EP 79: The Importance of Ethics in AI

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How should we be using generative AI? It seems like there's no shortage of tools and softwares that can help us do our jobs better, but we don't really ever talk about the ethics behind it. So that's what we're going to be doing today on Everyday AI. So welcome. This is your daily live stream, podcast and free daily newsletter helping everyday people keep up with what's going on in the world of generative AI. So, yeah, we can always read about it, but this is where we actually talk about it and we say, here's what it means to, to your business, to your company, to your career. So extremely excited today. We have a senior leader from IBM joining us. But before we get into that, let's talk real quick about what's going on in the world of AI news. Let's make sense of this. All right, so first story, the New York Times just says, just said that companies can't use its site to train AI models. So they updated their terms of service, kind of barring different AI chats from crawling their site and using that information or, sorry, restricting end users to use that information. So very interesting timing, especially as OpenAI kind of released, so to speak, their GPT bot, which told companies how they crawl their website and use their information. So this, I could talk about this one for hours, but keep your eye on that because I think it is pretty, pretty noteworthy. All right, next piece of news. ChatGPT competitor raked in a huge fundraising round. So Anthropic, which makes The LLM Cloud 2, recently just announced a $100 million investment from a Korean telco company, SK Telecom. So if you don't know, Anthropic was founded by former Open AI leaders, the makers of ChatGPT, and they recently raised, about three months ago, $450 million. So. So a lot of people haven't even used Anthropic in their Cloud 2. It's definitely worth checking out if you haven't already. And pretty big fundraising news here, bringing in another $100 million investment. All right, so last but not least, in our AI news today, Amazon just noted just less than an hour ago, just released that they are going to be using AI summaries in reviews. So they actually just started to roll this out across the US to select users. But more or less, here's what it means. You are going to see AI summaries of product reviews, which I think is fascinating because so many times, at least for me, you know, whether it's on Amazon or any other sites, I spend so much time reading reviews. So we'll see how accurate these AI summaries are. And there will also be a product insights feature that kind of highlights common trends found in reviews. So maybe I'll spend less time reading reviews and more time spending even more money on Amazon. So I'm excited, I'm excited to talk AI in ethics. It's something we don't talk about a lot. Don't worry, it's not just going to be blabbing. It's not just going to be me blabbing today. Have a great guest. So let's bring in our guest for today, Mo Alo, who is the senior sales leader, senior sales leader at IBM. Mo, thank you for joining us.

Jordan, I appreciate you having me. I'm excited to talk to you. I'm a big fan of your work.

Thank you. Hey, appreciate that. So as a reminder for those of you joining us live, like Nelson here, who's saying greetings, this is a live show. This is unscripted. So if you have a question for Mo just about AI and ethics, or if you're just interested even in, hey, what's IBM doing in this space, make sure to drop a comment like Michael who says cloud rocks. IB like cloud as well. So, so Mo, real quick, just tell everyone a little bit, you know, what you're doing at IBM. What's kind of your role as a senior sales leader at IBM and tail.

Sure. And at IBM, my role is I cover financial services. So I work with a set group of accounts. And you know, we, we believe in consultative process and the collaborative approach. And so we, what we do is try to learn as much about our clients and their pain points and then, you know, work with them to see how we can assist them as far as AI. And you probably are aware of this, IBM has been, you know, at the forefront of AI for a long time. It's something that we're proud of and we are as excited as everybody else is with all the new advancements that have been going on and how we can satisfy the needs of our clients and make sure that they're keeping up and also in appropriate ways.

Yeah, it's something I don't think we even talk about enough on the show is just IBM's role in this because I think if not for IBM's initial investment decades ago in OpenAI, Watson, Deep Blue, all of these Know, now that we kind of consider, quote unquote, old school advancements in AI, I don't know if we'd be here. Like what do you think about that, Mo? And, and how, how important do you think that IBM has been to even where we're at now, even with other companies?

Well, I, I think you're right. You're spot on. You know, IBM has invested into the research and into the process of developing an AI system and, and an AI that works and is trusted. You know, Deep Blue and Watson, you know, going back to, you know, the, was it Gary Kasparov, the, the chess player that was defeated by Deep Blue and then Watson won Jeopardy. And so it's kind of like the moon landing, right? Those are kind of like the first markers in, in making, you know, a large, uh, publicity for AI and the, and what large language models can do. And what, what that does is, gives us, you know, a basically two decades of, of working with AI models and fine tuning them and learning how to best deploy them. So. Yeah, that's something we're really proud of.

Yeah. Yeah. And timely, timely comment from, from Miguel joining the live stream here, saying, growing up, when I saw Watson doing his thing in Jeopardy, I was like, I want this for my personal life. And now we, we, we have this for our personal life. So, so Mo, as someone that's been involved in, you know, computer and technologies for a long time, can you just speak to now? Like, you know, even Miguel's comment here, we have this in our personal life.

Yeah, I mean, it's funny, right? We still don't, maybe a lot of us don't realize it and don't see it our way that way, but it is. And, and Jordan, I saw your POD recently on, you know, how you can personalize chat GPT, right. To learn how to write, writing like you, which I think is awesome. I mean, I think that's incredible that we can actually do that. And the way that you explained it made it very easy for people to use. Look, AIs is advancing at such an incredible rate and such a phenomenal rate. Everybody is being able to use it and learn from it. And Jordan, you do a daily show, right? Five days a week. You take Saturdays and Sundays off, thank God. But you could probably do an hourly show. Yeah, I mean all you have to do is be on Twitter, be on LinkedIn and, and follow, you know, people that are, that are, you know, pushing AI and, and just relating the latest developments. And you know, there's, there's so much that what you Touched on earlier. Ethics is obviously a, a big concern not, not just for IBM, but for all the, the large uh, companies out there that are involved in AI and developing AI.

Yeah. And kind of finally bringing us to our topic here, you know, ethics, because one thing that I find interesting is a lot of times bigger kind of bigger companies. So enterprise level companies that IBM would normally be working with are most set up or most, or maybe set up the best to leverage generative AI. But a lot of times the, the larger enterprise companies at times may be the, the last to, to adapt. So what's, what's just your overall take on ethics in generative AI? How should we be using it? Should you know, whether you're working at a, you know, a large company or small company, should we be using generative AI in all aspects of our work? Like what are your, what are your thoughts on that? Because you know, it's, it's a deep conversation and people have opinions but yet, you know, what are your thoughts? Just you know, given your background.

Mo. Yeah, so let's, let's try to unpack it and categorize it. Right. Should we, let's say should we be using AI? Absolutely. I saw your, your, your pod regarding should ChatGPT be banned in schools? And I love the approach that you took. Why would we give our students a disadvantage when they're going to be able to use it in the real world, learn how to use it? You know, what's the biggest, what's the, the most common statement that, that I've heard at least is, you know, job. Humans are not going to be replaced by AI. They're going to be replaced by people that use AI. Right? But the reason that thing that that statement took off is because it, it's true and it makes sense, right? We have to learn how to use it. You know, it's like I think you had mentioned, like banning the Internet, right. Etc. And so it is important for everyone to have an understanding of it, not only for them to learn but also so that they can know the trouble spots. They can go through trial and error. You know, there's, there's a lot of store. Let's go back to why it's important. Ethics and AI. I think that there's a personal responsibility, right? User ethics. How are we as individuals using it? There's the enterprise responsibility, right? Protecting data of the enterprise, of personal data that enterprises collect the outcomes of AI, right. Are we going to be, you know, creating, you know, the big fear that everybody has? You know, the, the terminator movie type AI, everybody dies or, you know, people lose their jobs. Obviously, you know, that's, that's not the case. That's a, that's an incredible stretch. And then accessibility, I think, is important. You know, everybody needs to have access. Everybody needs to be able to benefit from the, the tools that are out there. And I think as, as users, we are developing scar tissue and muscle memory when it comes to, you know, the, the dangers of AI just kind of like Photoshop, when that first became popular, you know, we kind of figured it out. It didn't take long to where, okay, that looks photoshopped, etc. Same goes for deep fakes. I know that there's a lot of talk about watermarking AI generated content, and there was a recent executive order or agreement on eight principles of AI that I'm sure you've covered. So I don't need to tell your, your audience has to be the most educated. There's like nothing new. I can tell your audience that's how good a job. Job Hallucinations we all know about. We've heard of, we've heard of, you know, situations where people, you know, got caught up or, you know, lawyers using AI that made up cases and, and, you know, those things are unfortunate, but I think that's part of our process as everybody to learn, you know, what exactly AI can do. But how should we be using it? I think we should be using it in the most effective, optimized way and doing our part to have guardrails. You know, just like anything else, the Internet has guardrails. You know, TV does as well. Yeah, let's see what doctor has to do.

Yeah, yeah, great, great transition here. So, yeah, Dr. Rostafa, get us with a great question saying there's two sides to ethics, the creative end and the user end. So kind of asking here, what's the responsibility of companies like IBM who are, you know, actually helping to create? You know, we haven't even talked about WatsonX AI, which we'll talk about here in a second. But what's kind of, what do you think is the responsibility of the companies that are helping to develop these AI systems? You know, obviously on the back end as users, you know, we, we have to have some of those ethics and guardrails MO that you talked about in place. But what are your thoughts for, you know, companies that are helping create these AI systems?

It's a huge responsibility. It's a great question. That's something that IBM, I'm very proud of the way we take it extremely Seriously, we have a AI ethics board, we have a privacy board. Any application that is developed goes through a AI by design, AI ethics by design process. We have AI pillars of trust, transparency, privacy, fairness, explainability, robustness, any. And there you go. I love it. Any AI involved development has to go through this process. Of course, anything that touches on a military application, anything that comes close to surveillance, facial recognition, those are things that IBM takes a very, very strong stance on. HR tools. You know, I think I read a stat from was it zip recruiter that I think almost 85% or something, a really high percentage, don't hold me to it, of resumes are initially screened by AI. And so think about the implications there. Admissions into schools, education, political. Right, political purposes, infrastructure, anything that's going to be harmful. So and, and this is, we're a leader in this field. IBM signed the Rome call to Action by the Vatican back in 2020, formed a partnership with the University of Notre Dame with an AI ethics institute. There's been so many different regulations that have, that IBM has been behind and regulatory bodies and what our position is. We believe in precision regulation, so we don't want to stunt the technology. Right. The use of the technology, that's where we want, you know, there needs to be guardrails. Right. But, but we are proponents of advancing the technology. Always that that's never something that we would be against, you know, at least at this point in time.

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Yeah, and you know, just, just a piece like I love mo that you broke down like step by step what IBM is doing in regards to ethics in AI because it is important, you know, for, for end users or for those that are ultimately consuming content from other enterprise companies that are using AI. Think it's important to know the aspects here that, that you kind of laid out. But a great, a great question here from Matthew. So we'll, we, we'll kind of transition here because, you know, I think we talked about this on the show before, but as an example, you know, some big companies are cutting down or downsizing their ethics teams, right. So Microsoft is one. They laid off kind of their, their ethics team that taught or that was, you know, working with ethics and AI. So what are your, what are your thoughts on, you know, larger companies or, you know, we don't have to single them out, but you know, what are your thoughts on the, these companies that aren't maybe prioritizing ethics as highly as IBM or maybe as highly as they, as they should be?

Yeah, you know, I think everybody's learning, right? IBM, we've been around for over a hundred years. We're one of the, if not the oldest technology company. I would hope that there's a pivot there somewhere that it wasn't just, hey, let's just take the garden grills off and we're not doing anything. Right. I would have to assume that there is something that they have in place or in the works. But you know, obviously it's not something that I, that we would be in favor of, that I would, that I'd be supported of, supportive of. I mean, we all know the, the typical example, or let's say the easy example to understand is people that would be disadvantaged by an AI because of their ethnic group or, or their zip code or they get a higher interest rate or they, you know, don't get approved for loans, etc. That's, that's something that I hope we as a society have really moved on and realized that that that needs to be taken care of. But the ethics around AI are, have to move as quickly as the AI itself is. Right. I know there was a recent study by, I think it was by MIT Technology Review and this is a little more in the weeds, but it found that programmatic ads are spamming and, and they're, you know, let's say Google, Google Ads are similar and they're being used on, you know, websites that don't necessarily have correct information or might be misleading information. And so those are the dangers and then a lot of those are just generated by AI. So, you know, the market's being flooded with people that want to monetize. There will always be bad actors and we have to account for that.

Yeah, absolutely. And you know, one thing we haven't even talked about yet, that I'm, I'm excited. So let's, let's quickly just kind of transition here because I'd love to talk real quick about what IBM is actually doing in the space because we, we haven't even talked about this a lot but you know, WatsonX AI. So you know, most people, and we kind of talked about this to open the show, most people have heard of Watson and it may have been actually for society. You know, seeing Watson on, you know, Jeopardy. May have been people's first big or main introduction into what AI is, into what its capabilities are. But real quick, just talk about WatsonX AI. So this is kind of more for enterprise companies. But just, just briefly Mo tell us why Watson X AI might be worth looking at for, for companies.

Absolutely. And it's something that we're very excited about. Like you said, IBM has a deep history with AI and Watson is a name that everybody knows. And what we've done is we've created the Watson X platform and it's for enterprise like you said. And you got to think of it with three subsets. WatsonX AI which is going to validate, tune, deploy AI models. WatsonX data allows you to scale the AI workloads for all data anywhere on prem cloud, etc. And then WatsonX governance. And this goes to our topic today. Think of that as the nutrition label of your data responsible transparent AI workflows. You want to know and make sure that the data that you're putting into your business is safe, that it's reliable, that is trusted. What we do is we help enterprises get off to a good start with a solid already trained model with where then the customer be able to insert their data and then also the domain or industry knowledge and that allows then the enterprise to have a structure, it has a head start if you will, and then the guardrails that are necessary. So we're really excited about it and obviously it's off to a great start.

Yeah. And you know, having access to these platforms, you know, whether it's, you know, IBM's, you know, Watson axe and I know that they are even integrating Meta's Llama 2 into Watson X AI. But I think having access to these generative AI systems, whether it's at an enterprise level or just as an individual, I think gives you so much extra benefit that maybe we didn't have a year or two ago. And I bring that up because Harold here joining the show has a great question because he's asking more about the approach to accessibility. Because Mo, you already referenced this, that this, these generative tools aren't necessarily open to everyone, right. Like depending on what, what end, you know, because again, there's, there's Google has their, their tools and software, Microsoft does, IBM does, you know, and depending on where you are or your budget, you may not have access to all of these. So what's, what's the right way? Maybe not asking from an IBM perspective, but as society, how do we tackle this accessibility piece and you know, to kind of create a, as level of a playing as possible because I think that's one of the biggest, one of the biggest issues facing generative AI use right now is this accessibility piece.

It's a great question and Harold, thank you for asking. IBM has always been extremely involved in the communities, right? So we have partnerships with universities, with local schools. We have a whole division that is around accessibility. Similar to what I said about the AI ethics involvement in the design process. We also have a accessibility check. And so now accessibility, you know, I can see there might be two meanings, access to technology, but also access for those who have different abilities. Right. And so IBM has a focus on both. We launched Skills Build where we have a free online platform where people are able to go in, learn, earn certificates. And AI is obviously one of the, the big topics in, in that. And, and I point you to skillsbuild.org and there you go there, there you are. And so this is something IBM takes very, very seriously and we're happy to, to do so.

Yeah, and I know this has been a long show, but I do want to end on this. Mo, you have such a great background and I think you've shared so much great information today. But what would your takeaway be for business leaders, for even individuals? As we kind of grapple with this piece on ethics and AI, what would your takeaway be for people that are trying to use it in responsible way to, to, to grow their business? How can people do that?

Well, I think they should, number one, watch the everyday AI podcast every morning. But no, you do a great service, Jordan. I want to make sure I get that stated. I appreciate what you do. You cut through and also highlight the things that are important. But I mean, as far as your question, I think what a lot of us don't realize or maybe haven't, you know, thought about is AI has been used in, in everything that we do for a long time. Right. I think what Chat GPT did was kind of shine the spotlight. You know, I think our CEO compared it to what Netscape did for the Internet. And so which is great, which is, you know, something that everybody is excited about and, and the accessibility to, to millions of people around the world to using a large language model like Chat GPT has been phenomenal. But my advice is to always ensure that you have ethics at the forefront. There's a lot of damage that can be done to a lot of people and a lot of businesses, small businesses, if ethics is, is not a serious component of anything that you are developing or rolling out to the public. And so that, that's really my advice and choose a great partner you have in house talent as well as consultative, you know, you know, get a view of, of the outside world of other. What your competition is doing. Make sure that you have ethics at the forefront. And I think it's an exciting time. This is, you know, the, one of the most impactful technological advancements in history. We're all part of it. We're all, you know, right in the middle of it and it's exciting.

Yeah. Speaking of exciting, this at least for me. And I hope if you're out there listening and tuning in live as well, I hope this was an exciting conversation because we went over a little bit of everything. Mo from, from ethics and the background of even IBM to how we can look forward to responsibly using AI in the future. So thank you so much for spending some time on the Everyday AI show to help us all figure this out together.

Really appreciate it. Pleasure. I'll be watching. Thanks a lot, Jordan.

All right, and just as a reminder, don't worry if you couldn't keep up with everything. Go to your everyday AI.com Sign up for our free daily newsletter and we're going to have a recap of the conversation that we just had with Mo talking about ethics and everything else. And if you are listening on the podcast, don't worry, look in the show notes today. We'll have links to this and even if you want to jump in kind of our, our daily LinkedIn thread and ask Mo questions. If, if you are listening on the podcast and you're like, oh, it would have been great to join, don't worry, you can click and do that. So thanks again to Mo for joining us and thank you and we hope to see you back tomorrow and every day on Everyday AI.

Thanks.

Pleasure, Jordan.

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