[0:00:00] Every day, animals across the country face abuse and neglect. And every day, the ASPCA shows up to rescue animals in crisis. But they can't do it alone. Visit aspca.org slash need. Become a donor today to provide the care and shelter these animals urgently need. And for a limited time, the ASPCA will send you a free gift as a special thank you. Visit aspca.org slash need.
[0:00:30] Plastic bags, plastic lids. What do we do with you? You can't go in the recycling bin, but you can be recycled if taken to a new RecycleOn center. Find one near you at RecycleOn.org slash Oregon centers. I can remember when the internet felt like a promise and everyone bought in. It spans the globe like a super highway. It is called internet.
[0:00:57] Anything and everything. Free music, new friends, pet supplies, just a click away. Internet is that massive computer network, the one that's becoming really big now. Bill Gates himself had to go on late night TV to make it make sense. What the hell is that exactly? Well, it's become a place where people are publishing information.
[0:01:21] Everybody can have their own homepage. Companies are there. The latest information. It's wild what's going on. You can send electronic mail to people. It is the big new thing. Back then, the internet was new, weird, and hopeful. Now? Today, U.S. tech stocks plummeted after China introduced a highly effective AI program called DeepSeek that could make American AI obsolete. That story again, AI is afraid of losing its job to AI.
[0:01:55] Ever since ChatGBT was released to consumers back in 2022, it seems like every day there's some new creative use for this technology. So you might see a White House-generated Studio Ghibli anime-style meme mocking illegal migrants, or watch robots doing surgery. So today we're going to talk to someone who has been at the heart of the industry for more than a decade, the CEO of Microsoft AI, Mustafa Suleiman.
[0:02:22] on the next era of the tech industry and about what it means to hold on to your values when the industry is moving faster than the rules meant to govern it. I'm Adi Cornish, and this is The Assignment.
[0:02:43] Full disclosure, I use a ton of AI chatbots, ChatGPT, Claude, Perplexity, DeepSeek, you name it. I have tried it for everything from researching family vacation ideas to researching this interview. At the same time, not a day goes by where I do not see a news story about the concerns people have about the technology.
[0:03:05] The effect of its power-hungry data centers on the climate. Its potential to displace workers the way it's used by law enforcement and militaries. So here's an example at a company event for Microsoft's 50th anniversary just last week. Shame on you! You are...
[0:03:22] Microsoft AI CEO Mustafa Suleiman stepped on stage and was met not just with applause, but with some protest.
[0:03:37] As the AI chief at one of the largest technology companies in the world, criticism comes with what is a very big job. He leads all consumer AI products and research, including Copilot, as well as Bing and Edge, with tons of major corporations already using it in their work, from Banks to BlackRock. But he doesn't have the typical Silicon Valley origin story of a student engineer tinkering in the garage.
[0:04:03] Suleiman is the son of an English woman and a Syrian father. He entered adulthood in the aftermath of the 9-11 attacks. I think many people were going through a difficult transition at that moment. He was a student at Oxford. Because they're often immigrant parents, didn't understand what it was like to grow up feeling British and being British, having been born in the UK, but also having a kind of cultural and religious context that wasn't really understood by anyone but your peers.
[0:04:32] He was raised Muslim and he understood. So he and a friend launched a telephone counseling service, the Muslim Youth Helpline. And so our approach was really to try and put...
[0:04:43] A peer-to-peer support service around young people rather than having to rely on their elders in their community who are often quite judgmental, didn't understand the issues that many people were facing with respect to their sexuality, for example, or respect to having relationships before marriage or starting to drink and stuff like that. And so there was so much taboo and pressure and it just felt like a natural thing to do. It's just find ways of talking to heal through understanding.
[0:05:12] Heal through understanding. That instinct to listen, to support, to help. It's the thread he says runs through everything. Throughout his career, founding companies like DeepMind to Inflection, he's always talked about potential regulations, but also values like empathy in AI. Now at Microsoft, he's overseeing the next generation of what he has sometimes described as a digital species.
[0:05:38] You know, for the first sort of seven to 10 years of DeepMind, so 2010 right up to sort of 2020, most of the progress we made was in the context of image understanding and image generation, video understanding, video generation. What can it see? What can it make? Exactly. What can it generate on its own? Right. And could it play these games and optimize score in a game? In 2015 or 16, I actually worked on some research.
[0:06:06] on natural language processing to try and predict which word would come next in a sentence. With these very same neural networks that had been successful in gaming, we thought, well, maybe we could apply that to the space of language. And we made some good progress, made some good contributions to the field, but it was clearly too early. But my dream was always to be able to model language, because language essentially is the real descriptor of culture.
[0:06:31] And shapes it. I mean, some of our biggest culture war fights are about what things are called and the way they're talked about. And so this question about what AI is going to do is very compelling to me, especially as a journalist, because bad data in, bad data out. And I've just watched a bunch of years of terrible internet, basically. And, you know, I have doubts.
[0:06:55] And yet language is also the thing that inspires us and motivates us to be our very best selves, right? And delivering that with kindness and empathy, I think, is one of the most scalable ways to positively impact the world. So the stakes are high, but the prize is also amazing. You've shared in the past this story of, at the time, your six-year-old nephew asking you what AI was.
[0:07:19] Because usually on the internet, people say, tell me like I'm five. So tell me like I'm five or your six-year-old relative. What is AI? How do you define it to the average person? One way of thinking about it is that an AI is really there to perform tasks on your behalf. It answers questions, explain things, collects information from across the web.
[0:07:40] And is it a program or an algorithm? Yeah, that is kind of the key question. So for all of computer history, we've been designing rules that computers follow very precisely. Like a relational database is a way of storing information. You put a bunch of information in, and then when you want to access that information, you get exactly that same piece of information out. With these new models...
[0:08:04] We actually teach them to learn their own storage mechanism, which is these neural networks. They store information in a way that is much more associative. Every word that goes into the neural network has a relationship to all the other words based on its experience of all words that it's seen in the training data. Now, as a human, that means I'm also associating it to my past traumas, things my friends have said, the way I've been raised.
[0:08:31] Machine doesn't have any of that unless it's getting the data from the internet, I assume. All the things we've collectively put into it. Is that how I should understand this and its limitations? That's exactly right. And that's the beauty of it. We want it to learn the subtlety, the nuance. We want it to be creative. People often say these models suffer hallucinations. They make stuff up.
[0:08:56] Well, actually, they're designed to make things up, right? We want them to tell us something that we don't know. We want them to imagine the space between a zebra and a fish, and then generate a new image that is in between those two points. And that's always been the limitation of old software. Old programming has been structured, heuristic-based, logic-based, rigid. This is flexible, adaptive, creative. And that's actually the great ambition.
[0:09:26] We're pursuing models that teach us something that we don't know, that give us a novel and creative answer on the spot. Is that like the human brain or not? You know, I think it's reasonably similar in the sense that when I say the word dog, your mind's synapses.
[0:09:48] are firing in hundreds of millions of directions. The sound of the word, the touch that you've experienced in the past, the idea of a dog both as a protector and a companion being silly. And likewise with these models, they have a similarly neural representation rather than a XY, you know, cells in Excel kind of relation, which is a relational database. And so it isn't...
[0:10:15] Exactly like a human, to be clear, but it's got some similar elements. While we're on this, there was this moment from the top executive at Anthropic that does Claude, which is one of the AIs, and he was saying that they were toying with the idea of maybe an I quit button that the machine itself could deploy if it didn't want to go through with a command and that they might track how many times it...
[0:10:40] It happens and what they would learn from that. And I thought of it and I thought of your claim of a digital species. How do you think of something like that? Would you ever consider that for Copilot?
[0:11:10] Corporate ownership and then national regulation. I think that's going to be the key thing to be able to steward this in the right way over the next few decades. But can the species have the right to say no? You know, species is deliberately not a literal representation. It's a best effort to try and make sense of something that's new. It isn't a species. It just has some elements of what a species might be like. And it will have lots of...
[0:11:39] But is that the kind of test to figure out what those characteristics might be? It could be. Yeah, certainly. I mean, it's very interesting to look at. We've focused very much on its IQ, right? So we're trying to get it to be factually accurate, very comprehensive knowledge.
[0:11:59] Reference citations so that you could look at the evidence base behind individual claims. It's getting better at its emotional intelligence. It can sort of mirror and be empathetic and supportive and so on. But there are some amazingly interesting qualities that it doesn't have which are good. For example, it doesn't have guilt. It doesn't have shame. It doesn't have competitive ego, right?
[0:12:27] There's no intrinsic desire inside of it, right? So it's not compelled to do anything other than just predict the next word with respect to the behavior policy that it's been given. And yet humans have all these underlying emotional drivers that form our behavior and our words. And so we're now designing these models without a lot of the weaknesses that we have as a species. And to me, that's what originally motivated me to try and...
[0:12:55] We're talking about the idea of containment. And that gets me to the idea of guardrails. Yeah. What kind of guardrails should there be? Because we are in a moment where we've literally seen them rolled back. Yeah. Yeah. This is a really tough one. I mean, there are guardrails. We have to think about guardrails at...
[0:13:24] All scales. At the lowest level, you described a proposal to put guardrails around the model itself. So in the machine itself. In the machine. Does it have a way of saying, I can't reason over this problem. It's too complicated. I have to exit. And then what's the next consenting ring out of that? Right. Beyond that, it's like, does the machine have the ability to self-improve itself? That would definitely be an area where there's going to be more risk. Can it edit its own code in real time?
[0:13:51] Then there is a question of what is the objective function of the machine? What is it trying to do? What is its motivation? And that speaks to the business model. Is it aligned to your interests? What is it actually trying to do? Do you feel it's accountable to you? Can you direct it? And then what is the motivation and the kind of governance of the company or the lab or the organization that's building it? That's a really important question. And I think this is a moment when...
[0:14:16] You know, we are going to need to believe and trust in our companies a lot and rely on them to do the right thing. I mean, we just had a decade or decade and a half where we witnessed unintended consequences take a toll on our democracy. Yeah. Right? And we are still, even now, wrestling with data exposure and the concerns around that. Yeah. So people have learned a lot of hard lessons, and I think they're a lot less, I don't know.
[0:14:46] Ready to believe. Yeah. And I think that's the right approach because it would be wrong to blindly trust. We're in a moment where it's a trust but verify. So let's verify. Let's look back in the last three years. We all worried in 2022, 2021, when these models started to come out, that as they got bigger, they would be less controllable. As they added more data, they would be more biased.
[0:15:13] As they got access to more tools, they would cause more harms. Now we have three years of empirical data of them being in production across many different labs, not just one lab, with hundreds of millions of daily users. And net-net, there have been some harms. Some people have clearly been hurt by it. But the 99.999% number is quite staggering. The fact that it is making cheap and abundant...
[0:15:40] Intellectual capital available to everybody, regardless of your well-being. You can get it on WhatsApp and pay virtually nothing. It's now available in the open source, completely free to experiment with. Again, I said trust but verify. So that doesn't mean tomorrow is going to be the same. So we should continue with a skeptical, critical approach because they're about to take on a bunch of new capabilities. They're about to call APIs.
[0:16:05] My guest today, Mustafa Suleiman, the CEO of Microsoft AI. Stay with us. Hey, I'm Anderson Cooper.
[0:16:37] On my podcast, All There Is, we explore grief and loss in all its complexities. My guest is Lil Jon. He's a rapper, DJ, and producer known for hits like Get Low and Turn Down for What. In February 2026, his 27-year-old son Nathan went missing near Nathan's home in Georgia. Three days later, his body was found in a pond nearby. Lil Jon has a memoir that just came out called I Only Shout So You Can Hear Me. It takes time to heal.
[0:17:06] I kept myself busy that I didn't let myself mourn. I needed to laugh again. I needed to be silly and interact with people and feel other people's energy and make people happy too. We have to share so other people can see that they can get through it too. Talking grief, building community. That's what the podcast is all about. This is all there is. Listen and follow wherever you get your podcasts. I'm Dr. Sanjay Gupta.
[0:17:36] Host of the Chasing Life podcast. You may have noticed gambling doesn't require a casino anymore. You can just open up your phone. It's designed to keep us coming back or maybe never even leaving in the first place. We're going to talk to Dr. Timothy Fong, co-director of UCLA's Gambling Studies program. You're going to learn what your brain is really chasing when you place a bet. And also importantly, how to keep the game from playing you. Gambling addiction, gambling disorder is the hidden addiction.
[0:18:04] You can't smell it. You can't taste it. You can't see it. You can't have a urine drug test. Who are we talking about here, Professor? Who's the most likely demographic to be affected by this? Literally any single human on Earth. Listen to Chasing Life, streaming now, wherever you get your podcasts. One of the things is you'll say trust but verify. But I don't know who's going to do the verifying. When I look at countries gathering for an international summit.
[0:18:29] It was kind of a mess. They weren't able to agree on their national interests versus what the collective interests should be. There were a lot of warnings issued about the potential problems. Most recently, we had J.D. Vance, the vice president, speaking about innovation and saying that needs to be basically the North Star of this conversation. So how do you balance the two? I know what the tech industry is like when innovation is its North Star. Right.
[0:18:58] And we're left in the dust of that in a lot of ways. Look, the debate moves forward and then moves in another direction. And that is a natural, healthy balance in our democracies, right? But it's moving really forward. Do you know what I mean? Like when you even talk about a few years ago, what AI could do a few years ago is not.
[0:19:18] What it does today or where it's in use today. I mean, I'm biased. I'm asking you this because I'm in a building that might not exist in a few years if a large language model, if an AI or an AGI can do the job better, right? And can generate that imagery of, I don't know what, a version of me that people find more engaging. So it feels very literal to people because when they talk about job loss or things changing.
[0:19:44] It's across many different kinds of industries and people feel it. And we've learned that that is destabilizing for people when they feel like they are not part of the world's economic advancement, right? Globalization taught us that. People are unhappy now with the result of it. So how do you think about that in terms of making a consumer product, but you want someone to still be around to do it?
[0:20:11] I mean, the nature of our work is going to fundamentally change. And every generation of technology changes where we work, how we work, who we interact with. This is happening faster than the previous generations. But I think this is also a moment where we will have to decide which parts of the science and technology we really introduce into our societies and at what rate.
[0:20:39] When I look out towards 2050, over the next 25 years, there will come a time when we have to decide what does it mean to be uniquely human? Not just in terms of AI, but in terms of synthetic biology too. There are going to be many people who have tremendous biological advantage and will be able to enhance themselves in quite fundamental ways. That sentence sounds so...
[0:21:06] You're underselling it there in terms of what you're saying. You're saying there will be people who have a biological advantage because of these various advances? Just as today you have a biological advantage compared to 150 years ago pre-penicillin, that we now have surgery that enables us to battle through cancer and live for decades longer. 200 years ago, the average life expectancy was 25 years old. Today, it's 75.
[0:21:36] In two centuries, we've tripled the amount of health and well-being that the average person on our planet can enjoy. So we're already on that trajectory. It's just when I, obviously, when I say over the next 25 years, it does sound crazy, but we're living in a crazy time. What's happened is already crazy, right? And so my point was just that there will be moments when we have to collectively as humanity decide what we say no to.
[0:22:05] And that is really the big challenge, is when do we think something no longer serves us, right, collectively? Are there any areas that AI should not be used, should not be deployed? It's very hard to say ahead of time, you know. Well, we're actually in the time right now. There were protests at a Microsoft event about the company's AI and technology being used in military context. So, like, we're in the time right now. Yeah.
[0:22:35] Part of the challenge is that a lot of the services that all the companies provide are foundational elements inside a stack, just as paper or pens or tissues are core pieces that are used by everybody. The tablet that you have in front of you is used by everybody for all sorts of things, whether you're on an airline or a three-year-old watching cartoons. And so that's the story of technology. It proliferates. If it's useful.
[0:23:02] And it is clearly useful.
[0:23:31] I don't have a good answer to that question. I mean, that is genuinely the hard sort of ethical governance question of our age. Do you see why people ask it? I think it's a central question to ask. There's nothing else to do other than to focus the mind on the fact that, you know, some of these technologies may make war cheaper, faster, easier. We've certainly seen that in Ukraine. It is remarkable that we now have...
[0:23:57] Decentralized access to the tools of war for a $1,000 drone that can deliver a payload that could take out a small APC. And that's going to change the balance of power. And that is the nature of proliferation. Technology really is the greatest equalizer we've ever imagined. There's no additional cost to actually copy that software and then share it again. It's information. And so that's going to change the traditional structure of power.
[0:24:26] Historically, power has been concentrated because it has been physical, right? Forts, tanks, governments focused around cities. But now knowledge and power are going to be manifested in information and bits and therefore spread very, very widely. And the single rule is very simple. If it's useful, it gets cheaper and easier to use and spreads far and wide. And that spreading is really a spreading of knowledge and power.
[0:24:53] Here's where I question this. I don't see the democratization of power through this for a couple of reasons. One, it's a trillion-dollar enterprise, maybe, given what we've seen with DeepSeek out of China. Maybe it's not. But the idea that it right now takes a tremendous amount of capital, tremendous amount of technological support, and the industry literally believes it has to consolidate to make that happen. So right away, it's in the hands of a few.
[0:25:21] And then where it's deployed, it doesn't feel, again, like we have the ability to contain it. I don't feel right now like this is a democracy, right? I feel like this is kind of happening to the rest of us. It's not feeling like it's something we're all getting to do. It's like some of us will get to, I don't know, make travel plans without using Boolean search. And some of us are going to get to do all the things you're talking about, never mind the climate impacts.
[0:25:50] Right now, this thing is labor-intensive, hurts the environment, and it's kind of steamrolling so much of the economy. Yeah. I hear you. It makes sense. I think...
[0:26:01] You can tell me I'm wrong. I'm just like, but you see what I mean? You always make it sound so great. And then I like open up the paper. Actually, I spend a lot of time saying, calling about the risks as well. Like I'm very, very obsessed with the risks, but I'm also trying to be balanced about it, right? It is certainly true that a small number of players can produce the biggest AI of the highest quality first. But many, many people.
[0:26:30] How we're able to produce the same performance, the best model in the world, but a year later at 100x cheaper in the open source available to everybody for free. That's just a subjective fact. Just three days ago, Meta put out an open source model that is the best in the world. So we have to just wrestle with that fact. It is widely available to everybody. That's true, right?
[0:27:00] On the environmental question, as it happens, Google, Microsoft, Meta, certainly at Microsoft, the vast majority of our compute consumption is renewable. And we actually make the market for renewable energy. Now, that's not to say that there aren't other issues to do with how these chips are manufactured and the resource exploitation question, which is...
[0:27:27] Really got no environmental positive story at all. That's a bad sign. But at least where we know there is a fundamental issue, like moving from oil to renewables, it's a pretty big deal that we've made a commitment to be net negative, carbon net negative by 2030, to be giving back to the grid, in fact, to be 100% water positive, clean water positive by 2030. Now, that's massive. We're one of the biggest buyers in the world.
[0:27:56] So, you know, I don't want to sort of always give you a positive answer in response, but I do think that there are some like fundamentally positive signs that we should be excited about and try and build on those things. You know, you've said in your book, The Coming Wave, that all technology is political. So where are we in this political moment with this technology? Yeah. You know, I think that there's a very sort of trite and...
[0:28:23] Easy to dismiss narrative. People often say, you know, the tool itself is neutral. It's really the person who uses it. And that's absolutely true. Yet we also design tools in much more complex and nuanced ways than when we invented a hammer, right? And part of the challenge is that our language is so weak. You know, the reason why we end up talking about a species, for example, or all the confusion around superintelligence and AGI.
[0:28:50] It's because our words just aren't subtle and precise enough to capture all the nuanced distinctions of all the variety of tools that we have. Today, what we're creating, it doesn't feel satisfactory to describe it just as a tool, right? You speak to Copilot, for example, the AI that I make at Microsoft. It gives you an answer that is unique to you based on your history, personalized to the things that you've talked about in the past, what you're interested in.
[0:29:18] And then you say something back and it gives you something completely unique. We have never invented anything that gives a unique, emergent, dynamically generated response on the fly before. So it's clearly not a tool. At the same time, it's clearly not yet a species. It may well be more like that in the future, but right now it's totally not. So we're all just sort of struggling with the right language to wrap our hands around these things. Most people talk about this in the context of science fiction.
[0:29:46] Like people keep bringing up the Terminator concept because the idea of self-replicating AI is a genuine concern, right, that has spread and that people have heard echoed in other areas of science. And you've said yourself, look, that's not going to happen unless someone develops it that way, which isn't that really much of a comfort because the odds are someone with the right financial incentive might. Yeah. I mean, part of the challenge is that because this is.
[0:30:13] So available to everybody because the cutting edge is in the hands of open source. You can't like there are problems with governing powerful companies, but there are a few of them. They're subject to shareholder control, to boards and to regulation and governments. When you put that kind of power in the hands of literally hundreds of millions of developers.
[0:30:38] The equation changes. Yes, it's much more likely that someone's going to do that. I personally don't believe one of the big labs is going to be the first to go and do that kind of risk-taking experimentation with self-improvement or replication. But can I say that some random developer in their garage is not going to do that? No, I feel more concerned about that. And that's sort of part of the challenge. What would you like to see in terms of a regulatory environment? What makes sense to you that we don't have right now?
[0:31:06] It's a good thing for us to proactively disclose to central audit functions what our models can do and to make claims about what they can't do and what they're designed not to do. We've certainly done that at Microsoft by proactively talking to the Irish Data Protection Authority before we've deployed a model describing everything that it was intended to do, all of the known weaknesses today, our best assessment of the risks, and then our ongoing analysis.
[0:31:34] And monitoring of what it's doing, keeping them updated proactively. So companies voluntarily. Voluntarily. Sharing information from their internal audits. Voluntarily. I think that's the right thing to do. That's not regulatory. It's not regulatory. Well, I mean, I've called for regulation for many years. Yeah, but we're not getting there. So what is it that you would like? That's the political environment. That's your domain. Like I've proactively called for regulation for most of my career.
[0:31:59] And been involved in drafting those things and briefing with people on it. So I'm definitely a big fan of not just making it voluntary. Yeah, but what then are the obstacles? You've done this work, I haven't. That's the politics of it, you know? That's the moment we're in, isn't it?
[0:32:15] Are you glad you're out of politics then? You were at one point working in a political office very briefly. No, I wasn't. I was 21 years old. You were idealistic, thinking things would be changed. I worked for the mayor of London writing policy documents on human rights for nine months when I was 21.
[0:32:34] Mustafa Suleiman, that's relevant here. That's relevant here because you have not been cynical once in this whole interview until I brought up the idea of the politics of this and of regulation. And now suddenly your eyebrows are up. It's very frustrating. It's very frustrating. I would love us to be able to make more progress there. But? I mean, my take is that, you know, so far there's a lot of fear. But if you objectively look back at the actual harm in the last three years, it's hard to say.
[0:33:06] Now is the time for aggressive or unprecedented regulation. Even I'm not saying that, right? And so I think that in most of these situations, we have to wait and see, monitor closely, be prepared to react really fast, be proactive and transparent, hold ourselves accountable in the best possible way, invite everybody in to kind of debate and discuss what they're seeing and just keep a very open mind. But so far, I don't see any evidence that it's time for some unprecedented regulatory action.
[0:33:35] I've asked you all of my scaremongering questions. So do you have any questions for me? Kind of what do you wish people would talk about in this space or in these environments? Yeah. How do we communicate in a way that enables us to both be optimistic and excited, but at the same time, skeptical and critical? How do you strike that balance? What do you hear in the line of questioning?
[0:34:00] No, I like the line of question. Yeah, yeah, but what do you hear when you're... I think, you know, flipping roles is helpful. You playing my role, me playing your role. Your role's a lot more fun. It doesn't always feel like that.
[0:34:16] And I think that's the art, I think, for all of us who are communicating publicly. Which is hard right now. I mean, I get asked that question by doctors and nurses. I mean, anyone with expertise right now is in the position of somehow trying to somehow have authority, right? Somehow assure people who, by definition, believe.
[0:34:38] They are not to be trusted simply because they have authority or some kind of credential. That's why I wanted to talk to you because I think you're a good communicator. I mean, that being said, what you're probably hearing from me is just like a decade of feeling lied to by a variety of tech industry leaders. Like everything was going to be voluntary. Everything was going to, we're just going to do it this way. Trust us. And I do think that as every industry grows up,
[0:35:06] This industry is at the age where you don't trust them as much, right? Just like, I don't know, some people out there have teenagers that they're like, okay, I'm giving you the keys, but not great. This could go sideways. And this is a very powerful industry that has at times loved the rewards and not the responsibilities equally. Yeah. No, I love what you say. I don't want to try and reassure anybody. And I certainly...
[0:35:34] Don't want people to say, just trust me. What I want are spaces where we can have a critical dialogue where the skepticism doesn't turn into mean spirited anger and basically verbal violence so that I can play other people's roles and they can play my roles. I love people to give me concrete and specific and practical suggestions of what they would like to see. So I'm always open-minded to hearing.
[0:36:03] What we should be doing differently. And also, what I think we need is people thinking about the third degree consequences. Because what happened in social media was, at least in the early phase of social media, I don't think they were really aware or could even see. I think they sincerely thought, clearly, this is helpful. More information, the better. No verification of quality. We don't want to centralize that, etc.
[0:36:30] I think that towards the latter part of that, it was maybe harder to defend. I think it was pretty clear that there was being used for inciting all kinds of chaos. And I think that in this moment, we've learned some of those lessons. And the question is, how do we put those into practice? How do we hear from people who are seeing the darker side of these chatbots, who do see some risks that maybe I'm not seeing? How do we vocalize those, bring those into the conversation? That's definitely my invitation and why I'm...
[0:36:59] This is why I'm here. This is what I want to be doing. Well, we really appreciate your time. I appreciate you being at Microsoft, frankly, because the company is so influential. And it's a little weird to be talking about this because, I don't know, 50 years from now, what we mean by computer could be completely different. Right. Like what Microsoft might be celebrating might be completely different. Right. I think it is going to look quite different. I think it's going to feel not like typing at your keyboard.
[0:37:28] And more like talking to an AI companion, talking to a co-pilot or an agent. It's going to feel much more like a sort of a presence that lives life alongside you, that really understands you and works with you, works for you. Mustafa Suleiman is the CEO of Microsoft AI. Microsoft is celebrating its 50th anniversary this year.
[0:37:54] The Assignment is a production of CNN Audio, and this episode was produced by Lori Gallaretta, Jesse Remedios, and Osman Noor. We had editorial support this week from Joanna Campioni and Jennifer Sherwood. Our senior producer is Matt Martinez, Dan DeZula is our technical director, and Steve Lichtai is the executive producer of CNN Audio.
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