This is about 50 minutes. Okay. Well, welcome, everyone, to our meeting on ai and advance system Quantum Information Sciences, quantum computing, et cetera. Im pleased to have an opportunity to welcome michael crosteus, chief Technology Officer of the United States. I think weve come to the right place to engage this important subject. As you know, the administration has taken a very energetic position in trying to advance the state of the art in both the applications of Artificial Intelligence and the Quantum Information Sciences to our nondefense applications. Parallel efforts of substantial scale in the department of defense through the Defense Advance Research projects agency and other defense entities, because these technologies are, indeed, of universal applications. So i would like to take an opportunity to begin the discussion with michael to perhaps start with the bit of current news where europe has European Union in particular has tabled some of their ideas about how to manage some of the particularly the ethical issues relating to use of Artificial Intelligence. Weve had, of course, quite a number of years of tension on a transatlantic basis about the application of advanced technologies to commercial as well as governmental applications. So, i would be interested in getting your take on this, michael. Thank you. Absolutely. Thank you so much for hudson for having me here and thank you for this conversation. Yes, yesterday was a big day of news for the world of ai regulation. As you probably know, the United States was kind of first out of the gate in january, where we proposed the ai regulatory principles, and those are out for comment. And then since then, the eu yesterday has released their attempt to do what we did in january, providing some sort of structure around thinking about regulations of ai powered technologies in the European Union. I think it will take us twofold. One, i think were very encouraged to see a lot of focus in the document on the importance of fostering an ecosystem that is friendly to Artificial Intelligence technologies. They talk about the importance of developing and working on research and Development Type projects and helping drive startups and Smaller Companies to work in the space. And they also talk very much about a valuesbased approach, and we put out our principles in january. One that i think is important to flag and one thing where i think there could be room for improvement is their next step from taking this sort of evaluation approach and actually implementing it. We found what they actually put out yesterday, i think, really does in some ways sort of clumsily attempts to bucket aipowered technologies as high risk or not high risk. The way that the scheme is structured, there will be some sort of group of some kind in europe that will make some sort of decision on whether or not a technology is high risk or not. If you are high risk, you have to go through a pretty extensive regulatory approach. If you are not high risk you dont have to do anything. We believe this all or nothing approach is not necessarily the best way to approach regulating ai technologies. We think ai regulation serves a spectrum of sorts, certain types of ai powered technologies that will require heavy regulatory scrutiny and we in the United States are prepared to do that, but there are quite a few that need a little or not at all and creating the spectrum is important. Thats where our biggest concern is. And ill be traveling to brussels next march, next month, and speaking to folks over there these concerns. I think theres a lot we have in common but this approach of very bluntly bifurcating the entire r r d to the entire system into two buckets is very harsh. Its a very good point. And as you may know, i also serve on the d. O. D. , defense Science Board and weve done studies on the application of modern technology to the development of both ai and quantum. And one of the opportunities that may evolve as the Technology Improves to facilitate better alignment with our allies in Europe Europe is underway in darpa to develop explainable ai, so that the user of the outcome or outmput of an aibased bit of analysis is able to understand the coupling between the outcome and the data that produced the outcome. And were of course not there yet, but there may be some opportunities for Research Collaboration between the u. S. And the eu to perhaps better solve this problem of explainable ai. I couldnt agree more. I think its sort of a thats a good segue into sort of how the u. S. Approach in some ways differs a little bit to the european. I think when we put out our principles last january, they sort of focus on three main themes. I think one of them hits directly on this explainability question. On the first goaround i think the most important thing on the u. S. Model is public engagement. Whenever we attempt to do this, higherpowered technology, we as the federal government have some experts, but the community is the people who know this best. They have the scientists, experts who can help us. Theres a lot of emfasis on public engagement. The second is limited overreach. We need to create a model that is risk based and use based and sector specific. The types of regulations you may have for an Autonomous Vehicle or a drone is very different for necessarily the type of regulation well have for an aipowered dying knottic. Rather than bucketing those as well, those are all high risk, you have to do 12 things, or these are not and you dont have to do anything, there has to be flexibility so youre able to do appropriately for the risks. The thirds which i think you bring up very astutely is this idea of promoting trustworthy ai. We care about this and need to engender trust in the american people. We need to create a regulatory model that allows that to be built. Having better r d and explainability will get us there. One of the issues related to this thats coming fast upon us is the interaction between ai and the internet of things. Science board has been doing some work on the technologies of autonomy and counterautonomy. Obviously Ai Technology is one of the things thats going to make iot work for the whole society. There may also be some opportunities for collaboration with our eu colleagues on trying to understand how we will manage the introduction of iot. Because like other applications where ai is involved, the range of applications is extraordinarily diverse. I couldnt agree more. I think where that where we manifested that type of thinking in our approach is actually through the first large white house summit we held on Artificial Intelligence was ai for american industry. We were trying to express, its going to touch every industry, whether oil extraction, biotech, youll be using this. If the u. S. Wants to lead the world with this, we need to make sure all of those industries are able to capture the benefits that that can provide. Being able to have that very important dialogue with our allies around the world on how to move forward is absolutely critical. Right. One of the lets say news items thats been a pretty constant drumbeat for the past half dozen years or so has been chinas alignment of its perception of its national and security interests with investments in advanced technology. They announced their made in china 25 initiative five years or so ago, which identified about ten areas of technology that would be getting particularly high investment from china. And its often described in the terms of billions of dollars. And id be interested in your observations, michael, about how chinas efforts have been coupled to the administrations initiative, and your perception of the chinese effort. Yeah. I think theres two threads to pull on. I think the first, which i think needs to be said, and i think to me should be evidently apparent and probably communicated more often generally, is that if a Chinese Communist party is using Artificial Intelligence to track people in their country, imprison ethic minorities, push forward a complete surveillance state, maintain a great chinese firewall and restrict content the Chinese People have access to, these are the use cases of Artificial Intelligence that are deeply in conflict with western values. And this is something that we have tried to communicate and continue to communicate with our friends and allies in europe. And there has never been more of an imperative than now to ensure we lead the world in Artificial Intelligence. We need to make sure that the next breakthroughs are made here in the west and under pinned by western values. If we dont lead we run the risk of these values that are opposed to everything we believe in, slowly permeating these new technologies and being exported. That is why the imperative is so great, why the president signed an executive order launching the initiative, why we have pursued to ensure art firnl intelligence and leadership. That is why we made the big announcement, we are committed to doubling nondefense ai spend in the next two years. That is moving from about a billion dollars to 2 billion of federally funded r d, nai, this is a massive step forward in our commitment to American Leadership in this particular domain. I think whats very important to remember, thats point one. I think point two you brought up, these commitments that have been publicly asserted by the chinese government, you know, we believe that theres a lot of we have a lot of skepticism in the validity or voracity of those particular statistics. I think i challenge we have a lot of brilliant think tank people here, journalists here, i challenge all of you to spend more time thinking about if youre attempting to report on an action taken by the chinese government, to spend more money on ai, is that actually happening . Are they actually spending billions of dollars . Can we do more . Is that really a true statement . Can you compare that number to the number that Congress Appropriates and is put out by our agencies . I think the short answer is no. I think there needs to be a better conversation around the validity of those numbers. Pointing to two studies, georgetown, a team put out that casts doubt on a lot of these numbers. They said theyre definitely not spending tens of billions and spending a lot less. We need to make that clear. When were trying to make comparisons around what the west is spending, we need to be actually be comparing apples to apples. Its a good point. One of the things i think ironically is going to render chinas investment less successful is that in parallel with their made in china 2025 initiative, they also have emphasized what they call Civil Military fusion, which is an effort to extract the military applications of these advanced technologies. Both sciences and ai are technologies that will have universal applicability. And trying to forcefeed the scientific effort into producing military advantage will have the more likely outcome that will produce nooergt military advantage nor advance the underlying science. So it is something of a limitation. And so i think were likely to be more successful with this approach. And i was very reassured by your observations about the scale of the increase. And having previously served in the office of management and budget as an official there a number of years ago, one of the questions i always ask about the Public Sector investment, which is easy to measure, is, what are your expectations for the outcomes of this investment . And are there pertinent metrics . Are there formed expectations that might help shape public expectations about the scale of this investment . Absolutely. I think the best way to answer that is to kind of give a little bit of a description of the type of Innovation Ecosystem we have in the United States and the role that the federal government and its agencies plays in driving innovation broadly in the United States. Whats very different than almost any other country in the world and particularly in china is the way that the federal government spends research and development dollars. We dont have a ministry of science that has doled out x number of dollars and a decision is made how to spend it. We have research and development happening across all of our agencies. Darpa is doing incredible work more on the latestage applied side. National science has appropriated 8 billion a year to invest in early stage basic Research Done at a lot of universities. Theres a department of energy which has billions of dollars that are spent through the lab structure. We have National Institutes for health which does a lot of biohealth related research as well. We have a very diverse set of places and each has their own goals and pieces of the puzzle that they play. So in some ways were creating were incentivizing and creating a free market of ideas around innovation. The part that the federal government plays in the larger spectrum is that generally speaking, the federal government is investing in earlystage, precompetitive basically research and development. Thats very different than what the private sector does. Thats buy design. So the types of research that the federal government generally approaches is a type of research that the private sector is not incentivized to do on their own. That is a gap we try to fill. We do it where these ideas can come to life, taken up and absorbed by the private sector and brought to fruition and completion. A great example is this breakthrough that happened last year on quantum sup remcy. Theres no doubt in my mind that someone in beijing had sort of called upon someone else in china to achieve quantum sue remcy before the United States did. We didnt make that call here in washington. Our community yet the United States made that breakthrough first. The question is why or how . The federal government invests in this. We made a commitment years ago to investing into a kwuntum lab at uc santa barbara. Were funding the research that didnt have any commercial applications. Some breakthroughs were made. Google saw this, said this is a great team, we could bring them onboard, equip them with more resources, compute time. They acquired the group, brought them inhouse, and that group was able to achieve it. They had to prove their device could be faster than a traditional computer. Who has the fastest . The federal government does at our national lab. They took their breakthrough and they went to the fastest in the world run by the d. O. E. And ran the test to prove it. You can see this incredible Virtuous Cycle of all pieces of the ecosystem working together from the federal government doing the basic early work funding at academic institutions, moving into the private sector, having to go back to the federal government for the check. This is the type of freemarket approach innovation which has led to a breakthrough which is world changing. Its a very good observation. Having done some work with the national labs, one of the things that theyve been able to do successfully that i think interacts in a particularly constructive way with the this initiative which is basically in the foundational science of Artificial Intelligence and quantum science is, they have extraordinary modeling and sumewlation capabilities. The application of Artificial Intelligence or quantum sensing for example can be put through a synergistic suite of modeling and simulation that contributes to the advance of the foundational science. And its the foundational science that creates the technology. And on that particular point, id be interested in any of your observations about how u. S. , ai, and Quantum Sciences stacks up . Our take is we continue the world in both domains. Theres a whole number of metrics you could use to kind of come to this analysis. But generally speaking, we have the best institutions in the world. We have the most highly cited papers in the world. We have the most vibrant venture ecosystem in the world. The most dollars invested. The list goes on and on. We continue to lead the world. The question is less about where we stack up today but how do we maintain that leadership . If you look at the president very intentionally again titled his executive order on Artificial Intelligence, maintaining American Leadership in Artificial Intelligence. This is what were doing through our national strategies. Generally speaking whether it is in quantum Information Science or ai, we generally follow a strategic approach that has four primary lines of effort. So the first line is all around research and development leadership. So back to this question of the federal government spends in the neighborhood of 150 billion a year on research and development. How do we coordinate those efforts in a way that will allow us to maximize the output of those dollars . Through coordinating, privatization, a lot of increasing spending at the federal level to historic levels with this 2 billion announcement last week, and the list goes on. Pillar two is around a regulatory approach. We want to remove barriers to Ai Innovation and broadly in these domains and c