 Okay, welcome back, everyone, to theCUBE's coverage of AWS Remars here in Las Vegas. I'm John Furrier, host of theCUBE. I've got Alexi Serkov, partner at Deloitte, joining me today. We're going to talk about AI, bias AI trust, trust in the AI for the, to save the planet, to save us from the technology. Alexi, thanks for coming on. Thank you for having me. So you had a line before we came on camera that described the show and I want to, I want you to say it if you don't mind because it was the best line for me, at least for my generation. That describes the show and then your role at Deloitte in it. Sure, listen, I mean, I may sound a little corny, but to me, like I look at this entire show at this whole building, really, and like everybody here is trying to build a better Skynet, you know, better, faster, stronger, more potent, you know, and it's like, we're the only ones, like we're in this corner of like Deloitte trust for the AI, we're trying to make sure that it doesn't take over the world, you know? So that's the, that's, you know, that's a gist of it. How do you make sure that AI serves the good and not evil? How do you make sure that it doesn't have the risk? It doesn't, you know, it's well-controlled that it does what we're asking it to do. And of course, for all the young folks out there, The Terminator is the movie and it's highly referenced in the nerd circles, Skynet's evil and helps humanity goes away and lives underground and fights for justice and I think wins at the end. The Terminator three, I don't get it. I can't remember what happened there, but anyway. I thought the good guys win, but I think they do win at the end. So that brings up the whole point because what we're seeing here is a lot of futuristic positive messages. I mean, three areas solve a lot of problems in the daily lives, you know, machine learning, day-to-day hard problems. Then you have this new kind of economy emerging, you know, machine learning, driving new economic models, new industrial capabilities. And then you have this whole space save the world vibe. You know, like we discovered the moon, new water sources, maybe save climate change. So very positive future vibe here at Remars. Absolutely, yeah. Yeah, no, it's really exciting just watching, you know, watching the speakers talk about the future and conquering space and mining on the moon like it's happening already. It's really exciting and amazing, yeah. All right, let's talk about what you guys are working on Deloitte because I think it's fascinating you starting to see the digital transformation. Get to the edge and when I say edge, I mean, back office is done with cloud and you still have the old, you know, stuff that the old models are people who will use, but now new innovative things are happening. Pushing software out there that's driving with a fintech, these verticals. And the trust is a huge factor. Not only do the consumers have a trust issues, who owns my data, there's also trust in the actual algorithms. Exactly, exactly. You guys are in the middle of this. What's your advice to clients? Because they want to push the envelope hard, be cutting edge. Right. But they don't want to pull back and get caught with their data out there that might been a misfire or hacked. Absolutely, well, I mean, the simple truth is that with great power comes great responsibility, right? So AI brings a lot of promise, but there are a lot of risks. You want to make sure that it's fair, that it's not biased. You want to make sure that it's explainable, that you can figure out and tell others what it's doing. You want to make sure that it's well controlled, that it's responsible, that it's robust, if somebody feeds it bad data, it doesn't produce results that don't make sense. If somebody's trying to provoke it to do something wrong, that it's robust to those types of interactions. You want to make sure that it preserves privacy. You want to make sure that it's secure, that nobody can hack into it. And so all those risks are somewhat new. Not all of them are entirely new. As you said, the concept of model risk management has existed for many years. We want to make sure that each black box does what it's supposed to do. Just AI, machine learning, just raises it to the next level. And we're just trying to keep up with that and make sure that we develop processes, controls, that we look at technology that can orchestrate all this de-risking of transition to AI. The load's a big firm. You guys saw you in the US Open sponsorship was all over the TV, saw that. You're here at Remar's show that's all about building out this next infrastructure and space and machine learning. What's the role you have with AWS and this Remar's? And what's that in context to your overall relationship to the cloud players? Well, we're one of the largest strategic alliances for AWS and AWS is one of the largest ones for Deloitte. We do a ton of work with AWS related to cloud, related to AI, machine learning, a lot of these new areas. We did a presentation here just the other day on conversational AI, really cutting edge stuff. So we do all of that. So in some ways we participate in that part of the, the part of the room that I mentioned that is trying to kind of push the envelope and get the new technologists out there. But at the same time, Deloitte is a brand that carries a lot of history of trust and responsibility and controls and compliance. And all of that comes- We get a lot of clients and we get big names. Get a lot of big name enterprises that rely on you. They rely on you now. Exactly, yeah. And so it is natural for us to be in the marketplace, not only with a message of, let's get to the better mouse trap in AI and machine learning, but also let's make sure that it's safe and secure and robust and reliable and trustworthy at the end of the day. And so this trustworthy message is intertwined with everything that we do in AI. We encourage companies to consider trustworthiness from the start. It shouldn't be an afterthought. Like I always say, if you have deployed a bot and it's been deciding whether to issue loans to people, you don't want to find out that it was like, biased against a certain type of population six months down. I can just see in the boardroom, the bot went rogue. Right, yeah. And you do all those loans. And you don't want to find out about it like six months later, right? That's too late, right? So you want to build in these controls from the beginning, right? You want to make sure that you know, you're encouraging innovation, you're not stifling any development and allowing your- There's a lot of security challenges too. I mean, it's like, this is the digital transformation sweet spot you're in right now. So I have to ask you, what's the use case? I was in call centers, obvious in bots and having self-service capabilities. Where is the customers at right now on psychology and their appetite to push the envelope? And what do you guys see as areas that are most important for your customers to pay attention to? And then where do you guys ultimately deliver the value? Sure. Well, our clients are, I think, are aware of the risks of AI. They are not, that's not the first thing they're thinking about for the most part. So when we come to them with this message, they listen, they're very interested. And a lot of them have begun this journey of putting in kind of governance, compliance, controls to make sure that as they are proceeding down this path of building out AI, that they're doing it responsibly. So it is in a nascent stage. What defines responsibility? Well, you want to be, okay, so responsibility is really having governance. You know, like you have a, you build a robot dog, right? So, but you want to make sure that it has a leash, right, that it doesn't hurt anybody, right? That you have processes in place that at the end of the day humans are in control, right? I don't want to go back to the Skynet analogy, right? But humans should always be in control. There should always be somebody responsible for the functioning of the algorithm that can throw the switch at the right time, that can tweak it at the right time, that can make sure that you nudge it in the right direction, that at no point should somebody be able to say, oh, well, it's not my fault. The algorithm did it, and that's why we're in the papers today, right? So that's the piece that's really complex. And what we try to do for our clients, as Deloitte always does, is kind of demystify that, right? So what does it actually mean from procedures, policies, tools, technology, people? Yeah, I mean, this is the classic operationalizing, so new technology, managing it, making sure it doesn't get out of control, if you will, stay on the leash, if you will. And I guess one piece that I always like to mention is that it's not to put brakes on these new technologies, right? It's not to try to kind of slow people down in developing new things. I actually think that making it trustworthy is enabling the development of these technologies, right? The way to think about it is that we have seed belts and ABS brakes and airbags today. And those are all things that didn't exist like a hundred years ago, but our cars go a lot faster and we're a lot safer driving them. So when people say, oh, I hate seed belts, you're like, okay, yes. But first of all, there are some safety technologies that you don't even notice, which is how a lot of AI controls work. They blend into the background. And more importantly, the idea is for you to go faster, not slower. And that's what we're trying to enable our clients to do. Well, Leslie, great to have you on the queue. We love Deloitte, come on, share their expertise. Final question for you is, where do you see this show going? Where do you guys actually hear you're participating? You got a big booth here. Where's this going and what's next? Where's the next dots that connect? Share your vision for this show and kind of how the ego system and this ego system and where you're going to intersect that. Wow, I mean, this show is already kind of pushing the boundaries, you know? We're talking about machine learning, artificial intelligence, robotics, space. You know, I guess the next thing I think, you know, we'll be probably spending a lot of time in the metaverse, right, so I can see like next time we come here, you know, half of us are wearing VR headsets and walking around in meta worlds, but you know, it's been an exciting adventure and you know, I'm really excited to partner and spend, you know, spend time with AWS folks and everybody here because they're really pushing the envelope on the future and I look forward to the next year. The show's small, so it feels very intimate, which is actually a good feeling. I think the other thing in metaverse, I heard that too, I heard quantum. I said next, I've heard both those, next year, quantum and metaverse. Okay, well, why not? Why not, exactly, yeah. Thanks for coming on theCUBE, appreciate it. Thank you. All right, it's theCUBE coverage here on the ground, very casual theCUBE, two days of live coverage. It's not as hot and heavy as re-invent, but it's a great show, bringing all the best smart people together, really to figure out the future, you know, solving problems, day-to-day problems and setting the new economy, the new industrial economy and of course, a lot of the world problems are going to be helped and solved, very positive message space, among other things. Here at Remarch, I'm John Furrier. Stay with us for more coverage after this short break.