Leaders at the World Economic Forum 2026 discuss shaping agile regulations for emerging technologies in a rapidly changing digital world.
At Davos 2026, leaders debated how regulation can keep pace with AI’s rapid evolution. Argentina’s Minister of Deregulation Federico Sturzenegger argued for restraint: “My only task…with AI law is that no AI law appears,” warning that policymakers overreact to salient incidents and regulate imagined harms. He also suggested AI could reduce the need for regulation by shrinking “asymmetric information,” a classic rationale for oversight.
The UAE’s Mariam bint Ahmed Al Hammadi described a contrasting, systems approach: after updating 90% of laws in four years and repealing 100+, the UAE is building an “intelligence-led regulation model” that listens at scale to social media, courts, and service delivery data, while preserving “rule of law foundation and constitutional safeguards.” Principles include traceability to a legal basis, privacy, transparency, and “human accountability…AI can advise, but still human is in command.”
Meta’s Joel Kaplan emphasized enabling conditions for AI—“talent, data, compute and energy”—and praised US efforts to remove barriers, including permitting reform and copyright rules that “ensure access to the training data.” He cautioned the EU AI Act “risks the EU falling quite far behind” by targeting technology rather than harms. NTT DATA’s Yutaka Sasaki underscored trust, sovereignty, and the need to manage “hybrid AI” across public and private models.
Hello, I'm Nicholas Thompson, I'm CEO of The Atlantic. I'll be the moderator today. We are going to have a fabulous conversation on regulation of technology and AI and deregulation. My hope is that at the end, we have a little bit of common ground, people with very different backgrounds from what laws should be changing, what needs to change structurally to get that done and what happens next. So let's introduce this absolutely marvelous panel, starting here on my left with Mariam bin Ahmed Al Hammadi. She is the Minister of State, Secretary general, UAE cabinet. Joel Kaplan, chief global affairs officer of meta. Yutaka Sasaki is at the end. Even though I wrote it down. How are you doing? The present CEO of NTT Data and Federico Sturzenegger, who says that you can pronounce his name just like his, Uncle Arnold, the Minister of Minister of Deregulation. Best title on this whole panel. Kind of amazing. Are you the first minister of deregulation in Argentina?
Yes, I guess so. And, you know, when we started thinking about this with President Milly, he said, well, maybe we should be the Minister of modernization. I said, no, no, no, because the state doesn't modernize. The state pushes you backwards. So so it would be we want to improve the state. That would be the backwardation, Minister. And I think that sounds very good. Okay. And also the president says, I also don't want you to be the simplification minister, because I don't want you ever to think about simplifying something without asking yourself before, if that thing that you were about to simplify should exist in the first place. Okay, so we kind of ask a deeper question, and that's how we got to the deregulation name.
It's so cool. It's a cool way to actually push policy and perception through titles. Yep. Yeah I'm going to start changing all the titles at the Atlantic. All right. So let's start with Minister Al-hammadi. So you have changed a remarkable number of laws in your country. I believe it's something like 85% over the last 90%. 90%. I was out of date. I googled this three hours ago. So 90% of the laws explain. And it's in the last three years.
Four years.
Four years explain the most consequential and interesting changes that you've done for tech and for AI.
There was a direction from the leadership in the UAE that, we need to, relook to our laws. When I'm saying about regulations, we have different layers of regulations. Now I'm talking about the first layer, which is the law itself. Yeah, we have laws that is, was valid since 30 years, 40 years, 50 years ahead. So we we need to know we actually did some type of deregulation. In terms of that, we look to our regulations and to see which one of them is still valid and which one of them we need to repealed. So there was, hundreds of teams working parallelly under the supervision of the cabinet in the UAE and all the teams they working because, as you know, United Arab Emirates is a federal country. So we have, laws at the federal and whenever we do any law, we have to coordinate with the federal entities and with the local governments. Also, we have seven local governments. So actually the process was, we were struggling a lot, but everyone has the same vision because we has been cascaded from the top to down that we need to do. That changes. And, we could within the four years, 90% of our laws have been updated. We did massive revolution in our regulatory, framework. 90% have been updated. We have repealed more than 100 law. So in terms of I was before the session, I was talking to the Minister of Deregulation. I say, how many regulations you have deregulated? He said thousands. I said, how come, how how many thousands you can do it. Then he explained to me, I said, is it low? He said, the number of the articles that they have, removed. And if we talks about the articles, even though in United Arab Emirates, thousands of articles have been changed, have thousands of them have been, modified. And to do that one, actually it took a long effort from us and then we thought, six years, six months back, how can we use AI to do for us that revolutions? Yeah. So we don't do it again as manual. And here there was a project has been approved by the, leaders in the UAE that we want to develop, intelligence led regulation, model. We need a model. Is it? Somebody will tell me the first time. Are you going to use, AI tools to draft for you your laws? I we said no, we need more than this. We don't want only, for example, ChatGPT to draft for us a law. However, we need to have a model that listen and speak to the social media. So any law that we issue within the UAE, we need to listen at a larger scale to all our stakeholders to see what is their comment or what is their feedback about the law. So anything that and then with the AI to analyze that one and to tell us that article that law needs. There is a lot of comments, positive or negative about it. And then he will suggest for us what changes we have to do in that specific law. We need that model to speak to the court. So we want to assure that the law, when it goes to the court is being implemented. Right. So the court ruling, is it compatible with the law or not? We need also a model, that speak to the service that is delivered to the customer and stakeholders and our investors to see if our requirements that we put in the regulations. Is it complicated? It is too much. Is it less or more? So we combined all these features in the project that we are working with one of the AI company, yesterday we have launched the first white paper about where what we have learned so far in this, project. And we hope that, within the project is two years project, we have a model that can be shared with all the government worldwide. They can share, they can learn from it. And there will be a lot of case studies about it.
Fascinating.
That,
Interesting stuff. Lots in it that I want to get back to. But let's go to Minister Sturzenegger. You've knocked out even you haven't changed 90% of your laws, but you've knocked out.
13,000 1300.
And what was the most consequential and beneficial when it comes to AI?
Okay, let me see where to start. We started working two years before Millie became president. We reviewed all the laws of Argentina and we classified them laws that had to go to go, laws that were okay and lost that change. And we had all these things prepared by the time he became president. And this is why what allowed us to make such a swift reform in one year. So the regulation requires some preparation. Correct. Now, we didn't have an AI law, so I didn't have any AI law to deregulate because there was nothing. So my only task in this moment with AI law is that no AI law appears. Okay. So we want Argentina to make sure and give the message that we do not want to regulate AI.
So you added a regulation?
No, no, we don't have we don't have. So I want to make but all the all the congressmen, they all want to have a law regulating artificial intelligence.
Isn't it a law saying we can't have a law.
Well, well, if you want to put it that way, yes. We don't want to. We want to have we don't want to have anything. Okay. Just call that as the way you want. Then I think actually two other questions, which I think are interesting in the relationship between regulation or deregulation and artificial intelligence, is will artificial intelligence change the need for regulation at large? Let me give you one example. One of the reasons we regulate some sectors is something called asymmetric information. So for example there's asymmetric. The financial sector is regulated because you think there's some asymmetric information that depositor doesn't know about the bank. So you have a regulated system which kind of provides the guarantee etc.. So asymmetric information in many areas of economic activity you have asymmetric information in many markets is the justification for regulation. Now I say if artificial intelligence gives us a lot of knowledge, doesn't it solve itself the asymmetric information problem. And if it solves asymmetric information problem then we don't need to regulate that. So so I think there's a relationship of artificial intelligence maybe changing the need. This is a question I'm just posing. I'm just proposing the debate. But I think it may be the case that it may, eliminate the need for regulation in certain areas because it will help solve those issues that the regulation was supposed to to, to solve. So I think that's an interesting line of thought. And then the third one is a can we use AI to generate the deregulation, which is a little bit what the minister was just mentioning. And we really haven't gotten in that way there yet, because the reason is we're not so much in the business of rewriting regulations, but in the business of removing regulation, because sometimes we have this fantasy that regulation and an economy is built like by a well well intentioned central planner, you know, some bureaucrat thinking about how to do good to society. Well, of course, this may be different in different countries. In the case of Argentina, my finding is that most of the regulation is not the result of a benevolent central planner, but it's the result of interest kind of people you see in the state as a way of building a regulation, which at the end of the day is like a ring fencing competition, generating privileges.
Deregulation also comes from interest to.
Well, I mean, if the regulation is the result of which is what I find in Argentina, which regulation is the result of some sector which has been able to generate something, which blocks entry, which is really what we're going after. Then in that case, deregulation is a is really kind of a an obvious choice.
Okay, sure. You, you're clearly a man in favor of deregulation. I've talked to you about it before, representative of the United States. Our president was just on stage talking about was 130 laws. He cuts for everyone, he adds. But what are the laws that you like? Right? I know that like section 230 of the Communications Decency Act, that law doesn't exist. Facebook's got a lot of problems, has got a lot of problems. What are the other laws that you think are important to keep?
So, first of all, I just want to say that what both of the ministers said was really fascinating to me because they're examples of people who lead organizations who are already thinking deeply about how AI is going to change, either the way that they conduct the work of their organization or or have implications for what the substance of the work is, which is what every organization over the next couple of years is going to have to do. And the ones that succeed, whether they're government agencies or whether they're businesses, are the ones who start thinking now about how AI is going to change their workflows and change the nature of the of the work that they do. So I really I thought it was really gratifying to hear both ministers on that front. Is your question about regulation that we like on AI generally or on AI in generally.
Not like speed limits? I mean, like.
Yeah, well, there are some, you know, for in the social media part of our business that we can talk about, but not here. So look for for to power AI, you basically need four things. You need talent, you need data, you need compute and you need energy. So you have to have a regulatory environment that ensures access to all four of those things. And for the most part, what we've seen in, in the US under President Trump's AI action plan is removing barriers to innovation across those four key areas. And I think that largely is what's necessary to unleash the investment. And the progress that we want to see on AI and that the president correctly views is, is necessary to to win the battle, the most important national and economic security battle that we face right now, which is, which is the AI race, and in particular against China. So the AI action plan, you know, removes barriers to innovation across federal agencies. It ensures energy and data center permitting reform. So, you know, reforms are possible. Some of those reforms are positive laws in terms of, you know, what they require agencies to do and what time frame to make sure that you can actually get the electricity generation plant that you need for a data center built, you know, as it you've got China built, 440 or put into, put into, performance, 440GW of power in 2024. And the US did about 50. That's a huge advantage that China has. We need to be much better about that. So we need to put in place, regulatory structures around energy and transmission, grid permitting. That's the kind those are the kind of laws that I think are very positive. We have to have laws. I know this isn't necessarily popular at the Atlantic, but we have to have laws around copyright, that ensure access to the training data.
Make laws around copyright fair access. And we have laws on the other side.
Ensuring access to data for the training. The models depend on having access to huge pools of data. And any country that doesn't ensure that that's going to be the case is going to be left behind, because their data is not going to be included in the training models. And so, you know, if you want, you know, if you're if you're another country that's worried about AI sovereignty, really what you should be worried about is making sure that the large language models that are developed include data from your country so that the models reflect, the culture and interests and, and expertise from, from your people. So those are a couple of examples of areas where I think, you know, you do have to have kind of guardrails, but but really the guardrails that you put in place are to make sure that you have access to the things you need to power, these data centers.
Great. I'm all in favor of regulations that respect the licensing deal that you and I are going to strike right afterwards. You talk, will you respond? Your your business leader. You operate in all these countries. You you operate in 50 different countries. You have.
Yeah. Yes. Yeah. Over 50 countries.
So actually let me ask you this way. How do you feel when you hear Argentina's deregulating everything? Because what you want is you want clarity and similarity across regulations, right. Explain how you felt listening to all this.
Yes.
So you felt good.
Okay. Yeah.
Our position is so that we accelerate the business with using AI, and, but we need to align with the regulation. And today that we have a to the government side people and the two business people. Now our position is a very, very business side. Yeah. And I think we need trusted. So an environment. Yeah. And by the people. Yeah. By the sole employees in business use cases and I think, we we are not only the IT service provider, but also the data center provider and, data center. It's so easy to be regulated. Yeah, it's a very laudable rules and something that are related to the power supply. Yes. Of some environment issues and cloud layer alignment layer. And the applications that will be the. So, very the difficult to be managed by the regulation. Yeah. And I but the in the business use cases that we need to establish trusted infrastructure. Yeah. And that's one, one of the key words is sovereignty. Yeah. The from the government view, the from the big companies view, the we need to manage the confidential data that they are reluctant to store their confidential data in the public eye. And so we the we need to manage that their confidential data in the sovereign the cloud or sovereign AI. The in the AI case, we're calling the private AI the we of course we need to use the public AI. Very intelligent. Yeah. The and employees that would like to use public AI. But in the future we need to establish private private AI and in the future. But we will manage hybrid hybrid AI. The combination between public and private AI. Yeah, that will be the very trusted environment.
That that that that makes it. That makes very good sense. Minister Al-hammadi, will you talk a little bit more? You mentioned this public feedback, which I think when I was listening, this is one of the most important issues because one of the hardest things with AI, certainly in my country, is how little people trust it like they don't. I love AI, I think it's amazing. I use it all the time. It's awesome. And like most people hate it, right? So you need or not most a majority. You're building trust in part by having feedback on everything you do and building using AI to help get comments. Explain a little more about that because it's fascinating.
Can I zoom out a little bit?
You can zoom out, you can zoom in, you can pivot sideways however you want to answer it.
Okay, okay. Because that is only one angle. When I spoke about the model that we are developing in the UAE, there is you know, with the AI always, you think that we will have more agile, faster regulations. But actually there are some of the principles that we put in the model that we are developing that we cannot compromise, which is the, the rule of law foundation and constitutional safeguards. Let me explain. For example, equity before law. We have we are not allowing, that fast to become a bias. So whenever the model or the AI tool is giving us any biased or harmful outcomes, we have developed in our model a mechanism to stop it. There is also the rule of law. This is one of the principles that we put it in the AI model. We need all the AI output to be traceable to a legal basis, not only to statistical patterns. There is also, fair, procedures AI can detect for you. Gaps can tell you about the recommendations, can give you outcomes, can analyze, can tell you the red flag risk. But it will never, bypass the procedures. I will tell you, for example, AI can tell us the non-compliances, but it will not impose penalties on the community. So this one is not allowed is one of the principles that we use it in developing the AI model. We have also, as the professor was saying, we have put the principle in the model that we have it regarding privacy and data protection. So we have we need to ensure that one, because as I said before, we are dealing with massive number of information. It's related to federal, local court, economical, social. We have many datas. We have to ensure that we need to tackle with them in terms of quality. We need to ensure that data, data we have it is quality, and it is consistent because if we don't have consistent we we will not have, a good AI, model that will help the government. So we need to lay out, the, the ground to ensure that we have quality data available. So AI model for the regulations can work perfect. There is also something also, the principle is transparency is very important for us that here we say here AI transparency can add tremendous value for us, where it can strengthen, the consultation process at a larger scale in a very short time. And here is the, the feedback of the stakeholder and our, investors. We can listen to them at a large scale using AI tools. And also, there is one of the principles that we have put in the model is the, human accountability. Still, we believe that at this stage AI can advise, but still human is in command. And this is very important for us at this stage.
Great Minister, you wanted to respond.
I want to touch on the question you just made. First of all, a quick remark on the copyrights. It's a kind of an interesting legal issue because we, for example, buy a book and we pay the copyright for it. Okay, but if an AI reads the book, it becomes the book. I mean, it can replicate the book perfectly. So so I think, how do you solve the problem of property rights that once you read it, once you become the book with perfection? Anyway, it's a question there.
Who knows? We've sued some AI companies and the courts will decide.
We'll see, we'll see. Exactly. But look at this. Look at this. Alejandro parrot. Parrot. That parrot. Okay, so now imagine that he's a robot and he's obeying my orders. Correct. And the. So in a few years, we're going to have people going around like this and they're going to be robots, so we'll have.
To I don't know. In fact.
We don't know if we don't have some here. So he's human. He's human, by the way. Okay. He was just being friendly with me. So we have to build a legal framework for this guys. Who's responsible for the actions? Because the robot goes out and goes out and who's going to be responsible? Okay, so we need to build a framework. So that's an interesting I don't think it's a very complicated I mean there's someone is going to build a robot and then it's going to sell it to someone and that someone will take the responsibility. I guess that's it. But I think something that happens is interesting is that in regulation theory, you have something called saliency or I call it the Baltimore effect. Remember this boat that crashed the bridge in Baltimore a few months ago? Well, the road crashes, the bridge pulls down the bridge, and then you change all the regulation on navigation. And there were 1 million boats that were going. Never. No one crashed. No one crashed a bridge. So the saliency is the politician reacts, feels that they have to react to a salient event and then regulate and impose a tremendous cost. Okay. And I say people make mistakes all the time. But I think that if Alejandro were a robot and he would make a mistake, people would immediately jump and say, oh, we have to regulate the robot so that this doesn't happen again. So I think also.
It's part of your job in anticipating future demands for regulation and preemption.
No. Well, I think that's a trap because most of the most of the regulators, they they are very imaginative of all the terrible things that will happen to people if they're free. Okay. And I tell you, the imagination is I mean, you can be the, the it's better than the best novelist, okay. In the world. No, I think we have to be in that sense. We have to take more risks. I mean, we have to see if something left free generates a problem and then react to the problem, but not try to solve a problem that we didn't even know that we have. So I think but I think this is important because this question will come over and over again as AI starts to move into different activities. And I want to finish with one thing I'm sure you'll appreciate what I'm going to say now, which is the latest the resistance to AI. Okay, so what's the so the the last you know, you have this book by Isaac Asimov called iRobot and the last, it's a series of stories on kind of robotics and artificial intelligence written in 1960s. I mean, you read this thing today and you kind of blows your mind away. So in the last story, it's about a political campaign, and there's a guy who's a very good politician, but people are suspicious. He's a robot. So you have a debate in society whether we should allow. And then the politicians know we can't allow having a robot being a politician. And other people say, no, wait, wait a minute. Maybe it's better. You know, these guys are fair. These guys work. 724 they're honest. So I think but but you see, I'm seeing artificial intelligence coming into lots of mechanisms. And I think we're going to have a lot of resistance from the people who somehow are left to the sides because of artificial intelligence. We may not have industrial jobs in ten, 15 years. Correct. And so I think this is we have to be aware that we need to resist this fight against the implementation of AI, because if we don't, we would still be using candles, okay, because the candle producer would have protested because Edison invented the light bulb and we would.
Not fight against maybe. Joe, you can I would imagine that you agree philosophically here, but let me ask you. So, you know, some of the regulations we just heard about, like, let's have a right to privacy for citizens in the UAE and let's build that into the AI we have. Let's make sure there's some protections against harms. Are there not a set of regulations that can build trust so that more people use it? And actually the benefits spread throughout society?
It may be that there are new regulations that are necessary as the technology develops. I think the risk is that and we've got some real world examples of this. The risk is that imaginative policy makers are much more focused on the risks and the potential harms, and much less focused on the benefits of innovation and the benefits to the economy and to growth. I think we've the model we've seen the clearest model we've seen of that is in the European AI act. The AI act. You had there was work underway for a long time on the on the regulation. The regulation was, was technology neutral, focused on real world harms. And then ChatGPT came out and immediately, the, the EU, changed the focus of the regulation and began actually directing the regulation at the technology. And as a result, you've got you had a piece of legislation passed in the EU that was very harmful to innovation, that I think really risks the EU falling quite far behind in this new technological revolution, in much the same way that, unfortunately, they become less competitive over the last 40 or 50 years because of regulation. And it was largely because they were they were very focused in those early moments on all of the possible harms that could come from the technology itself. So I think waiting to see whether, you know, what kind of robots are developed and which, which harms they create, possible harms they create. And then deciding, do you need to regulate against those harms and figure out who's going to be responsible for it and legislate that way? I think is the right approach. Rather than just regulating the technology on the basis of all of the possible harms that you might imagine.
You talk. Do you have the same analysis of the EU AI act?
Yes. Yeah. The we understood EU side that they have a hard law and the compared to the EU and the United States side are soft law. And in Japan also we we have soft law and we need to align the region by region. And I mentioned and the private AI or the AI that we will have, lots of models in the world in the future and I believe so, the, the AI edging AI model, is is a different from the conventional ID systems, the conventional traditional IT systems. It's a very programmed. Precisely. The input and the output is a fixed. But AI models, you know, the the prompting and but and sometimes the various answer and it's written. Yeah. And I think the conventional IT system, it was easy to be managed. We can manage the the traditional IT systems. But AI is a different it's a very difficult. We need to monitor the performance and the quality. And that is a very important. And managed services will be very necessary in the future. Yeah.
Minister Sturzenegger, so one of the things that you mentioned is that or not that you mentioned, but that you've said in the past is that concentrated markets are good and that you should let companies get as big as the market will let them get. Are there any areas where you believe there should be competition policy to try to prevent, say, you know, a company that controls one side of the market from using that power to get dominance in another?
No, we think there should be competition policies, but competition policies should be focused on entry. It should not be. It should be focused. I'll give an example. For example, in European markets you punish someone if they charge kind of way above the market prices and they're a dominant firm. So I say imagine an airline that flies a certain route and they're the only guys. They're dominant because they're only one. They have 100% of the market and they charge an exorbitant fee. I think they have no competition problem there because anybody can enter into that route and fly that route. So in fact, you want a high price to entice other people to come into the market. And it's a paradoxical we wrote actually, we wrote an op ed in The Economist with the president on exactly this question that you're asking, which which came out last week is there's a paradox, which is most of the time, the restrictions to competition come from regulation, because regulation kind of erects all these barriers to entry, which make it more difficult. So so I think you need to have, of course, if you have firms colluding to exclude other players, that certainly is like the US antitrust approach to I think that's perfectly and should be applied, but I think we don't put too much attention to the need to make sure that the government is not itself responsible for generating the barriers to entry, which are responsible for, for, I think, markets which work less. I'll give you an example. Nokia, BlackBerry iPhone. So imagine that at some point we said, look, BlackBerry has two largest share of the market and we should kind of split it out and split it into parts, etc. I think it would have been a terrible mistake. We didn't actually have a competition problem because a third player could come and compete and challenge that market. We call it in economic theory. We call it contestable markets. So as long as you have a contestable market, I mean, if you have an increasing returns to scale, which reduces the cost. Well, as a society, we want to produce at a lower cost. So you want to profit from that, but always making sure that, for example, these guys, that he can be challenged by anybody. Okay. And that but to the extent that no one challenges, you have to let them run. They're increasing returns to scale and their efficiency. So that's kind of our approach to the thing.
To be clear, we feel like we have very fierce competition.
As I read in the government's complaint, Pniewy and.
The district court agreed.
Let's talk a little bit about the US-China competition, Joel, because it's quite interesting given the AI competition, which is one of the most interesting stories in the world right now between the United States companies and Chinese companies. How should the government take that into account when setting regulations? China clearly has an entirely different regulatory framework, and it's not one that's fully deregulated. Explain what U.S. administration should do to to make sure that America is maximally successful.
Yeah, I mean, I don't I don't want to sound too much like a broken record here, but, I mean, I think the the AI action plan was designed exactly that.
And also, I think another element that is so important is open source, which is the area where China. Let me rephrase the question. One of the most interesting critiques of American regulation is that it made open source AI much harder and in fact ceded that to China. What could have been done differently to prevent that outcome?
So I actually I actually don't think that ultimately happened. I think there was a real risk that that was about to happen. We actually I mean, the first real, you know, powerful open source large language model that was released was ours was the was.
The framework for deep seq.
Yeah. And and it saw, you know, wide scale adoption. We released an open source model called Lama. And the Lama models have been downloaded 1.2 billion times. So that's an incredibly democratizing, effort, right, because that means that developers all over the world, academics, universities, governments all over the world have access to the to the output of these incredible investments that that meta made. Right? It's it's very capital intensive, as you know, to build one of these large language models, we open source it then everybody has access to it for free. That's what it means. So, during the Biden administration, that was really just we released Lama, I think in 2020, 23, time frame, early 2024. There was a lot of debate and discussion within the Biden administration as to whether open source was too risky, good thing or bad thing. We believe for any number of reasons, including the democratization, diffusing the benefits of open of of AI across populations and regions. And and from a national security standpoint, we thought that there was a real benefit to having the the global standard for building on top of AI to be set by a US company with US values embedded. The Trump administration ultimately embraced that position, and that's reflected in the AI action plan. So the debate about whether open source is is a net positive, I think has been resolved in the United States in favor of open source. And I think that's a good thing. Now, the Chinese, you know, whatever it was a year or so ago, Deep Sea came out with their open source model. It was quite good and quite competitive. And and it's achieved a lot of adoption since then, as have a couple other Chinese models. So there's a real, I think, battle still for where the global standard is going to be who's whose technology. The global standard is going to be based on. But I think fortunately that was an area where there was a real risk of the government, really hindering the spread of, you know, Western values in the technology. But I don't I don't actually think at the end of the day that that was why the Chinese ended up having, having some good entrants in the open source.
Entrance and more downloads on hugging face than American companies. Minister, when you listen to the minister from Argentina. Right. And you listened to him, you know, taking a chainsaw to regulations, do you wish you could do some of that too? How do how do you respond to him, do you think? Great job. Let's do more of that. Or do you feel like maybe that works for him? And I've got something else that works.
For me. I have a meeting with him tomorrow, 8:00. I want to ask him a question straight forward in Argentina. Is there any regulation?
Is there any regulation? Yes, yes, there's a lot of regulation.
How many?
I still have a lot to cut.
I think, I feel that the whatever is being done, for example, in the UAE or Argentina is very close because, it's it's only the name, His Excellency using the word of deregulations. And, the aim of us, whenever it was four years back, that we want to eliminate any law that is not valid for us at the same at that at this time. Maybe it was good 20 years back or 30 years back, but now it is maybe not valid for us. So actually we did deregulations, when we look to any law, we look to the clauses of that law and we tried to deregulate the requirements, which is unnecessary. And we try to, to make it compatible of the changes that are happening in different sectors. And that's why I feel that, any country that is working into, laws or regulations, reforms, actually, they are doing deregulations by, as, as at the heart or as a center of the reform they are doing. One thing that also, Mr. Kaplan was saying that the, the, the people, I feel with the AI or with the age of the AI government should not resist the change. Now, actually, we have to invest in our people. And that's why in the UAE, we are now preparing the new generation of the legal professionals. We need our legal to be blend between the law and technology. We need to have regulatory, data scientists, that can handle the data, understand the data, and from the data they can know how the law is being performed in, in, in the in the real. We need to have, a regulatory, knowledge engineers who can convert the complex law, complex law text to something knowledgeable, something they can people can understand it. And this is actually what we are doing now. So we can have a system that we can work on it. And the same thing, our professional legal can also handle it. And this is actually what should we do.
Can I get a 200. Can I get a 200.
Yeah.
You can counter.
No, I'm saying I mean the process of the regulation is different in every country. I think in the case of Argentina, it's so extreme because we build a status quo society where interest groups have captured the state and had built a regulatory framework which was built in privileges for them. And I'm sure that it's totally different in her setup. So so I think we can be we have to be much more aggressive in the regulation because much more of the law has this kind of, the original incentive objective was not really the one that you want for a society, which is more just and growth enhancing. I just wanted to make that clear, because if not, it seems that kind of I'm proposing that the regulation for I think every context is different. I just wanted to clarify.
That we need to understand, so the we need to have, various regulations in aligned with each country, countries, each regions, the culture of some rules. And, the you mentioned. So we need to think about the relationship, the regulation and the innovation. Yeah. The if a strict regulation that sometimes prevent the speed of innovation. Yeah. And so that we need to have a balanced. Yeah. And innovation will give the benefit for the people. Yeah. And so strictly to strict regulation we need to see the worldwide use cases. Yeah. The for example it's a very so simple use case. Covid 19. That was very various response in each countries. And we that studied the which countries use case was the best. Yeah I think AI technologies is very evolving rapidly. And the common understanding will be very important. And the technology that literacy. Yeah the regulation regulator side and technology innovator side that we need to have the common understanding the food, the latest technology of AI. Yeah. How do you think. Yeah.
Let me ask a question because we have one minute left and I can't resist the temptation. But Minister Sturzenegger, we talked about how we're going to regulate robots. If there was an AI that became much more capable than we have right now, and it could really take into account public opinion, and it could listen to all sides. And like the UAE's AI, it understood the law and was so much better than the president. Would you cede decision making to this AI?
Well, through a democratic process?
I mean.
What are you asking me to know through a democratic process? This is the example I was giving.
It would be hard for it to be elected. So, I mean, I don't know what the constitutional rules are in Argentina, but if you had this, you know, on your desk, would you say, tell me what to do? I'll follow it.
Well, maybe I can do it as an official. I can take opinions, but we have a democracy, and that's the way we elect our rulers. In the story of Asimov, it was a democracy and it was an elections. People at the end decided, well, let people decide if they want to choose a robot or not. I won't tell you how the story ends.
Yeah.
All right. Thank you very much. We're out of time. That was a fabulous conversation. Thank you so much, all of you. Wonderful to share.
With you. Thank you. Mr.. Thank you.