[Music] live from cambridge massachusetts extracting the signal from the noise it's the cube covering the MIT chief data officer and information quality symposium now your host dave Volante and paul Gillett hi buddy welcome back to Cambridge Massachusetts we're at MIT Paul Gillan and myself are here for two days and we're really pleased to have sandy Pentland on he's the director of MIT Media labs entrepreneurship program just coming off a keynote mr. Alex sandy Pentland Spellman thanks for coming with you how'd you get that name sandy was that the color you know my dad was named Alex too so I had to get the diminutive so Alexander turns into Zander or Sasha or sandy ah excellent so man it's stuck so we learned from your keynote today that like your mom said hey if every other kid jumps off the bridge do you and the answer should be yes why is that well if your other friends or presumably as rational as you and have same sort of values as you and if they're doing something that looks crazy they must have a piece of information you don't like maybe Godzilla is coming bridges come and it really is time to get off but and so so while it's used as a metaphor for doing the irrational things it's actually shows that using your social context can be most rational because it's a way of getting information that you don't otherwise have so you broke down your talk to chief data officers and new types of analysis smarter organizations smarter networks and then really interesting new new architecture if we could sort of break those down sure you talked about sort of networks not individual nodes as really should be the focus to understand behavior can you unpack that a little well it's a little bit like the bridge or metaphor you know a lot of what we learn a lot of our behavior comes from watching other people we're not even conscious of it but you know if everybody else starts you know wearing a certain sort of shoe or or you know acting in a certain or using a phrase in business like all these new sort of buzz phrases like oh you have to - because it's to fit in it means something it's it's part of being hyper formants and being part of your group but that's not in data analytics today today what they look at is just your personal properties not what you're exposed to and the group that you're part of so they would look at the guy on the bridge and they say he's not going to jump because he doesn't have that information but on the other hand if all of other people who like him are making a different decision he probably is going to jump and your research has been you dig into organizations and you've found the relationship between productivity and this type of analysis has been pretty substantial very substantive offenses a ssin and outside of the organization dealing with customers so people focus on things like personality history various sort of training things like that what we find is compared to the pattern of interaction with other people so who do you talk to when and what situations those other factors are tiny they're often a whole order of magnitude less important than just do you talk to all the people in your group do you talk outside of your group do if you violate the org chart and talk to other people if you do you're almost certainly one of the high productivity high innovation people so what what impact does this have or were the implications of this on organizations which historically have been have been highly Madonn hierarchies reporting structures all of these institutions that we evolved in the post-world War two ERA is this working against their productivity well what they did is is they set some simple rules in that they could deal with and wrap their head around but what we find is that those simple rules are exactly the opposite of what you need for innovation and because really what they're doing is they're enforcing silos they're enforcing atomization of the work and everybody talks about we need to be more fluid we need to be more innovative we need to be able to move faster and what that requires is better communication habits and so what we find when we measure the communication habits is that that's exactly right better communication habits lead to more innovative organizations what's really amazing is almost no organization does it so people don't know does everybody talk to everybody in this group do they talk outside of the group there's no graphic there's no visualization and when you give a group a visualization of their pattern of organization of communication they change it and they become more innovative they become more productive I'm sure you're familiar with holacracy this idea that of doing away with with organizational boundaries and sort of do titles and sure everybody talks to everyone is that in your view a better way to structure an organization think that's too extreme but it's headed in the right direction I mean so what we're talking first of all people try to do this without any data so you know everybody's the same well everybody really isn't the same and how would you know if you're behaving as well as the same as other people or I mean there's no data so so what I'm suggesting is something that's sort of halfway between the two yeah you can have leaders you can have organization in there but you also have to have good flow of ideas and what that means is you have to make talking outside your org chart a value it's something you're rewarded for it means that including everybody in the loop in your organization is something you ought to be rewarded for and of course that requires data so the sorts of things we do with peoples we make displays could just be piece of paper that shows the patterns of communication and we give it to everybody and you know what people actually know what to do with it when you give it to them they say well gee you know this group of people is all talking to each other but they're not talking to that group maybe they ought to talk to each other it's that simple but in the lack of data you can't feel so you instrumented people essentially with let's badges and you could measure conversations at the watercooler yeah they're their frequency their duration not the content not the content just that's the activity just is it happening right and is it happening between groups just just people from this group go to that other groups water cooler stuff like that and that actually is enough to really make a substantial difference in the corporation and you gave an example of you were able to predict trending stories on Twitter better than the internal mechanism and Twitter did I understand that Kerina so what we've done by studying organizations like this and coming up with these sort of rules of how people behave so the notion that people learn from each other and that it's the patterns of communication that matter you can encode that along with machine learning and suddenly you get something that looks like machine learning but in many ways it's more powerful and more reliable and so we have a spin-out called Endor and what that does is it lets your average guy who can use a spreadsheet do something that's really competitive with the best machine learning groups in the world and that's pretty exciting because everybody has these reams of data but what they don't have is a whole bunch of PhDs who can study it for six months and and come up with a machine learning algorithm to do it they have a bunch of guys that are smart know the business but they don't know the machine learning so it endured doesn't supply something like a spreadsheet to be able to allow the normal guy to do as good as the machine learning guys there's a lot of focus right now on anticipating predicting customer behavior better a lot of us been focused on on individuals understanding individuals better is that wrongheaded I mean should marketers be looking more at this group theory and treating customers more as buckets of similar behaviors it's not it's not buckets but treating people as individuals is is a mistake because while people do have individual preferences most of those preferences are learned from other people it's keeping up with the Jones it's fitting in its it's learning what the best practice is so you can predict people better from the company they keep than you can from their demographics always virtually every single time you can do better from the company they keep than from the standard sort of data so what that means is when you do analysis you need to look at the relationships between people and at one level it's sort of obvious you analyze somebody personally without knowing something about their relationships right about you know the type of things they do the places they go those are important but they're usually not in the data and what I find is I do this with a lot of big organizations and what I find is you look at their data analytics it's all based on individuals and it's not based on the context to those individuals absolutely I want to ask you further about that because when I think of the surveys that I fill out they're always about my personal preference Yahoo I want to do I can't remember ever filling out a survey that asked me about what my peer group does are you saying that those are the questions we should be asking yeah exactly right and of course you want to get data about that you want to know if if you go to these locations all the time to go to that restaurant you go to this sort of entertainment who else goes there what are they by what's trending in your group because it's not the general population and these not necessary people I know but they're people I identify with Yammer haps that's why I go to certain restaurants not because my friends go there but because people who I aspire to be like yeah there yeah and and the other way around you go there and you say well gosh these other people are like me because they go here too and I see that they're you know wearing different sort of clothes or they're by or the simplest thing you go to restaurants you see other people all buying the mushi yes maybe I should try the mushi I usually don't like it but seems to work well and this is I like this restaurant and everybody else who comes here likes it so I'll try it right it's that simple so it's important to point out we're talking about the predictive analytics Capas they're probably people watching might say this Sandi's crazy we mean we don't want it personalized we want to personalize the customer experience still I'm presuming sure but when we're talking about predictive analytics you're saying the the community the peer group is a much better predictor than the individual that's right yeah okay so I want to come back to the the org chart these are you saying that org charts shouldn't necessarily change but the incentives should or your previous thing to do is you have an org chart but the incentives that are across the entire organization is good communication within the box you're in and good communication outside of the box and to put those incentives in place you need to have data you need to be able to have some way of estimating does everybody talk to each other do they talk to the rest of the organization and there's a variety of ways you can do that we do it with little badges we do it by analyzing phone call data email is not so good because email is not really a social relationship it's just this this little formal thing you do often but by using things like the badges like the phone calls surveys for that matter right you can give people feedback about are they communicating in the right way are they communicating with other parts of the organization and by visualizing that to people they'll begin to do the right thing you had this notion of network tuning oh you don't want an insufficiently diverse network but you don't want a network that's too dense you might find the sweet spot in the middle desert how do you actually implement that that tuning well the first thing is is you have to measure okay you have to know how dense is the social interaction the communication pattern because if you don't know that there's nothing to - right and then what you want to ask is you want to ask the signal property of something being two dances the same ideas go around then around and around so you look at the graph that you get from this data and you ask you know this Joe talked to Bob talk to Mary talk to Joe talk to you know is it full of cycles like that and if it's too full of cycles then that's a problem right because it's the same people talking to each other same ideas going around and there's some nice mathematical formulas for major in it they're sort of hard to put into English but it has to do with if you look at the flow of ideas are you getting a sufficiently diverse set of ideas coming to you or is it just the same people all talking to each other so are you sort of cut off from the rest of the world in your book social physics you talk about rewards and incentives isms and one of the things that struck me as you say that that rewards that people are actually more motivated by rewards for others than for themselves correct me if I'm wrong if paraphrasing you wrong there but but there's but but rewarding the group or or doing something good for somebody else is actually a powerful incentive is it is that the true the case well you said it almost right so so if you want to change behavior these social incentives are more powerful than financial incentives so if you have everybody in a group let's say and people are rewarded by the behavior of the other people in the group what will they do well they'll talk to the other people about doing the right thing because their reward my reward depends on your behavior so I'm gonna talk to you about it okay and your reward depends on it you'll talk and I don't know so what we're doing is we're creating much more communication around this problem and social pressure because you know if you don't do it you're screwing me and and you know I may not be a big thing but you're gonna think twice about that whereas some small financial award usually it's not such a big thing for people so if you think people talk a lot about you know persona persona marketing when I first met John Fourier he had this idea of affinity rank which was his version of you know peer group PageRank hmm do you do you hear a lot about you know get a lot of questions about persona persona marketing and and what does your research show in terms of how we should be appealing to that persona so sorry good questions about that some time and I don't know what he really originally intended but the way people often imply it is very static you have a particular persona that's fixed for all parts of your life well that's not true I mean you could be a baseball coach for your kid and a banker during the day and a member of a church and those are three different personas and what defines those personas it's the group that you're interacting with it's it's the the people you learn with and try and fit in so your persona is a variable thing and the thing that's the key to it is what are the groups that you're you're interacting with so if I analyzed your groups of interactions I'd see three different clusters I'd see the baseball one I'd say the banking one I'd see the church group one and then I would know that you have three personas and I could tell which one you're in typically by seeing who you're spending time with right now is the risk of applying this idea of behaviors influenced by groups is there the risk of falling over into profiling and essentially treating people anticipating behaviors based upon characteristics that may not be indicative of how any individual might act back credit alcoholics as you example right I don't get a job because people like people who are similar to me tend to be alcoholics let's say this is different though so this is not people who are similar to you if you hang out with alcoholics all the time then they're really eyes are good on that you're an alcoholic it may not be yes and there is a risk of over identifying or or extrapolating but it's different than people like me I mean if you go to the you know the dingy bars were beers or a buck and everybody gets wasted and you do that repeatedly you're talking about behaviors rather than characteristics behaviors rather than characteristics right I mean you know if you drink a lot maybe you drink a lot so we have a question from the crowd so it says real time makes persona very difficult yeah so it was come back to furriers premise was I was Twitter data you know such is changing very rapidly so are there social platforms that you see that can inform in real time to help us sort of get a better understanding of persona and affinity group affinity well there are data sources that do that right so first as if I look at telephone data or credit card data even for that matter sure this geo-located I can ask but what sort of people buy here or what sort of people are in this bar or restaurant and I can look at their demographics and where they go to I showed an example of that in San Francisco using data from San Francisco so there is this data which means that any app that's interested in it that has sufficient breadth and although sufficient adoption can do these sorts of analyses can you give an example of how you're working with the many organizations now I'm sure you can't name them but can you give an example of how you're applying these principles practically now whether it's in law enforcement or in consumer marketing how are you putting these to work well there's a bunch of different things that that go together with this view of you know it's the flow of ideas that's the important thing not the demographics so talk about behavior change and we're working with a small country to change their traffic safety by enrolling people in small groups where you know the benefit I get for driving right depends on your safety and we're good buddies we know that that's how you sign up sign up with your buddies and what that means is I'm going to talk to you about your driving if you're driving in a dangerous way and that we've seen in small experiments is a lot more effective than giving you points on your driver's license or discount on your insurance the social relationships so so that's an example another example is we're beginning a project to look at unemployment and what we see is is that people have a hard time getting re-employed don't have diverse enough social networks and it sounds kind of common sense but they don't physically get out enough compared to the people that do get jobs so what's the obvious thing well you encouraged them to get out more you make it easier for them to get out more so those are some examples when you talk about health care what you can do is you can say well look you know I don't know particular things you're doing but based on the behavior that you show right and the behavior of the people you hang with you may be at much higher risk of diabetes and it's not any particular behavior this is the way medical stuff is always pitched is you know it's this behavior that beer every combination of things all right and so you're not really aware that you're doing anything bad but if all your buds are at risk of it then you probably are too because you're probably doing a lot of the same sort of behaviors and medicine is a place where people are willing to give up some of the privacy because the consequences are so important so we're looking at people who are interested in personalized medicine and are willing to you know share their data about where they go and what they spend time doing in order to get statistics back from the people they spend time with about what are the risk factors they pick up from the people around them and the behaviors they engage in um your message this to the cdos today was you know you were sort of joking you're measuring that right and a lot of times they weren't a lot of the non-intuitive things your research has found so I wanna talk about the data and access to the data and how the CBO can you know affect change in their organization a lot of the data lives in silos I mean if they certainly think of social data Facebook LinkedIn yeah Twitter you mentioned credit card data is that a problem or is data becoming more accessible through api's or is it still just sort of a battle to get that data architecture running well it's a it's a battle and in fact actually it's a political and very passionate battle and it revolves around who controls the data and privacy is a big part of that so one of the messages is that to be able to get really ditch data sources you have to engage with the customer a lot so people are more than willing our research we've set up you know entire cities where we've changed the rules and we've found that people are more than willing to volunteer very detailed personal data under two conditions one is they have to know that it's safe so you're not reselling it you're handling it in a secure way it's not going to get out in some way and the other is that they get value for it and they can see the value so it's not spreading out and they're part of the discussion so you know you want more personalized medicine people are willing to share right because it's important to them or for their family you know if you want to share we're willing to share very personal stuff about their kids they would never do that but if it results in the kid getting a better education more opportunity yeah they're absolutely willing so that leads to a great segue into enigma yeah you talked about enigma as a potential security layer for the internet but also potential privacy yeah solution so talk about enigma where it's at yeah what it is where it's at and how it potentially could permeate yeah so we've been building architectures and working with this sort of problem this conundrum basically datas and silos people feel paranoid and probably correctly about their data leaky now companies don't have access to data don't know what to do with it and a lot of it has to do with safe sharing another aspect of this problem is cybersecurity you're getting increasing the amount of attacks done stuff bad for companies bad for people it's just going to get worse and we actually know what the answers to these things are the answers our data is encrypted all the time everywhere you do the computation on encrypted data you never transmit it you never unencrypted it to be able to do things we also know that in terms of control of the data is possible to build fairly simple permission mechanisms so that you know the computer just won't share it in the wrong places and if it does you know skyrockets go up and the cop scum you can build systems like that today but the part that's never been able never allowed that to happen is you need to keep track of a lot of things in a way that's not hackable you need to know that somebody doesn't just short-circuit it or take it out the back and what's interesting is the mechanisms that are in Bitcoin give you exactly that power so you whatever you feel about Bitcoin you know it's speculative bubble or whatever the blockchain which is part of it is this open ledger that is unhackable and and has the following characteristics that's amazing it's called trustless what that means is you can work with a bunch of crooks and still know that the ledger that you're keeping is correct because it doesn't require trusting people to work with them it's something where everybody has to agree to be able to get things and it works it works in Bitcoin at scale over the whole world and so what we've done is adapted that technology to be able to build a system called enigma which takes data in an encrypted form computes on it in an encrypted form transmits it according to the person's permissions and only that way in an encrypted form and you know it provides this layer of security and privacy that we've never had before there have been some projects that come close to this but know we're pretty excited about this and and what I think you're going to see is you're going to see some of the big financial institutions trying to use it among themselves some of the big logistics some of the big medical things trying to use it in in hotspots where they have real problems but the hope is is that it gets spread among the general population so it becomes quite literally the privacy and security level that doesn't have Warren Buffett might be right that it might fail as a currency but the technology has really inspired some new innovations that's right so so it's essentially a distributed it's not a walled garden it's a distributed black box that's what you're describing you never exposed the data that's right you don't need a trusted third party that's getting attacked that's right nobody has to stamp that this is correct because the moment you do that first of all other people are controlling you and the second thing is is there a point of attack so it gets rid of that trusted third party centralization makes it distributed you can have again a bunch of bad actors in the system it doesn't hurt it's peer-to-peer where you have to have 51% of the people being bad before things really go bad how do you solve the problem of performing calculations on encrypted data because they're classic techniques actually it's been known for over 20 years how to do that but there are two pieces missing one piece is it wasn't efficient it scaled really poorly and what we did is came up with a way of solving that by making it essentially multi scale so it's it's a distributed solution for this that brings the cost down to something that's linear in the number of elements which is a real change and the second is keeping track of all of the stuff in a way that's secure it's fine to have an addition that's secure you know but if that isn't better than a whole system that secure it doesn't do you any good and so that's where the blockchain comes in it gives you this accounting mechanism for knowing which computations are being done who has access to them what the keys are things like that so Google glass was sort of incubated in MIT Media labs and well before yeah my group you go right in your group and yeah it didn't take off me because it's just not cool it looks kind of goofy but now enigma has a lot of potential solving a huge problem are you can open-source it what do you yeah it's an open-source system we hope to get more people involved in it and right now we're looking for some test beds to show how well it works and make sure that all the things are dotted and crossed and so forth and where can people learn more about it oh go to a nygma dot media dot mit.edu all right sandy we're way over our time so obviously you were interesting so thanks keep right there buddy Paul and I we right back with our next guest we're live from see this is the cube right back [Music]