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LSE: Public lectures and events
You Are Being Tracked, Evaluated and Sold: an analysis of digital inequalities
01:25:44
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- [00:00]
A
Okay, can we make a start, please? Thank you. It's great to see such a large audience. Tonight I am chairing this event. My name is Mike Savage. I'm professor of Sociology here at the lse and along with John Hills, I'm one of the co directors of the International Inequalities Institute. And it's really thrilling to be chairing this event with Beverly Skeggs, who is. Who began working at the LSE three weeks ago as the first director of the Atlantic Fellows Program. Bev will be known to most of you, all of you, as an inspirational figure, one of the leading feminist sociologists in the world. Previously being chair at University of Manchester, where I overlapped with her and was a colleague of hers for several years and more recently at Goldsmith College in London. She's famous for many pieces of work. Probably the landmark study you'll be most familiar with is Formations of class and gender, 20 years old, which was kind of a really vital study for developing our understanding of the intersections between class and gender. And more recently she's been working on questions of value, how value is extracted, notions of individuality, and actually be talking about in a few minutes how the social media are involved in these extractions of value. Before I introduce the other two speakers, let me just. Or the other two people on the stage, let me just say quickly, speaking as director of the iii, that the Atlantic Fellows Program is one of the flagship programs at the lse, funded with a very large donation from Atlantic Philanthropies. We have recruited our first cohort of Fellows, some of whom are in this audience. And I did want to say that the applications for those of you wanting to be Atlantic Fellows next year will be opening shortly. And this is a scheme which is available to people wanting to do the Masters in Inequalities and Social Science, as well as doing a non residential series of short courses, as well as become visiting Fellows. So if your appetite is whetted by what you hear tonight and by our work, please do look at our website and please think about applying to be an Atlantic Fellow in the future. I also want to say that there will be a reception afterwards. You're all welcome to join it and say hello to Bev and to all the other people involved in the iai and just also to say two other people on the stage. Simon Ewell apparently has a non speaking part, but he will be. He is the person who developed the software which Bev will be talking about. He is a software developer and a visualization guru and he's on hand to answer any questions about that aspect of the work. And after Bev has spoken, very privileged, very pleased to welcome Sita Ganhadaragan who's assistant professor in the media and communications department at the LSA. He will be discussant and she'll be spending about 10 minutes opening the conversation around Bev's work. So it should be a fantastic evening. Let me hand over to Bev.
- [03:18]
B
Thank you. Okay, so there's two lectures going on in this building. The other one is for unrequited love. So if you're in the wrong room, it's not me. I. Okay, I'm going to talk about a project now. I'm going to go through quite a lot of slides. There's a lot of information. The slides will be available and the genius who enabled all the visualizations and the software is sitting here. So thank you, Simon. Without Simon none of this could have been achieved. And he worked so hard to produce all the amazing things you're going to see. So I'll explain the project and how we got to it. It comes from an ESRC funded and values project which was looking at how forms of. What happens when forms of intimacy get monetized. So I looked at prosperity theology and friendship. What does it mean for social relations when our key relationships are monetized? So before I begin and kind of go into some of those more interesting sociological questions, I just want to draw your attention to how, how quickly as you sit there with your laptop open, you are being traded, evaluated, tracked and traded. 120 milliseconds is about a third of one time it takes to blink your eye. And bids are currently being made as you sit there for access to your data. It's up to 50 billion times a day. So you can imagine how many times it's going on. There are 100,000 requests from advertisers per second. It's going on as we speak. If you're on a laptop, you're being easily accessed at this moment in time. Phones are a little more difficult, iPhones are slightly more difficult. And it has to be this fast because it's like flash trading, financial flash trading. There's a race to see who can get in for your a browser page and all your information quicker than anybody else. And basically if they don't get in really quickly and trade you really quickly, somebody else will. So there's a competition to trade you as well. If you remember, if you think about this is in a third of a blink of an eye 50 billion times a day, light travels Fast, but not fast enough to compete with the number of times you are being traded now as we sit here, especially if you've got a laptop or an Android phone, but a laptop is really, really very easily accessible as our desktops. In 2014, Facebook had 52,000 unique attributes on your data, on your profile. It buys other data mainly from Experian. So it buys data from demographics to enhance this profile. So, so they know about you. That code there comes from a laptop and that code, each single figure has a huge amount of information about my demographics, about the person's demographics, and that is what is identifying you. This comes from a book called Chaos Monkey. Chaos Monkey is by a man who got sacked by Facebook. So kind of spilled the beans, told the whole story in the most vitriolic way possible. So you actually do get up until 2016 what was really going on, how useless they were to begin with because they weren't interested in monetization, but once they got into it, how very, very good they became. So I'm taking it from the horse's mouth in that sense. So by the time you've finished reading the sentence here, you will have been tracked and traded, especially in this audience. You are likely to be high net worth individuals. You are likely to have a very highly influential network of friends and they assess your potential in the future. So even if you are a student on a loan with not much money, they check your network of friends and they can find out whether you've got influential friends and what you're likely to be in the future. So they are trading you on your potential. There's 5,000 trackers on the top hundred websites. Google is obviously the top tracker. It's your potential that makes a difference. Phones are more protected. And one thing I want to signal that I'll go on to talk about, it's not just about financial tracking and trading. Tracking is also sold to the state. It's a commodity that is not just used to, to make commodities to monetize your data, but it's also used to keep you under surveillance. So that's also very important. All this tracking and trading happens through machine learning algorithms. There's not somebody in the room going, oh, I like the look of that person. It's all through machine learning algorithms that learn incredibly quickly and very effectively. And they speak to each other with over 100,000 signals and they experiment continually with your data to see if they've got a good match. Is your friendship group the right group? Are they your real friends? And you provide signals every Time you turn on your device, every time you use your browser, every time you load a webpage. And they are checking your speed of connection, your emails, your web pages, banking languages, messaging, videos watched. The competition at the moment is on facial recognition, so they can see what adverts you're looking at or where you're looking on your screen. So that's the technology that a great deal of investment is in. And as we'll go on to look, the governments do also. Governments aren't just buying your data or paying people to analyze your data, they're also selling it, as we saw in India recently. You can turn your phone off now if you want to. I'd certainly turn your laptop off. It's not going to make much difference. Okay, so our project, Rhythms of Interaction. This is what we looked at and this is where the genius enters the Simon Yule, who designed the software for this program, which took a long time, six months. We thought we'd get the whole project over within a year and we're still doing it. So it has taken a huge amount of time to gather this data. But what we wanted to look at was how Facebook operates as a social relationship, how it shapes social relationships. So we're looking at rhythms now. We know capital has rhythms, stock market rhythms, continually trading, moving up and down, but we were looking at friendship rhythms. And it's kind of interesting that the last time I was in this lecture theatre was when the project began and I was full of hope and optimism and I was looking at values rather than value. I will end, I will end on hope and optimism, I hope. But what's really interesting, the research question that I began with was is there anything beyond capital? Is there anywhere, any part of our lives that capital monetization, commodification, financialization hasn't encroached into. That's what I wanted to look at. So it began as a study of social interactions and ended on identifying how new forms of capitalism work through us. And it's the through us that's really, really significant. Not just on us, through us. So what we did, and I'm going to go through this really, really quickly, a random digital survey of people's use a Facebook app that Simon designed, a plugin for Firefox browsers. They gave us permission to put on their laptops. I said it took a long, long, long while to write the code because it kept changing. A heuristic Device to analyze 2 million AdWords, a live website. And if I trusted technology, interestingly, I would show you the live Website where we can hit on things, but it often crashes if you try and do it in a presentation. So everybody who was involved in the project, they could check their daily visualizations and what was happening to them. Generation of data books we could read across the data. And the funny story in this is at one point I've got a photograph of Simon on the floor with eight pages of data trying to read across them because you can't handle that much data on one screen. It's an interesting methodological question in that. And then we did post data interviews where we frightened the life out of people, where they saw what had been happening and what we could see. And even those who put ad blockers on, even people who were trained as hackers, could not believe how much tracking was going on their site. We were registered as Facebook developers. We did it all ethically, legally, and our participants, only 33 of whom managed to register as Facebook testers. But you can see the results and the findings. And everything is open source. So it's available at GitHub. But of course, the software code for Facebook has changed completely. We tell the stories of the difficulty for anybody who wants to know in an open source paper, which is very academic, on multimodeling. So this is what we found and what we looked at. We were looking at all the flows. Is that my pointer? All the flows here. And that's the communication between people. But then you can see Facebook posts. And then we saw where Facebook was putting adverts on people's pages as they communicated between people. But this was the most interesting thing. When we saw this, we thought we had a problem with our software. Remember, we thought, what on earth is going on here? Can you see that little bit there? It's what we call the gray matter. What is that? We thought, how do we know what's going on there? And that's when we first identified all the tracking that's going on behind your communication with friends. And then we realized this is all the tracking on the browser. So there's the code there. But can you see all the grey matter here is all the tracking and the advertising that's going on on your web page as you are looking at various different sites. There was quite a lot of evidence for it. To give you a sense of the complexity of the data. This is just a very small version, some of them. Because people are on it 24,7. Amazingly, some of them would be effectively 12 meters high if we had it in real space, real time. Yeah. So it's really, really hard and the interactions between people are intense. This is a visualization of the news feed. And what's significant about this is when you're on the Facebook platform and you're looking at your news feed, you may think you're communicating with your friends, who you want to communicate with, or your family. But this here shows how Facebook is making you see other things. It keeps pushing posts up to the top of your news feed. So you, in this case, the person's looking down, kind of keeps ignoring these posts, but Facebook keeps them them there and keeps them there for quite a long time. So they completely try and determine what you see. That's when you're on the Facebook platform. So we also looked at networks and looked to see how people's networks worked without them in it. Who were they communicating with and what they were doing. And what we found that was significant was the tighter and more influential networks enable Facebook to build a profile from your friends and target you most effectively. Simon was the worst targeted out of all our participants because, of course, being a computer scientist, he never went on Facebook. So it was really interesting. They couldn't quite work out who he was. But people who were on it regularly, who used it a lot and had influential networks of friends who used it a lot were very easily identifiable. And Antonio Garcia, the guy who worked for Facebook, he shows how that's really important. Your network is really, really significant. And this is one of, I think, the best visualizations that you produced, which is literally of the tracking of general browser use. So that's all the trackers that are on a site as people go through their browser pages. So everybody who's looking at them, watching them, the bigger the dot is, the more interest of the advertisers in your site. And then you can see there's lots of small dots as well. And that's when they're tracking your activity on other websites. Anything with a little F on it. I'll come to that in a minute. So the circles, Simon scaled these to a size that represents their relative size to the trawling that's going on on your website. And there's lots of small circles as well. And there's lines as they trawl through your profile. All these visuals are available on the website in high quality resolution, so you'll be able to see them in more detail. And if you were a participant and if I trusted technology, we'd click on them and you could see who the advertisers were, how often they'd been there, and for how long did they dwell on you or really how the machine learning dwells on you. Now, Facebook itself is quite phenomenal. It has phenomenal processing power and people gift it a huge amount of information. They upload up to 300 million photographs perhaps per day. And of course, I'll go into Facebook also bought Instagram, so they can get access to all the Instagram photographs as well. And they process 600 terabytes of new data per day. And they check it all. It's all machine learning. And it's quite interesting. This, again, was a question raised. They're claiming They've already got 2 billion users every month. It's disputed. People say, oh, well, it's not that many. But if we subtract China and Russia from that, who have developed their own copycat systems, that's only about 35 billion people left in the world for Facebook to collect information on, which I think is a staggering figure. So this is. I just put this up here because the other really significant thing that we found is you do not have to be on the Facebook platform for Facebook to track you. It doesn't make any difference. So even if you sign off and you're not on it, any site, including the LSE site that has that on it anywhere, is tracking you. So anytime you book a ticket, anytime you do anything, that's all you need to see. They've got you. And once they've got you, they've got you for life. And when we began the research project, they denied they were doing this, which makes Simon even more of a genius, actually, because they said they weren't doing this. And then the Belgian government took them to the European Court and tried to reveal, using five computer departments in the us tried to reveal the extent of the tracking that was going on off the Facebook site. The five computer science departments revealed exactly what Simon had found. They got prosecuted for doing it. And at first of all, I mean, it revealed that they were doing it. But then they appealed. They appealed and actually they won because Facebook's registered in Ireland and there's no jurisdiction of the Belgian government over an Irish company. So they've carried on tracking, trading completely. They haven't been stopped. The Belgian courts do not have that control. So this comes from the Facebook advertising page. Why so much tracking and trading? Well, I guess you can work that one out quite clearly to make money. That's their main aim, growth. It's very interesting. Again, the inside story is that the growth department is always looking for ways to monetize everything. And the technology department kind of has to Jump to their tune. So they have to pay the shareholders, they have to keep investing and they really want to grow. The majority of Facebook revenue comes from advertising. 97% I think when we began the project it was only about 78%. But because they've moved on to mobile phones and they have the most phenomenal advertising capacity on mobile phones, better than anybody else. That's how they've been able to capture that market. I always joke that if I bought Facebook shares when we began the project, I'd be really, really rich by now. Because if you look, it keeps going up since its initial IPO and it's now 495.2. Its market capitalization value, £495 billion. And to keep ahead of the market, it does what capital must do, monopolise, consolidate, diversify. It buys everybody else up that it possibly can. That's why the debate between Snapchat and Facebook is really interesting. I know who I'd put my money on, but we'll see. Its USP is what it says there. Two million people, one in every five minutes. People are looking at Facebook and 500 million Instagrammers and they can match. But the key in there is they capture your attention. And that's absolutely key. They capture your attention, but not just attention, they capture your time. That's one of the most important things that I think they do. Now this is just a map of digital capitalism. Where do they all make their money from? They don't produce much. Apple produces phones, fair enough. But the rest of them don't produce a great amount of stuff. They are platforms basically, and they rent you the space on their platforms and that's paid for by the right to your personal data. They are, they have when you sign the I agree to use this, which you probably don't remember and apparently would take over a year if you read every privacy agreement on your phone, but by the time you'd finished reading one, it would have changed because they usually they're written so you can't understand them and they change so regularly it's impossible to know. So there's quite a few American legal scholars that show it's impossible to know how to understand a privacy agreement. How difficult it is because they're changing all the time. But what's significant, you can see the massive amount of advertising for Facebook there and that's how they make their money. But what's also significant, they're making money from other areas of the economy. It's like moving and circulating capital from non productive areas. So they're kind of like a speeded up traditional advertising industry. They're just enabling the circulation of capital. And in the process, at the moment, they are destroying the traditional advertising industry. Because why pay for creativity if you can just do programmatic matching, especially if it's about behavioral prediction and looking where you're looking. So restructuring the traditional advertising industry. But what's significant at the moment, I'd argue in terms of the capital analysis of them is they're extending the circuits for circulation. So messenger itself was initially designed as a peer to peer financial transaction site. And so everybody thinks they're talking to their friends, but actually it was designed so you can have unregulated financial transactions. And they're going to. They spent a huge amount of investment developing financial markets. And when the new. I'll get the right, the right law. There's going to be a new law in 2018, which I have somewhere in the midst of all this detail, they will be able to actually access banking information and all banking is going to be completely deregulated and open to financial companies. I'll get to that slide after this. This one with the actual directive on it. So basically I just want to say in the tradition of pure capitalist economies, they do consolidation, monopolization, diversification. And for those of you who didn't know it, they have games. Free Basics, the one where they give you a free phone in a developing country so that you can only access the Internet through it and they can access all your data from it. There's been lots of campaigns against it, but Free Basics is already in 49 different countries. The other key thing where I put my money on Facebook, mobile banking. They've got mobile banking apps in China. Massive. They have peer to peer drones, they have 3D, they have dumb phones. And unlike other companies, they bought a German telecommunications company. So they have telecommunications and social media. That's a really powerful combination. And they also are in the SIM card market. So it's a big diversification. They are one of the most. Google's, probably the most litigious, but they're very, very protective of proprietary rights. They control your data, you cannot get access to it and you've given the right over to that data. They own it, you don't. So I think we'd argue that they are like a utility, they're like water, they're like electricity and we use them as a network connection to connect to other people. And they have become really significant. This is just a very basic map of the levels of diversification. The most Significant ones you may know are WhatsApp and Instagram. They just buy anything up that's a threat, and they often discard the employees. They just want the ip. So this is what Facebook says about its advertising data. It says advertising on Facebook means you can capture people. Capture is a really interesting word. Remember attention. Remember capture. They can capture attention. So the advert auction determines what can be shown to you when you're on your browser, what you're likely to be interested in. And they say, they say when showing ads, we try to balance two things. Creating value for audiences and providing positive, relevant experience. Our goal is to match the right person, the right ad to the right person at the right time. And it's what traditional advertisers have always been interested in. In eyeballs. How valuable are your eyeballs? Do you have purchasing power or not? So they're really interested in who they can match. That's significant in terms of inequality, who they can match to what product. Really significant. Hold on to that point. So it is scale in terms of this. Matching cannot be matched. They are faster than the speed of light and getting faster. And in the tradition of monopolies, they can access the largest audience and access the highest revenue because nobody else can get near them. Nobody else has the capacity to compete. And gel stuff shows how they plan this kind of architecture from the start. And interestingly, they help design the advertising regulations that regulate them because of the. The only people who were doing it. So they're the only people who could advise the government on how to regulate the industry of which they were the key player. And then again from Martinez, he says he basically tells the insider story that they are experimenting with you all the time. One bizarre thing is they use New Zealand for experimentation. I still don't know why. And if anybody can answer that, that would be worth knowing. So he says it's like testing people in a clinical drugs trial. Will they respond? Will they buy? Will it make them sick? Will they turn off? They're experimenting. In fact, as we speak, they are experimenting with your data, seeing what works, what doesn't. Clearly you're not going to pay attention now, but they can track a product if you pay attention in the future. So what we found, and it's not just Facebook, that is the platform that's selling. They have their own ad exchange, but there are lots of other ad exchanges on the Facebook platform. We found Rubicon, didn't we? Rubicon. And they're not the biggest, but there's a lot of them that Facebook rents out. Access to advertisers or charges advertisers for access to the Facebook platform. And rubycon, you can look them up. They are one of the kind of fast expanding, programmatic marketing companies. And again, if you just look down there at the amount of attention they're giving you. So you're not just being traded on the Facebook platform by Facebook because you're on their site. Facebook are tracking you across every site. And then they are allowing advertisers to come in and pay for the data that is going through your site. So it's like any opportunity, they will do it. Now, what's very significant in all of this is how they compile an algorithmic profile of you. And I would recommend this book to everybody. It's called Networks of Control. Wolfie Grisle and Sarah Spiekelman. And again, we came across this because we had. We found Axiom and Experian on people's sites, tracking them. Now Axiom brags that it has on average 1,500 pieces of information on more than 200 million Americans. And what's really significant is Experian were a very traditional data broker company that would collect all the information on you from government data, from hospital data, from general demographics. But in a very traditional way, they got together with Facebook and what a perfect marriage. You've got all the traditional data offline, married with all Facebook's data online. And that's how they kind of trade you and they allow you to. They allow Facebook to build up a better profile. Facebook pays for Experian data or they will pay. Likewise, there's lots of trades. Now what's significant is all this. They get through and they look at lots of different statistics. ATMs, browser use, do you like cats in your photographs? Geodemographic. And they can monitor which adverts you're looking at if you're walking down the road, if they've built some pencils into the adverts on the wall. So data brokers become really significant. But for me, the most significant thing about them is when they were called to appear before the Federal Trade Commission in the US they just didn't bother turning up. They're not accountable in any way. Nothing. They just don't bother. So beyond regulation. So data brokers are really, really significant because what we have is a combination of all the social data that comes from friendship networks, I.e. friendships, your ratings, your influence, health, welfare, consumption, and all the other data coming from the traditional data brokers. And what I think seems significant. This is the direction I was trying to remember is that they're going to have so much more financial information on you than your bank. Because if they've got all your ATM habits, if they've got all your consumption patterns, they also. And then they combine that with all your banking data, your history of banking in various different ways and the banking's about to be deregulated with the European directive PST 2, they can actually start increasing what you are, understanding what you are worth, how you're going to spend and predicting what you will do. So it's a really serious issue. Now why do I think this is significant and what did we find? And it's all about the matching. Remember their USP is that they can match the product to the people. So what's really significant with the matching is that they match high net worth individuals with lots of expensive consumption. But what do they do with those? Individuals with a very loose network, no friendships of influence, no future potential, not much spending power. They're non high net worth individuals. What do they sell to them? Because they'd never miss a chance to sell something. What do they sell to them?
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C
Political assets.
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A
Huh?
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Political assets.
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B
Ah, I'm coming on to that. Yes. But mainly they sell them debt. They sell them to debt companies. And as you know, David Graeber is somewhere in this room. Where is he? That brilliant book on debt. As David will say, the future is debt for most people, different sorts of debt, good debt, bad debt. Mortgage is different from your wonga lender, but debt. So the difference we saw here was a very high net worth individual, a BBC World Service journalist, she said we could use her data. Who is on. She said she has to be banned from Facebook some of the time, but she's actually on web pages all the time. They track her very, very accurately. You can see she gets tracked constantly. Constantly. And then over the other side, somebody who's hardly tracked at all, what does she get sold and targeted for? Debt. Debt. Debt is absolutely key. But she's also very worried that she might be under state surveillance as well. So when we interviewed her, that was one of her concerns because she's on benefits welfare. So matching has really serious consequences for how inequality gets reproduced, not just in the present, but over a lifetime. If you are being matched as somebody that has no worth and your data is being constantly traded between data brokers, social media companies all the time, you are basically being categorized and classified all the time as high net worth, no worse. So there's a really big significance to these inequalities being drawn through stealth that we have no idea about. We can guess through our research, but we don't know exactly. So it's about the generation of digital inequality by stealth. We don't know this if we're being classified by the registrar General or by social economic classifications or the welfare state. We know, but we don't know how they're classifying us and what consequences we have. We do know, and thanks to some Sita's research, we do know that those who are not high net worth individuals, the working class, black and white in the US experience phenomenal levels of surveillance. Harsher consequences from this surveillance. We do know that that privacy harms cannot be contested by those who don't have any money. We do know that job applications, criminal statistics are all connected to data. The idea that police use predictive policing is all connected to data where you are and what you are. We do know that the companies, data broker companies work with sociological categories that are quite abhorrent. Rural and barely making it or fragile family families. Think of the recent Conservative party's trouble families. It kind of matches data brokers performing policy by stealth. And we do know that most or a lot of these algorithms have problems, but you can't contest them. And it's particularly problematic if you do have a very common name. We also know that those who are seen to have. There was an incredible case and it's in the book that I'm just going to reference in a minute. We do know that the vulnerable are targeted in very particular ways. So when there was an attempt to sell subprime student debt, subprime student courses in the US Trump University no less has since been prosecuted the only way we found out because of the prosecution, the legal case. We do know that they were targeted because the people who've been trawling through the data, and this was people because it was marketeers who bought tranches of low net worth individual geographically specific data. We do know that they were targeted because they had no education, nobody in their family had any education. Therefore they would be much more susceptible to subprime university loans and subprime universities, that is the President of the United States who actually as we all know, I mean nothing would shock us, but that whole system is in place. So it makes me want to argue many things. But we'd argue very strongly, although high net worth individuals are subject to hyper surveillance because of course you can sell them or you can sell it more quickly, you can attract them more, you can make more money out of them, you can trade them for A higher price. It's the consequences for those who are not high net worth individuals that are really significant. Really significant. So very, very different digital tracking with very, very different digital consequences. And this is the book I love. This is the book I would have loved to have written, if only. It is absolutely brilliant. Cathy o'. Neill and she looks at how this occurs not just now in the present, while you're sitting in the lecture theatre and you're being traded. She looks at how this happens over. And she was one of the people who worked in these companies to sell these products who had a kind of epiphany and thought, I can't be a complete horrible person anymore. So she looks at how it works over a person's lifetime and think about that. It's the inheritance of digital inequality that's opaque and uncontestable, that becomes really, really, really significant. So you're inheriting your network of friends and family, all their geographical containment, all their state surveillance and that will be inherited through children. So this isn't just a kind of you're being tracked and traded, you're being sold. This has massive consequences for the reproduction of inequality, all done by stealth and not many people are paying attention. I just put this in because I'm so outraged. So it's not just what we would expect. Capitalist companies trying to find any way to make money out of you and becoming so incredibly, incredibly good at it. We can't keep track of them. This is about the Indian government thinking it knows how to control its population through biometric data fingerprinting. Interestingly, 36% failure because a lot of laborers in India have had the fingerprints burnt off. So that's not exactly a clever system in the first place. But what WikiLeaks revealed this August was how. And it's disputed, of course it's disputed, but keep following the case, Always follow the money and follow the case. That's how you get there in the end. But the government, the government sold Indian biometric data that's like everything about you, sold it to various different companies in the UK and the US and to the CIA. And it's interesting, the company that devised it so, so follow Navarro Media, who's very, very good. And actually I go at the end I kind of say, look at this, look at this, look at this. But navarro Media and ProPublica are really on this. Now. The other thing that's an irony is that the cyber insurance industry is being developed to protect the state who's selling the data in the first place. It's kind of called who thought of that? And I was going to take this slide out, but I can't resist because this man may become the head of intelligence in the US Peter Thiel. What more can we say? An Ayn Rand fundamentalist libertarian who doesn't think women should have a vote is now the tech advisor for the American government and who has been trading and selling data and who helped to set up Vanguard Org to track Move Org and were caught hacking into trade union data in the US but just watch that space. Watch Peter Thiel. And what's the sort of state. These are all the digital giants. These are Peter Thiel, if you can see him on the. Hold on.
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C
Where's me?
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B
What's it, Peter Thiel. Over here. Peter Thiel's over here. But it's all of them. The woman, Sheryl Sandberg, not surprisingly. Facebook, Google, they're all there sitting around the table with Trump. What we also know about Facebook is that machine learning and algorithms are not innocent. So who's responsible for all of this? Who designed the algorithms? Who taught the machines to learn? We know facial recognition is a huge problem in terms of race. And we know. I just. I can't believe it. Every time it happens when Facebook just goes, we're innocent. They really do not have any responsibility for all the tracking, the trading and everything that's going on and how they're classifying people and how they're being racist and how they completely. The manipulation. So it's the political point, how the election was manipulated. They are innocent. But what's key is a lot of the fake news, a lot of the political manipulation all went through advertising platforms, Facebook platforms. The manipulation of the Brexit debate all occurred through Facebook data and psychological testing. You know, when people say, what sort of personality are you? Do not fill it in. It was used for the Brexit manipulation. So what for me is really key in this, the relationship between capital and the state isn't very clear. Isn't very clear at all. It's advertising that's becoming the main platform for the distribution of fake news, which is about political manipulation. Facebook have just handed over all the data, apparently to the government, so they will reveal it. This is the great one about the boys in Macedonian schools. Worked out that if they put sensational fake adverts, Google would pay them money for every time they got hit on. Read the full story. So back to the research before I go off on many political tangents and get completely outraged and rant a lot. So that's why I like PowerPoint. It keeps me under control. Our findings detail how Facebook's desire for future capital accumulation means they're constantly tracking you. They constantly collate all your browser data, match AdWords to profile. They shape your network over time, who you interact with, whom, when, where, how. It's your attention that they want. They constantly expanding their capacity to experiment. And their real USP is the ability to do all of the above. So how is inequality being generated by stealth? Classifications are unknown. There's no accountability. Debt silos, sub prime market creation are not known until the legal challenge reveals it. We do not know how our data traces are being traded and valued. We are the fodder, the resource from which value is extracted in order to sell us stuff. In a constant circle of expropriation. There's very little protection. And actually turning off some of the platforms sends out a signal that you're not interested. They transfer you to another one, but we won't go into that. And they're very litigious if you get through. But it's not just about the making and legitimation of structural inequality. It really is political. Not just political in the manipulation of votes, Brexit and Trump's state surveillance and Indian government selling data. I think what happens, and if you remember the first slide at the beginning about rhythms, I think we become aligned to the rhythms of capital. We become attuned, we become aligned. And this happens because we found fake books. Makes us do things. It shapes our habits. It makes us complex, compulsive. Hands up. How many people have checked their Facebook page to see what's going on? That's very honest of you. I suspect it's about half the room. Yep, compulsive fomo, fear of missing out. It makes us perform our subjectivity in particular ways. One of our research respondents said, I think about how I will tell this story on Facebook before I tell it. So it's literally shaping how we perform our subjectivity in various different ways. It makes us pay attention. We look at things. The significance of sensation is incredibly important, as we saw with the election. We look at things that make us laugh or kind of produce disgust, produce very powerful affects in us. We even walk in antisocial ways. This means our phones are like prosthetics. It converts all of our time use for the interests of consumption. So all those fights the trade unions had to protect the time from being forced to work and go down their mines all the time has now been completely eroded as we willingly pick up our phone and get tracked and Traded. Our intimate relationships are being shaped. Friendships, but very hard to identify. Why haven't we heard from that person for a few years? Well, that's because Facebook's trying to get every other post at the top of your feed. So I'd argue power works through us. It connects these devices to bodies, people to people and advertisers to us. It's working through us. It's not us consenting, it's not all those theories of ideology and hegemony and us consenting or doing things or giving our consent. We're just doing it. We're doing it. We're walking, we're thinking, we're looking, we're seeing. Our time is filled up with it. And it was terrible because all our participants, and I'm sure most people in this room, were just resigned to the fact they defined Facebook as a necessary evil. In fact, the terms, the discourse were really interesting, but they were resigned to it. A contract with the devil. This is ideology without ideas. This is about ideology made from convenience. So it's ideological, but not in the ways we normally understand it. Power working through us, demanding attention, filling our time. I've gone through all this and it results through bodily habit and convenience. So what do we do? And now I'm going to go through lots of really quick slides. Very, very quickly, I promise. Really, really quickly. So what do we do? Because I always used to end really penny pessimistically and everybody used to complain. So what do we do? Regulate and nationalize? Well, maybe, but look at the government. UK government. The Open Democracy open rights group said the last sale of data in Britain was more suited to a dictatorship than a democracy. So what, government's going to nationalize our data? Bit worrying. And I'd just like to point out on here, read anything by the brilliant Carol Kold Walder. Absolutely brilliant stuff, seeing what's happening. But how? Regulate and nationalise, address privacy. We want technology to work for us, not to do things to us. Do not let objects into your house. I cannot believe people do that. You know they're listening out for you. They're called pre emptive. It's like the pre emptive strike. Pre emptive. They're listening out to see what you want to do. Don't let them in, I say. Pre emptive capture. Keep them out. Make the machine learning work harder. I used to think it's obfuscation, but really it won't work. Minimize information given, Take back time. Tear off the prosthetic. Avoid all online shopping. Use cash. That's not going to work, learn to hack and code. I wanted to. Simon told me it was pointless. I'd be useless. Change the identifier on your phone. I've tried to do that. It's impossible unless you're really clever. Go dumb, turn them off, Educate and activate. I'm just going to very briefly go through all of these. You need to read ProPublica. They have done some brilliant reports recently. They're the most up to date reports on what's going on. Ad blockers, the track, me not. None of them are brilliant, but that's probably the best. Yeah, we all got. We got through them. All alternatives, they're not that good, but you can play with them and hopefully someday. Someday somebody's going to come up with a good one. Really read a lot of the very good links that are around at the moment. Lifehacker is very good. Wired, it's worth reading. And then I'd like to do a plug for the workshops that are coming to London for an exhibition, the Tactical Technology Collective. This looks absolutely brilliant and it's coming soon to a place near you. So thank you very much. Is that okay? Is that all right?
- [51:44]
A
Thanks, Bev, for that tour of force. And I've never seen anyone work through so many PowerPoints in such a skillful way. So now we turn over to Sita, who will have about 10 to 12 minutes to make some responses.
- [51:56]
C
So thank you so much. That was terrifying. And just to get started, I think this is going to work best if we're more conversational.
- [52:07]
B
Oh, good.
- [52:08]
C
Rather than a conventional respondent. But I do want to get a show of hands from the room. First of all, how many people here have never been on social media? Raise your hand. Six. Wait, Four, Five, six of us.
- [52:32]
B
Simon was only forced to.
- [52:36]
C
How many people have been on Facebook or social media and then deleted their accounts? And do I just assume that everybody else in the room is still connected and vulnerable to some of the impacts that Bev has just talked about? Is that fair enough? So, yeah, we have reason to be terrified or angry and angry. But I think that. So for me, one of the things that's come up in reading your work and thinking about how many of us here, how few of us have raised our hands about never being on social media. The question for me is, are we too late in telling this story? Because it seems like adoption has already taken place. We're already embedded in these systems and it's very difficult for us to work ourselves out of it. So that's one question that I have for You. The second question is one that relates to sort of the orientation of the work. So within the field of computer science, there is a longer tradition, I think, of doing these kinds of web privacy measurement types of research. So I can think of four people in that specifically has helped broaden public discourse about how tracking has become so, so pervasive by social media and other kinds of technology companies. So I'm thinking of the work of the computer scientists and maybe these questions are Simon.
- [54:32]
B
Yeah, you're Simon as well.
- [54:33]
C
But I'm thinking of the work of Arvind Narayanan who discovered that anonymization is not really what it seems that companies, both first party companies or first party trackers and, and third parties, there's a lot of identification that already happens of individuals that is stealth that we're not aware of. That happens all the time. There's the work of Jonathan Meyer, who was, I think in 2010 doing a lot of this work on cookies and how they, how, for example, if you're on Facebook and you visit another site and you're still logged in, there's a chance that your user data, your username will actually be leaked to that new site that you're visiting. There's also the work of Latanya Sweeney, who I think is really influential thinking about the ways in which data leakage happens has occurred in what is otherwise known in the United States as a very well protected domain of data that's in the health industry. Health information is protected by the HIPAA act in the US but she also looked at data leakage in her studies. And I think that work was in 2010 and more recently in 2015. Someone from the field that I come from, the field of media and communications, Tim Leibert, who's now at the Reuters Institute, looked at again this process of leakage, right? So that people who look for health information, for example, on reputable sites like the center for Disease Control, say they're looking up information about a sexually transmitted disease, disease. And that little widget is there at the bottom of the screen. It means that that information, which most likely the user thought was not being shared, is actually very much being shared with third parties, with Facebook, et cetera. And I mention this scholarship because I partly wondered where does that sort of body of work and that world sort of fit into this work? Thinking back to my original question that I started with, which is are we too late? Right. Because when I think of some of those early studies on tracking and privacy, it seems that they've done quite a bit of work and yet we're stole at this point where we don't necessarily. It doesn't seem like we have much of a way out, despite the wonderful work of technology tactical tech collective and otherwise. So and the other thing that I'll mention that's sort of related to that is do we need to have a broader cross disciplinary conversation to actually imagine the possibilities of challenging what seems like an incredibly huge problem to deal with?
- [58:04]
B
Right.
- [58:05]
C
You're talking about the accumulation of wealth by companies like Facebook in a way that seems unstoppable. Right. And I wonder if doing that cross disciplinary work with computer. I'm not suggesting that for example, that social scientists become computer scientists or that we need to all become computational social scientists. It's that I feel like we need a better opening to imagine the alternatives. And so I guess the last question that I'll end with is if you had to reimagine, for example the Internet, this is a really simple question. If you had to reimagine the Internet, an Internet that does not run on personal data, that it wouldn't be the personal data economy, what would it look like? So I'll end there. We're here and I hope that we'll have some comments conversation about how we envision an alternative.
- [59:22]
A
Do I really want to respond?
- [59:24]
B
What a question?
- [59:26]
D
Several questions. I mean just on the tracking one, we want an interesting, I think a response that we've had this kind of growth of the whole idea that we can put in come forward to this. We've had this growth and idea things like putting in ad blockers and tracking blockers and all these kind of tools protect us from these mechanisms. And one thing our research showed was that's slightly delusional. In fact, I would argue it's a kind of more relates to your work on TV in a way. And it's a form of possessive individualism in which middle class users off the web want to show that they're educated and doing the right thing and using the web in the right way. So put in these tools is a kind of investment. But in fact a lot of these tools don't have a big impact. So we had one participant who even built his own software to block tracking, but he was still being tracked. And we found out because it happens in various different levels in various different ways. And like with cookies, cookies regenerate so you can clear your cache and they can come back with the data it gets stored and then reloaded and things like that. And also with the way in which machine learning algorithms work, an individual putting in these blocks isn't going to have a big impact. For things like obfuscation and blocking to work, there'd have to be a massive number of people doing it. And even then machine learning algorithms could pick up what the patterns of people putting blocking in place are. So that would then become a pattern that machine learning can then recognize and work around. So these kind of personal measures are not that effective. And think of it as a purely. We're jumping to your issue about cross discipline. Think of it as a purely computational problem that can give a computational response, which is what they are doing with these things is really far too limited a response. So I'd say a big yes to your issue about cross disciplinary approaches.
- [61:29]
B
Yeah, we'll only out to questions, I think, after this. But it's so difficult. We tried everything, didn't we, when we began? We did try obfuscation, we did try lots of random things. We were trying to mess it up. But I don't know how you do it now. And it's really interesting because every time you come across a different solution. Nationalisation. Look at the government, what they've just sold regulation. Look at the lawyers, they can't keep up, they don't have the legal technical capacity. It's like every time you think of, and it's been the first time in my life when I've done a research project and I've been completely foiled. But we always think, right, there's resistance here and there's resistance there and we can look for those pockets and we can challenge it and we know how we're going to challenge it. And so maybe, maybe we have to think what's going on beyond it, into those social pockets of solidarity and localness where people aren't. But if there's only six people in the room who aren't on social media, maybe that's not going to happen. I mean, how would you do it? I'll throw it back to you. What would you do? What would you do?
- [62:41]
C
So, you know, I've thought about this a lot, partly because I've, you know, my research is related to this, but also I've had the pleasure of doing digital security and privacy trainings for a variety of individuals, from organizers, community organizers to library professionals. And one of the things that I find is, at least as a starting point, really important, is to recognize the. I know it's going to sound a little bit corny, but to recognize what we are either already doing to protect ourselves or already creating alternatives, Right? And I Think that as a sort of grounding perspective actually starts to orient us in a different way so that we recognize that it's not that this is an inevitable choice, these are inevitable technological infrastructures that we have to deal with. It's that recognizing at the very beginning that we have the capacity to create something different is just the basic starting point. Beyond that, I don't know. Imagining a different kind of distributed Internet sounds super exciting. And I think that that's not necessarily out of the realm of possibilities that we'll be working with a very different type of Internet in the years to come.
- [63:59]
B
Yeah.
- [64:00]
A
Okay. Thank you very much. We have about 20 minutes for questions from the floor. I suggest we take them in bunches of three, so to make sure that people have more chance to speak. So who wants to go first? Microphones here. A man over there.
- [64:17]
E
Thanks. I thought it was really interesting you mentioned about you were saying you were angry and you were saying you were terrified. I guess it's a combination of two. We talked a little bit about Peter Thiel or Thiel, but do we know anything about Mark Zuckerberg and his intentions and how he sees the role of Facebook?
- [64:38]
A
Okay, another question over here. Yep.
- [64:40]
F
Thank you. Do you think that the technology is underutilized for good causes? Because potentially it could have been far more effective for saving lives than 999. And if they can track for commercial gains, why it can't be put to track and capture bad guys before they cook up something and leave a bucket in. In a Parsons Green station, why it is not used to detect, deter, and destroy such elements? And finally, if Facebook is the panopticon of today in sheep's clothing, why we have so willingly agreed to it? Thank you.
- [65:39]
A
There's one question. Yes. Mammoth appear there.
- [65:43]
B
As I understand it, the main difference between traditional media advertising is specificity. So, you know, you can pick whether you advertise in the Financial Times or the sun, which is targeting in a similar way to what Facebook provides. But Facebook is significantly more specific. What is it about that specificity that you think is so damaging to inequality? Could we start from the back? Start from the last question and then do you want to answer some as well? Yeah, chime in.
- [66:13]
A
Yeah.
- [66:14]
B
So matching, precisely because it's looking and it's making divisions. The matching is making divisions between the people who can buy things and the people who cannot. And the people who cannot are being sold a very different product. So for me, that is the basis of inequality. And debt is debt. It fastens you into. If it's bad debt as in like mortgage is debt, but that's like middle class debt. But bad debt is when it locks you into a future of insecurity, poverty and complete inequality. I mean debt is a controlling and debilitating form of financial control. So for me that's what matching, that's the danger of matching is drawing those inequalities. That was brilliant. Panoptic in sheep's clothing. We got seduced into it over time.
- [67:06]
C
I have a new Halloween costume in mind now. I think Mark Zuckerberg wants to run for president.
- [67:16]
B
Yep, definitely read his last statement.
- [67:20]
C
I think Peter Thiel's political ambitions have never been. They've always been explicit, even from the time he was a graduate student at Stanford University.
- [67:29]
B
With you, with you.
- [67:32]
C
And you know about advertising and the relationship to inequalities. You know, part of me is absolutely concerned with the type of instant targeting that happens and the capacity for things like subprime loan products or other predatory types of products to be sold to particular populations. The other thing that really worries me is the wealth of these companies and how that wealth is handled and traded on the financial markets. And I think very that is an under explored aspect of this debate. I think Martha Poon, who's at Columbia University and at the New School has started to explore this and I think it's really fascinating in terms of thinking about how money is invested, how that takes away from things like our pensions, who gets to benefit from that investment strategy. So that is I think another angle to these companies and the type of digital capitalism or surveillance capitalism that we're seeing.
- [68:49]
B
Did you want to answer technology? Technology put to good use? If only.
- [68:53]
D
I'd say that's true of most of our use of computing. It's like a huge wastage of computational power upon things like advertising on the subways and computing used in places that we don't necessarily maybe need it or. So it's not just social media where you see that happening. It's our general use of how computing is made into a commodity and used at a commodity level means that we have very powerful systems that are often being used to do quite wasteful stuff and that's having a big environmental impact as well. The carbon footprint of social media is immense. So there's all these factors as well. So it's not uniquely social media because.
- [69:34]
F
The Parson Green accused individual would have been on the Amazon side for weeks, if not months. And if the seller can predict what next he is going to purchase, smart people should have predicted what next step is going to take. So who will be held accountable as men?
- [70:01]
B
Yeah, yeah.
- [70:03]
A
Should we get some more questions? There's a woman there.
- [70:07]
B
Hi, I've been using the Tor browser. I have a sticker on the camera on my phone and my computer. Should I just give up? Is that useless?
- [70:25]
A
Okay, man. There. That's it.
- [70:27]
C
Yeah.
- [70:29]
G
Thank you for the very informative session so far. And speaking of which, I mean, even if we end up, you know, deleting all our Facebook social accounts and all other social accounts, even if we just access one LSE page which is linked to Facebook at the bottom of it, we're still being tracked. I mean, how do you address that? I mean, you just can't run away from the Internet. It's like around us, everywhere. I mean, you go around, you need to make a payment. Nowadays you use Apple pay, you use Samsung pay, you use everything for that. So how do we run for it? And when you talking about so many companies, you haven't specifically spoken much about Apple and you've said probably, you know, there are chances that people using iPhone may be difficult to track. So, I mean, is it like, you know, Apple really locks out all the privacy? I mean, does it really provide the privacy, the stealth?
- [71:20]
A
From these trackings, can you pass the microphone along to.
- [71:27]
B
I just wanted to know about how online dating apps such as Tinder play into this and if you'd looked into that in the reproduction of inequalities, do.
- [71:38]
A
You want to apply to any of those or more questions. Lots of things to go on Tour.
- [71:41]
B
Tour. Tour Tour was set up by the American Navy, wasn't it? To track the. Those who weren't. Who were unconventional. Simon, may want to think about.
- [71:52]
D
I mean, there were. I think it's been. There was a back door built into Tor. There was a back door built into Tor at certain points that allowed the US Military access to the networks. And it was partly created to have that. These, I mean, these things, I think these. There's an issue between whether you feel you're personally protected by using these tools and whether these tools change the infrastructure and have any kind of bigger structural impact. And I think most of them don't have much of a structural impact, including unless there's a massive use of it, a massive switch over to it, which isn't happening on a scale that's going to have a big strength. Structural impact. So it's the structural impact. If we care about the wider social ramifications, not just about whether we feel secure in our own use, then these tools don't do that much in terms of that bigger structural impact. They can be useful from a rhetorical point of view, I think, in terms of highlighting certain issues and making people aware of them. But we do have to think more about the bigger structural issues rather than personal privacy or personal control over data. It's a little bit of a red herring in a way that we're inclined that we're almost encouraged to think of this more as the most important thing when there's maybe other bigger issues as well.
- [73:21]
C
I think that's a great point. The only thing that I'll say is.
- [73:24]
B
Don'T give up hope.
- [73:27]
C
And I'll use as an example, there's a group in Detroit called the Detroit Community Technology Project. And one of the things that they've started to look into. And Detroit is the emblem of the decline of American capitalism.
- [73:45]
A
Right.
- [73:46]
C
It's a city that still, even though it might be on the rebound, is still in. It's the physical remains of the automobile industry. And what's really fascinating about Detroit. Detroit is that this group, the Detroit Community Technology Project, has been investing in infrastructure, so thinking about building its own Internet, so leasing as a third party, the Internet, helping to build wireless mesh networks throughout the city, using that as an engine of education as well as community and local business development. And as a component of that, but not as the only thing. It has started to address privacy and security. Right. But it's trying to do that at the collective level, not at the individual level. And I think that's what's different and that's what we ought to be thinking about for this next wave of dealing with the type of pervasive tracking that we've heard about tonight.
- [74:51]
A
Okay, are there any questions? At the back. Right at the back.
- [75:00]
E
You haven't mentioned Uber.
- [75:01]
A
And I suggest that there's a really.
- [75:04]
E
Positive opportunity with TFL's cancellation of the.
- [75:08]
B
Uber license to actually have a dialogue.
- [75:12]
E
In what is the future for technology.
- [75:15]
B
And how it can play a part.
- [75:18]
E
In society, but also not dominate it.
- [75:24]
A
Woman with a hand up here.
- [75:27]
H
This is on a slightly lighter note, but I'm an LSE graduate and therefore I hope you all realize as LSE graduates, I am high net worth and I have got an amazing network. But on a more serious note, what a load of shitty ads I get that have nothing to do with anything. I've just rented a house in France for the summer. So what comes up? Houses to rent in France? Didn't they realize I've just done it? I'm not going to do it.
- [75:54]
A
Again.
- [75:55]
H
But seriously, if all the algorithms are meant to be so intelligent and learning stuff, why aren't they.
- [76:04]
A
And Woman in Pink down here.
- [76:09]
C
Yeah.
- [76:10]
B
Thank you. I was wondering if you also looked into the implications on the labor market when data is sold to employers, and also on the housing or urban developments, on gentrification, like which is the next neighborhood, that is the hype neighborhood, et cetera, when they get to know your consumption habits. Thanks.
- [76:33]
A
Any thoughts?
- [76:35]
B
We've got a lot of them. We didn't answer the Apple one last time. Apple, very interesting, because they are. They've just hit the top 10 digital top 10 companies in the world in terms of money and a lot of their wealth is made from horrific means in China. So just look at the suicide nets that they put around their factories at Foxconn. There's a different story to be told about Apple, which we don't tell, but other people do brilliantly. Online dating apps, or loop lucrative if you've ever been one, you've definitely been traded. But they're very, very lucrative. And they are also a site for a lot of hacking that I've never understood. Like the match breach, the match.com recently. But Monica Krauser, who's in the sociology department here, has written about the sociological consequences of online dating apps. Uber. There's some experts in the room who could tell you a lot more about Uber that was. And that connects to the labor market. How to use a computer platform to destroy labour markets but make bourgeois life so much more easier. Why aren't algorithms clever? That's always puzzled me as well. If you imagine the power of them, they. Interestingly, if you read the Chaos Monkeys book, which I don't really want to plug because it was, you know, a guy, it's kind of oob. I was going to say it's uber macho. It is, it's uber macho. But he says in about 90% of cases, in terms of selling, they don't need to hit you correctly. They just have to persuade the advertisers that you're worth hitting correctly. So it's the hype of the advertising industry. We can do this better than anybody else. It doesn't matter whether they get you accurately or not, they're selling that to the advertisers. So that's what's critical.
- [78:21]
C
I'll just add one thing to that, which is I think it's really important to think of when data driven and algorithmically run systems are accurate and when they're inaccurate and what the consequences are, because there are many different situations where they are actually accurate, they have low impact or they have high impact. I think it's disentangling that that's really important.
- [78:50]
B
Right.
- [78:51]
C
I think one of the things that I've appreciated about your work is the historical and contextual aspect of it. And I think that's a really important thing to remember when we're evaluating and assessing and thinking about alternatives.
- [79:04]
B
And I just want to say we haven't studied uber labour markets and all the other different companies, partly because it took ages just to do this one. For anybody who's written that much code to actually access Facebook, most research on Facebook is done with Facebook. Only 5% is not done with a Facebook company. So the amount of effort that went into getting that data, imagine trying to do it for Apple. It would be really, really, really, really difficult if it took five computer science departments to actually prove what Simon got. Imagine the amount of work it would take. So that's why we haven't looked at other companies. But I would love to know. I'd love people to go out there and do that.
- [79:51]
A
Okay, another five minutes left. The man over there with the yellow hair. That's okay. Sorry.
- [80:06]
E
What I was going to ask was how do you see the future of cryptocurrencies and blockchain technology relative to all this kind of cost analysis technology that Facebook is running in the background? So what's the future of Bitcoin and all this kind of stuff that's happening on the side and how do you see that and personal finance developing in the future?
- [80:26]
B
No, you're really good at that. You can actually do blockchain.
- [80:29]
F
Shame.
- [80:31]
A
Question in the front here with a microphone in the front.
- [80:35]
B
Seeing as this is basically Facebook's business model and several of the other data and tech companies, do we ultimately need to reform or replace capitalism in order to beat this?
- [80:50]
A
Okay, and man over here with the ginger hair. That's right.
- [80:56]
B
Just don't dig that hole. Just don't dig that hole.
- [80:59]
E
Thank you for the talk. So it really seems to me it's a problem with privacy laws. They've not really kept up with how technology has changed. So there's two extremes with Facebook. Privacy laws aren't strict enough. Then you'd mention the Google NHS link up. It was almost a case their privacy laws were too strict because that link was actually having benefits to the patients. But it's just how the patient data has been managed.
- [81:27]
A
Any thoughts on any of those?
- [81:29]
B
Well, Simon's very good on blockchains.
- [81:34]
D
We haven't been Looking at much. I mean, Facebook itself is moving towards being a kind of financialization platform. Its own. It's looking at its own currencies and issues like that. Sorry. So Facebook itself is looking into becoming a financial platform and is doing that already in countries like China. And it's been doing experiments with its own currencies and things like that, which initially were an alternative to bitcoin. Obviously, Peter Thiel has a long history of being interested in again in alternative currencies, financial systems. So it's part of that landscape. There's some interesting work and I thinking going around whether things like bitcoin and blockchain do offer possible. Potential for positive possibilities. More in the case of blockchain, in terms of what people are looking at, which is separate from Bitcoin and not necessarily a currency system or a sort of privacy system. Bitcoin I see, is just kind of probably getting absorbed into mainstream banking. It's already in. I'm doing other work looking at logistics and. And looking at Uber in the logistics sector and things like that. And bitcoin and blockchain are getting heavily used and introduced there now as a way of bypassing. Speeding up logistics operations and bypassing a lot of the kind of regulatory frameworks that exist there. So I think it's definitely a space to watch of the kind of positive suggestions put for the brown blockchain. A lot of them sounds like the rhetoric that was around open source when it first really broke and this would create the new thing and this would be. And it didn't really happen. There's some positive aspects on. I use Linux and stuff, so I'm not like a. But it didn't happen in the way that people thought it through. So I think it's good to be skeptical about the blockchain, but definitely worth watching. Certainly. I think Facebook is part of the larger instrumentation of restructuring finance and financialization that we need to be aware of. I think bitcoin would just be a little bit of that. I think that gets absorbed into a bigger legacy that's going on. I don't think it's an alternative to it.
- [83:51]
A
Sita Bev.
- [83:56]
B
Well, we definitely need a new model of capital. It's like I keep using the word Uber. It's supercharged and things like deregulation. We're getting more and more financial deregulation. We need more regulation, not less. We had the 20078 crisis as a result of deregulation and now it's kind of technical deregulation of all financial controls. The investment of Goldman Sachs into things like Bitcoin to is phenomenal. I mean, you know, wherever they are, you can see what's going to happen. So for me, it's like an amplification of everything that went wrong is now happening in the digital world. But I wanted to end on a positive note. So I do think, and it would be very interesting to see, I do think everybody knew. Most people know they're being tracked. I'm not sure everybody knew how or how frequently or how often or all of that. And to be able to politicise that for good ends for me is absolutely critical. And we really do need to think how technology is being used, you know, not for us literally to extract stuff from us. So I think we really, really need to think about how we try and take it back in some way, but it's incredibly difficult. So, yes, we do need a new model to be put to good uses, not to be put to the horrific uses that it's currently being put to, which is just to make money out of every. What was your soul? Every move you make, every breath you take. We'll make money out of you.
- [85:28]
A
No.
- [85:29]
B
So, yes, that would be. Yeah, that would be a good change.
- [85:33]
A
I think that's probably a good note on which to finish. Can I just remind everybody that there's a reception outside if you want to. If you've got time to share some wine libels.