared to other politicians in the race. i also didn't have experience in running big scale presidential

campaigns. they had to basically do it on a budget, in a new way. peoplearted talking to directly about the issues that , which meansabout at the end of the day we have those two candidates, and you may be stuck with one or both of them, but i believe it is great for democracy that you don't need a lot of money and backing from the industry and establishment to be a part of the political process. we have seen the same with brexit. i'm not a big fan of brexit myself. it seems even people campaigning for brexit are not fans. but at the time of the campaign, these ragtag political militia with no experience or money but they were able to enter the political process. i'd like to challenge you a

little bit on this characterization. micro-targeting is producing messages that are relevance of, the these messages is they are persuasive quality, it has nothing to do with their accuracy, nothing to do with their positive contribution to civic discourse. the be-all and end-all of the messaging is persuasion. see as the great danger in this sort of work is actually an assault on consensus reality. . if there is pervasive and endemic and ceaseless micro-targeting, especially of messages that are intended to be persuasive politically, you will end up -- a result of that, i fear, is that people will end up

living in essentially different informational worlds and will no longer have the ability to agree on what reality is, so how can you have a democracy if you cannot agree on what is real or not real? [applause] david: that is not against you. michal: i am glad you guys are clapping, because you know where there was a perfect consensual reality, you know where there was perfect consensus for reality, soviet russia. perfect, one tv station government approved, one pravda, the truth newspaper government approved. if you knew something that other people did not know, you probably ended up in the concentration camp. so i am glad you guys clapped, because it was a bit ironic to me. i'm sorry. let me actually -- why? because, thank you. [applause]

michal: it is actually, no, i reacted too aggressively, but maybe because i was born behind the iron curtain in a country where we had perfect information bubble. you know, the bubble was exactly the same for everyone. america luckily, tried to break the information bubble by dropping printing presses into poland so the underground press could produce and spread some, some fake news, as the communist regime would call it. so yes, basically we have the this myth now, which i believed for the longest time, everybody is telling you we are living in echo chambers and information bubbles and systems are giving us information crafted for us that somehow is making society worse, because we now know different things about the

bubbles not really overlapping. i was thinking, this is very bad because everybody says it is bad, but then i actually in the context of the findings started thinking about it. look, i strongly believe, and i did some research on that as well, that it is not bad at all. first of all, there is absolutely no evidence -- let me start differently. humans are just, we are just destined to live in an echo chamber. it is called confirmation bias in psychology and it basically means that if you have a worldview and get new information, and it contradicts your worldview and is not compatible, you will have a tendency to reject it. you don't always reject it, but you like information that confirms your worldview a bit more. it is not a bad trait to have. if you did not have it, you would be crazy because any new information you got, you would

think -- ok, interesting. lizard people running the world, very interesting. no, luckily we have this, like our brains like to have consistent mental structures there. so one of the effects is we will have a preference for information that confirms our views. and the systems recognize that, so they will give us more information that will confirm our views. of living in kind echo chambers. but those echo chambers today are way larger than they have ever been in the history of humankind. let me give you an extreme example. if we are born in a little town anywhere in the world, let's say america, 100 years ago. you only knew what your priest or your teacher or your community told you. guess what? 99% of that was fake news.

now you are living in a society where there is not only other people like teachers, and your friends at work, social networks are much larger, journalists are trying to constantly give you some additional information, get you out of your bubble. and algorithms are entering the race and try to give you personalized views of the world. what happens is the bubble is expanding. in the process of the bubble expanding, they also stop perfectly overlapping. if you live in your bubble, by the way it is larger than whatever bubble a human has occupied ever before now. i live in my bubble, my growing bubble, and our bubbles grow apart, which makes me aware, he is in a different information bubble. tragedy, tragedy. if you live in soviet russia, you are never able to look at

people with different information bubbles. so you never thought about it. you just kept living in a small, tiny echo chamber. which brings me to a related topic of fake news. i did not see any evidence, and i encourage you to send me some if you have any, that we are somehow surrounded by more fake news today than we were surrounded by 20 years ago. quite the opposite! [laughter] michal: i will take that. quite the opposite, the amount of valid information that we have, not only as a society but also each individual person in the room, is again away larger than whatever people had in the past. and one of the outcomes of us having so much valid information, and also being able to access any information

humanity has ever produced, including sensitive data, just with one click of the mouse on on the internet, what happens is if you have fake news or you heard something, you heard a story, you can quickly debunk it. what happens in the present society is we have gotten so quick at debunking stories that you basically hear the phrase fake news, fake news, all the time, which creates an impression of -- wow, we are surrounded by fake news. of course we are, there is a lot of fake information around, but it is way less than ever in the history in the past. if someone has evidence to the contrary, i would love to receive it. please send it to me. david: i think, from my perspective having those bubbles

overlap is a really important thing. but let's turn, let's pivot and talk about some of your very interesting work that is going on right now working with photographs of people's faces. particularly facebook profile pictures. in recent talks you say that these neural networks, the machine learning algorithms you employ, can identify a man as straight or gay by pictures of his face, or identify a woman as extroverted or introverted by a picture of her face. how is that possible? michal: yes, in my recent work i got interested in seeing what the algorithms can predict, if they can determine intimate

traits based on a still image of their faces. when i mention it, especially when i mention it to colleagues in academia they say, oh my god. we lost you. [laughter] and it is very bad. but what i think they keep forgetting is in fact humans are great at predicting intimate traits, determining intimate traits of other people based on their faces. we are so good at it that we kind of do not realize we are doing it all the time. let me give you an example. gender is a pretty intimate traitsbut you have no looking at somebody's face. emotions are intimate psychological traits. we can very quickly detect other people's emotions just buy a quick glimpse on their face, even when they are trying to hide that emotion we are still able to detect it.

think about race. think about genetic issues, like there are certain disorders we can recognize by looking at some -- someone's face. another genetic expression of genes is recognizing that somebody is the child of somebody else. when you say, you look like your father, you are actually saying i see through your face your genome. i see it is similar to the genome of this other guy, and he seems to be your father. it is like a magical skill. now, humans are good at predicting those kind of intimate traits, but we are not good at predicting other intimate traits like personality or sexual orientation, or political views. this might mean that there is no information about your political views on your face, but it also could mean that your brain has not evolved or do not learn to extract this information from a human face.

it might be that sexual orientation is as clear, clearly displayed on your face, as your gender, is just the human brain does not do well at revealing it. guess what, it seems that algorithms can basically do it pretty well. in terms of sexual orientation, more than 90% distinction between straight and gay men. and personality predictions, those are comparable with a short personality questioner. how to computers do that? well, actually it is no easy answer, because it is a black box model that i would love to understand, but my brain is too weak to do it. it seems computers are great at looking at giveaways that are on

our faces, then putting together hundreds of little pieces of signals into an accurate production of a given trait. much like facebook likes. and there is some evidence of that. one example is if you take one picture of an extroverted person, you would not know if they are extroverted or not, but if you take 100 pictures of extroverted people and you overlay them, make an average face, suddenly a human being is able to very accurately distinct between an extrovert and introvert. it seems the information is there, but it is too weak for a human being to detect. for a computer it is easy. david: with the networks you are using to do this classification work, they are explicitly and fundamentally like non-explanatory. they do things, right? you train a classifier with pictures and you tell it, this,

yes or no, yes or no, and then it starts to be able to identify cats, pictures or whatever. it is just a trained classifier, so whether it is picking up in the case of your work like on straight or gay male faces, is it detecting subtle social and cultural information in the photography, or is it picking up, you know, something that is actually of the face? there is no way to know. right? michal: we can test it by changing morphological -- by taking a picture in photoshop in some elements like making your nose longer or broader or whatnot, and see what the computer does, if it changes its mind about you.

by doing that, you can basically experiment with the computer and reveal what features of the face are predictive of being extroverted or introverted, gay or straight. at the end of the day, we could have a separate conversation just about that, what makes your face look extroverted or gay, but at the end of the day it does not matter whether those are morphological features or whether it is something cultural or environmental that allows the prediction, because at the end of the day we see that the prediction is possible. when people say, what if i try to maybe change my hairdo and fool the algorithm. guess what, as soon as people change their hairdos, the computer would move on to you something else in the prediction. what i think is crucial and key

in those studies showing you can take a human face and predict their traits is the following. we can talk about introducing good policies and introducing good technologies that will protect our data from being used to reveal our intimate traits. but at the end of the day, it is difficult to imagine this working out. why? first of all, it is difficult to police data. they can move across borders really quickly and can be encrypted, stolen, without a person even noticing. organizations such as nsa cannot reliably defend data, so how can we expect that we as individuals can protect our own data. which basically means in the future there will be more data about us out there. algorithms are also getting better at turning the data into

accurate predictions of our intimate traits, our future behavior, and so on. moreover, even if you gave me full control over my data, there is still a lot i want to share. i want the discussion to be available to people after, i want my blog to be read by people, i want my twitter feed to be public, and most importantly i want to walk around without covering my face. [laughter] basically, my conclusion is, going forward it is going to be no privacy whatsoever. the sooner we realize that, the sooner we can start talking about how to make sure that the privacy world is still habitable and safe and nice to live in. now when people say, how can you say that we should work on technology to continue protecting our privacy, but yes let's do it, but realize it is a

distraction because it makes people believe that we can have privacy in the future. and i believe now, this belief is completely wrong. to stress the importance of that, we are having a conversation about how invasion of privacy, how revealing our intimate traits can be used to let say manipulate us to buy products or maybe vote for political candidates. well, creepy, it makes me feel uneasy and so on. but we have to realize that outside of our western liberal free bubble, losing privacy can be a matter of life or death. think about countries where homosexuality is punished by death. if a security officer there can

take a smartphone, take a photo of somebody's face, and reveal their sexual orientation, this is really, really bad news for the gay men and women all around the world. now think about political views. think about other intimate traits like intelligence and so on. basically, the sooner that we make sure that we are acting, or we think -- we basically take an assumption that there will be no privacy in the world, how do we change the international politics? how do we make sure that lives of minorities, religious minorities, sexual minorities, political minorities in other countries are preserved, even in in the post privacy world? it is a question we should be talking about now and not how to change the policy to protect our

privacy better, because guess what -- you already lost. we can win the battle, but we completely lost the war already. david: we can really talk a lot about that, because in preparing for this and reading about this very position, you know, it is a post privacy world, deal with it. i really truly wondered, is democracy possible in a post privacy world. does that make the effort to create laws that mitigate or prevent such a condition, does that make it sort of an existential question? it's how my thinking went. i do not think we can solve that in the time available. i want to turn to some questions from the audience. apparently, lots of people had this question.

can you change your digital profile by liking items you actually do not like, or by searching misleading things to sort of cover your tracks? [laughter] michal: that is a great question. great question. my answer would be, no you cannot. because maybe you can like some random things, but first of all it would make you look pretty weird. to your friends. people would not do it, right? imagine posting like 100 status updates and only one of them is real and the rest is some kind of random gibberish. [laughter] nobody would do it, not to mention a computer would have no trouble figuring out which one of those 100 is an actual status update and which one is not. so, no, you cannot do it because it not only would make all of

those platforms like facebook and google in netflix completely not fun anymore, but it also would make your life not fun. imagine with your credit card, you have to buy 100 random things -- [laughter] before you bought whatever you want to buy. it is not possible. let me give you -- even with facebook likes it is not possible. there is an anecdote here. one of the results i wrote about they study, and this was result that people with high intelligence -- people who like curly fries on facebook tend to have higher intelligence. the correlation is actually very tiny, because the fact that you like curly fries does not make you smart. but there is a tiny correlation that when you combine it with other likes, you can reveal a

person has a higher iq. there was a test dog when this fact was mentioned and the next day the popularity of curly fries on facebook went through the roof. everybody liked them on facebook. guess what, algorithms quickly discovered that. so this is why we call it machine learning, because it realized, ok, curly fries is no longer diagnostic of high intelligence. [laughter] david: does that suggest that it is like the pattern of data points rather than any particular data point that is where you have, or you can find a signal for those traits? obviously, even though i love curly fries -- of course, as we all are. everyone in this room. it is nonsensical that that could have anything to do except

by some baroque argument that there is some cultural signal in liking curly fries. i do not see it. does that suggest -- not a particular data point, but it is patterns? michal: the power is in numbers. the more data you have about someone, the more accurate prediction would be. even when you look at things like signal theory. i didn't want to bring it up, but look at signal theory -- if you have a real signal, but you add a lot of random noise around it, you just need a slightly more of a signal and you are still going to discover what was the truth there. so unfortunately this is a great idea, but it is not going to work. [laughter] david: here is another representative question i think also many people asked. you argue data analytics can be used to engage more people in

politics, to which the writer of the question agrees, however could it not also be used to dissuade voters from voting? some argue certain political parties benefit from lower voter turnout. may incentivized to try to achieve this through this sort of thing we were talking about. michal: good point. no question that trying to discourage people from voting is an awful democratic thing to do. -- antidemocratic thing to do. but, you guys have to realize it is not the fault of social media that this is possible, it is the fault of the cultural and legal environment in this democracy, where it is ok to put negative adverts on tv, telling bad things about the other politicians. so if you are concerned with people being discouraged from voting, i think that it will be

, again, it will probably be impossible to come up with regulation that would prevent politicians from actually doing it somehow. because maybe they will not do it themselves, they will ask friends in other countries to leash out some bots that will do the job for them. at the end of the day, also when i am discouraging you from voting i am not saying do not go and vote, i make up a story and tell you about a pizza place -- [laughter] so there are other ways, ways that are difficult to police. if you are concerned about people not going to vote, think about a smarter way of solving the problem than regulating traditional media or social media, like for instance -- and i am not an expert, but one thing that comes to mind is left -- let's make voting and --igate everything

obligatory thing, but also the duty that we have as citizens. [applause] david: the french example. [laughter] i think this is a very interesting question. can or maybe how can the sort of technologies and techniques we have been discussing be used to allow individuals to understand, how they are being profiled? what they look like in these kinds of big data views? michal: great question. i see quite a few apps out there that are basically aimed at doing this. you can go and open such apps and they will tell you how you could potentially be seen by advertisers or platforms. one of such apps is hosted by my previous academic institution.

cambridge university. it is called apply magic sauce.com and you can go there and basically the platform will take your facebook likes and tell you what predictions can be made based, what predictions, what can be determined from your facebook likes. i would argue a simpler way of a -- a a a a a a a a probably see stories about hillary or another politician. how facebookbly

sees political issues. >> i think you'd find this question encouraging. how to live get into this? question. a great i would encourage everyone to get into the field of research and continue setting. it in the past, i nearly dropped out of high school because i was so excited about getting my start up and i cropped up from college three times because i was so excited about running my but then i discovered thence by accident in it is best thing in the world.

people pay to work in academia. there's another angle to it which is i would strongly whether youeryone are an artist or politician or journalists, you should try to learn programming. programming is actually fun. building toys. we are leaving a few minutes rightso discuss human issues in the democratic republic of congo. adoptionsrnational - ersight activities, and