Ep 502: Sustainable Growth with AI: Balancing Innovation with Ethical Governance

Topics Covered in This Episode:

1. Balancing AI Innovation with Ethical Governance
2. Introduction of Rajeev Kapur 
3. Rajeev Kapur's Background in AI
4. Companies Balancing AI Innovation and Ethics
5. Formation of AI Ethics Board
6. Data Management as Competitive Advantage
7. Privacy and Ethics as Product Features
8. Governance and Ethical Standards in AI Use
9. Impact of Regulatory Changes on AI Use
10. Deepfakes and Their Implications
11. Encouragement for Companies to Lead Ethically in AI

Keywords:

AI innovation, Ethical governance, Large language models, Data privacy, AI ethics board, AI governance, TDWI, Microsoft stack, Generative AI, AI algorithms, Spatial audio, Deep fakes, Data differentiation, Machine learning, Cyber security, Enterprise technology, Rajeev Kapur, 11:05 Media, AI safety, OpenAI, Data utilization, Ethical AI alignment, Regulatory aspect, AI models, Innovation vs. ethics, AI data privacy, Explainability, Data scientists, Third-party audits, Transparent AI usage, AI-driven growth, Monitoring feedback loops, Worst case testing, Smart regulations, Digital twins, Disinformation, AI bias mitigation, Data as new oil, Refining data, Diverse community partnerships, Long-term AI strategies.

Podcast Transcript

 Jordan Wilson [00:00:15]:
Leveraging AI can kinda be like a tight wire rollback. Right? Like, you wanna be innovative. You wanna, you know, take advantage of the latest and greatest that AI and large language models have to offer yet at what cost? Is anyone out there reading terms and service of, you know, all these random AI tools that you and your team wanna take advantage of? Do you know what happens with your data once you sends it once you send it to one of these big AI tech companies? Do you care about governance, or do you really just care about keeping up and getting ahead and, using the latest AI update from one of the big players? I think these are important conversations that, are worth talking about, and that's exactly what we're gonna be doing today on everyday AI. What's going on y'all? My name is Jordan Wilson, and I'm the host. And this thing, it's for you. Everyday AI is your daily livestream podcast and free daily newsletter, helping us all not just keep up with what's happening in AI, but how we can get ahead to grow our companies and our careers. So it starts here with this livestream and podcast, But if you that's that's where you learn. But if you wanna leverage it, you need to do that on our website.Jordan Wilson [00:01:27]:
So if you haven't already, please go to youreverydayai.com. Sign up for the free daily newsletter. Yeah. You can go listen and watch and and read hundreds of of website hundreds of back episodes where I've, interviewed some of the world's leaders on topics all over across the board. But also we're gonna be recapping, valuable insights and takeaways from today's conversation. So make sure you go check that out. Technically, a prerecorded one. So if you're, dropping in for, AI news, that's gonna be in the newsletter as well.Jordan Wilson [00:01:56]:
Alright. Enough, chit chat y'all. I'm excited for today's conversation. So please help me welcome to the Everyday AI Show. We have Rajeev Kapoor, the president and CEO of eleven o five Media. Rajeev, thank you so much for joining the Everyday AI Show.Rajeev Kapur [00:02:11]:
Jordan, it's my pleasure. It's an honor to be here, and I'm I'm glad I'm here, and I hope, people get real good value.Jordan Wilson [00:02:16]:
Alright. I can't I can't wait to talk about this. But before we, kind of talk about this balancing act of, innovation and governance, Rashid, can you first tell us a little bit what is eleven o five media, and and tell us a little bit, of your background as well in the AI space?Rajeev Kapur [00:02:31]:
Yeah. So Eleven o five Media, we're a b to b marketing media technology company. So I guess the best way to describe it is we're like a political, but only for technology b to b. So we do everything from face to face events to lead gen, to newsletters, to webinars, to those kinds of things. And we cover big data, so I have a company within eleven within the eleven o five umbrella. There's a company called TDWI. That's one of my companies. It's one of the largest big data analytics AI training companies in the country.Rajeev Kapur [00:03:00]:
It's phenomenal. So people go to tdwi.com and check it out. Then we have another business that does cyber and physical security, media, and marketing of another business that does enterprise technology. So our customers, they are like Amazon Web Services or Google Cloud or Azure or people like that. They come to us and say, hey. We wanna get more developers of x y z. Can you help us get our product out to those people? So, essentially, that's where we're a middleman that basically helps connect buyers with sellers. It's kinda what we do there.Rajeev Kapur [00:03:31]:
And we cover and one of our big partners is in terms of doing some of those things we do as Microsoft. We do a lot of things in the Microsoft stack. And we're the we have the largest non Microsoft event in Microsoft headquarters coming up in August. So we'll have about seven, eight hundred people there at Microsoft Headquarters, for our Versus live event all around, that's happening with Microsoft. That's great. So that's the eleven o five media side. Now it answered the question about my AI world. I've actually been involved with AI for for a long time.Rajeev Kapur [00:04:00]:
So about eleven a little over eleven years ago, actually sold a small AI startup in the machine learning space. And we were building AI algorithms used for audio technology. Originally, when I kinda became CEO of that company, it was kinda VC backed it. We were building chips, processors, but we quick quickly found that, you know, the TV guys, the phone makers, they weren't gonna redesign their boards for another chip. They wanted less chips. Right? So we actually took the algorithm out of the chip, build out, you know, and and basically build AI algorithms where we tested soft sound audio quality three we called it three d sound. Now you hear it as spatial audio. And so as a matter of fact, like, you know, if you, if you if you saw over the holidays here in The States, there was that Apple commercial where the where the daughter gets a guitar and then the the the dad sags, he can't hear a plane, and then they give him the new AirPods and he puts them in and he can hear it.Rajeev Kapur [00:04:57]:
That that was kind of the technology that we had built that we used AI for that. So that company got sold. And then, I went took the classes on AI at MIT, and I got a dual AI dual AI certification at MIT. And and then here at 11:05, we've been kinda covering the machine learning side of AI for the last eight, nine, ten years. The generative AI stuff is obviously very brand new over the last two years, and so we've been all over that. And then I remember the morning chat sheet, BT came out, I jumped out of bed. I remember looking at my phone going, oh my god. This is gonna be the greatest thing since electricity, right, to change the world.Rajeev Kapur [00:05:31]:
And, initially, I was met with some skepticism from people, but I think I've been proven out to be right. But, you know, but literally, like, within twenty four, forty eight hours, I decided, you know, I'm gonna write a book about this. So I wrote a book called AI Made Simple, and it was the number one best AI book on Amazon for about seven months. It'll get published in, May, June of '20 '20 '3, I think. Yep. And so yeah. And then I had a second edition, and and now I'm working on a third edition and now also working on another book kind of around prompting and AI for the executives. So, anyway, so that's kind of my experience, with it.Rajeev Kapur [00:06:06]:
And, you know, I'm a techie. You know, I was an executive at Dell computer for a long time, so I always kinda been in the tech world my whole career. Prior to that, I worked for an old computer company you may have remembered called Gateway. So yeah. So that's my, technology and AI background.Jordan Wilson [00:06:20]:
Love it. So let's let's maybe skip to the end here, and then we can unwrap this a little bit, Rajeev. But, you you know, as we look at this balancing act, right, like, you you know, companies wanna take advantage, you know, of every new model update, every, you know, every single shiny AI tool in the corner ever wants to jump into it. So how do you balance keeping up, and and using all of these AI models, but with the ethics side, with the governance? How do businesses do that?Rajeev Kapur [00:06:49]:
You know, that's a really good question, and I think that's an area where people right now are just learning and understanding and realizing they actually have to put a little bit of effort energy into. Part of it is I sit on a board of a kind of ethics and governance AI company called Lumanova. Basically, it's like the watchmen where the who watches the watchmen. So it's basically an AI platform that watches AI for the most part. But if you think about, you know, how to think about ethics as, you know, in in the same vein as making sure you don't hamper innovation, you gotta take a little bit of effort and start creating some sort, whether it's a cross functional AI ethics board for the lack of a better term. Like, how do you grow the teams to optimize for speed and scale? But then how do you use the f ethics team to protect your the long term license to operate and to provide value to your customer base. Right? So what what would that look like? It could include legal people, you know, scientists, ethicists, technologists, end users of your product, you know, kind of like a like a core solution. You know, how do you then how do you then go about mandating the review of all the different AI models that you might be using? And then one one thing is, I I think one opportunity might be tying some compensation to the executives based on ethical outcomes and concerns, not just purely revenue and EBITDA based type solutions.Rajeev Kapur [00:08:07]:
So there's I think that that that's a good way to start. Another one is understanding and realizing that AI as we know it, you know it, has got and people listening know it, it's got some biases. And the AI system, the LLM you're using, is gonna inherit and amplify those biases. So unless we're using it unless we're fighting it, like, literally every step of the way, we're gonna do regular third party audits or looking at the training sets, the models. We're building some sort of explainability into the models. And our is there is there a way to partner with diverse communities to look at what's happening? You know, it's it's so that's kinda, like, I think where where I would start in terms of looking how to balance that. So, you know, like, a lotJordan Wilson [00:08:46]:
of times people, in in in companies we've worked with, they always look around and they're like, who should be in the room? Right? Like, you you talk about kind of this, like, AI ethics board or the, you know, a a team of people who needs to be around that table because sometimes, you know, people are looking at at IT or or or CSOs and, like, you know, sometimes it's just, oh, c suite or HR, marketing. Right? Like, who needs to be around that table, when we talk about the the ethics team or the people that need to be involved in making those ethical decisions on AI use?Rajeev Kapur [00:09:20]:
Look. I I think look. You remember what happened with over Christmas with Sam and the OpenAI group where you you got you know, like, the gov and he came back and, you know, all that stuff. Right? If you remember that that nonprofit board, part of their charter was to kinda be that kinda ethical board makeup. Right? Now they didn't went out in this whole power struggle thing. But I think, ultimately, the answer to the question is that if you wanna do this right, you need to have you have to look at stakeholders across more than just your company. You know? And I'm not saying you have to give these people power, but you should you should give these people the ability to voice their opinions, their concerns, whoever they might be. Maybe you have one or two frontline users that rotate every six months onto this board.Rajeev Kapur [00:10:04]:
Maybe you might look at, is there a technologist for maybe one of your customers that might make some sense? You're you're like like like, you know for example, if you're opening an eye, maybe one of your biggest customers is, is, make it up. Like, some big health care organization. Right? Then let's get let's get this let's get, you know, the head of HR for that group to be part of it because HIPAA laws and all these things. And there's so much opportunity on the medical side of AI as you know. That might make some sense. Legal scholars and whatever. So I I think I think it's gonna be a combination of two you know, three or four core people from within the company and then probably three or four people from outside the company that can come together, work with the CEO, work with the team and the board the regular board to really understand and, you know, and and and go from there. And so that that that's how I would look at this if it were me, but I can imagine that not everybody is going to be like me and follow that.Rajeev Kapur [00:10:59]:
But, you know, but it does concern me. And I and I think the more you hear about deep fakes and these kinds of things, I think more and and, look, long term, I think you and I were talking before the show started. I think the long term winners that people could really figure out how to do both in parallel.Jordan Wilson [00:11:14]:
So I do wanna get into deep fakes in a little bit here, but, I think it's worth diving a little deeper onto the data side. Right? Because I think, you you know, speaking of Microsoft, you mentioned Microsoft earlier, you know, their CEO, Sadia Nadella, a few months ago said, you know, LLMs are a commodity. Right? And I I I think we've slowly come to realize over the last, you you know, year or two, you know, that using large language models, generative AI isn't going to be, you know, your company's moat. Right? Like, in in competing with, whoever else you're competing with, it's actually gets to your data. So, you you you know, how can companies really both separate themselves with their data, but also I mean, I think that's probably one of the most overlooked, pieces in in terms of, you know, guardrails and even ethics and how you use that data. So let's talk about both sides of that.Rajeev Kapur [00:12:06]:
So I've spoken to probably 3,000 CEOs in the last twenty to twenty four months. And one of the questions I ask them before I do my talk, I say, how many of you have a good command, not a great command, a good command of your first party data? I can count on two hands how many hands went up. Right? Because I think what happens is is CEOs look at data as an expense rather than an opportunity for growth. I think they see CapEx. I think they see cash going out the door. I don't think they see how they can how they can turn this into something really valuable. So to me, and I mean, to you and to probably a lot of your listeners, data is the new oil. But what's missing is the refineries that sit on top of the data to turn it into something.Rajeev Kapur [00:12:58]:
Right? You can't do anything with just raw with raw oil. You need the refineries to refine it into something. The same thing goes with data. You gotta understand your data. You have to have the right practice around your data. You have to look up data privacy, and then you have to understand how do you now mine this data? How do you refine this data to use it to your advantage? Quite frankly, if you can figure that out, I'll tell you, just by doing that one step, which is arguably a little bit more machine learning ish, probably the generative AI ish short term, you might actually just build that mode that you didn't think you could build because no one else is doing it. And so if you don't have a data scientist on staff, if you're not spending any a little bit of CapEx money on figuring out your data issues, you're gonna fall you're gonna fall behind at some point. So so so take some time and effort to understand your data.Rajeev Kapur [00:13:43]:
So that's where I would start first. Now in terms of the privacy side, you know, and and other things that the problem is that if you just do this on your own and you half ass it, it's gonna be garbage in, garbage out. Right? You know, and it's gonna you know, you're gonna have to really understand how you can make the the to me, the challenge is how do you make the your privacy a real differentiator? Now some would argue Apple's probably like the the golden child when it comes to privacy. I like what they're doing with them. Granted, their solutions keeps getting rolled out or whatever. I'd rather them roll it out and push it back than launch something Apple intelligence or this shitty product. But, you know, to me, I think if they're the gold standard and and the LLMs gonna run locally on the phone and all that, it there's more security, then that minimizes data collection. It gives the user a bit more control and opt out capabilities.Rajeev Kapur [00:14:32]:
There's there's potentially the ability to really have really good transparent usage, logs, I guess, for the for the lack of a better term understanding. So that's so that it the the real opportunity, I think, is how do you how can you turn this into a feature? How do you turn your privacy and your ethics into a feature of your offering as opposed to an expense that might cost you some money. How do you turn into a feature that helps you drive everything?Jordan Wilson [00:14:58]:
So let's let's dive a little bit more into just governance. Right? I I think it's this, this word that, you know, sometimes it's it's it's it's it's like, oh, you're you're you're safe AI bingo card. Right? Like, I need to say data, you know, privacy, and I need to say guardrails, and I need to say ethics. And as long as I say those things, you know, people are gonna nod their head, and it's like, alright. We're doing AI the right way. What does it actually mean when we talk about not just governance, but, you know, when like, tying in, governance in an ethical way? Let's break that down a little.Rajeev Kapur [00:15:34]:
Look. I mean, I think it's, it's are you reviewing your major AI initiatives? Are you understanding your AI product road maps, partnerships? You know, are they all how are they being linked? You know? Are you leading from a are you leading kind of from this I like to call this enlightened leader perspective, right, to where these types of thing matters, you know. You know, I I mentioned earlier, I you have a diverse group of folks in the room helping you understand and realize what what type of AI you are deploying, You know? And do you have real good explainability of your model, for example? You know? And do you have a monitoring and feedback loop for, you know, for for your model? I think all those things are are really there. You know? I think one thing is I I think two things. Number one is, do you have, like, are you really when you have your AI model, are you really doing your worst case testing? Right? I think there's needs to be some of that. I think you need to have just like I think, like, Microsoft, Google will will pay hackers to hack their software. You know? You gotta basically do the same kind of thing. You know? I I think, you know, those are some of the things I think that that are that that are absolutely, you know, you know, necessary to start thinking about governance and, you know, how do you build it in? And then it's, you know, understanding and realizing is probably never done, and then how do you keep iterating and learning from and going back and giving that feedback loop and mechanism.Rajeev Kapur [00:16:55]:
And I think that those are all the things. And, you know, I hate to say it, but I'm I'm not I I I don't know if companies, especially the LLMs out there, are gonna really put a lot of effort energy into this unless it's something that's being done on a global basis. Because I think the last thing they wanna do is do something that's gonna tie their arm behind their back in terms of innovation. Because if they do it, but then no one else is doing it so, for example, like, if OpenAI says, oh, yeah. We're gonna do it. But then Grok says, we're not gonna do it, then then you have you you're gonna have issues. So so so anyways but, you know, I I I think another thing here is, to me, it's also making sure that the consumer really understands what you're doing with the data. So I'll give you an example.Rajeev Kapur [00:17:42]:
So I'm a big basketball fan, and I'm born and raised in LA, so I'm a Laker fan. And the Clippers opened a brand new, beautiful, beautiful, amazing stadium into a dome. It's gorgeous. Like, probably arguably the best stadium in the world for basketball. And everything's facial recognition. And I've talked to so many people that don't wanna go because they don't wanna pay with their face, you know, because they don't know what's gonna happen with the data. Who's getting that data? Right? So a small example, even though if you got TSA precheck, you walk up, you're taking your picture anyways and everything about where you're going. Right? Or global entry.Rajeev Kapur [00:18:19]:
Right? So, you know, the company and the government has everything about you anyways probably, but there's just something there where I don't believe that they've done a good enough job of explaining why this is better for the consumer. So you have to be able to do that.Jordan Wilson [00:18:34]:
So, you know, I think it's worth exploring a little bit more because even the concept of AI innovation, you know, I think has changed. You you you like yes. We have listeners from from all over the world, but the majority of our audience is is here in The US. And, you know, with the, the the presidential, transition, you you know, things have changed drastically. Right? The whole, like, AI safety institute was essentially dismantled. You you know, it seemed like we kinda had this, like, yellowish light, you you know, for the last couple of years. And now it's like, oh, there's no stoplights. We're just going with with with innovation.Jordan Wilson [00:19:10]:
We'll see if we break anything, see what happens. Right? How can companies both, you know, keep up with the the the pace of AI, right, which is crazy to do, you know, and this is coming from someone that does it every day. But also even when you look at the the the regulatory aspect, you look at the, you you know, the federal, the government's involvement and and how it's changing. Right? And all those people sitting around the boardroom, you know, if you're bored, if your leadership is only meeting, you know, once a month, once a quarter, whatever it like, whatever it is, how can you keep up with the regulatory side, let alone everything else that that that that's happening on the, you you know, the LLM, the tool side?Rajeev Kapur [00:19:48]:
Yeah. I mean, look. You know, the cop out answer is you probably can't, but it doesn't mean you don't try. And I I really think the companies that are long term gonna thrive and be there are gonna once you can figure out how to do both, and and what what what are some of the things that they can do? Look. And by the way, I went to the White House about ten, eleven months ago before the election, and I met with people from the Biden administration. I was on the White House grounds. I met with people from the Office of Technology and Science. You know, all the alphabet agencies were % into this under the Biden administration.Rajeev Kapur [00:20:26]:
There's thousand couple thousand people, like, literally dedicated AI and understanding this challenge and issue. K? I don't know what's happening now, but I think we can guess what's happening now. But I think to do this, at the end of the day, companies are gonna have to regulate themselves if they really care. And my point is is that I don't think I don't think the big guys will. Because if they do, they could very well end up amping their ability to be innovative and grow, and it could cause so, again, I'm only gonna use an example. If OpenAI says, yes, we will do this. We're gonna publish AI impact reports. We're going to look at smart regulations, and we're going to I don't know.Rajeev Kapur [00:21:07]:
We're gonna create our own bill of rights for people or shared shared industry standards for AIUs. We're gonna do this ourselves. We're gonna self do we're gonna self regulate. We're gonna self govern. We're gonna do it ourselves. But unless Meta and Google and, you know, x slash GROC and others, half the people in Hugging Face or whoever they are, unless they also step up and say do it, it's gonna be difficult, to do. And so so look. I mean, you and I were talking earlier, like, you know, the future, it it's it's hard.Rajeev Kapur [00:21:46]:
In the future, if the The United States wasn't built on people who said it's too hard, they never did it. Right? It would have been hard. If that's the case, The United States wouldn't be here today if it was too hard. Right? And so, you know, so how do you do this? So technologists, CEOs, founders, entrepreneurs, somebody out there, you know, you know, they're gonna figure out how to do this. And, you know, they're gonna figure out how to embrace this and figure out how to do both. And, again, I come back down to, you know, the people are gonna figure out how to build it anyways. They're gonna build it better. They're gonna bring it ethically and smarter.Rajeev Kapur [00:22:21]:
And if you've got challenges, concerns about AI's dark side, like we talked about earlier, like deep face and these kinds of things, then do something about it and lead and lead with lead with vision and a purpose that stands up and says, we're putting our foot down. Here it is. And, oh, by the way, I guarantee I have a feeling that the first company that really comes and do that does that is gonna get a lot of positive buzz and feedback, and they actually might see an uptick in their in their adoption of their of their opportunity and solution. There might be,Jordan Wilson [00:22:47]:
but I could do. So I'd I'd say we can't, not talk. You know, when talking about innovation and and and ethics, around AI, you can't not talk about deep fakes. Right? Because I think there's there's there's obviously a very, you know, a a a very defined line in the sand between, you know, your digital twins, you know, people using it for corporate use and then just unauthorized deep fakes. Right? Which are extremely easy to use now. Right? Anyone with, you you know, ten minutes and a couple dollars can make something convincing that can, you know, really fool a lot of people. What's what's your take on both, you know, the innovative side of kind of this this digital twins and, you know, enterprise companies have been using them for a while now. But also the downside for deep fakes and deception and misinformation and disinformation, like, where do you lie on that kind of, like, innovation versus, this is risky?Rajeev Kapur [00:23:40]:
Look. I mean, you know, the Internet has was risky. And then there's good things about the Internet, there's bad things about the Internet. There's good things about social media, and there's bad things about social media. The good news about AI is that everybody has access to it. The bad news about AI is that everybody has access to it. Right? That that this is kinda the way it is. So anytime there's something good, there's gonna be something bad.Rajeev Kapur [00:24:01]:
You know, the the yin and the yang of life will always be there. I just think that companies who are really leading this effort need to do a much better job, and I believe they have the technology. You would probably know a little bit better. You just came back from GTC unless something was there. I think the I think the companies have all have the ability to watermark something that is a deep fake. You know? I really worry about society when someone can take your voice or my voice for eleven ten or eleven seconds, put it up in 11 laps, replicate our voice, and I was saying do do something that we never did. Right? It could damage the reputation. Us, me, you, people listening, you know, somebody taking our somebody taking your daughter's face and putting your you know, on someone's body that that's unfortunate, right, or something happens.Rajeev Kapur [00:24:46]:
Or you hear the stories now. Right? You I don't know if you heard the story about that CFO in Hong Kong. So if, you know, where where the where the employee of the of a finance institution at in Hong Kong got a deep fake invite and went to the Zoom call, and it was basically a deep fake CFO and a deep fake controller who convinced them to wire $25,000,000 because it looked and sound like just like the CFO. And that's his boss. And he was like, okay. Yeah. Yeah. Alright, boss.Rajeev Kapur [00:25:09]:
I'll do it. You know? Then you hear the story of how, you know, there's a school principal in the Midwest. You know, I don't know if you heard this story, but there's a school principal in the Midwest who reprimanded one of his teachers. The teacher got angry, created a deepfake of him saying the n word, and it wasn't him. Right? And the but but, fortunately, this person had some sort of connection with the FBI, and FBI got involved, and they discovered it was a deepfake, and it were able to trace it back to the to the person that he had reprimanded. So, you know, not everybody has access to that. And then you heard the story about character AI and what happened with that poor kid, you know, which I don't wanna get into because it might be sad. But, you know, it's a that's really a risk and challenge.Rajeev Kapur [00:25:48]:
And, frankly, the onus of that has to come to has to go to YouTube. It has to go to Meta, Instagram. It's gotta go to whether it's Snap or or whomever they might be or, you know, x, you know, to really police these things. I mean, it's it's better for society and for humanity and, you know, and again, everybody's susceptible. And because it's so personal, to me, deepfakes could potentially be and I'm being I might sound a little hyperbolic with this statement, but to me, I think deepfakes could be as bad on the as as nuclear weapons. You know? So there has to be I think there has to be some sort of regulation around deepfakes. I mean, it's almost like creating the AI AI AI, you know you know, the AI, you know, the AI agency for information tracking or whatever. Right? So there has to be something at some point, but we'll see.Rajeev Kapur [00:26:36]:
We'll we'll see what happens. You know, I'm hoping that, you know, you we do have a fairly influential AI person associated pretty close with the president. So, hopefully, he'll be able to really tackle this, I hope, and and we'll see where it goes. But it is a concern, and everybody should watch out for it.Jordan Wilson [00:26:53]:
Alright. So, Rashid, we've covered a lot in today's conversation from how companies can make data their differentiator, how to set up ethical AI alignment, and then even a little bit on deepfakes. But, as we wrap up here, what is your one most important, takeaway or piece of advice for business leaders trying to walk this tight rope tight rope, between, AI innovation and the ethical side?Rajeev Kapur [00:27:17]:
I kinda mentioned it earlier, and I don't mean to, like, come back to what I said about five, six months ago. But just because it's hard doesn't mean it shouldn't be done. And now is the time where CEOs and leaders in this space really need to lead with a set with a set vision, ethics, and quite frankly, courage to really stand up against this against the norm of what's happening now and really lead from the front because that's how they're gonna win. And I really believe that the company or companies that figure out how to manage this and figure it out and really put this forward, this idea of privacy and and this idea of really of governance and really understanding and protecting the consumer, the end user, they're the ones who are gonna eventually, I think, win in the future. Mhmm.Jordan Wilson [00:28:03]:
I think it's great advice and and and extremely important conversation, to have, you know, especially with all the developments and regulation and all these uncertainties we have fled around. I think today's was an important, conversation to have. So, Rajeev, thank you so much for taking time out of your day to join the Everyday AI Show. We really appreciate it.Rajeev Kapur [00:28:21]:
My pleasure. Thanks, buddy. Good to see you.Jordan Wilson [00:28:22]:
And, hey, as a reminder, y'all, we covered a lot. If you miss anything, don't worry. It is going to be in our newsletter. So if you haven't already, please go to youreverydayai.com. Sign up for that free daily newsletter. Thank you for tuning in. Hope to see you back tomorrow and everyday for more everyday AI. Thanks, y'all.