[applause] good afternoon, everyone. As we settle in i often pick a word for the day. A kind of how i govern myself often times and my frame of mind. But today im going to take an image of the day if you look at your screen, one of our commissioners shared with me this image and i think it sets the tone and stage and underscores the importance of why we are here. This is a chinese book for kindergartners and even if you dont speak chinese, circled r. Two letters, ai. Kindergarten textbook. The senator talked about us getting ready from grade school to graduate school. Now we are talking about kindergarten or even pre k. If we are going to keep ahead and stay number one when it comes to ai so i just want to start with this image because again it really for me underscores the urgency of why this commission was formed and why its so important as we are here today. We have a broa had a broad mandh concrete steps the government should take to build and maintain a Machine Learning work force to address the National Security defense needs of the United States. Over the last eight months this working group assessed the current state of the National SecurityEnterprises Work force, explored the role of the workforce and you should play and examine how the government might recruit, train, educate, manage and to the extent that its necessary retrain the workforce. Now here are the judgments so far and you will affirm this if you have read the reports. National security agencies include extending the familiarity and spreading that use of modern software. It is especially critical because without more wellinformed readers who can go beyond talking points and reshape their organizations, the intelligence communities will fail to compete in the ai era. Now because of all of the military presence here today im going to make this the next point. The department of defense and the Intelligence Community do not have effective ways to identify the do not have effective way to identify ai relevant skills that already exist. [applause] i will make it out alive. Thank you very much. They often fail to capitalize on their technical talents. Existing authorities are adequate are close to adequate more to the point. Government agencies are not fully utilizing to recruit ai talent, often due to riskaverse Human Resource teams and commanders or civilian leaders who do not hold them sufficiently accountable. It is not clear if the same holds true for pay scales. Expanding ai focus fellowship and opportunities can give officials and servicemembers access to cuttingedge technology and bring talent from our Top Ai Companies into federal service. These programs already exist but they need to expand. Government employees pay valuable skills from the private sector, should have an opportunity to use them when they return to Government Service and my the point is military and National Security agencies struggle to compete for top ai talent. The government needs to spend more effort showing that service is an opportunity to solve unique exciting programs and have a positive impact and tried to reduce if it exists any disparagement of its workforce and better use pathways for recent graduates. They are two additional hard questions we will explore with our panelists today. Since the american ai talent pool depends on students and workers our Global Competitiveness hinges on our ability to attract and retain top minds from around the world. If we fail to do so it is unclear how we will continue to compete. Colleges and universities are under strain to keep pace with Student Interest in ai, the number of Computer Science majors is increasing at ten times the rate of that. To continue we asked the chairman of the director the chairman and director of Mckinsey Global institute and i take liberties with names if it allows me to use a lot. The former principal and Deputy Director of National Intelligence and the chair of work for singularity at university. They provide their perspectives on these two questions primarily but not exclusively. How important is our organizational structure to capitalize on emergency talents and how should the National Security enterprise educate leaders and users who do not participate in the Development Process for the resource ai solutions effectively and ethically. Miss gordon. Very and thoughtfully. I am sorry. Organizational construct is important and the second is how to deal with your existing workforce. Let me begin before that and after it. I think of four things we need to have in order to effectively integrate these technologies into overflow, you need the organization has to believe it must. If the organization doesnt believe it must then it will be a technology, left to the innovators but it will not be at scale or at speed. For the Intelligence Community you need to see the world as it is. Understand what your mission is. It isnt about secrecy but knowing a little more sooner and if you look at this world with abundant data and ubiquitous technology, speed of decisionmaking, if you are the Intelligence Community you must find a way to introduce the ability to handle data from speed and volume but the technologies that are emerging. If not, you will fit it into what is left over after your real mission. The second, you need infrastructure. Earlier panels talked about information infrastructure in various stages to build infrastructure and we are trying to figure out the infrastructure because data uses it different than they must. There is that information infrastructure but also the infrastructure that brings it into the mix. People can play with new capabilities. If we dont have infrastructure, you get the curiosity that will get the organization to figure out what it can do and you cant get the mission pool to pair with the technology push. I would opine we can attract anybody. Our mission is so exciting and the kinds of things they find on your mark, they cannot stand not being able to pursue their craft so they go somewhere where they can. You have to have a way to get them around people. But the other thing is you need to think about where the organizational model needs to change, the serial process of pumping capability into a work unit is not the model we need. I think your organizational model changed, organizational construct and new work units that allow integration and transfer ideas at speeds to happen and you need process. You need process revolution because even when a leader wants it and you need infrastructure supporting it and the organizations that demand it, all of them come into processes that were never designed for this moment and our contracting processes are the rules that do that. One thing we need to do is think about who we are putting in charge of designing these processes so the people we have now dont. As far as how you deal with a mixed workforce, you need to provide the opportunity through the things i mentioned for people to want to come and recognize some people will not come, you need to treat them honorably and we do have a demographic problem we have to address. The leadership is the most our most urgent need. If i have meal middle leadership it doesnt understand this is a technical world that wont trust that the idea is coming up can affect the solution and i will end it there. It underscores the culture of what people find when they get there. I appreciate the four points primarily, everything on that. Im glad to be here, thank you for having me. I would like to applaud the report the commission put out. It is spot on. I enjoyed speaking seeing what was in that and the fact that it puts talent at the center and a talented workforce, that is absolutely critical and in particular when you think what was mentioned earlier in the discussion the triangle that is government, universities and the private sector, that is a critical triangle. What is it about the ai talent that we need to address and need to see reflected in our organization. Basically 405 specific things worth understanding, these are problems. The first problem is the too view problem which is we dont have enough people with distinctive ai capabilities in the government and you can argue broadly in the economy. We have too few problem we need to solve somehow coupled with the second problem which is what i will call the pipeline problem. If you look at the pipeline that is supposed to feed the talent need that is woefully weak but looking at k12 or universities or what we relied on for talent which is a good domestic pipeline but International Students coming to the United States and other places of the pipeline issues are enormous. I was struck by the fact that if you look at video and the federal agency put out that suggests only something less than 3 of all it professionals under the age of 30 that is problematic. The pipeline challenge is absolutely important. The third challenge, the talented workforce, what i call many types leader problem. What i mean by that is often the talented workforce, we meet many different types, not just the experts, we need many of those but we need phds or whatever they have but also developers, not the fundamental research but the Department Work to build applications and users understanding enough to know how this fits into work clothes and how they use these technologies. We need leaders and the report does some work to categorize different sites that are needed but it is important to recognize the whole talent ecosystem here and value chain with different capabilities and roles, some of those are easier to transition people to. Some are harder but this other monolithic problem when it comes to the ai workforce, problem number 4 is the flow problem. A challenge that the element of the triangle dont work very well and you could argue the 3 legs of the triangle, government, universities and private sector right now the flow to the private sector. Almost entirely. So how do we solve the flow problem . This problem even for universities, i did my phd in robotics years ago telling you how old i am. You are looking for the best cuttingedge research in robotics and you look a handful of universities, that is where the best work has been done. That is not true anymore. Most of the most amazing groundbreaking fundamental research is in the private sector so the flow problem is a big challenge. I might characterize this as a mission problem in the following sense, it used to be the case that you could imagine technologists at a time people imagine if you wanted to do something good to the world you go into Public Service or the military, do things that are good for society. Technologists have a few more choices, they see the private sector as one way to change the world, technology for good. The monopoly Public Service used to have is a mechanism for smart, talented people, as many other competitors. There is more work National Security agencies what does this mean for organizations and organizational structure and there is useful lessons in the private sector. One thing you see now where days was they had a hard time Understanding Technology is fundamental to what we do. They came to realize that every time we had a technology company, they had their do but it is fundamental to the whole enterprise and that needs to come to our federal agencies. It is not something a few people will deal with in quantity. It has to be part of the system and this shows up in a few places. It should affect the person you suggested so i wont go into that. But the infrastructure question was one of the things specific to ai, and in the algorithms, you also need tools and data. What is one of the reasons people go to the private sector for ai is tools, so making sure the organizations have the ability to give people access the amount that they need, the infrastructures they need to do the work in interesting ways is a piece of the organizational change that is required. The other thing, general shanahan talked about the mismatch for the agility and pace that our defense agencies doesnt quite match the agility in ways of working that they require, to test things and so forth. Let me end on a couple notes that remain to people. One of the things we have learned if you like the investment of technology in the private sector, the metrics people use, for every dollar investment in the technology you need to invest another 20 in the change management. Not just about buying the technology that needs to happen in the organization, this is what you are alluding to about the change that has to happen and i will end on this note, pathways one thing that helps a lot is you have organizations and Career Pathways where they can go to the highest level of the organizations, you see this all the time. Until you see chief Technology Officers to affect organizations and people can see Career Pathways this was not taken seriously, kid doing technology stuff but people could see the progress in the organization. That was part of the thinking in our defense in National Security agencies which you had already spoken about. To round things up . Wonderful. Second or third, thanks for inviting me and the marvelous work, i look forward to seeing more output. In Silicon Valley, neither the singularity nor a University Story that we are working on. In the United States you pull glue on your curriculum for two years, we are 300 brainiacs around the world are experts on Artificial Intelligence to nextgeneration medicine and the impact on the future of the organization and future learning. To distill these things down, the framing i often get, are we trying to put our efforts on upgrading humans or are we trying to change the systems including our organizations and my answer is yes, got to do both. In an outsized manner, disadvantage, help the right kind of skills and if you dont help people have the tools in learning you have this continual mismatch so i will focus first on the humans. What i talk a lot about is the framing i see, we are going through as big a shift as we did from agriculture to industrial economy and digital work economy and doing it on a short period of time. What that means for humans is a bunch of ways we are reacting to that and the technology is a great enabler but also increasing that pace. We are shifting to portfolio of work rather than one person one job where having this much worse in different constructs with different activities people do parents ask me did my kid get a real job . The answer is working at a day job, start up with your friends it is a response to an especially changing world. How do you think about how you then leverage that kind of unbundling of work and being able to channel human energy to solve the problems so that is the first opportunity to think in terms of helping humans to upgrade themselves to other issues with the workforce to take advantage of because it creates opportunity if we change our organizations in the right way and it is one of those Situations Technology can help if we use it correctly. Lets talk half a dozen ai superpowers. China and russia and others but what are the superpowers technology can help us to have so that we can be supportive in solving the problem and to the organization issues. The same way we see constructs around the way humans work changing the organization itself is a construct, the whole idea of a corporate hierarchy traced back to alexander the great and in that shift from agriculture to industrial model we create the organization and i use the analogy of a box. There is abundance outside the box and scarcity in the box. There is corporate hierarchy and slots. We did that with a rational response to build factories and channel the energies of humans. The best Communications Technology was a carrier pigeon. Now we have digital distraction devices we all carry around to have the people in the world. The organization had to change. A lot of unbundling the organization from my friend john hagel but basically the idea is to shift if you want to picture of it to a model of a network. Will more you unbundle the organization, this is especially germane to agencies, apprenticeships, mentorships, crowdsourcing platforms, going through tours of duty, whatever allows you to take advantage of resources, skill sets of people that can solve these problems, you can open the box and turn it into better advantage you have. I talk a lot about these issues. It isnt about change management but managing change. There is a mentality that the current state and future state and then you are done. What is the difference between them . We have our plan. We cant see any point at which exponential change will slow down as one of our favorite phrases, following the slowest day of the rest of your life, you will look back in 10 years and say i remember when you didnt embed chips in your head or print your clothes in your closet and that kind of thing. You see it is going to increase. The idea an organization has a future static state we dont see that so the process is you need to be able to help people to adapt especially as we think of the lens of ai and the technologies themselves that are not going to slow down but will only increase we just need to figure both. A new way of thinking about solving these problems. I am listening to the three of you and if there is a simple refrain i could put forward, it is that you are demanding from us or asking these organizations to do some things in ways that were not organically poised to do because you are throwing out the entire model which has built this framework and you say going for word, the model Going Forward enablin