Husain. Amir explored Artificial Intelligence for many uncommon angles. Part reflection on the existential questions. From military and health care and so on as well as draw narrow and narrow. Hes the founder and ceo of spark cognition. Awardwinning company which provides ai powered from cybersecurity and beyond. Hes also the Founding Member of ibms advisory, amir presented by south by southwest as well as numerous conferences and work appeared in many publications including the new york times, wired and its the first tv. Thank you book tv for broadcasting the event. Feel free to step up to the microphone to your left over here if you a question in mind. Without further due welcome me in joining me amir husain. [applause] thank you very much for that generous introduction and also for your kindness in hosting me at this lovely bookstore and i came in here and was really enjoying the ambiance and its a wonderful place to be. What i will start by doing is reading a passage from the book and then perhaps we can start to explore some of the themes that the book covers. The book goes through the sections by asking some of the existential questions, the ai, what that means for us and then we talk about some of the fears around the ai, two of them that ai might kill us, another one that if it doesnt kill us, it will take our jobs and will lead to mass unemployment and instability. We talk about these things and we try to quantify whether these happen will only happen with a certain level with Artificial Intelligence, with agi or otherwise, and is there something to, you know, pushing the band, is there value in pushing the band. These sorts of discussions an the book really separates that out to multiple to what we call the hyperwar, application to ai in the battlefield, health care, the future of spaces, architecture where intelligence is within the buildings and also mind hacking which is a ai powered campaign thats used to transform and shape thinking and will in a society. For example, potentially to hijack an election and a lot thats being talked about with the last election and we will find out here shortly hopefully how much of a roll some technologies played. Broad impact across all the different areas. So i will start perhaps with a reading, we will get into the few of the chapters of the book, beyond the book what i want to focus on are some other slides and ideas that build on whats in the book, the book you can read but i wanted to take our time today to bring a little bit extra to have some ideas that perhaps enrich or expand or otherwise elaborate on whats in the book and then we will take some time for questions. Okay. So for those of you who do have a book, im going to read just five minute worth of text here from a section thats called decoupling work and purpose which is on page 159. Decoupling work and purpose, what differentiates humans from apes. In his brook sapians, historian argue that is one of the reasons we are singular indifferent is because we can tell collective lies. Other apes couldnt do this. Believing in these collective allowed us to create forms of mass cooperation organized religions, tribal affiliations and trade. That became larger than what any other animal or organism could sustained. The combined power of cooperation through fictions, provided a means of us training and perpetuating our interests and form of life and it made us dominant over individual organisms that might have had more power otherwise. So what is the essence of this humanity, as we discussed in part one, our current debates over the future of Artificial Intelligence tend to get stuck with either the loss of our jobs or a fair for all mortality. Today, our sense of identity is so tied up in our ability to produce economic output that we stake all ourselves by the last names of our productivity. Goldsmith, farmer, and miller, but these identities are not fundamentally human, they evolved over time, when homosapins appeared as see cheese almost 200 years ago we appeared and over time evolved into larger and larger groups, bonded together through religion and afill combraicions until we created an organized macro organism the human race. When we didnt have any other mek niced devices to perform labor, we enlisted the force of our own people, we organized way that is we now describe as subhuman. The valued not exist in any one individual or another pushing the block, it was contained in the organizational process that transform people into cogs in the machine. Human kinds created pyramids, tim ls, city states and ultimately entire empires n. The modern area, the age of capitalism, the systematic structure is no different. In the same work of capitalism, most humans provide specific and repeatable tasks, these culminate in one global macro process in which the vast majority of humans are cogs. Todays fiction, the prevailing cultural belief system of global capitalism exhorts us to take pride in this work, whether its to wake up at 5 00 a. M. And tend the fields or work at office at 9 00 a. M. And pull spreadsheet laboratory top. Our faith in the fiction has gotten the better of us. Modern society is now contending with the same mythology as capital, as system it continues to progress in a process so that the numbers the top, the top 1 become smaller and smaller until it is the top. 1 and then the top. 01 . In 2016, oxford reported that the worlds 62 richest billionaires had much wealth as 3. 6 billion people or the bottom 50 of the worlds population. In 2017 that number had dropped to the worlds eight richest billionaires. Fewer than one dozen people have more wealth than half the worlds poorest population in total. The same report assessed that the annual income of the poorest had increased by less than a single cent every year in the last quarter century. So we see different cultures attempting to adjust their own storytelling and response in the global system. Its currently experimenting with universal basic income and switzerland is in the midst of considering it. Like Everything Else in culture, political ideas, movements, food choices, the midst that our worth is tie today our productivity is a fluid one. In the economic context and this too will change as the planets population make such notions completely and sustainable. All of these ideas are in accordance with times with which we live and the what we tell ourselves often that our worth comes from ability to create value is no different. Whether we are farmers, marketing directors, Truck Drivers or commodities traders, in the near or far future, our work will be completedly some form of Artificial Intelligence. For our purposes here, i invite all of us to use cooperative skills to create a new fiction together. Imagine decoupling existence from the notions of more conventional employment. In the real world, involves, politicians, leaders to be successfully achieved, but as a part excerpt imagine our social system has embraced the decoupling. This allows us to move beyond feelings of alarm and fear that arise with the increasing powers of Artificial Intelligence that triggers of amyydala. Where would we live. I do not wish to den gait the realworld concerns regarding the rise of ai in our world, but i contend that this is the least interesting place for our discussion to end. Since the origin of our species human values, troops and traits have all changed. Theres no such thing as a fixed state human being. There is no such thing as a fixed state human being. 6 million years ago when our ancestors first roamed the planet we were not like what we are today and only 10,000 years from now, we would not maintain our present state, our humanity is on an evolution, its all essential to our being, human values, fundamental traits are in a permanent flux, just as we evolved into something different, we will evolve into something different, something unrecognizeddable. We must accept this as a fact of our existence and from this acceptance, then we can identify our greatest purpose. The start of many sessions have a different tone. This one is more philosophical and ends with the question of let us take for granted that machines will perform the labor as the economic laborers that we claim today and feel so proud of and even associate with our identity. Does that capability, the capability to do these labors in a better way, does that make us less human . Highquality of execution that is we call labor, was that really what defined . Of course, for me the answer is no. The book starts to explore what is fundamentally human, for example, we get into things like people say, look, this was very humane behavior. What does that mean . What that means that there was an element of charity in this behavior. Element of love in the behavior. Two participants in relational exchange where one was given from one to another, act of charity. We find that if you start to think about things in a purely philosophical way, the exchange, the idea of that exchange exists even if the people dont exist. That exchange as pattern can be seen in many other places. What is fundamentally human is a very difficult question and its something that we will discover, of course, but one thing that makes human beings very unique in that they are the only form of creation is they are able to perceive the unlimited universe of all possible ideas and in that perception there is value, however, our society is structured in a way that doesnt allow that value to be recognized in any tangible terms to give credit to help in the daytoday needs of an individual that is surfing and uncovering from that ideological landscape. Questions are some of the questions that i dont want to get into any further, these are the types of things that we talk about the book but i explain what genetic al go rhythms are and what supervised learning and what unsupervised learning are and what latest state of the art in Many Industries and autonomous weapons and health care advancement. Any questions or any thought that is anybody want to bring up . Okay. So this is sort of the bonus material and obviously, you know, my very strong view that a new form of intelligence is coming, can i tell you why i think this is a new form of intelligence, why this is fundamentally different from how we think and i will explain that to you in detail but where we are now is close enough to where the question doesnt need to be asked, hey, when can you build data from star trek, the general purpose intelligence that can go solve all types of problems, these ai systems with capabilities in areas that are meaningful, the most obvious example is driving a car but maintaining aware house, flying a fighter plane and radar to more accurately determine where the enemy aircraft are, are we able to identify packages that go into the hold of the plane or hold of a large truck accurately than ten people running around trying to find the packages. There are tasks that the the systems that the system can begin to automate in very viable and component ways. Those niche areas represent likelihood for human beings. Its not a question of when we will get modern data, its a question when we will get to 25 or 30 or 40 unemployment. The reason i want to raise the question is whenever the question is generally raised in the context of ai, you suddenly are slapped down with some sort of a random latitude that dont worry, technology always progresses and, of course, in the past also it progressed and at that time, you know, we had the Industrial Revolution and so other jobs came up and theyll be other jobs in the future that you dont even know about, maybe the way that i look at it there are only two meaningful things that the human race has done or attempted to do so far in the history of the human race. One is the replication of physical muscle in the late 1600s with the steam engine where we were able to create a muscle that could move things that no animal or naturally occurring muscle could move. We build trains, network of trains, we built cars and we built steam boats and warships powered by all of this and now we have come to the cusp of a period of time where we have a pretty good chance of being able to replicate the mental muscle and if you think about a human being, theres muscle and then theres mind. With these two things replicated, its very, very difficult to argue then that there will be jobs that will be of sufficient quantity that will neither require better muscle nor require better mind. So what does that mean . What that means is that the ai debate is almost absent of policy and this is where i want to get to, so what qualifies me to talk about this . Why did i write the book, i have been passionate about the space for a long time but what qualifies me to talk about these things is im the founder of spot cognition, one to have Fastest Growing companies in austin and the u. S. , Computer Science which was named the number one Computer Science department by u. S. World and also i serve on a think tank in dc as a member of the ai committee. So i bring the three elements as i do business every day, i work with the largest customers in the world from boeing to raytheon to look heed lockheed and all of the Significant Companies on a daily basis. Im also involved with moving the science of ai forward and i care deeply about the implications that all of this work has in the area of policy. I go around meeting with the nato leadership, two generals of nato explaining some of the concepts which will need to be integrated and looks like they will be in the nato strategy going forward. Ive spent a lot of time at the dod in trying to create this impetus, really, to think about ai in a very different way, not just as yet another technology and i think thats working, so policy, science, and the practical element of the business all coming together, thats what ive been doing and i feel that thats a good combination. So just very quickly, many of you may be wondering, we have been saying machines think, what does that even mean, how do machines think . Machines can think in various different ways and the slide is not designed to explain to you all the various ways in which machines can think but i wanted to show you something thats pretty simplistic that one can follow along with in graphical terms. One way that machines can think is that given a very simple set of rules, they can apply those rules to create large graphs and the graphs represent all of the state that is could exist in that world that the alga rhythm is modeling. Lets take tic tac toe and in the world of tic tac toe you can have a machine generate possible states and a machine can do that very quickly and start, you can make a move and at that point, the machine already knows that one move that youve made where does t fall in the tree and is there a connection between there and a state in which the machine wins and if so, the next move is the logical step for the machine to take. This comes from a different kind of thinking, it can recomp out the world and the rest is just search. It already knows what of the 29 parts it has options to go down. Itll go down that path. The tic tac toe game is not very useful. Doesnt need to be hold much but its not very, you know, broad. Reinforcement learning has been able to play most ataric games and not just pac man and in most cases the ai just with no competition. The way its done that in packman theres additional choices and options, where exactly is mrs. Pac man, how many gold nuggets are left, where the ennis coming from, where on and so on, a huge number of cases which are not as easily modellable as tic tac toe. What that does is so im going to start knowing nothing. Im only going to look at one factor which is how far ive got and in games, im going to use score as a proxy of how far i got. And im going to play this darn thing at machine speed and im going to keep going on and on and on and on and every time i play and fail, i will remember what my last score was, i will take my score, say i got a 100, i played random nonsense moves. I got to a 100. The moves were up, up, less, less, right left, left and died, right . So looks at that and says, okay, well, i started with completely random moves, i might make somewhat less random moves because the value of the very first move ive head was 100. The very first move got me to a hundred, the value of the second move ive head however many points the first move game me minus that and whats left thats the value. What does that tell you, as you come closer and closer to the death the value of the moves close to your death are by definition pretty low. At this point, heck, i dont have much value, let me start trying Different Things and in this way in a selfway running very, very rapidly at machine speed, its able to train itself, it goes through the reinforcement learning cycles to rapidly train itself and this is the kind of methodology using for selfdriving cars, the kind of methodology for the game players, this is the kind of methodology that was used for alga go that defeated the number one player. This is a mechanism thats showing a lot of progress and it gets around the problem of having to provide these algorithms with all the data, right, so they can generate a lot of their own data. We were talking about the crosses. You can see that only three things algorithm knows is that for every success generation, you can only add one symbol at a time. The rule of the game is that in one shot you have two crosses. The winning is when you a line diagonal or horizontal. When you go from one row to other row you to alternate symbols. First you get across and then you get a cross. Those are the moves it needs to know to be the worlds best player. I deliberately came here because i want to pivot to something. Think about it this way, three basic rules and thats it and computation, three basic rules, multiplied by computation, create this large tree, if i was to draw those three bullets inside the graphical outline of a seed, you would see that that seed plus some computation gave you a full developed strategy. Now, that actually turns out to be a very possible concept because it turns out that in the universe, in reality much of what we see works the same way. In fact, a tree of a physical tree is encoded for the most part in a seed and there are processes that then run on the information thats contained on the seed and resources that are extracted from the outside and those processs ultimately create a tree but this happens in mathematics and also in Computer Science also. This is something thats called the game of life, how many of you are familiar with the game of life . In the game of life, there are incredibly simple rules, for example, that if you have two or three neighbors, then you live, if youre a cell which is colored in and you have exactly two or three neighbors, t