 For those of you that are logging into Zoom and just getting set up for the webinar, we will be starting in about two minutes. All right, let's get started. Welcome to the Center for Global Enterprise, Global Scholars Expert Connect Series, Identity in a Digital World. My name is Ira Sager. I am Vice President of Global Learning Initiatives for the Center for Global Enterprise, CGE. This is our final Expert Connect forum in this series exploring the complex issues surrounding our digital identity. For those of you who have been with us for the entire series, I hope you've enjoyed these forums. For those of you new to this forum, CGE and our Global Scholars Program, I'll briefly explain our mission. CGE is a nonprofit research institute focused on the study of global management best practices, the modern corporation, economic integration, and their impact on society. Our Global Scholars Program is a worldwide learning community for business-interested students, academic faculty, and business professionals. Through Global Scholars, we offer online courses, digital internships, as well as this and other Expert Connect webinars. Participation in all our programs and membership is free. You can find more information on our activities on the website, on the CGE website, rather, www.thecge.net. Before we begin today's program, a few housekeeping issues. Today's program will be recorded and available on-demand from the CGE YouTube channel. We'll leave approximately 15 minutes at the end for questions from the audience. And if you have a question for our presenter at any time during the presentation, you can submit your question using the Q&A feature at the bottom of your Zoom screen. We'll try to get to all your questions time permitting. Over the next hour, we will explore the new economics of identity, the concept of data ownership, and the global rise of digital identity systems. We will look into the future of personal data collection, storage, and analysis and the analysis industries and what sorts of tools and institutions we need going forward. Dr. Irving Lodowski-Berger, a CGE Fellow and former IBM Vice President of Technical Strategy and Innovation, will lead our discussion. And now, we'll introduce today's presenter. Irving. Thank you, Ira. It's my pleasure to introduce Tarun Bhadwa. Tarun is the founder and CEO of Day 1 Insights, a startup focusing on these kinds of issues. He's a visiting instructor at CMU's Carnegie Mellon University in Silicon Valley. He is a contributor to Forbes, and he's the recent author of the digital transformation of who we are. And I'm very happy that Tarun will now discuss with all of us the new economics of identity. Tarun? Thank you, Irving. Thank you, Ira. Thank you, Monica. It's my pleasure to be with you here today. Identity is an issue that I've spent a lot of time thinking about. I've looked at it from several different perspectives. My interest in this field started about roughly seven years ago in New Delhi, India. I went there to look at how the government was dispersing their public goods and looking at some upcoming economic disbursement formulas they have. Instead, what I found was they were working on this massive IT project. At that time, it was just in the policy planning stages. So there were just a few papers about it. But I was really struck by the ambition of what the Indian government was trying to do. Here you have a country of 1.2 billion people, roughly 400 million of which can't reliably prove who they are. All around the country, the infrastructure is a mess. So what the Indian government and a series of entrepreneurs within that government were planning to do was really amazing. They were going to take a series of technologies and create a cloud-based portable ID system. So the vision of that really struck me as something powerful and applicable around the world. Now, as I studied the Indian model closely, I began to have some concerns about how they were going about executing it. But what it did was it started me on this global study of digital identification. Identification and its many, many different forms all around the world. So I began to look at the tools and systems that people use to see who we are. Companies, governments, each other, tech startups, that sort of thing. And looked at how are they changing our lives? How are they changing the way we live our day-to-day, the way we carry out our day-to-day activities? So since that time, I've studied this issue from a policy angle, from a cybersecurity perspective, as an entrepreneur. These days now, I have a consultancy firm, as Irving mentioned, and I help companies navigate some of these issues. So for the purpose of today, I want to talk about personal data. Now, with great respect to the many, many people who've done a lot of work around identity and the definitions of identity and the definitions of the many, many words that make up the field, I want to side-set that discussion a bit. Not because it's not important, but because I want us to focus now about businesses and business value and really look forward to see what's coming down the pipeline. So I put this presentation together today as sort of a response to a conversation that you hear us having a lot. And that's this conversation about data ownership. Here in the world in 2019, we feel that something is wrong. We know that something feels a bit off. About the way the world has been digitalized. So you've seen this big reaction in the last few years, which I'll get into in just a moment, about own data ownership. That if we as individuals could take back some sort of control over our information online, that perhaps we can get to the beginning of a better deal or a new ecosystem, or just a different way to interact with the computers and the companies around us. I believe in that vision, but I think it's incomplete. And what I want to do here today is fill in some of the details. So without further ado, let's begin. I'd like to take you back now to 1999. It was a different time. It was a different world. So there was an interesting debate going on within the confines of Google at the time that I think is worth revisiting now, which is that Larry Page, who was the CEO at the time, he was a CEO originally and he's a CEO now. But there was a ticker in the Google Lobby. And that ticker would show where people are searching. So people would come in, especially journalists, and they'd look at this ticker and they'd mesmerize, looking, wow, look at all this information that this company is able to access. Think about all the ways they can look into the world and describe our future and describe things that are going on in that sort of situation. Well, Larry Page was really conflicted about this ticker. In fact, he wanted to take it down because he uniquely understood the power of this personal data and what it could do. So when the whole world looked at Google and they just thought they were a search engine, Larry Page saw differently. He saw the basis for a new economy and a new industry. So there's a fascinating conversation with the venture capitalist John Doar and Larry Page tells him, man, that Google is going to be worth over $100 billion. Now, today we'd say, okay, big deal, $100 billion. That's what a bunch of kids raise on a nothing idea in Silicon Valley here. But back in the day, that was a huge valuation. That was far exceeding any of the other players in the industry. So Larry Page had that vision about personal data that a lot of us didn't and he was able to make decisions about Google's architecture and future that have had huge ramifications 20 years down the line and explain why there's such a dominant company as they are today. By the way, when I have conversations about security and people say privacy is dead, get over it. My favorite thing to do is say, okay, let's go to Google.com slash history and you let me choose a date and we can see what you search. So if privacy is dead, let's see your Google searches and usually that ends the conversation there. The point being that our searches are really, really intimate, powerful information. They reveal not just what we were looking for but what we were thinking, what we were feeling, our strengths, our weaknesses. Think about how often we Google search on emergency information or health data or if a child is sick or a parent is sick, that sort of stuff. It's incredibly personal, valuable information. Google saw this, Larry Page saw this, Sergey saw this and they were able to see the future of a new industry there. Now you look around and what is Google doing? Google is doing nearly everything. Google is trying to defeat death there, trying to provide internet to everybody. They're trying to map the human body. What the hell business does Google have doing any of this? The reason they're doing that is because these are all data-based enterprises. Google has understood that data is the new life flow of industry and they're able to harness data and understand data, analyze data and wield data. Unlike really any other company in the world outside of a few perhaps Chinese rivals and companies like Amazon now today, there's only a handful of companies in the world that have that understanding of data that Google does. So Google saw, Larry Page saw and through that Google saw the true vision for personal data, which is that this is the basis for an entirely new set of industries, products and services. And that's the real genius of Google in my opinion and Facebook to an extent too. They went to thin air and they pulled out hundreds of billions of dollars by making up a new asset class out of thin air. And that was taking your personal data and selling access to it. And that's the core deal there. That's the bargain that we've had the last 20 years of the consumer internet, which is that I give Facebook and Google every single piece of information about me in exchange they keep it secure and then they sell access to that data and deliver me value. So they get my location data. Yes, they sell me ads, but Google Maps works great and on balance that's been more or less a fair deal. But we are starting to see that deal now be tested. So you look around and literally we were talking about a multi trillion dollar asset class made out of data. It's not just Google. It's not just Facebook. It's the whole pie. It's a way that Microsoft and Amazon and all really US corporations not use data. It's a fact that these corporations now exist all around the world. China has its own set of giants which we'll be talking about as well. And there are many, many other upcoming companies in other countries that are database too that are worth huge amounts of money. You look at a company like DD in China that's a very much database engineer-based play. We're three decades into the modern internet as we know it. But we can't help but feel like something has gone wrong. You look around, you see the signs everywhere. You see the discussion right now about addiction to phones, about society, about the value of social media, these sorts of things. We can't help but look around and feel like something is wrong, something is missing. And that's because something is missing. There's a piece of critical infrastructure that's missing from the internet. And I love this map here. This is from a Carnegie Mellon professor from 1973. This is the internet at the time. This is all we had to defend. This is all we had to worry about. Nobody expected that you use the internet to buy dog food, to find a date, to do all the sorts of crazy things that you do on the internet today. Those sorts of vectors, those sorts of attack points were never considered. So we've designed the internet for almost an entirely different world than the one we built. And this goes back to the original sin. Many of your other guests have said this as well too that the internet never had identity and payments from the beginning and that's the original sin. It's true in some respects. The protocols that we use just aren't built for the activities that we have them for. But the thing is that there's an enormous cost to this. And this is what I wanna talk about today. We're paying an enormous price for this. But because it remains abstract and not that visible, we don't really notice this cost. So we don't really address this issue as the economic catastrophe that it is. So how do we go about calculating the losses of things that are abstract? I think we can do this in a couple of ways. First, let's look at its losses. Let's define this problem by what we lose. Let's start at the top. Governments, governments lose a huge amount of money in the inability to target goods effectively. And this is especially true in the developing world. A country like India and some estimates are 50 to 80% of the public goods are being leaked along the way, aren't making it or go down in the result of fraud. That's a huge, huge economic loss. You're talking about a huge hole in the social safety net of a country where people really rely on that. And the vast majority of the world looks like India, then it does looks like America in that sense. And here, even here in the United States, we have huge problems with targeting government benefits appropriately, tracking people through the system, making sure they get the care that they need. So there is a huge loss at the government level and in this ID sense. Now, take the US case alone. Our reliance on the social security number leaks data left and right. It causes a huge amount of fraud. So if it were to add up the cost of not building an alternative to the system that we built for taxes almost 100 years ago, it would be enormous. So that's one way to calculate it. Another way is to look at the huge cost of identity theft directly around the world. Now, in the US alone, that's 60 million Americans, almost one in six people and over $16 billion taken. Globally, that problem is much bigger there. But if you look at the stats, people say that, experts in this say that if you look at cyber security issues in general, almost 80% of these have some sort of identity component, whether that's a username or password that was stolen or an account that was hacked, this sort of thing. So that's a $6 trillion a year problem. Now, how much of that is identity? I don't know, but a good portion of that, if it's related, then all of a sudden we have to look at the bigger cybersecurity picture and say, hey, identity is a huge part of this as well too. And then there is the cost for companies. You look at a huge corporation, those sorts of things. They spend enormous amounts of money on password resets and help data requests. You look at large consumer-facing companies, it's the same story. It's a huge pain point for consumers, massive friction, and don't even get people started on passwords. We all hate passwords. We would go on and on about how we have to manage 250 long strings and characters that aren't human that don't interact like we do. So there's huge unhappiness. If we can quantify that some way, there is a major unhappiness to the way we deal with logins on the internet today. And then let's define this by the industries that don't exist yet. We're not used to thinking in this way, but think about the massive opportunity costs of our ID systems too. There are so many opportunities that haven't yet been made possible because we don't have proper architectures and data and control in place. Now there was an interesting story last week about IBM and Flickr, and IBM using a facial recognition set of images that was scraped from Flickr. People's social media photos were put online. Now the dirty secret about that is it's not just IBM and that's really not even the main issue. The problem is that we have a decade of technology built on data that was collected without proper controls or checks in place. That's a much, much bigger issue than people want to realize. And it's coming up for businesses in different ways. So that was a small embarrassment for IBM, but that's a dirty secret about facial recognition databases generally. A lot of that stuff is scraped off the internet. More and more, we're going to find this to be the case in a lot of data that industry uses. And then how do we calculate these other effects that have happened? Take, for example, the Ashley Madison hack. Now, for those of you not familiar, in short, that was a social network for cheaters that was hacked and that database was exposed. And it was one of the first hacks that we've seen that not just goes after payment data or that sort of thing, it goes after secrets. Now we're not really used to attacks like this whereby something that wasn't known becomes known by way of a cyber breach. And the effects of that have been catastrophic. It's been a little quiet, so it's hard to see, but for the 30 million people caught up in the Ashley Madison database, and I hope none of you listeners are in that database. It's been a nightmare. We've had six confirmed suicides from this already. We have groups in the southern part of the United States church groups going together, combing these lists, looking for their members. People in this database have reported receiving extortion, email and physical mail and calls and threats. Basically telling people they're gonna let their families know that they're in this database. So it's been catastrophic on a human level. There's been an enormous cost to that. How do we quantify that? I don't even know how we quantify the type of damage that is. And then the Office of Personnel Management, not exactly an identity issue, but if you look at it in the sense of a broken background check process and perhaps some credential mismanagement on the part of contractors, this is also a huge issue. And how do we calculate the national security cost to having all of the special form 86 in the hands of we think Chinese hackers? So one senator said that this was more damaging to the US than September 11th. Now he's a senator, he exaggerates that sort of thing, but it's important to take this point to heart and understand that there has been a major cost to this. And then what about the other social effects? Would it's impossible to have a second chance in life now? Our reputation for better or worse or something we'd done we did online carries with us everywhere we go. Our identity information is attached to every single interaction we have. We built filter bubbles for ourselves. Who thinks this is a good thing for society in the end of the day? Yes, we get some better content and recommendations, but this is how to cost. And then the risk and damage of selective targeting has never been higher, meaning that if somebody wants to destroy your reputation or hack into your computer or make your life harder, they can wield so much identity information against you because we have a decade of constant data breaches. If I want to know your mother's made a name, that's just $30 away online, I could find those sorts of things. And then there's little recourse for people affected by this. Information is then used in insurance, it's used for all sorts of different purposes and that creates huge issues. So an example of this to me is the data broker industry today I mentioned, your mother's made a name, that information can be purchased. This has been a huge hit to knowledge based authentication, but at the same time, this has been a security nightmare. Everywhere I go in the world and I advise companies, to say, learn from our mistake in the US, don't build a system like this. You can do the sorts of activities you want with data without building such an architecture that's so leaky and so damaging that passes so much risk down to the individual level. That's really what many of these companies are doing. And there was a report from the World Privacy Group, I believe is their name, I may have that incorrect there, but they testified to Congress about data brokers and they revealed that these companies were selling lists of victims of people with AIDS, of suffering from cancer, seniors with dementia, these sorts of things. So the classification of our data has gotten out of control to the point where it's objectively no longer in our favor. At the same time, we gain a lot of value from personal data and enable things like insurance, background checks, financial transactions. If I wanted to go buy a car right now, it would be much, much easier because all this data is there, because experience can prove who I am. We don't like to say nice things about these companies, but they do make our lives easier in some respects. So we have an entire ecosystem where our data is traded as a currency, but we're not involved in the exchange at all. Information is processed by machine to render judgments about us, whether we like it and there's little to nothing we can do about that in today's world. And then the judgments and the effects that leads down the road, we're stuck with the consequences yet we have no visibility into the process. I would argue that this is entirely unsustainable. I know it's worked so far, but we're reaching a point of diminishing returns with this sort of system. Let me explain a little bit about the driver to see around the world. First of all, I studied this issue globally. I mentioned I started my research in India. I've been to about 30 different countries studying their ID systems, asking regular people if I can see their license in their wallet. First they're put off, but then when I explain why they come around to it. But I'm basically trying to get a feel for how do we translate our identity systems through the cultural and the societal lens that exists in every different country? We have different sensitivities about privacy. We have different sensitivities about government data collection everywhere you go in the world. So how do we translate that through our identity systems? And what you find is pretty remarkable in that these ID systems are a reflection of who we are on a national level too. For good and bad. In European countries, you see this used in the design whereby in France, you don't have a central register. And in Germany, you limit the kind of collection that's done about race and religion and those sorts of things. But in places like China and places like Egypt and places like Pakistan, that is also used to enforce a government religion. So our government preference for religion. If you're not one of those and it's not officially recognized. So you're seeing ID systems used to consolidate state preferences and state power for better or worse in both good and bad cases. You're seeing ID systems being used as a driver for political inclusion and rights. And then there's the explosion in fintech in bootstrapping of financial services which we'll talk about in depth later. There's the ability to build reputation-based economies especially now that everyone has a phone in their hand. There's increased connectivity. There's mobile biometric sensors and hardware improvements. And then there's accessible cryptography and let me explain what I mean by all of these here. First, you're seeing vast majority of the world move to biometric back national ID systems by the end of the decade. In vast majority of the world, all your interactions with government are becoming digitized, tracked, stored, that sort of thing. We're having seeing surveillance normalized for both public safety and for reasons of government control. And then again, that breaks down a little bit differently depending on what country you're in. We have a very different conversation about this in Singapore than we do in Germany, let's say. But in China in particular, it's been interesting to see just the nexus between the state and the Chinese tech giants and how they work together and how they use each other to push their own interests. And an interesting example of that right now you're seeing is a widespread use of facial recognition in commercial transactions. There's an example about Alibaba is a part owner in KFC now. So there's a huge push to digitize there and personalize in those sorts of things. And some of the biggest tech companies coming out of China right now are facial recognition startups, SenseTime, Face++, huge amounts of value being created. And really what we're at is this interesting point in history where we're at the end of the freedom of record. Basically, everything we do leave some sort of trace leave some sort of record in some database somewhere and things are coming together. And that's very much a story of right now and what's going on. Reputation is becoming central interaction. So reputation is identity expressed over multiple instances with a degree of certainty in a way. That's how I look at it personally. Whereby, if I can prove who I am and then I can have someone to test approval who I am and I can start to collect those attestations and then I can prove I am myself in many, many different instances, all of a sudden that data forms the basis of a reputation which can then be filled out by other people and such. And reputation is becoming central nearly all of our digital interactions really. And increasingly our business interactions too. There's a more macro change going on in the world about trust and reputation, where it's shifting from institutions to individuals. You see this move away from governments and businesses towards people in communities. And the perfect example of this is a reliance where the preference that we all have now for social media reviews, excuse me, for product reviews over ads. We wanna know what people like us and other people who've been in this situation think about these sorts of things, not what the company for sure says or that sort of thing. So there's a move towards communities rather than marketplaces. And this trust in individuals is based on things like reputation scores and validation and connections and interests. So the Uber economy is a perfect example of that. It's rating two ways. My driver rates me, I rate my driver. So trust is becoming key to everything. And then another interesting trend has to do with the proliferation of mobile phones. I know this seems like a horse that can beat him to death, but I really think that we've missed the main stories that are going on in this situation where we kind of in the West especially we paid attention to the stat about how many phones there are in the world. And once we hit four or five million or something we checked out and said, job well done and moved on. But what's been really, really interesting is the second wave of mobile that's happening. And that's the move from dumb phone to smartphone. This is such a profound shift that people miss this whereby if I have a dumb phone, I can make calls, I can do SMS and I can get basic information gathering. If I have a smartphone, I have a software platform that can be scaled to a virtually unlimited amount of use basis. That's profound. So look at China, look at what's been happening there. You've seen an entire country become sort of a sci-fi cashless futuristic society in a matter of five years. Now what drove that? Really, if you look at the data, it was shopping and games. It was China building one of the most addictive e-commerce engines in the world. What they're doing with a T-Mall, with JD, with Alibaba is incredible. And then you look at Tencent, you look at WeChat, that's become infrastructure for the company. WeChat was made by Tencent. Tencent is a gaming company, that's their DNA. So it's been really, really interesting. These two software drivers combined with China's ability to drive down hardware costs at scale. And you look at a company like Xiaomi, it's been fascinating what they've been able to do. People miss how profound this is. You can now buy a smartphone in the developing world for $40 or give or take $10, $20 around that, depending on whether it's used or not. So you're talking about a $40 smartphone. That's a fascinating development. You look at a country like Africa, we've hit about 800 million cell phones. What happens when we hit 800 million smartphones? All of a sudden you have a radically different set of possibilities that are available to you. Now there's another possibility here that people miss, which I think is absolutely fascinating. Which is that, if you look at this challenge of how do we get everyone an identity? How do we identify everyone, recognize who they are, et cetera? Well, in theory, right? You can give everyone a public private key pair. But the problem is that they'll have to manage that key. And that's a really, really, really hard thing to do for the average person. You look at the Bitcoin world and the cryptocurrency world and the amount of losses that are piled up there. It becomes very, very difficult to do, especially in difficult situations, geographically, culturally, et cetera. But if we start having these advanced hardware devices put in more and more hands, and maybe not the devices of 2019, but the devices of 2022, all of a sudden we have a chance to democratize the distribution of cryptography in an entirely new and novel way. Because those phones are powerful enough to do proof of work type things, or they have a hardware enclave. Or also very interesting, is if you look at the fingerprint sensor, that is now done at such scale that it's become cheap and advanced and virtually available for everyone in the world. So you have another factor there. So now if you can go in the developing world and have a phone where you're able to biometrically authenticate yourself, that's a game changer. That's fascinating. And that's probably the least problematic implementation of biometrics that we can have there, whereby the person stays in control of the device and the fingerprint is used just to unlock the device as a cryptographic identifier. So we have a huge opportunity here to democratize photography. And they're much, much different expectations by users. This is the example of WeChat in China. It's like Facebook on steroids. We don't really have a comparison for this anymore. It used to be a Facebook clone of sorts. Then they localized and they took in directions that are unimaginable to us here. Now if you look at Facebook's pivot from social network to messaging, they're trying to clone WeChat. So they've seen that the world is moving into these smaller groups and they wanna get a cut of service revenue and that sort of thing now. But WeChat, it's a platform technically speaking, but really it's like an entire operating system. Within one app you can do everything from food to pick up your kids, to access government services, et cetera. So those are huge increases in the demands for mobile products and what they're able to do. You look at a country like India and beyond just their ID system, what they're doing now is they're building UPI and payments and other things. Their goal is to become data rich. And that's when things start getting interesting from an e-governance point of view and from the ability to invite entrepreneurs and build industry and such. And then it's not just India. It's really all the developing nations that are along this path. They're all becoming data rich. Our ability to process information has changed a lot too. We have new types of computing. We have graphical processing units that have made a big impact in deep learning that we more or less found these technologies accidentally. They were made for gaming. And then we found after the fact that they could be used for AI, narrow AI. We have massive amounts of data. We have massive amounts of information compared to the last 10 years. And then we're getting better and better at analyzing and understanding that information. So these three trends together which were identified by Kevin Kelly of Wired, these are really changing the landscape for machine learning and for the ability of computers to process information. We're seeing computer vision able to now look at the real world and classify enormous data sets, populations of people moving through a city at scale many, many times a day for many years on end, that sort of thing. So the amount of information we have about our environments is getting very rich. And so machines are getting smarter and smarter in their ability to identify who we are, what we say, our emotions, these sorts of things. But the dream of personalization has kind of stalled out. Businesses talk so much about what they could do if they're able to build this relationship with us. Yet outside of a few use cases here and there it's become very rare to find good examples of personalization. So I would argue that all the personal data has been given, but the dream of personalization remains unfulfilled. And that leads us to the situation we have today about this discussion about breaking up big tech, about the fact that we've understood that these companies realize something the others didn't and that they were able to gain some sort of what we believe to be an unfair advantage and sustaining them. Whether that's true or not, we'll see whether, how that plays out and all the complexities we'll figure out in the next few months as we have the discussion. But it's led to this anxiety about the concentration of power and tech. I look at the blockchain movement and I'm gonna talk about that more in a minute but I see that as an ideological response to this sort of issue. So the way we extract mine and discard personal data is achieving diminishing returns and I would argue it's holding the back, the quality of our digitalization. So we need to assert our modern right to transform who we are under conditions that are favorable to our interests. And this is key because we're losing this more and more. And the only way I've seen in my years of looking at this issue to accomplish this is to develop an entire ecosystem of needs. So this is what I was responding to in terms of ownership, that if a law were to pass tomorrow that says you own your data, I don't believe it would change very much. Honestly, I think that we would be tricked into giving up our data in different ways just as we have been in the last 10 years and we'd end up roughly where we are today. That is unless we really think this through and we really build out a new world for our data, for that information. So we need to develop scale, legal regimes, audits, agencies, interfaces, protocols, and markets to make this new economic possible. So what does that involve? First, and I'll walk you through each of these. Let's begin. We need to revamp individual rights and protections. So that's the legal reform that I want. Ownership is fine. If we wanna pass a law starting ownership, that's great. But really we need to look at individual rights and protections. And this is in the larger context of consumer privacy rights. We need digitally native identification systems. It's interesting we're in this world where we've been digitizing our paper-based ID systems. And we're still struggling with that. Now we're getting glimpses of this future of a digitally native ID. Whether that's useful or not, or applicable or not, we can discuss. But it's interesting to see what that looks like. We're building systems to automate value transfer between machines. We're rethinking social networks and data brokers. And then we're creating market demand by unlocking value. Let me walk through that. First, I'm not so sure that we even have a clear understanding of who owns what data. First of all, it's not clear that if I go to a website and I interact with the company and data is made out of that interaction, who owns that data? Yes, it's my data I helped create it. But the company also has a legitimate interest in that information. So there's this question of ownership, there's a tension there. And then Jeffrey Moore pointed out that there's different types of data. There's data as records and there's data as signals. And so the value of data is very, very different. Now think about a self-driving car. One mile on a sunny suburb in Europe or something is very, very different than one mile driven in Brazil after a soccer game. So the value of data is very, very different. So when we talk about owning data, it gets very confusing. Now a self-driving car makes 750 gigabytes of data a second. How the hell is that gonna work in this sort of framework? What part of that is personal data? What part of that do I own? Do I get to have a copy of that? Or do I get to control how that's used? So the question of ownership is really masking a whole set of other questions that are really thorny and hard to work out. And then we got to work through. And there's been this demand for many years for a personal data store. Many, many brilliant people in this field suggested something of the sort. And I don't mean to disagree with them on the substance of what they're suggesting here. But I would argue that we're talking past each other to the extent that we have no idea how this looks. And what I mean by that is something very specific. I mean UX. And UX is so brutally ignored in this field to the detriment of everyone involved. That we have these ideas such as take all of your data and put it in one place. Well, what in the world does that look like? Do I go to data.com and see every single interaction I've ever had? And what the hell do I do with that? And why do I have to manage this? I'm busy. So I think that's a situation that we're gonna get in there. So I see a grand challenge here in this field and that's design wise. What do these databases look like? What do these dashboards look like? What do these interactions look like? And I'm the only one that still talks about Google Plus but I'm still mad about Google Plus and that Google went and they made an iterative social network when they could have built this. They're one of the few companies in the world with the know-how and the complexity to build a real proper design interface for the world and for our data. But they didn't do that. They spawnered it that opportunity trying to compete with Facebook. So I am very sympathetic to the need for this sort of system. I don't know how it looks in practice. And I think we need to focus a lot more attention here. So we need to reach out to the designers and UX people of the world and say, how do we build this sort of thing? And I suspect what we'll find is that this idea of one personal data store makes very little sense and that we're gonna have different data storage for different activities. There's gonna be different people involved in there. Now, there's fascinating work being done in the field of self-sovereign identity. That's sort of an older term. They're calling it a verified credentials, verified claims now. But it's this idea of an entirely decentralized identity where there are no intermediaries. Now, I am sympathetic to this point of view. I understand why these people are working on this. I think there are some absolutely brilliant technical minds doing fascinating, important work on this, but I don't yet see the business case for self-sovereign identity as it's been presented in this way. I think there are huge obstacles. The biggest being similar to what I mentioned before about key management. I see this as the Achilles' heel of the field. Adam Mingus, an analyst, said something similar. And I believe the CEO of Evername also said something similar to the effect that the Achilles' heel of this field is key management. It's that the individual for, and this is the whole point of the system, the individuals in control. Well, control is a dangerous thing too. Control is hard to manage. So the individuals in charge of their private key, well, what happens when they change their phones? What happens when they lose their phone? What happens when they move to a different address or they get married and their last name changes? All these sorts of things. So I don't see this scaling to those challenges. I also don't see this generating enough of the business demand to reach the network effects to be anything useful of the sort. But I do think these core ideas and this core research will become very, very valuable for the future later. I joke with my blockchain friends and despises them off a bit, that they're building infrastructure for big banks and the Chinese government through their work. But I believe that a lot of that work will move to the realm of big institutions. I was recently giving a talk at a large bank and we were talking about this sort of idea and they said, you know, if this exists, we would use it in a heartbeat. But the problem is that getting this to exist is the core challenge. And I find this to be the issue in much of the blockchain world too. I call myself a blockchain skeptic and I used to give me very dirty looks in San Francisco. Now nobody cares, because it's obvious. But two, three years ago, that was a big problem here. And the issue being that blockchain is useful in identity in certain contexts, people put PII on blockchain and stuff and that discussion is very toxic and dangerous. What I find interesting and valuable about what blockchain is bringing to this conversation is this discussion of cryptography about imbuing cryptography in our identity transactions. And I think this is very, very much the future. Now, what the blockchain does useful here is it orders those transactions. It doesn't do much else useful here in my own personal analysis, at least today in 2019, but perhaps that can change in the future. So that's one key piece. We're gonna need a digital identity of sorts that's not just paper-based, but digitally native. Whether this comes from a big bank or comes from a startup, I don't know. My bet is on the big bank, but we'll see how that plays out. We're also gonna need an infrastructure and this has been referred to as a consent layer. There's some great work being done in this field, whereby we have privacy policies for ourselves and our devices and such, and they're machine-readable and machine-to-machine communication can be done. So my car can drive by somebody else's parking spot and they can have an exchange of value or exchange of information, that sort of thing. It's still in the realm a bit of sci-fi and in futuristic talk right now, but this sort of infrastructure will be key for integrating the internet of things into our lives. And one of the standards being worked on is UMA, user-managed access. It's making great strides toward this. So there was looking past the data brokers now in the social networks, there was a fascinating point the economists made where they went through and they did some quick analysis looking at what a Facebook user would pay to use their services and what they would pay in ads. And they found on balance that we're leaving about a third of money on the table, meaning that if Facebook were to be unbundled, we could buy Facebook as a service and then have some money left over for ads. So clearly the economics are not working in our favor. There's some fascinating research being done. Irving, I know you're part of this here too with MIT's enigma system. There are many, many versions of this now, fascinating and absolutely valuable research. And this is more in the realm of, I would say, private blockchains and then the sorts of public blockchains you see with cryptocurrencies. What this does is allow people to share data without giving underlying control and allowing algorithms to scan that information. And I see this as hugely valuable in industry, especially when you look at use cases like genomic data and pharmaceuticals and that sort of thing. So the data is encrypted. It doesn't get shared underlying that sort of stuff. Now, the blockchain movement has brought us a lot of fraud, a lot of hype, a lot of broken promises, but there's one thing I'm extremely, extremely grateful for them for. And that's that they've got us thinking big about protocols again. And this is a fascinating and lovely and wonderful thing, which is that we are now reimagining the way data moves across the internet. And if this is the sole legacy of the cryptocurrency praise, I will say it will have been a great thing for humanity because we are now starting to think about different ways to share information. These are several protocols, but one in particular I'd like to point out is the ocean protocol. And they're creating, they're thinking through these issues of what does it look like to actually exchange personal information and data? So it's no longer this thing about selling data. This is the marketplaces through which it'll work. I just wanna touch on this briefly, but tokenization is really the next aspect of this. When that personal data is stored in some sort of blockchain or order or whatever it is, then we can then move to tokenization. That has to do with a cryptographically secured set of rights, a digital representation of the set of rights. So there's a lot of hype around tokenization and people are talking about real estate and art and these sorts of things. In my opinion, for physical assets, this makes very little sense in today's world. We're not nearly digitized enough for these businesses to be viable, but for digital assets, it starts to make quite a bit of sense because it's a way of ordering digital assets and sharing it. So we wanna know what is my last visit at the doctor worth in terms of selling that? Well, this is how we can do price discovery, these sorts of means. So it will reduce cost barriers for fractionalization and it will allow these automated marketplaces to come about that will be very useful. So when I talk about this sort of thing about these marketplaces for personal data, it's very, very hard to imagine because we don't have much that looks like this in today's world. Where by, and I need to say that I don't think I'm gonna be going logging online and inputting my data, hitting upload, setting a data set, selecting the data form, that sort of thing. If that were to happen, there would be no scale. It would be a nightmare. Only a handful of people would ever do it and we get nowhere. This has to be in the realm of machines. This has to be automated. So people have talked about in AI bots helping you. I wanna break that down because anytime I hear the word AI bot, I just, I turn off mentally and get sad because usually they're just talking about nothing. But if you look at RoboAdvices and the financial services today, we have companies like Wealthfront and Betterment. And what they do is they allow you to invest a certain amount of money and they make suggestions based on what your portfolio should be, based on where they think you should be allocating assets. I see something very similar emerging in the personal data world. Where by when we have these marketplaces and these networks, we're going to need automated agents on our behalf to negotiate for us and to sell information and handle those sorts of transactions. So again, this is touching on the realm of sci-fi here but it's not too very far off. And we have analogies for what this looks like today. So it'll be dominated by machine to machine communication and a lot for scalable exchange. So a new company wants to start up and they come about and they'll be able to access data sets that they never had before. So I don't believe in this future about people owning their own data about no intermediaries. I wish I did. I wish that were possible. I want that future. I just don't think it's feasible for better or worse. I hate to be killing some dreams by saying that but I just, I don't see how it works. What I do see is a rebirth of the intermediary basically redesigning that. Now, whether that is a small startup or a peer-to-peer service like we've seen in peer-to-peer lending or if that's a bank or if that's a tech company, we don't know. There are many, many opportunities. There's a lot of logic. There's a huge, I would say that the most obvious fits here are banks and tech companies. And I refer you to the last webinar for some of the logic around banks. It was an excellent presentation. Tech companies is very much the same logic. They have access to our information. So when I meet with banks, I tell them that tech companies are going to steal your payments business. They're going to steal your checking business. They're going to do everything you do better with better security and better scale. What are you going to be? What are you going to do? The most obvious future I see for banks are as identity managers. Basically these new intermediaries, being these people in these different fields, because we don't want to deal with this. We want this to be taken care of and we want to know who to blame when something goes wrong. That's what we want. We want certainty. We want service. We don't want to deal with anything else. So whatever companies are able to deliver on that, I see great things ahead for them. And then there's new threats on the way too. I just gave an interview on Al Jazeera a few days ago about deep banks and the threat that poses to our world. These are starting to go global and people are really starting to worry about these. Now, the point I made was that I'm not so worried about deep banks causing a war as I am, I'm worried about them ruining reputations and relationships. To the point I made before about identity information being wielded and targeted against people, it's a huge issue. And then just making this point here that our broken verification practices are also having a large social culture degrading our public discourse. We're starting to see fascinating things happening with fake IDs online in social media interacting with people. We're passing, we're flirting with that Turing test right now about whether you can even tell whether you're talking to a bot. And we've seen bots used in the Middle East to solicit scams from refugees. ISIS created bots to scam refugees and they worked, these sorts of things. So we're seeing huge advancements in fake ID beyond just creating a fake person and a fake ID, fake personalities, fake identities that go very, very deep. So I wanna look at this now from two sides and wrap up here. What's in it for users? What's in it for business? I try to take a cold hard look at this and put all my ideologies and wishes aside and talk about value. As in what are we building here? And is it really worth it for both people? This is gonna be a lot of work to build. Is it worth it? So for users, what's in it for me? So first, and this I see is a key problem today. Our incentives are not aligned. Companies are incentivized to do whatever they can with our data to gain value from it. And they're not incentivized to give any information back to us. So I see a reorientation of this ecosystem as aligning incentives, increasing my protection. And then third, income streams through selling data. I don't think that's gonna be a huge driver. I don't think that this rush to get us all paid that sort of thing is going to sustain this ecosystem. I'm not even sure if there's enough money in it today to really justify people cooking up their bank accounts to their identity accounts, that sort of thing. But the point is as we go forward, every interaction will have some sort of commercial interest. Think about that. If you have a fully digitized world of sensors everywhere, how I open a jar or how I lift up a cup or these all sorts of things, they're all data. They're all information. They're all valuable to somebody. I mean, that's a beautiful thing about capitalism, right? That all of this information, if it's a value and if it's discoverable and available, it will reach somebody and they will do something with it. So we have these privacy enhancing frameworks that reduce my exposure to security downsides. And with intermediaries, it shifts the risk away from me. And it allows the challenge to move the collection of my data and set combination of my data. So think about the healthcare space. I'm gonna touch on that in a minute. If my data was brought together in intelligent ways, it can reap a lot of benefit for me. And then last, we can move to a world where I have my own privacy policies where I have full visibility of information and data and I have the ability to challenge decisions made based on that information. So I don't care about ownership. I want control and I want enforcement. Telemedicine's a great example of that. If we were to be able to unlock these new architectures and new ecosystems, I believe we have an explosion in telemedicine in the way data is short and all these categories you see on the left, all that could be stored securely and shared. Now, what's in it for business? Reduce liability by not having to handle data, lower compliance costs and decreased security threats. This can lead to faster innovation, faster development to second or third order effects and use cases that we can't even determine today. Data is really, really important in the future of digital business. This can't be understated. Labeled, clean data sets are not easily available. And once you have that, that's just to start you need data constantly to improve your forecasting. This can solve that problem, which is an enormous problem for business. It can reduce their fraud, lower their compliance costs and reduce friction for users. At the same time, there's a big problem with machine learning and business right now. It's a black box. If you can't explain why a decision was made, you're on the hook for that. And if something goes wrong, you have a regulatory headache. So this can unlock hundreds of billions of dollars in value in new technologies, DNA, telemedicine, finance and much more. Any technology that requires sufficient, rich, sensitive personal data can now be used and unlocked. So this is what I'm proposing here. And this is what I've tried to lay out in the last 40 minutes. A new way of handling personal information that shifts the industry from extraction to co-production from one way exchange to two way exchange. And in the process, hopefully, and it's my belief that we can unlock an enormous value for everybody involved. So I started running a little late there. Thank you very much. And I'm happy to take some questions. Tarun, this is Serving Bladowski. This was an absolutely wonderful presentation. Thank you. I really want to thank you on behalf of all of us for such a wonderful presentation. Now, let me ask you a question or two. And then we have two questions that the attendees have submitted. So the World Economic Forum has done some really good work in this area, Jesse McWaters. I don't know if you know him. Yes, great work. And what I liked a lot about their work is they recommended the notion of having identity service providers. Yes. Who would put together an ecosystem of companies that already have your data, you know, like banks and telcos, whatever. And they made the point that an identity service provider by definition almost will be regulated, which I think leaves out the technology companies which, you know, Silicon Valley where you are, the last thing they want is to have any of their things regulated, but financial institution and credit card companies are already regulated. So do you see that as the right approach for bringing some order to the management of personal data, the notion of a trusted identity service providers? It's certainly a step in the right direction. It certainly can be helpful. You know, there was a better, I'm forgetting the better idea in America that that group that came together. I know you've had them on recently and they're exploring things like that too. It makes a lot of sense. You know, you look at a bank, you look at a telco and they have a lot of data, a lot of personal information on us. My colleague Anish Mohamed likes to talk about resolution of data. Telco data is very, very high resolution in the sense that if I'm interacting with my phone and I'm pinging a cell phone tower, that's very, very accurate up-to-date information about me. So there's certainly something there. I think they're definitely onto something. Now the challenge is cultural. I mean, how do you get all of those companies to work together? That's a really hard thing to do. Perhaps if you're starting from scratch in Latin America or Asia or something, it makes more sense. Doing it in a country like the United States is very, very hard. Witness how much difficult thing we've had getting the telcos to work together to solve things like robocalls or spam, et cetera. So good idea, very, very hard in practice. Tarun, I spent some time consulting with MasterCard, which was very interested in the concept. And the number one issue for MasterCard was managing liability, that even if you do an incredible job, there will still be a probability that you made a mistake. And if you have unlimited liability, if you make a mistake, then most companies wouldn't want to become identity service providers. So somehow, government policy has to get involved in the notions of limited liability as they do for many other things, correct? Absolutely. And I think this is why you can't use Facebook to log into your bank, because the risk mismatch is just so off. Yeah, my view is, with all due respect to technology companies in Silicon Valley, they are absolutely the wrong people to trust with your data. They are, you know, and I don't mean they are bad people, just that's not their culture, correct? In respect, you know, there's two points. There's the data culture and the regulation culture. Let's take those apart. The data culture, there's no one better than tech companies to do that. You know, you talk about what a company like Google or Amazon or Apple is able to do with data and the insights and the services they're able to get, second to none in that sense. Regulation, you're absolutely right, in that they avoid regulated industries. The exception here may be Apple, in that they have a larger appetite for more serious tech to see them stepping into health with a watch, et cetera. They're willing to wait seven years to get regulatory approval. I absolutely agree with you. And to the point you made about governments, I think that's critical. It's really, really hard to do these things without some sort of government body setting legal standards, certifications, service level agreements, this sort of thing. So to Jesse's point, public-private partnership in this way of bringing government to some respect and banks and others and telcos, et cetera, makes a lot of sense, but it's a big effort. Yeah, and by the way, you mentioned blockchain. The one place where blockchain can help a lot in all these things is to have a non-revocable history of who had access to what information about you. So that if a year later, something happened, there is a record that you can go explore and find out what, and when I say a record, I mean a trusted record because it's non-revocable. I agree, but I pushed back there on the use case, which I think the threat model is kind of off there, and I know you're not saying it in this way. A lot of people talk about this as being divorced from government, that... No, no, no, no, no, government has to get involved. Absolutely, absolutely. No, no, no. As a backup for paper documents, sure, but there's, I see other ways to accomplish this as well too. But I don't wanna get in the blockchain argument with you. No, no, we can do that. We can do that another time, absolutely. So now Sharid Hussein asked the question, in your presentation, you mentioned the use of crypto to make this new data foundation, but the corporations that are already vested in the old infrastructure are reluctant to move. How do you see this transformation occurring? It's gonna be very, very difficult to move, especially in the... You mentioned a great point about data existing in all the infrastructure's old standards and such. This sort of thing makes a lot more sense going forward for future data sets, for future digitalization, things like that. Now dragging the past into these systems is gonna be a whole industry. I suspect there's gonna be many, many startups and companies working on this very problem because the enterprise value is so high, but you're absolutely right, it's a huge challenge. Now, we have a question from Anand Rao. First of all, Anand says, Tarun, great webinar. How to make the companies feel responsible to use their own data for making effective decisions using machine learning algorithms? For example, intent to buy insurance and willingness to pay premium by the insured. So his question is, how can you make sure that the companies will be responsible in using their own data for making effective decisions? That's really the key to the question. Got you. That's a bit of a difficult question to answer because it's something that we need to figure out still in that way. Now, how to make companies act responsibly with data from two sides? First, we need some sort of legal recourse and protections from the user point of view. I think what he's asking about is from the business point of view there. So how do businesses derive value from their own data sets and such? That's gonna be one of the challenges in the defining questions of the next few years in this digitalization process. So I don't know how to quite answer his question, but I think he's absolutely right about the importance of the question. Yeah, and Tarun, let me just make a comment and then I'll pass it on to Ira for any last minute questions that he might have. Tarun, you know, I think Adam Smith viewed free market capitalism as absolutely being dependent on trust. That if you don't trust that your baker isn't going to sell you bread that will poison you, then you won't do business with the baker. And if you don't trust that your bank or pick your favorite company isn't going to respect you and your data, then you'll stop doing business with them. I know we're not there yet, but we are in the very early stages and then you have regulation. So I think the combination of classic trust and then regulation maybe, I mean, you may say, well, Irving, that's not good enough. We want machine learning. We want bots, we want robots. I don't believe that. I think it's going to be much more classic things that have worked over the last few hundred years that are going to take us into the future here. Is that a reasonable way to think about it? Yeah, yeah, I agree with many of the things you said there, absolutely. So one last question before Ira, we just got from Mary Mepesijo. Very great work again. By the way, everybody, we keep getting comments in our chat here about how wonderful your presentation has been. And Mary Mepes says, currently working on a data-driven project, what is the best hosting platform in your experience? I'm not sure what hosting quite means there, but I would have to defer that question to my technical partner, Anish Mohamed, who's not on the call here. So I'll have to get back to you on that. Okay, and Shahid Hussein just said, Tarun, wonderful presentation. Thank you, Shahid. Ira, on to you. Great, I'll ask one last question. And then we'll wrap up. I was struck by a phrase in the presentation, data-rich nations, which of course, reminds us of oil-rich nations. And I think India and Adha are one of the goals was to monetize the data that they collected. And I wonder if you can talk a little bit about where you see that going and how nations monetize it. And if it isn't another issue of trust and use of our data by just a larger entity, our governments. Yeah, no, certainly. And the challenge, I would kind of frame it as bootstrapping reputation, right? You have a country of X million people, however, you have institutions that interact with you, people that know them, you have people that know them in the village level. So they're not like aliens that just got dropped out of the sky. They have some sorts of local reputation systems and all. So how do you digitize that? How do you balance that all? How do you bring that together with telcos, with hospitals, with banks, these respected institutions? And how do you stitch together that information? That's a very, very difficult challenge. It's very unique to the nation in which it comes from in that sense. So let's take the example of India. India is such a large country, such a fragmented country that you almost need some sort of government push to get something done in that way. Now, what's interesting about India is just by creating the identifiers. Every person corresponds to unique 12-digit number. Whether that's good or not, let's put that aside for a moment there. The fact that you can start indexing records and start bringing together multiple sources of information, that's really how they went about targeting it. So they said that we have all this disparate information, let's turn people into numbers and bring their data across to that one number. So that was their way of answering the bootstrapping challenge. I suspect many smaller nations, many less chaotic nations, it may look something more like what Jesse was talking about with banks and governments and major institutions involved with sort of setting the rules and then private industry taking the mantle there forward. But I think you're gonna see a lot of mixes of different public private flavors in that way. But the idea of data rich nations will be apparent and common everywhere, I believe as countries see that as a path to prosperity and inclusion in the modern world. Great, thank you. I'll add my compliments to a wonderful webinar as well. This was really informative and I think it is a great ending for the series. So thank you. Thank you Irving for moderating and our audience, thank you for participating. And if you like this webinar, please look for Tarun's book, upcoming book, Identified the Digital Transformation of Who We Are and Tarun, when will that be available? Later this year, I've been working on this book for almost seven years because I've been looking at the subject really closely and I keep changing my mind about where it's headed and how it's working. So, Tarun, I think we've done what is done, but later this year, we look forward to it. Do you have the first chapter or executive summary already written? I do, I have a lot already written. That's not the issue. The problem is what's gonna make that final draft and cut, but I'm happy to share that with you and get some of your thoughts. I would love to see the executive summary because this is so fascinating. Thank you very much for having me on this webinar today and allowing me to end this wonderful series you've done. It's been an honor. Well, thank you very much and thank you everyone. And the next Expert Connect, which will be on a different topic, it will be about authentic inclusion and it's really about diversity inclusion and how you can leverage it as a manager to grow your company, your business, your marketplace. And that will be conducted on April 14th. So we hope to see you then. Thank you everyone. Bye-bye.