Word for the day, it kind of governs how i conduct myself often times and just my frame of mind. Today, im going to pick an image of the day. If you look at your screen, one of our commissioners shared with me this image. And i think it really sets the tone and the stage and underscores the importance of why we are here and the significance of this panel. Is a chinese book for kindergartners. Chinese,ou dont speak circled our two letters. Ai. Kindergarten. Textbook. Ai. Us senator talked about tooling ourselves and getting ready from grade school to grad school. Now, we are talking about kindergarten or even prek, if you are going to keep ahead and really stay number one when it comes to ai. I just wanted to start with this image. Because it really, for me underscores the urgency of why this commission was formed and why it is so important that we are here today. Nscai has a broad mandate and working group number three is charged with recommending concrete steps the government should take to build and maintain an ai machine morning look force, address National Security and defense needs of the United States. Over the last eight months, this working group has assessed the current state of the National Security enterprises ai workforce, explore the roles of an ai workforce, explored the roles how the ai workforce might play and examine how the government might recruit, train, educate, manage, and to the extent that is necessary, retrain an ai workforce. Here are our judgments thus far. You will affirm this if you have read the report. Agencys needity a holistic workforce renovation for the ai era, that includes extending ai familiarity throughout organizations, infusing ethical training at every level, and spreading the use of modern software tools, developing ai ready leaders is especially critical, because without more wellinformed leaders who can go beyond talking points and reshape their organizations, the defense and intelligence communities will fail to compete in the ai era. A little hesitant because of the military presence today, but im going to make this next point. The department of defense and the Intelligence Community do not have effective ways to identify ai relevant skills that already exist in their workforce. [applause] so, i will make it out alive. Thank you very much. [laughter] they often fail to capitalize on their technical talents. Existing hiring authorities are adequate or close to adequate. More to the point. Government agencies and departments are not fully utilizing civilian hiring authorities to recruit ai talent often due to riskaverse human ofource teams and commanders civilian leaders that do not hold them sufficiently accountable. Am i going to walk out still . It is less clear if the same is holding true when it comes to pay scale. Fellowships focus and Exchange Opportunities can give officials and servicemembers access to cuttingedge technology and bring talents from our Top Ai Companies into federal service. These programs already exist and we have been talking about this yesterday, but they need to expand. Government employees who gain valuable skills from the private sector should have an opportunity to use them when they return to Government Service and my complementary fifth point is that the military and National Security agencys struggle to compete for top ai talent. The government needs to spend more effort showing that service is an opportunity to solve andue, exciting problems have a positive impact. It should try to reduce, if it disparagement of its workforce and better use pathways for recent graduates. There are two additional hard questions. We will explore them with our panelists today. Since the american ai talent pool depends heavily on International 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 and Computer Science generally. The number of Computer Science majors is increasing at 10 times the rate of tenuretrack salaries. So, to begin and continue this theussion, we have asked chairman of the director and director with the Mckinsey Global institute and i take liberties with names, especially if it allows me to use some consonants that i dont usually use a lot. The former Deputy Director of national intelligence. And the chair of the future work for singularity university. They will provide their perspectives on these two questions, primarily, but not exclusively. How important is organizational structure for capitalizing on Emergent Technology challenges . How should the National Security agencies educate leaders and users who do not participate in the Development Process to deploy, use, and resource ai Available Solutions effectively and ethically . Very and thoughtfully. [laughter] im sorry. [laughter] organizational construct is very important. The second is how to deal with your workforce, you have to do it thoughtfully. Stepet me create a quick for you that begins before that and extends after it. Things we need to have to effectively integrate these technologies into a workflow. The first is you have to have imperatives. The organization has to believe it must. If the organization does not believe that it must, then it will be a technology or it will be left to the innovators and you will have change, but it will not be at scale and at speed. For the Intelligence Community, you need to see the world as it is. You need to understand what your mission is. It isnt about secrecy, it is about knowing a little bit more and little bit sooner. And if you look at this world with abundant data and ubiquitous technology, speed of decisionmaking. If you are the Intelligence Community and you are a leader, then you must find a way to introduce the ability to handle volume,m speed and from but also distance making. The technologies that are emergent are the ones that you must have. You have to have imperative and you have to have csuite buyin. If you dont, then you will fitted in after you have done your real mission. You need infrastructure. Earlier panels talked about the information infrastructure to support it. Various stages of building that infrastructure, even those of us who built infrastructure built it for humans to use and now we are trying to figure out how machines use the infrastructure because data uses it differently than people. They use it differently. There is that information infrastructure, but there was also the infrastructure that brings people into the mix, and the reason why you have to have that is so that people can play with the new capabilities. What is really important when you want to have data is you need to be able to integrate it with no cost. If you dont have infrastructure that allows you to have barriers, you wont be able to get that curiosity that will get the organization to figure out what it can do and he wont get pair withn pull to the technology push. Organizationally, you need two types of organization. Organization to support your technologies. Opine that we can attract anybody. The Intelligence Community, our mission is so exciting still and such a possibility that people will come, but they find they are not supported with the same sorts of things they can find outside. At the 510 year mark, they cannot stand not being able to pursue their craft and so they go somewhere where they can. So, you have to have a way to support them technically and get them around people , but the other thing is you need to think about whether the organizational model needs to change because technology is so embedded with what we do that the serial process of the technology is sitting someplace else and pumping capability into a work unit is not necessarily the model we need. I think the organizational models change. Organizational construct for your technical humans and then work units that allow the integration and the transfer of ideas and at speed to happen and the last one is you need process. Revolution. Cess itn when the leader wants and you have the infrastructure supporting it and you have the organizations that demand it, all of them come crashing into processes that were never expected to be designed for this moment, and we dash people into despair because the processes do that. One of the things we need to do is think about who we are putting in charge of designing new processes, because the people we have now dont. As far as how you deal with a mixed workforce. Need to provide the throughes to those things i mentioned for people who want to become to be able to come and you have to recognize that some people are not going to be able to come and you have to treat them honorably and offer them other solutions. We do have a demographic problem that we are going to have to address. I think the middle leadership is probably the most urgent need. It does not understand this is fundamentally a technical world and they wont trust the ideas coming up can actually affect the solutions. I will end it there. I appreciate that. It really underscores the culture. What people find when they get there. I appreciate those points. Primarily everything that you just said. Doctor . Im delighted to be here. The report the commission has put out is very spot on. I know there is a lot more work to come, but i particularly liked the fact that it points talent to the center. Puts the talented workforce at the center. That is absolutely critical. When you think about what was mentioned earlier in the discussions today, the triangle that his government, university, and the private sectors, that is a critical triangle when it comes to these talents. What is it about ai talents that we need to address and reflect in our organization . That there are four or five specific things worth understanding. I will frame these as problems. The first problem we have is we just dont have enough people with distinctive ai capabilities in the government and you could even argue broadly in the economy. We have a two few problem that we need to solve for somehow. This is coupled with the second this is coupled with the second problem, a pipeline problem. If you look at the pipeline we need in ai, it is woefully weak. We look at universities and places we have relied on for talent, which has been a good domestic pipeline, but also students coming to the United States from other places. The pipeline issues, i was struck that if you look at the and the federal agents that put them out, they suggest less than 3 of all i. T. Professionals under the age of 30, that is problematic. Challenges is absolutely important. The third challenge in the thece is what i call many types needed problem. What i mean is when we have a talented workforce for ai, we need many different types. Not the deep experts, we need many of those, we do not have enough. But we also need people who are developers, who will not do the fundamental research but do the Development Work to build applications. Who needlso need users to know how this works into the workflows and how they use these technologies. We will need leaders. The report does categorize the difference, but it is important to recognize the talent , thereem and value chain are different capabilities and roles. Some are easier to transition people into, some are harder, but it is a monolithic problem when it comes to the ai workforce. Is the flower four problem. Of the threeue legs of the triangle, government, universities, and private sector, right now most of the flow is to the private sector. Almost entirely. The government gets the short end of that stick. How do we solve the flow problem is problematic. This problem is real for universities. Robotics 23 in years ago, that tells you how old i am. At that time, if you are looking at the best cuttingedge robotics, you look at a handful of universities, that is were the best work is being done. That is not true anymore, most of the groundbreaking research is in the private sector. The flow problem is a big challenge. I know in some conversations this has come up, and i might characterize it as a mission problem. Case you couldhe technologists, and a time when people imagine if you wanted to do something good for the world, Public Service, you go into the military and do good things for society. Technologists have a few more choices. Look at the young graduates who see the private sector as one of the ways to change the world, technology for good. Arguably, the monopoly that Public Service used to have is the mechanism for smart and talented people to do Amazing Things without many more competitors. There is more work that the government needs to do. What does this mean for organizations and the organizational structure . There are some useful lessons from the private sector. I spend an amount of time in the private sector and one of the things you see, there was a time when companies had a hard time Understanding Technology is fundamental to what they do. Now everyone has come to realize every company is a technology company, it is not something people in the corner do, but it is fundamental to the enterprise. Tot mindset needs to come federal agencies, this is not just something a few people will do in the corner, it has to be part of the system. This shows up in a few places. We should also think about infrastructure. Things specific to ai, if you talk to ai people, they will tell you you need amazing people for the other rhythms, but you need tools and data. Of thelook at one reasons people go to the private sector for ai is compute and data and tools. Making sure the organizations have the ability to give people access to the leading tools, the amount of compute that they need, the infrastructure they need to do the work in interesting ways is another piece of the organizational chains required. The other thing is ways of working, and general shanahan spoke about this in the morning, there is a mismatch in terms of agility and pace. I think our defense agencies worked historically that does not match the pace in ways of working that these technologies now require, the ability to iterate and test things and so forth. Organizations have to be comfortable doing that. Let me end on a couple of notes related to people. One of the things we have you look at investment in technology in the private sector, there is a , forc that people use every dollar of investment in the technology you make, you need to invest another 20 in management. It is not about buying the technology, there are the chains that need to happen in the organization before organizations can capitalize. This may be what you are alluding to for the change for our agencies to work. This is something we have not talked about, Career Pathways. One of the things that helps a when youu have bring people into organizations, and there are Career Pathways where they can grow and succeed to the highest levels of those organizations on the basis of their unique skills, you see this in companies all the time. Until we see chief information toicers at the table able affect the organization, and people can see Career Pathways, this was not taken seriously. It was the kids in the basement doing technology, but this is how people can progress in the organization. That is some of the fundamentals that need to be required for our defense and National Security agencies. Those are some Lessons Learned from our experience. Wonderful. To second or third thanks for inviting me. I am looking forward to seeing more of the output. Universities, think tank based, and Silicon Valley is not about the identity issues we are working on. To be United States, accredited you have to pour glue on your work every two years. We have brainiacs to work on everything, and i get to pull from their brains about the future of the organization, and future of learning. Things in the way i read the questions, the framing i often get is let me understand this are we putting efforts on upgrading humans or trying to change the systems including our organizations . And my answer is yes, you have to do both. The systems are at a disadvantage, the opportunities to help the right kind of skills and capabilities to solve the right problems. If you do not help people have the tools and learning they need, you will have this continual mismatch. I will focus first on the humans. Is thatalk a lot about some of the framing i see, we are going through the biggest going from did agricultural to industrial economies. We are doing it in a blinding amount of time. What that means for humans, there are ways we are reacting isthat, and technology potentially a great enabler im a but it is increasing that pace. We are shifting to what i call a portfolio of work im a rather than one person, one job, we have an ambiguous set of different constructs and activities that people do. Can my kid get a real job . The answer is, working at a day job or on a startup with your friends is the rational response to an exponentially changing world. How do you think about how you then leverage that kind of unbundling of work, and being able to channel human energies to solve the problems you want . That is the first opportunity, to think in terms were we help humans to upgrade themselves. There are issues in the workforce that we can take advantage of, because it creates we change our organizations in the right way. It is a rare situation were technology can be helpful if we use it correctly. , talk about the ai superpowers china and russia and others, but what are the superpowers that technology can help us to have so we can be supported in solving the problems of tomorrow . To the organization issues, in the same way we are saying constructs around the