YPO London 2017

I was part of the panel at the YPO Conference in London on November. Here’s the audio and the transcript of my talk.


Speaker 1:
You’ll see that you can begin to score. For those micro-casts, and those products that are of interest to you, services of interest to you, you can score where you are today, where AI is today, where that gap is, how fast you think that gap is going to close. Those questions are questions that require lots of data on your end about what you’re actually doing, and then some idea of how fast things are moving. A reasonable approximation in AI is doubling around, capability doubling around 18 months, so you can do the math, and the things that are of considerable importance to you.

Speaker 2:
Other questions? We’ll go here, yes sir. If you want to shout it out, we’ll … Could you get the mic over there?

Speaker 3:
Hello. When I hear all your projections, which will have an impact certainly on all our business, whenever you think about an eight-year-old, you were talking last night, talking about hunger, school, and when I see here all this happening, and really she’s going to a classroom that is basically a forum that has not evolved much in the last 200 years, what would you recommend to this class, how she can fit in?

Speaker 1:
Yeah, I have a set of specific recommendations. If what she’s doing mostly is fact stuffing, and memorization, I would get her out of that school, that’s recommendation one. I think the most important thing’s for children to learn, are critical thinking, creative problem-solving, the ability to frame entirely new questions, the ability to think boldly, and I also think it’s important to develop a good foundation in STEM.

A good foundation in science, technology, engineering, art. That whole area, machine intelligence, that whole area is very important as a foundation for innovation. It’s not like science, and technology don’t matter anymore, you don’t have to study them, literacy, and science, and technology, all those areas, mathematics, really matters, because those are the tools that you use to create the future. I think she is living into the best time in human history potentially, and I would encourage her to be aware of the huge potential that she has available to her, and her ability to be an innovator, and to create the future. She’s got to get away from fact stuffing, and get into a good science and mouth foundation, and creative thinking.

Speaker 4:
A good way of thinking about it, is rather than giving content, get them to learn how to pose the right questions, and that really serves that inquiry.

Speaker 2:
Okay, we’ll take two more questions okay? The one at the back there, yes.

Speaker 5:
The big question is, and you see all these frameworks …

Speaker 2:
Can you hold the mic close to your mouth?

Speaker 5:
From your perspective, when is that becoming a commodity, how quickly is that moving from you have to understand it, and learn it, to you just simply have to apply it.

Speaker 1:
Right, great question.

Speaker 5:
The second question would be the power shift, because when I look at these frameworks, either they come from the West Coast, somewhere in Washington, California, and so on, or increasingly they now come from China, but there’s not a big framework that we know of that comes from Europe.

Speaker 1:
Yeah, so on the first question, I think that it’s clear that we’re getting increasing commoditization of AI capability. I think we’re going to see that over the next five years, simple things that AI scientists do, are going to be available in white box systems that [Morals 00:04:36] can use. They won’t understand the underlying assumptions for those systems, and that actually turns out to be very important.

You can get people using systems, clicking on algorithms, and getting the algorithms to do things, but the problem is that they need to understand what are the weaknesses, and strengths of each algorithm, and what are the assumptions that break according to the classes of data you’re using. Those things still require expertise, so I still think there will be a premium on people who understand the underlying foundations of machine learning, but we’ll see a lot of commodity software in the States.

You asked about frameworks developed in the US, or in China. I do think China is moving very fast to try to develop a leadership position in AI. They sometimes use publications as a metric, the reproducibility slide that I showed you that challenged the reproducibility of computational papers is relevant to this, because they sometimes just crank out papers. I think if you look at creative, new frameworks, really breakthrough frameworks, China hasn’t delivered most of those yet.

We may see that, I anticipate seeing more and more of that in the future. I do think that the European community, and the UK in particular has actually had a leadership role in machine intelligence. DeepMind, which is the powerhouse group at Alphabet that developed AlphaGo, and the Atari game player, was a London-based organization for a long time. You can be proud of them, there still is a DeepMind group in London that works with the team in Mountain View.

I don’t agree that Europe hasn’t contributed to the machine learning framework software, I think they’ve contributed a lot. If you look at the literature, they are a powerhouse group, and DeepMind is not the only one.

Speaker 2:
All right, Neil Jacobson, thank you very much.

Speaker 1:
Thank you.

Speaker 2:
We’re going to move on to our next speaker, then after we’re going to take a coffee break, so we’ll have artificial intelligence for you in caffeine once we get to that point. With great pleasure let me introduce our next speaker, David Orban, who has been with us since the beginning has an admirable faculty, and is one of the core advisers in Europe on how do we think about expanding into Europe, and our representation here. He’s from the area, but lives in Italy, he’s a global expert in the Internet of Things, and he’s the head of Network Society Ventures, if I’ve got that, I’m sure he’ll describe that, with great pleasure, David Orban.

David Orban:
Making sense of the themes, the technologies, the changes that we are presenting to you is definitely not easy. It’s our objective to give you not only information, but really a toolkit for reading what is happening around you. Both in terms of exponential technologies that are disrupting current businesses, but also in how the world is changing, as a consequence, in its social, economic organization.

When I talk to all the audiences like you, I find great pleasure in continuing the conversations after my lecture. Feel free to get in touch on LinkedIn, or Twitter, and let’s continue the conversation. Because, what we are seeing in these trends gone soft. Sardine and Neil had an opportunity to remark on the fact that as we look at the progression from mainframes to main computers, personal computers, smart phones, and what I am going to describe to you today, the world of sensors in a network, the Internet of Things, we are looking at phenomenon that start humbling.

It is easy to ignore them, it is easy to listen to the naysayers that what is happening is not fundamental, it is not really important. The psychological point of the one percent, where we typically represent the exponential crossing over the linear projections, is a very good symbolic point, because after that, it becomes easier to see how disruptive, and important those can become.

The difficulty stems also from the fact that obviously while these changes are accumulating, it is not happening in a very clean, and clearly identified way. Everything happens in a very noisy environment, where the error bars on measuring the data, on which you want to base your decisions, maybe even more important than the data points themselves, and the signal-to-noise ratio may not work in your favor. That is why it is easy to call those who believe in these trends right from the beginning, very optimistic, or even crazy. They will latch onto something that many other people don’t see, or choose not to believe in.

Another factor that is worth remarking, is that especially ecologically inclined, or trained in logistical sciences, people will say, “Well, you are naïve, you are referring to trends that are necessarily going to stop, and peter out, because in a finite world, nothing can continue for ever.” However, in this chart designed by Ray Kurzweil, one of the founders of Singularity University, you can see that actually the generations of technologies that each follow one another, design the exponential, and that is what we are talking about, not this more modest, smaller representation that you see in the corner of the image.

The superstructure that these trends create in the world, now are at the basis of our globally interconnected civilization that spread the entire planet. Whether we talking about supply chains, or scientific communication, or the interactions of geopolitical decisions with everything around us, we are seeing the outcome of a virtual circle of how the scientific method of analyzing, and understanding the world, that turns knowledge into engineering, products and services, that consumers, and vendors spread around the world, is really benefiting everybody.

The electronic brains of the 50s were hulking machines that needed to be pampered, and a real priesthood of people who would have the specialized knowledge to understand how to work with them. The integrated circuits that followed rapidly generation after generation, are now at a point where we are reaching atomic limits of how small they can get. However, already, we have new solutions to keep the self-fulfilling prophecy of more small going. The next generation computers will be based on exploiting, rather than trying to hide, and overcome the quantum phenomena that at atomic scales we are seeing very evidently in the circuits.

On the software side, very similarly. At the beginning, the computers knew nothing about the world. Every night when you turned them off, they would forget everything that you told them through the punch cards fed very carefully, and then the day after, you would have to start over again. They became more interactive, and you could type in these interactive teletype machines, even though still the language that they used was very specialized, and unless you had a passion, and you had the time, and you invested the time that you needed in order to learn, and become proficient in those languages, really, there was very little that you could do with the computers.

They started to learn that actually we like the metaphors and the analogies that we use in representing information and knowledge, the documents, the folders, the desktop metaphor for organizing work, assigning tasks. That we have an aesthetic sense, we like color, and we differentiate between beautiful, or ugly design. About 10 years ago, computers broke free of the geometric constraints of our hands.

The keyboards were the ultimate limit of the previous generation, but by acquiring the capacity to interpret touch, computers were able to become tablets, and smart phones, of all kinds of sizes. Furthermore, starting to view the world, and starting to be able to interpret what they saw, they could start interpreting our motions. They could start by hearing about the world, they were able to start interpreting our words.

The conversational interfaces that are now being developed, the operating systems of computers that disappear into the environment, where they see us, but we don’t necessarily see them, where we have a dialogue with them in a very natural language without having to learn the vernacular of geeks and programmers who enjoy learning exotic languages, programming languages, lead to the point where already Google states that in the United States, about 40% of the queries on mobile phones happen in a spoken form, in a conversation with our computers.

The next-generation interfaces are already being experimented with, are behind the corner. Where this interaction, interfacing, some would term it a merger of machine, and human, is becoming even more intimate, with computers being able to understand our thoughts, and in turn, us being able to work together with them to model our world, and to understand our challenges using our thoughts.

In terms of how the world took advantage of the information revolution that started not in the 20th century, but really as we were able 10,000 years ago, or maybe a bit more to start to accumulate, and to spread knowledge in our various groups, and communities, and then societies as we start to build them, was mostly centralized, and hierarchical. These structures served us very well.

What we are seeing today, is the appearance of a new type of organization, because in globally connected communication systems, whether human-based, or machine-based, the physical proximity, the need of being together, of having an office building where you go to work, rather than being able to extend the radius of search for talent, in order to assemble, that all the things that is going to be able to achieve the breakthrough you need, is a very novel way of thinking about problem solving.

Here, the ever decreasing price of computation, and communication, is going to make a big difference. The possibility of Apping these functions of computation, and communication, to every possible object, is what is going to design the Internet of Things, and the Internet of Everything around us. We are seeing it in energy, where the unionization of energy sources, and energy uses, creates new kinds of communication networks, and challenges.

Energy trading, where we have the production of energy, and the storage of energy among consumers, that peer-to-peer, want to be able to maximize their desired outcomes, rather than relying on a signalized utility. The digitization of manufacturing, where as, we heard before, complexity is free, the ability to create a very complex object doesn’t depend on the capital invested in the manufacturing capacity, it depends on the talent, and the creativity of the people who design those objects to start with, and then it can rapidly scale all over the planet through new kinds of 3-D printing, and digital manufacturing plants that are being set up.

We are turning food into Digital Products, whether it is hydroponics, that is capable of radically reducing water and soil consumption, radically increasing the variety, and the quality of the type of food that we consume, or synthetic meat that is produced without animal suffering, and overcomes the very Western centric objection of Indian and Chinese empowerment and emancipation. “Oh no, we cannot afford them to become rich, they will start to eat meat, they just should keep eating rice.” Evidently enormously racist, and biased, we are also seeing traditional agriculture becoming an information-based industry, where satellite systems communicating with your body, combines, and other machinery roaming the fields.

Precision agriculture is delivering big increases in food production at lower, and lower costs, and at lower, and lower use of the human labor in that area as well. Personalized health, we are able, and we are made responsible of maintaining our state of health, rather than intervening after the fact. The capacity of learning, and teaching anything that we can understand, where the syndrome of maybe liking a Facebook post that a friend of yours shared, having only read the title of the article, and not having read the article itself, rather than being something that you are chided for, is actually an evolutionary adaptation, because we are able to grow very broad in our understanding of the phenomena around us.

We realize that going deep, like a three-year PhD project worth of understanding of a very specific field, may not gain the same type of return on investment that we need. It is easy to point the finger to finance, and blame it for the 2008 crisis, or the banks that are not delivering on the quantity leasing of the European Central Bank, or whatever other stimulus they would need to help the economy, but finance is also a technology, and just as the era of gold-based, and gold-backed currencies ended after several thousand years, definitively in 1973, the era of bank notes, and centralized currencies is now ending.

You can ask yourself whether the future robotic societies, as they interact, and negotiate for resource allocation, and to fulfill their own objectives, whether they will be using the 70-year-old credit card system, or whatever they will be using, maybe bank notes that they will exchange on paper. Obviously, the answer is neither, there will be new systems that will allow us to measure value in these novel platforms, and Blockchain, and Bitcoin that we will be hearing about today, is going to be part of those new systems that we need around how do you measure the economy.

The trust networks, and the relationships that are the very fabric of our society, of how we create communities, have been based forever on intervening after the fact, on imposing based on rules that in turn was based on violence, what was the social contract. I often say that Airbnb don’t compete with the hospitality industry. Uber don’t compete with the transportation industry. Of course, they do both of those things, but really what they do, is compete with the police.

They are able to design, and implement a new type of crossnetwork, where completely different rules are in place for resolving conflicts at a degree of reliability that is radically superior than what we had before. Policymaking is also a technology that is being rapidly digitized. Rather than being happy to leave Winston Churchill’s unresolved provocation of how democracy is the worst kind of government except every other kind, we are now taking up the challenge, not only starting to design novel systems of decision-making, not only basing policy on objective data that now can be garnered.

For example, Waze, the App and platform that allows people to drive around knowing quite reliably when they will get to their destination, even that Waze aggregates data from millions and billions of sensors, we are, our phones are those sensors. Waze has a system of sharing that information with policymakers, cities, that as a consequence can enact decisions based not only on the traditional, political compromise, but on how are the data.

The next challenge in policymaking is going to be upping the ante, and understanding how to upgrade policies that have been debated, enacted, but whose consequences have been measured in front of the rapidly changing technologies that are at the basis of new decisions that need to be made. Self driving cars, and the policy frameworks around self driving cars are a good example, where in the past several years, the regulators have been able to be fairly active, proactive, and dynamic, rather than lay down rules that were static for too many years, they were able to have a conversation, a dialogue with the industry, and then update year after year the regulations, so that today we are at the point where in California, in Arizona, and in other States in the US, actually in more than 40 states now, there are rules that provide clarity around how to test, and then how to drive, how to start selling, or providing paid services for self driving cars, today, and in the near future.

If you read the mainstream press, very often there is a game that is being played, a new technology comes around, it being hyped, and over hyped, and then a few new cycles later, you will read the articles about how it didn’t really deliver on the excessive expectations that the press itself created by writing the first series of articles. It is not easy to understand what is real, and what is not.

When you see the context in a broader sense of the series of changes in your world, you realize that the changes are actually unstoppable. When computers decouple their operations from us, and they start to not need our pampering, and our help for understanding the world, then their physical dimensions become smaller and smaller, and they still are able to interact when the time is right with us at an ever increasing level of functionality. That is what, from a technological point of view, generating the Internet of Things, which is nothing else but a network of networks interoperable, and interconnected of computing nodes.

Nodes that can calculate, that can store, memorize information, that can achieve through input channels, and output channels, sensors, and actuators, the desired value for us, and for the systems that they design. I have been talking to Cisco, and other companies for the past 10 plus years about how these systems will develop, and need to develop. I remember 10 years ago, I would tell to audiences like you, “Yeah, absolutely, chairs will be connected to the Internet, doors will be connected to the Internet.” People would tell me, “No, you are crazy, there is no reason to do so, why would they?”

Sometimes I would attempt an answer, other times I would say, “Well, I actually don’t know, I just know that the incremental cost of providing objects with these capabilities is trending to zero, and the risk of putting on the market a next-generation product that doesn’t have those capabilities, is going to become unbearable, regardless of the product category that you are in.”

Today, many of you traveled from far enough so that you decided to stay at a hotel for the previous night, and unless you stayed at a very quaint boutique hotel, that had metal keys big enough so that you wouldn’t put them in your pocket, but leave at the reception, you actually had a plastic card that activated a sensor on the door of your hotel, and the door communicated with the network to decide whether to open the door, and whether to let you in, or let you out.

That is the fulfilling of one of these predictions, just as Keurig, I don’t know if it’s popular in the UK, it is the leading coffee machine maker of the capsule type in the US. Keurig released Internet connected coffee machines recently as well. Now, as we talk about the capabilities of these nodes, of the networks of networks in the Internet of Things, we have to realize that there’s a long way to go.

There’s a long way to go until we get to the point where the systems can deliver to the level of those that had billions of years of evolution of designing them. However, we don’t have to respect nature to an excessive degree. Nature finds local maximum, a wonderful evolutionary point, and then it stops trying. We, on the other hand, are at a higher level of abstraction, we can see that that solution actually is quite nice, but there may be others that we can find, and we keep searching for them.

For those of you who are familiar with the terminology of the Internet, may have heard of the Internet protocol that had many versions, IPv4 was the one that created a few years ago quite a crisis, because the address space, the number of objects that could be uniquely identified on the Internet through that version of the protocol, was merely a billion in terms of an order of magnitude.

Actually, I was here in the UK at the launch of IPv6, which was the next generation network, together with WIND SURF, one of the fathers of the Internet, and at the time I made the calculation of the order of the magnitude of the unique nodes in this network of networks that a new protocol could support. It turns out, that that’s a lot. 10 to the 38th power is a billion, billion, billion, billion, billion nodes just to give you an idea how many.

If we assign a unique Internet address to each of the cells of the human body, we could have a billion, quadrillion people completely described this way. There will be plenty of space for growing unique innovative solutions in the future, not only achieve the level of understanding of our world that we have today, but go radically beyond with the help of more and more intelligent machines.

However, the behavior of these machines needs to be very different than today. When the phone that I’m carrying with me, my Exocortex is more and more, it is something that helps me be a better business person, a better investor to cope with the needs of today’s complex society, regardless as some would say, what my wife says about it. The chore of very simply keeping the phone charged, is something that makes me realize how enslaved I am to an object that is unable to care for itself.

As you surround ourselves with more and more electronic devices, I feel like a juggler, especially when I’m in a country with some exotic type of electric plug, and I have five different kinds of things that I keep charged, or attempt to so all the time. This is of how to power themselves, just a very simple example of how machines that comprise the Internet of Things need to get better at what they do.

Of course, it is just one, but the data that they generate, is of an incredible magnitude itself, a very, very large amount of data. To the point, that managing the amount of data generated by these devices itself becomes not only a challenge, but a science. The image you see is of the large hadron collider, this has been one of the most complex, and most expensive machines humanity ever designed and built.

It has been designed, and built to find elusive traces of very exotic elementary particles, collecting data every day, very, very precious data, €25 billion to build, 25 additional billion euros to operate over its life, and 99% of the data is thrown away by machines deciding that the human shouldn’t even bother seeing them. Then 1% of the data is kept, and the machines sift through that data, and then highlight maybe another one hundredth of it, and call one of the 15,000 physicists that work at the LHC in Switzerland, and say, “Hey, I think you really should look at this.” Then one of those, or a group will win the Nobel Prize that the machine has helped them win.

Robots are in our homes, and they are getting smarter and smarter. Navigating our world, whether the cognitive world of our ideas, our categories, our judgments, our desires is as complex as navigating our physical world. One of the challenges of robots currently being tackled with variable success, is filling in, and emptying the dishwasher. I know that is personally a chore that some of us enjoy as a meditation, a daily meditation, but others definitely do not.

The capacity of these machines, not only to power themselves, which this vacuum cleaner knows how to do, because it remembers where’s the power outlet, and it has the level of introspection necessary, and self-awareness necessary to know not only that it is running down in power, but what is the path needed to go back to its base station where it can recharge itself, and then eventually start to keep cleaning after it achieved the necessary recharge.

When we invented the World Wide Web, we were able to start collecting knowledge based on data, on an unprecedented scale. One of the most beautiful, and unexpected outcomes of this, was the World Wide Web, which, if you … I wanted to say Wikipedia. The outcome of this kind of aggregation of knowledge was Wikipedia, which, if you were told beforehand that the Encyclopedia Britannica would throw in the towel, and say, “Our experts, and our business model cannot keep up with this living dynamic thing,” not only you wouldn’t have believed it, you wouldn’t have believed that it was possible for this continuous creation of something like we are now very familiar with.

The example, some of us love it, others love to hate it, of the second generation of aggregating social information, is of course Facebook, where billions of people are at the point almost that for them, the Internet is Facebook. Now we are at a point where sensors are going to deliver the technology stack that will generate unexpected applications based on the city data around us, based on the movement of people, and the movement of robots that we have seen in previous generations.

This is going to be largely a conversation that happens among machines, it is not going to be a conversation that we take part of on a daily basis. That is why policymaking is so important, because those conversations have consequences, and we have to set the rules that are right, so that machines can agree what to do just among themselves without negatively impacting us.

Just like your thermostat will have a dialogue with your heater, and say, and decide what to do day in, day out, where you can optimize for comfort, or you can optimize for energy-saving within a certain internal, and the machines by themselves will make it happen. Robotic warehouses are now enabling not only hyper fast Internet delivery of whatever E-commerce was about in the previous years, but grocery delivery in larger and larger warehouses that are built for robots, they are not built for people.

For example, they are permanently dark, they are permanently cold, or designing new values, and new infrastructures around. The world of the Internet of Things is very different from ours, whether you believe you have four, or five senses, or you realize you have many more, but still a fairly limited number, the cars that are in the self driving mode, a beautiful metaphor for so many of the things that we are touching upon, see a world that is extremely rich in data, and in decisions, and the opportunity for delivering value through all of them is huge.

These nodes, these robots, these decisions, this data, is becoming democratized very rapidly. A half a million, or a quarter of a million robot is now something that you can buy for $25,000, and it has the capability of being trained by example through using advanced systems of software, and it has an ability to recognize its environment, so it can work together with humans effectively.

If you have been in an Apple Store recently, and you looked at the shelves, you realize all those shelves are apart from the Apple products, selling nodes on the Internet of Things that bringing home, or bringing in your office, you are designing on a daily basis. These things are not only outside, but they are starting to be inside us, in the health applications. They provide incredible value, if you have a state of illness.

You have seen the anecdotes maybe of Amazon Alexa enabling inadvertently orders to be sent to the Internet, at least say the previous versions that were not checked for this, because a television announcer maybe said something, “Alexa, buy me a six pack of beer,” I would have thought, but the Alexa in the houses of thousands of people listening, put in the shopping list the same product.

This is a very benign example of problematic consequences, where for example, as of today, a known attacker or attackers brought down twice over in the middle of winter, a large part of the Ukrainian electric grid that was vulnerable. We read stories about vulnerable remote controlled video scanners that are connected on the Internet. Just a few days ago, a very well done new video came out that I invite you to watch called, slaughter bots, that talks about autonomous Internet connected weapon systems that may be unstoppable once the knowledge of them spreads the world over.

I am one of the signatories of an open letter from this community against autonomous lethal weapons, and for global prohibition for their development, and deployment. We believe that these, these steps are very important in order to establish what is the right level of achieving the promise of the Internet of Things, of distributed, democratic access to data, and technologies.

We heard how important it is for the future of the society to overcome the limitations of our current systems that drive, and fly, without considering the moral implications of their decisions. The enemies are not the smart machines, the enemies are the dumb machines that are together with sometimes, often times dumb people, creating the harm. We can do very important, and necessary steps to overcome that.

Some of us are experimenting radically on this, some of us are asking themselves, “What is happening when humans and machines learn? What will be a society designed by the type of enhancements, both physical, and cognitive that we will be able to see, and what is the shape of society that will come out of it?” It is client/server systems, which some of you may remember, were so brittle, that they couldn’t scale to more than a few dozen, maybe a few hundred nodes.

Today, Google, Facebook, and other systems on the Internet are so powerful, that we have a prime time newsworthy event when one of them becomes available. Tomorrow, the new Internet of Everything is going to deliver systems that are as reliable as the biological replication that in trillions of cells in each of you, for millions of years, has been able to deliver on its promise.

We’re not stopping at Earth, when we’re thinking about the Internet of Everything, we mean it. Already, Planet, a company that was born at the NASA research campus where Singularity University is as well, achieved just very recently its original goal with 2000 satellites in orbit, it is taking an image every day, of every place on earth, and delivering it over the Internet as a service for all kinds of applications that you can take also advantage of.

We are already thinking, what is going to be the Internet? What is going to be the Internet of Everything as our systems go to mine asteroids, as robots are going to swarm intelligently creating their own goals, and their own civilizations in the asteroid belt? Then, of course, having achieved after 13 billion years such an important step of waking up the universe through our own awareness, self-awareness.

Understanding of the gradient of values that implement a nonzero sum game that we call life. We have a universe in front of us, thank you very much.

Speaker 2:
We’re going to take a few minutes for questions, and then we’re going to take our coffee break. Any questions for David, because we’re starting to connect all of these trillions of sensors, and putting them into everything. You heard about some of the applications that will come out of this. We’re essentially turning every single sensor into an intelligent device, and the implication for society are very profound. Any questions? Yes ma’am. There’s a microphone coming right over there to your right.

Speaker 7:
Thank you. I’m going to start because my seat is gone off. I just wanted to ask, in terms of … Perhaps you see the impact of the Internet of Things, and how it’s going to go. How is it going to affect things like national boundaries, and governments, and tax systems, and all that kind of thing?

David Orban:
National states have been extremely successful, for 500 years they grew through the piece of Westphalia, establishing today’s social contract where for example, not having a passport, or not having a citizenship, is extremely difficult for an individual if you want to travel internationally, or if you want to access to services. The new paradigm of energetic autonomy through solar of unfettered global communications, and economic transfers, through Bitcoin, and Blockchain, the capacity of peacefully aggregate in a non-geographical, and nonexclusive manner, is already designing a new system that I call network society, and that is competing with the national state.

There will be conflict, this conflict must not be violent. The nation state in the past has not hesitated slaughtering its citizens when it felt right, and this dynamic is already being to play out. In Greece, it is illegal to install a solar plan, that is not connected to the national grid. The taxes are paid through the electric bill, and a group of citizens can not legally discuss constitutional reform among themselves. It is a trifecta of futile vassalage that has been implemented in the heart of modern democracy.

Speaker 2:
Okay, other questions, yeah.

David Orban:
The question is what are the data privacy implications? Each society, each country, or continent is going to be free to decide how to answer that question. In America, today for example, corporations have basically absolutely unfettered access to every possible data, and even if there are laws and legislation, they are toothless. As demonstrated by all the breaches that did not have as a consequence billion dollar fines, or people going to jail, whether it was Yahoo losing passwords of billions of users, or whether credit from reports from Accufax practically destroying the financial privacy of every US citizen.

In Europe, the conversation is slightly different. More in favor of the individual and his or her rights, however, I think there’s a fundamental misunderstanding. First of all, no, privacy and security are not an alternative. We do need, and can have both, and the second, maybe even more important, is that many societies, or countries, don’t realize that they need privacy even more than any of their individual members.

If you think about it, every minority opinion before becoming a majority reality, needs to be able to take root. In a radically transparent society that imposes with the force of law, the existing regulations cannot adapt. If I love a black woman, and you my friends wanted me to marry her, we would be criminal conspirators in 1965 in the United States. 1966 as well, and in 1967, miraculously that would be perfectly legal. A society that does not respect privacy, becomes rigid, brittle, and it breaks apart. Yes.

Speaker 2:
On that optimistic note, a couple more questions.

David Orban:

Speaker 2:
No, I was just saying that was a nice optimistic comment.

Speaker 8:
… With Google today, there’s probably no more powerful company, especially the capability of nation states to regulate those, how will that evolve, and is that even possible going forward?

David Orban:
There is a very interesting dynamic between the huge amounts of data that corporations have been able to compile, and the nation states, that on one hand look at them if they are monopolies to be regulated, and maybe to be broken up. On the other hand, salivate, and are really eager to put their hands on this drove of data to the point that quite regularly, we learn how the convenient vulnerabilities of the architectures that these corporations put in place are exploited by the nation states for their needs.

A few years ago, it became known that the National Security Agency of the United States attempted successfully to corrupt the standards process for cryptography under the false assumption that it would only benefit them, rather than the bad guys too, and as a consequence, your bank may have contacted you to change the fab for the one-time password generator to switch it out, and I don’t know whether you asked them if they knew why that was, and whether the new cryptographic scheme was maybe more reliable, and the last purposefully corrupt.

Now, I believe that the business model of building larger, and larger haystacks in a search of better needles is broken. The opportunity cost is now negative, Microsoft surprisingly was the first to demonstrate that they realized this when in order to resist the requests they believe illegal from the Department of Justice for the data of one of their users, they decided to radically re-architect, and break apart their cloud offering called Azure. Basically they said, “All right, you want to have that Irish users details, you go and talk to the Europeans,” and now Deutsche Telekom is running on behalf of Microsoft Azure offering in Europe.

Now, if you go from a single cloud to two pieces, that is just the first step in the process. We will hear about Blockchain this afternoon, the radical promise of Blockchain is to have naturally decentralized architectures, and business models where the value generation, and the value flows do not depend on the radical exploitation of data on billions of individuals that become products rather than legitimate beneficiaries.

Speaker 2:
Okay, one last question. Yes.

David Orban:
The question is, do you believe that the increasing computing power, and machine learning can take away responsibility from human decision-making in the future? We can decide what kind of future we want. One of our most important abilities is to model the future, or several alternative futures, and then pick the desirable ones, and make every effort possible to make it real.

When maybe 15 years ago I would think of an occasion where I wanted music, I would compile a playlist by hand. I had my favorite software program, I had a few hundred songs to choose from, and then I would say, “Okay, I want more upbeat, rock, or whatever else.” Today, I have access to millions of songs, and I delegated the emotional programming of my music experience to an artificial intelligence that knows me better than I do. Regularly, Amazon recommends me books that I know are so good that I already have them, but I couldn’t resist, and I hold them in a bookstore for some curious reason, rather than waiting for Amazon to tell me that I should read them too.

I regularly save in a watch later list on YouTube, or a read later list on my browser, articles, and videos that I perfectly know I will never have the time to read, because I realize that AI is going to extract, and synthesize the actionable knowledge that I will need when the time is right. Sometimes this already happens, I use Evernote as my aggregator of information, and Evernote contextually pulls in data sources when I need people telling me that either I’ve already met them, or this article mentions them, or that we were at the same place some years ago.

That doesn’t subtract from my agency, that doesn’t diminish my human potential, it elevates it. Many times we cling to non-human activities. When we invented technological civilization, the human, the average height of humans actually shortened, because we entered an era, lasted 10,000 years, where it wasn’t great to be a farmer, which was everybody’s life.

Today’s dogmatic assumption, which all of you need to relinquish as fast as you can, is that in order to be a dignified human in human society, or to be respected by your family, you need a job. The concept of a job is very pernicious in today’s livelihood, because we allow measuring people on their capacity of generating economic output, and that is why we allow society to label somebody unworthy, because they are unemployed.

We allow society to give them conditional rights to exist. Either you will find a job in three months, or you can go and die in a ditch. In America, it’s three days, it’s not even three months, so when people talk about universal basic income, the natural reaction to that, “Wow, that can’t be. If you work, you earn, if you don’t, you don’t.” The syllogism is difficult to accept.

I prefer, and I propose an alternative, universal basic love. Just as a tree in a forest has value, whether it lives or dies, nature doesn’t understand the consequent waste, and it is all part of a very complex, but very important ecosystem, we need everybody in the human community to face, and step up to the challenges. We don’t even know if 7 billion people are enough, there is an asteroid ready to kill us, whether it’s 1000 years, or 1 million years, it is coming.

Unless, we believe that all of us contribute to realizing our roles, and overcoming our challenges, the asteroid will be right. That is my final remark.

Speaker 2:
Thank you David. Two quick thoughts before we break for coffee. One is a very important point about where we started this morning talking about [inaudible 01:08:39] lead to abundance. If you believe in the thesis that technology delivers abundance, and we have a reasonable amount of definite proof for that, then all of our structures, our top down, hierarchical curved style structures that we use to run the world, the …


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