The geopolitics of artificial intelligence

So we're far enough into this, you know, current AI revolution to where it's a point of prestige. People have been hearing if you don't get into it, you're going to get left way, way behind. And there's, there's truth to that. And we're starting to see that truth now in terms of what different social or political groups, you know, whether they be nations or corporations, we're already seeing power shifts. And some of that is prestige based, some of that is the ability to drive economic interests, obviously, some of that's to drive military interests. But they're all related. And now that AI is touching every field there is. It's super, super important. So it's going to, it's going to change all of those. And it already is.

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Welcome to another fully connected episode of the Practical AI podcast. This is where Chris and I keep you fully connected with everything that's happening in the AI community. We'll take some time to discuss some of the latest AI news and dig into some learning resources to help you level up your machine learning game. I'm Daniel Whitenack, I'm a data scientist with SIL International and I'm joined as always by my co host Chris Benson who is a strategist at Lockheed Martin. How you doing Chris?

Doing very well, Daniel. How are you doing today?

Doing pretty good. Lots of exciting progress on various fronts and with projects, lots of of new results coming out. So I feel like there's a lot of plates spinning which is good, but then you have to kind of bring in focus sometimes. I don't know. Do you ever read productivity hack type books and that sort of thing?

I hate to say it but yeah, I get those feelings of desperation and I go I gotta level up. And so occasionally, yeah, not constantly, but yes, I confess.

Have there been any hacks that, that have really helped you over time?

Turning off email and slack like it work. I will like, I will like put in a slack notice on like on some of the channels that are teams and I'll be like I'm going gone for a little while just to focus. I've learned I have to set the expectation but yeah I'm. I'm starting to really focus on time to think and get things done versus time to collaborate, both of which are very, very important. But, but I've learned that if I try to do them all at the same time, it, it often is, is not what I wanted.

Yeah, I've really liked the reminder slash. You can set up reminders and there's also automatic reminders in Gmail.

Yep.

For like, remind me of this email and you know, next Tuesday or something like that. That's been really, really helpful for me in, in all sorts of ways. It's like the single greatest feature, at least for my workflows that, that I've seen and one of the things that I use for quite a while. But yeah, I don't know if they use AI to determine when to remind you about things or if it's. It's all rules based, but however they're doing it, it, it works for me.

That sounds good. No, that works. That works.

Well, speaking of redefining workflows and the power of artificial intelligence and machine learning systems, last week we had this discussion on a fully connected episode about kind of large models, sentience, some new paradigms and models and that sort of thing, which was really fun. Another side of this though, that I think we wanted to follow up on in this episode is maybe a more global perspective of how artificial intelligence, how machine learning is shifting, kind of both geopolitical, social, economic change in the world and as practitioners, how that should be on our radar as we're building systems that are contributing to that. So yeah, I know that you put in a lot of thought about this.

I spend a lot of time on this topic, as you know.

And I'm coming at this from a person who maybe doesn't spend as much time thinking about, maybe thinking systematically about things, but not necessarily politically about things. Because I even remember around the time of GDPR that came out, there's a lot of discussion about regulation around algorithms and that sort of thing. But it was more of a, it got a lot of news because it was maybe this first really, really big regulation around this sort of stuff. Stuff. But as you're maybe following this area more closely, how have you seen the discussions of AI plus politics plus economics plus social change in the world? How have you seen those progress generally over the last couple years?

Oh, there's so many, there's so many paths we can take down that I'll actually start with the one that you just brought up, and that's GDPR and that, you know, Was the first, as you pointed out, big regulation to regulate data concerns in Europe. But its scope was fairly limited and it kind of addressed everything in a. In a uniform manner and a little bit ambiguous. It was a bit ambiguous. And in conversations, in European related conversations that I've had, I've. I've heard a lot of criticism over the subsequent years. I think. I think the hope was that it might be the first very imperfect step that would. Then we would. Learnings would occur and further regulation that was a little bit more insightful and thoughtful, having learned a bit as we forged through this new landscape. And I think that may have somewhat stalled at some levels. And I think having that has been. There was a recent conversation I had where it was interesting, some strong, strongly worded conversation against GDPR from someone I was talking with.

I guess one follow up to that is do you think that regulations around AI or machine learning systems are keeping up with the sort of widespread deployments and applications of. Okay, that was sort of a rhetorical question, but I thought I would just mention it to be completely transparent. So there's this wide gap between deployment and scale of AI and machine learning systems and regulations around those.

There are so many things to go into that rabbit hole on. I mean AI is affecting. It affects politics directly and I don't mean the output of an algorithm. I'm talking about having the capability of conducting both applying AI and novel research. There are things that people don't think about that that is a form of prestige, for instance.

Yeah.

So we tend to go to things like economics and the science and all that. But the ability for a nation to do that is a point of pride. And the perceptions among nations or large corporations, it could be any large entities and what they're able to project in terms of their capacity and that it has a huge impact business and on people's perception of business and thus economics at a large scale. So I mean that's just one little rabbit hole we can go down. But there's a lot out there.

How much around sort of a nation state's focus on an AI strategy do you think, and this is kind of generalities, but how much of that do you think is merely for the prestige and to not. Not sort of get left behind? Or how much of it do you think is related to real strategies that are core to whether it's the economics or the social aspects or the political aspects within a nation?

So it's a great question and it has. The answer is yes to everything, but on different timescales and priorities and budgets. So we're far enough into this, you know, current AI revolution. I mean, you and I have been doing this podcast for four years now. We started in July of recording this. Yeah, it's July of 2022 as we record this. And we started this in July 2018, and we were several years into it when we started this. And so it's far enough to where it's a point of prestige. People have been hearing if you don't get into it, you're going to get left way, way behind. There's truth to that, and we're starting to see that truth now in terms of what different social or political groups, whether they be nations or corporations or whatever social division you want to make in there. We're already seeing power shifts in a bunch of different areas. And some of that is prestige based. Some of that is the ability to drive economic interests, obviously. Some of that's to drive military interests, which is obviously kind of the industry I'm in on my day job. But they're all related and academic too. If you are a country who is trying to build its educational system and you need your universities to be the types of destinations that will draw not only your citizens in, but citizens from other countries, and you're trying to build that. Well, there are not enough professors in AI out there. They're not even close here in the United States. It's a massive problem that we have about not enough instructors just to teach the basics. That spreads around the globe. And there are portions of the globe that are really struggling to find anybody that is competent to teach these areas. And so that impacts the universities. Each university ability to be reputable enough to draw a Daniel Whitenack in or somebody with your interests, you went through some years back, as you were going for your PhD, you had to make choices on where you were going to go. And the students of today are making those choices. But the landscape is changing and now that AI is, is touching every field there is. It's super, super important. So it's going to change all of those. And it already is.

And I think that if we're looking at a global scale, there's the sort of nation state actors, but then also global companies and organizations. I'm even just thinking of SIL in my own context. Just because we're now kind of intentionally making efforts in the AI and natural language processing area and we're establishing intentional projects in that area. The sort of pipeline of talent into SIL is sort of some new opportunities have arisen even with that kind of pipeline of talent that maybe just wouldn't have even known about our organization were it not for those efforts. So I think there's also this pressure at a company level to have a visible AI effort indeed, regardless of if they really understand what their goals are there. It's this. I don't want to get left behind, but also I want to make sure and get some of this talent because it seems like everyone's trying to get this talent. And I do wonder both at the political level and the corporate level, those kind of higher leadership, at what level do politicians and at what level do corporate execs actually understand the implications of establishing an AI strategy within their whatever's under their purview.

So it's becoming very common to have both national level AI strategies and corporate levels. And for the most part a lot of them look a lot alike as you move across different organizations, which is probably a tell. It probably is. And I think the differentiation occurs with leaders who are very forward leaning and they're spending a lot of time thinking about where they want to get to versus what they have today. And I think that makes a big difference on whether or not their approach is actually going to be viable from an investment standpoint in terms of its outcome. But yeah, I mean, I know for a fact that there are leaders of state that are directly involved in these efforts, not because they have expertise in it, but because they understand that their national interest is hinged to it.

So this is maybe a lower level question, but I think it's connected to this. If you are an AI practitioner out there or a technical person or a tech lead or a manager, whether it's in a government organization or in a corporate organization where this sort of trickle down of AI strategy is reaching you and you sort of got a mandate to do something with AI, but it's unclear to you maybe what that means or how the value comes out of that. What recommendation would you give to such a person to navigate that scenario? Because I do think it's happening in many places.

Well, it's funny that you ask that on our show called Practical AI because my answer is incredibly practical, as you won't be surprised, and that is for your organization or your nation, what are the challenges that you're expecting to face? And I think a fantastic example of that is the AI in Africa series that we've been doing over the past year has been or maybe longer now. It's been fantastic in seeing these AI researchers in various African states addressing the needs of their populations. And they are, they are channeling productive AI research to address those. And when I have conversations with other people throughout the world in other contexts, I actually point to that directly and say that's a fantastic way of approaching that. Because big fluffy AI strategy is fine, but if it's not something that makes a difference in outcomes, it's a waste of money and time and effort and stuff. So you've got to bring it all the way down to solving real needs.

So, Chris, I've been reading a few articles related to this and we'll link some of those in our in our show notes. But I think what you were just talking about is really interesting in that in this series that we've been doing about AI in Africa, we've learned that applications of AI within the local, either language, ecology or geopolitical situation, or nonprofit situation, or whatever situation are being applied are very different than often a parallel in a location, maybe in a Western country. For example, the agriculture things that we talked about, like the way AI is being applied in agriculture in the west, is quite a bit different than a sort of large scale application that's needed within the African context. We learned that with our guests on one of the previous Spotlight shows. And as I've been reading in these articles, it's talking about kind of new models of growth and how AI will shift sort of power structures and that sort of thing. But one of the things that's interesting is that AI systems applied systematically and very globally, if they're coming purely from a perspective of one nation state, they might try to scale out globally, but in a way that's very irrelevant to other contexts. And for example, an effort to apply text machine translation for every language of the world would ignore the fact that some languages of the world have no written form. So what does that mean when we say that we're changing, we're creating this new structure of growth and enabling wider commerce with machine translation and that sort of thing, when actually, if your context doesn't fit into that model of growth, then you're further marginalized in some senses.

Absolutely. I would summarize that by saying that diversity matters, diversity of experience and diversity of the challenges of a particular culture or group of people, and that the complexities that are arising in their experiences have to be accounted for if they want to use AI in that toolbox to address those things. And so, so going back to your original point, which I thought made a lot of sense, was the fact that if you're not customizing what, how you're using AI and the focus of your research on the particular needs of your area, your. And the, those issues which arise from, from your point in a diverse world, you'll get a substandard outcome from that. So you can't, you can't take, you know, something that might be a good approach in the United States and drop it into a country that has a very different culture and a very different economy and stuff. It's not going to work well. So it takes that thoughtfulness. And so when people, when I see somebody, when I say somebody, meaning like a, a nation or a corporation or something like that, just kind of copying what the others are doing, it always makes me cringe a little bit because it shows me that either they didn't understand the need for that, that focus and that customization, or that they simply weren't thoughtful enough about it. So, yeah, yeah.

And it makes me wonder kind of generally if, if AI systems continue to be dominated in terms of their development and the strategy around how they're developed continues to be dominant, dominated by a few, certain actors, that runs the risk of a lot of, at the minimum, irrelevance when they're applied in a whole variety of contexts, but at the most, a sort of harm when they're applied in many contexts.

And the number of unintended consequences that you can have without that is pretty key. And the way that you apply them, for better or for worse, directly affects the power structures of the institutions and, and nations that we're talking about. So it has a very real and extensive outcome, much of which is outside the scope of what people are thinking about when they're trying to apply it. So it can affect both how those organizations are, the relationships they have with others or other nation states, and it also affects the internals of those organizations and where budgets and power lay going forward because of investments people are making there. And that can be in the private sector, it can be in the public sector terms of education, in terms of government, obviously can be in military investments and approaches forward. So there's so many places that it has consequences that based on observation, I would say usually aren't expansively seen ahead of time or not predicted.

And what are some of those key shifts in power or shifts in power structures that you think would be worth highlighting is one sort of nation state government versus private sector. What other ones are kind of in your mind when you're thinking about shifts of power in various ways?

Well, at the highest level, if we're talking kind of nation state level competition in a general sense, there are aspirations that nations have and they compete with each other in a variety of domains. There's economic competition, there's academic competition. On this show we've talked many times as we've, you know, people often speak of kind of the, the competition that has arisen in AI between the United States and China, you know, and the economics involved around it, and the number of academic papers being published. All of these contribute to trying to position obviously as an offshoot of that. There's the way that power projection in a military context is, is changing over time. And AI is certainly affecting that. And so we're at a really curious moment in history right now. And I say curious not meaning good or bad, just kind of one of those moments where you go, you know, you start watching. And one of those is as we are recording this, Russia, you know, invaded Ukraine a few months ago and the whole world has kind of banded together, thank God, you know, and stood up for the world order of not invading your neighbors and killing your neighbors. And. But if you look at how that affects non military concerns, you have every nation in the world is watching how the conflict and the economics around it with the sanctions and everything else are being affected. And a lot of those mechanisms are now being optimized with AI algorithms. So you have these little AI solutions sprinkled all over the place economically and military capability and all that. And then you have everybody in the world kind of watching to see what happens. And before I abandon the military thing to move back into the general thing, I'll note that we are proliferating AI capability all over the place, which will proliferate autonomy all over the place. And so the nature of conflict between these nation states is also changing. And in Ukraine, Ukraine is doing this heroic job of, of defeating big platforms, these big tanks and things, and expensive aircraft with little missiles that only cost a few thousand dollars. And some of those missiles have capabilities. And over the future we will see more and more autonomy and AI enablement in those types of things. So you're seeing a world where conflict will be judged by the proliferation of many, many, many more than we have now, mostly autonomous things. And so that also changes the need on investment. And so as you're looking at that, countries are having to think, if I'm going to be safe from an aggressor, in this case like Russia going forward, how do I invest to do that? They're having to do that. In the military context, they're having to do that. In the economic context, they're having to do that in the academic context. And then all of these global organizations that are all household name stores are having to react because they're operating in those environments. So it's really, it has this endless web of influence that's going around.

And also those that are in charge of, or have the power in, in certain domains of technology oftentimes make, make an even more visible impact in these sorts of conflict zones potentially than even nation state actors. So in the Ukraine thing, just thinking of like, well, even in certain cases, more so than any other government or state intervening in that situation. You have a lot of companies, whether that be IBM, Dell, Meta, Facebook, Apple, who made a big impact by ceasing operations within Russia as a result of the conflict. And you just see the power that has, in pulling away that, that technological capability. There, there's a, there's a huge impact by that. And then you have even individuals, you know, like Elon Musk, who did all the stuff with Tesla and his Starlink satellite stuff in Ukraine. And you know, whether, whatever you think of Elon Musk, you must realize, you know, this, this had at least publicly a very visible impact on the effort to see support from that type of person, from that type of technology. And so whether it's a perception thing or an actual kind of tangible impact, those that hold the technology and I think more specifically are really plugged into this advanced technology like AI enabled technologies, autonomy, they hold a lot of the power maybe even over nation states, at least in certain scenarios.

Oh indeed, yeah. I mean, I agree with that completely. The sway of powerful people with powerful corporate backing has tremendous impact on the decisions that nation states are making. So AI is an incredibly valuable national resource or corporate resource, depending on what structure you're in. And so like any valuable resource, it is now being used and has been for some time to change the balance of power and change future paths. So this is an uncommon conversation for us. We're usually focused more on the practice of using AI or AI research and stuff like that. But we're living in this larger context which our community often isn't paying super close attention to necessarily. And we'll think about things like AI ethics, but that's at the practitioner level as opposed to the environment that these activities that we're all engaged in has made a huge impact on above us. So it's all connected. We're not working in isolation as we do these things.

Chris, you brought up autonomy as one of the things that's at play in this whole geopolitical side of artificial intelligence. I'm wondering, as you've thought a lot about autonomy, both used by governments and used by companies and other things, as that's becoming more widespread and global in its application, what are the strategic and maybe human security risks associated with a wider spread of, of autonomy or systems that maybe, that maybe operate with very little human input?

If any autonomy will be pervasive going forward. And I'm not going to put a timeline on that and you can define pervasive however you want, but. But what I have certainly observed for a number of years now is this steady progression. You see things happening in the news. You drew Tesla into that and there are many other companies also driving autonomy. Ford we're going toward a world where many of our activities are autonomous and it will change what it means to live day to day as a person in any culture. And so that's some of what we have to navigate going forward. And doing that changes the power structures associated with, with those cultures and who is influencing different things. The creators of the autonomy and with the ability to apply autonomy to certain points in their society are having outweighed influence compared to others in that. So we're definitely going in that direction. Clearly military applications, clearly many, many different industries are doing that. I've long said that there will be a point in our lifetime where it becomes uncommon for us to drive cars. And I'm not a spring chicken anymore because the technology is moving really, really fast there. And so, and we're already seeing, I mean, there are Teslas all over where people are using, you know, Tesla's technology to drive autonomously. And that's only going to get better and better across all autonomy manufacturers. So it will not take long to see crash reports that the number of autonomously caused crashes is quite tiny compared to the number of human caused crashes for driving cars, for instance. Same thing for aviation. Military has led the way in autonomy for aviation, mainly because they can, because the civilian world is still quite frightened of assuming that a machine is going to fly the airliner for them. But the data tells a very clear story about safety there and capability. So yeah, that's going to be our world, whether it's be robots or whether it be vehicles or whether it be other tools that we have in our work, in our, in our houses. This is part of our lives and the people who bring us those tools and allow them to happen will be the ones with the power, whether they be politicians or corporate leaders or whatever.

What do you think about companies that would explicitly sort of put in their set of principles that hey, we are going to explicitly build human in the loop AI systems and we're not, we're not going to venture. And maybe that's too broad of a statement, but how would you encourage people to think about that side, both in terms of the strategy and as a sort of wider reaching principle within an organization?

I think it depends on the application. It's funny, I have a lot of friends and colleagues that I have these debates with. This is what we're chit chatting about over coffee on a regular basis. And I'm going to come down with what, maybe most folks may not agree with me, but I tend to come down with opinions that aren't what I want, but they're what I think is inevitable and what I think is inevitable. And there will be many, many instances where humans and AI are interacting because the nature of the work itself is human. It requires both human and AI, not because we want it to be, but because that's what fundamentally how the work gets done. It's human centered work. But there are also many activities that don't necessarily need a human in the loop. It might make us more comfortable, it might preserve jobs, things like that, but it's not the most efficient route. And so whether or not I like that or not being irrelevant, I think that we will see that going forward where there are, where we get to a point where if it's not a human centered activity or the partnership with a human in the loop versus a human not in the loop, it just doesn't make sense anymore. The human becomes the big challenge, the limitation, performance wise in terms of speed, all sorts of things. And we will see activities that occur without a human in the loop because at the end of the day they're going to have to be. And I see that a lot. And it makes people, when I get into specifics, it makes them very, very uncomfortable at times. But I, that doesn't change the fact that I think that will happen. So there is a need for us to be very, very careful with our decisions on that. But then we're also inevitably going to have to get comfortable with autonomy all over the place in some of those cases. Not I, I know most people are terrified of the idea of getting on that airliner and flying cross country with no one in the cockpit. And I don't think that'll happen soon. I think there will be a human pilot that sits there and basically does nothing but monitor the systems with inability for an override. But that pilot's skill will be fully far, far, far below what the autopilot can do automatically. So that strictly will be done to make the humans in the back feel better. Because your backup, your human is going to be orders of magnitude less capable of handling that aircraft in an emergency than your autopilot. So that's the kind of thing that is inevitable at some point here.

Well, I do have to make a confession and that's. So this is going to seem off topic, but I've been using VIM as my editor since, you know, when. Whenever. I. I don't know, years and years and years. But I'm now. Not completely, but I'm using VS code a lot because of copilot.

There we go. I knew that was coming.

Yeah. So it's so me too. And this I think really brings home. Yeah, I'm just. I love it and I know there's mixed opinions on it, but I would say overall most people that I've talked about that have really dug in and tried to use it like legitimately tried to use Copilot, are pretty astounded with the efficiency gains and just like what you're able to do with it. So for those that aren't Familiar, Copilot from GitHub and Microsoft is a coding assistant that's sort of built into VS code and I think it actually does support other editors now, although I wasn't able to quite get it set up otherwise. But it's just amazing. Like all of those piece. Like as a human I can focus on the bits that are really important for me to logically consider in terms of how the program flows and maybe more complicated bits of it. And the other things which are like get this data from this database, like write a SQL query or whatever, like boom. It just does it like almost like really good. Like maybe I modify a couple things, but often I just actually don't because it's pretty good.

Yeah, it's.

Yeah, it is. It is amazing. And I think that that's a good example of. I really don't believe that programming as a whole is going to be automated. I mean, they've been saying this since like programming started. Like there's going to be automated things. I think there will be a lot of things that will be easy to generate, but I think that programming will not go away. That's my own opinion.

So interesting. I think programming, I mean, the way Copilot, you know, the model that drives Copilot is using all of that open source code in GitHub and there's a whole debate about whether that's inappropriate Use of open source to create a business that Microsoft's been criticized for in the last few weeks. But the fact is that that model is learning from a wealth of the best code on the planet. And so much like that airliner that doesn't really need the pilot flying the plane. And I am using Visual Studio code myself because I'm working on a project that's hands on code and doing that. So I'm coding every day. But I've got to say I don't know that I agree with you there. I think I'm starting to feel like that airline pilot who's sitting there kind of just saying, yes, I'm accepting that code, yes, I'm accepting that code, but it's just doing it.

Yeah. I think that the fundamental difference in my mind is that similar to what we were actually talking about last week is this apparent coherence that's produced by these types of models. I think perception wise, you as a human coder, I never expected it to be able to produce a function like that, but it's because of this vast wealth of data which it's able to assemble apparent coherence out of. But the bits of the things that I've seen in Copilot are the bits of things that are really like specialized logical pieces of the thing that are specific to my context still require a lot of tweaking. And I think it actually, I mean you can comment on this because you're way more familiar with the aerospace use cases and all of that. But my impression would be like an autopilot for 737 or something that is flying between known routes in the US is probably able to almost do everything perfectly. If you sort of created a new, a complete new airplane and just put the same model in the new airplane, like it's not going to work. Right. So there does still need to be this fine tuning and I think that that's where the human element comes in. Like there's still an adaptation to out of domain data. Right.

I'm going to make a stretch here and I'm not speaking literally but you know, like we were just talking about, I think last week about these visual transformers and the amazing things that they can take from the text input. And we were talking about addressing different domains where you're taking the same techniques. But what if one of those domains that you're talking about is conceiving of some of the software systems ahead? So instead of, instead of drawing pictures of raccoons, which I was really enjoying by the way, instead what if it is conceiving of software architecture for a particular problem set and then you already have things like Copilot that can go and find just the right code and to fulfill each of the, of the, the things you're trying to do there. And so I'm not saying that we're there at this moment, but what I'm saying is I can certainly conceive of putting chocolate and peanut butter together in the context of coding and, and having something that's particularly tasty.

Yeah.

So I don't know you have a point there, but I don't know if that point will survive very long. Is kind of what I'm getting at in terms of. And I love programing, I love to see human. I think it's a wonderful thing for human to do and which is why I've stuck with it off and on for all these years. But I also. It won't surprise me when there's no utility for a human to be there anymore.

I think it's one of those things that the domains in which we operate continually evolve as well. So like as soon as I'm writing code to do a thing on Mars that I already wrote code for to do the thing on Earth, it seems to me that there will be a sort of out of domain issues that are unexpected and will need kind of human input over time. And so I think it maybe is just like part of what you're saying is the jumps or the adaptations that we're able to handle now are kind of fine tuning adjustments for domain and the generalist models that are able to switch between different domains, that the switching will probably become easier over time. But also the domains that we're exploring are becoming increasingly different and big over time. So the question will be how do both of those trends evolve over time? That's a really interesting question, I think.

So I'll speculate as we're kind of winding up a little bit on to kind of bring it back to that kind of how is power shifting, you know, at the corporate or geopolitical level and the role of AI. And we're talking about these capabilities that we've been talking about over recent episodes, those who have the creative insights where they can take advantage of these capabilities and see opportunities. But you know, the thing that humans still have right now is you have a form of very limited creativity in AI. In other words, it's not self aware, but you can create those raccoon on rocket pictures now that we were talking about, which is pretty cool. But it's not sentient and it's not self aware and it doesn't have a special understanding of the overall world at all the different scope levels that we have.

Right. There's an apparent intent behind the model, but it's only a perception.

Yes. And so we still have the real thing there and that it will take a while to eclipse all that. And so there's a role for humans. And the humans that learn to do that really well and are very flexible and creative in the way they approach the world are the ones who will have the power.

So you're saying because I switched from VIM to VS Code and Copilot, I will have the power?

You are a power monger, Daniel Whitenack. You're just grabbing power where you see it. I see this in you. I understand how this works, but. Yes, but it will be those who take that and recognize something and can go do, do something new that their peers are not yet able to do that will continue whether they be in, whether they be technical or not technical people will have the power because of these resources that we have. And they will sway them at all levels from the practitioner all the way up to the geopolitical leader.

Yeah, well, I think that's a good way to sort of come to a close. Maybe one more thing, Chris, if you. Maybe there's practitioners out there that are. They're aware of what they're doing in their own, in their own company. They're aware maybe even of sort of best practices across industry, but they're just curious about maybe looking at some of the conversation that's happening at the geopolitical level around artificial intelligence just so they can learn kind of broader trends and what's being talked about about their industry at the maybe government level. Is there a place that they can go to to at least be exposed to some of those things?

Yeah, and I'll, I'll give one in a second. But I'll lead by saying that, that most large organizations and most nation states now have official AI resources on their websites and such. And so whatever country you happen to be listening in, and we have listeners all over the world, your nation has resources there for you as you and I are sitting here in the United States. And so I'll point to our own government's resource starting point is@the URL AI.gov and if you go there, it is called the National Artificial Intelligence Initiative and it was created by a law in 2021 called the National Artificial Intelligence Initiative Act. I'm sorry, of 2020 I got the year wrong there. And so it is a website where you can start to see how, how the United States government at large. This is not specific to military. DoD has a strategy you can Google. Most militaries also have that. So if you're, if you have an interest in your country or military or whatever, all of these different domains or dimensions has these resources online. If you go to the AI.gov one that the US government has, it has what they call strategic pillars in it. It has different sections with documents such as strategy doc documents and different publications and, and some of the laws associated with it. And then they all, they have other resources available. So if you're interested to see how the people in power over you are thinking about AI and how it may directly influence you and your life and your family, you should go and see what these governments are thinking. And you know what? I'm going to finish by saying participate in the process in your where you're at so that you can influence people toward the right decisions.

Yeah, I know. I mean this is, is happening at a local level too, even in my small town. We recently had a bunch of discussions locally about facial recognition in policing that were going on in our local community. And yeah, so this is happening across the board. Thanks so much, Chris for helping me learn a bunch today. It was a fun, fun discussion.

Yeah, it was.

I'll talk to you soon.

Take care. Foreign.

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