The Quest For Trust In AI (Guests: Ariana Smetana, Noelle Silver, Tolani Jaiye-Tikolo)

Andreas Welsch: 0:21

Today we have a special episode for you. I've been playing one of my favorite retro games again, What's the BUZZ? And I'm really stuck. And so that's where I've asked three experts to help me on the quest for trust in AI. Ariana, Tolani, and Noelle. Thank you so much for joining.

Noelle Silver: 0:43

Thanks so much. We're excited to be here.

Andreas Welsch: 0:47

Awesome. Why don't you tell us a little bit about yourself?

Ariana Smetana: 0:52

Thank you, Andres for having me today. I'm Ariana Smetana and I'm the founder and CEO of the AccelIQ digital innovation consultancy. And we guide companies to different creative differentiating value for their customers, employees with development of digital tools, solutions, and advanced technologies that can implement in their organizations. Over the last three years, I've been focusing predominantly on emerging technologies, and I have a very keen interest in AI and I use applications and actually creating the business value the most importantly with. I came to AI field a rather non-traditional route. I'm not technologist. I'm actually economist and have a business degree and long history of business knowledge and actually being an entrepreneur. So that's where I come from and bring value to the businesses with use of technology.

Andreas Welsch: 1:55

Fantastic. Thank you so much for joining. I'm so glad you're you're here and to have you on. Likewise. Yeah. Over to Noelle.

Noelle Silver: 2:04

Awesome. Hello. I'm so excited about this game. It seems so fun. I hope I can help. I don't know. But I'm Noelle Silver. I'm the CEO and founder of AI Leadership Institute, where we educate executives across the globe around artificial intelligence and really around responsible AI at scale. One of the other things though that I do on a daily basis is I'm an executive at IBM and I always think it's interesting cuz my career 22 years ago started at IBM. A very different IBM but it's interesting, we're gonna talk about like transformation and AI and building inclusive teams. And all of these things I've watched happen in my career. So super excited to hear from all of the people playing the game today and happy to be a part of it. And of course you can always find me on LinkedIn if you guys need another LinkedIn friend.

Andreas Welsch: 2:57

And that's how we met as well. So I'm really excited about the power of the platform and connecting on that topic that we're so passionate about. So then maybe over to Tolani. Great to have you on as well.

Tolani Jaiye-Tikolo: 3:08

Thank you. I'm so super excited to be here. Cuz we've been talking on LinkedIn for god knows how long. It's really, it's sometimes it's like a dream for me. Just as you've mentioned, my name's Tolani Jaiye-Tikolo. I'm the founder of RPA Jargon Buster. The good thing about RPA Jargon Buster, it's not just, busting jargons or busting memes. It's actually a small business based out of Ireland. And what we do is quite simple. We do four things very well. We do intelligent automation research. Adversary consulting and corporate trainings but doesn't, literally about myself. I've been in the digital transformation space for seven years or I've been more focused around robotic process automation, and that's where I literally started my career from. And within that know timeframe I've seen, RPA evolve into other sort of other technologies such as what we are beginning to talk about like intelligent automation. And that's really why I founded my own business to really, get into that market share and see what's going on in that space. So what we do is cross consortium rem. We work with SMEs and mid-market financial services and healthcare. It's a no-brainer why I'm in the financial services. I'm also an employee as well. I work with Allied Irish Bank as an RPA lead. But I'm really happy to be here. Thanks for having me..

Andreas Welsch: 4:42

Excellent. Thank you so much. I don't think I realized it when I set it up and the fact that all three of you are founders of your own companies that's exciting too. So really glad that you're able to add that perspective to it as well. So maybe just a quick shout out to folks in the audience. If you're just joining the stream, drop a comment in the chat, what tricks you're looking for, but like last time, no cheating allowed. What do you say? Should we start playing?

Ariana Smetana: 5:15

Absolutely, yes. Let's do it.

Tolani Jaiye-Tikolo: 5:17

Yeah, let's do it.

Andreas Welsch: 5:18

Excellent. So this one is a warmup. When I hit the buzzer, you'll see a sentence and I really need your help. So can you answer with the first thing that comes to mind and why, in your own words. And so together you have 60 seconds for your answer. Keep it short, right? So team, are you ready for What's the BUZZ?

Noelle Silver: 5:41

Yes.

Andreas Welsch: 5:44

Let's do this. If AI were an animal, what would it be? Maybe Noelle. What do you think

Noelle Silver: 5:54

I'm like it has to be a unicorn. Because some people believe in it and some people don't. But it's capable of incredible things, if you believe. So I like unicorns or rhinos, which are actually the real life version of a unicorn if you need a real animal. Cuz some people say unicorns aren't real. Who else got one?

Andreas Welsch: 6:20

Perfect. Who else?

Ariana Smetana: 6:24

It's funny, first thing came to mind was actually a monkey and I think, it's really constantly working and dealing with lots of data and information and you're not coming out with the answers. Like you said, some people believe it, some don't believe it, and it thinks something. Some people think it's a monkey business, but it's definitely not

Andreas Welsch: 6:47

Lovely. I love it. How about you, Tolani? I know we're out of time, but keep going.

Tolani Jaiye-Tikolo: 6:52

Yeah, so I think it would be a chameleon. It's a lizzard just because people think they know it, but they don't. So it always changes based on what you fitted and how it turns to work around different environments. So I would say chameleon.

Andreas Welsch: 7:10

I like that. Fantastic. Thank you so much. Thanks for coming up with those things on the fly. I really appreciate it.

Ariana Smetana: 7:18

Fantastic.

Noelle Silver: 7:19

Like I went first. That's fair.

Andreas Welsch: 7:21

I put you right on the spot.

Noelle Silver: 7:23

I know.

Andreas Welsch: 7:23

I think that part around it's different things. It changes. That's something I feel really resonates at least with me and I'm sure with folks in the audiences as well. And changes and means so many different things to so many different people. Let's maybe take a look at the first question and what that is. And that is: What's the first thing in a transformation? So wondering Ariana if you can help me with that. What's the first thing you do in a transformation?

Ariana Smetana: 7:59

So what I advise my clients to first think of is business problem. We started with the business problem. What is the business problem and how can it be solved with AI? Should it be solved with AI? And why is this problem important for the organization to be solved? There are so many tools that we use in organizations and AI is another tool to be applied. Certainly it's business problem. The next one will be business value of solving that problem and how we going to use that to generate the value and then creating what is the data strategy objective functions. Modeling and all of that comes later. But certainly, knowing our resources from the data, from the people, from the processes, these are so many layers that need to be addressed. But I would say, business problem is the first one to start with.

Andreas Welsch: 8:54

Fantastic. And I think that's a theme we keep hearing, right? Start with the business problem. Worry about technology later. If you do it the other way around you're just in love with technology and you struggle to make that case.

Ariana Smetana: 9:11

The business value is where the every company will want to use that. Otherwise, there are so many other tools you can use for solving problems and decision making.

Andreas Welsch: 9:23

Let's maybe then take a look at question number two that we have here. And that is: How do you build trust in AI? That kind of goes along with it. If you start with the business problem and you roll it out to people, how do you make sure that they actually appreciate what you're doing here and that they accept what you're doing? And I know Noelle, you've been doing quite a lot of work in that area. What do you recommend?

Noelle Silver: 9:51

Absolutely, this is a good question. And it's so interesting, like of course it's level two cuz the first thing, as you mentioned in any digital transformation, right Ariana, is figuring out what problem are we gonna solve? And then you think, okay, how can I solve this, like the fastest way I can with the best technology? And AI is often thrown on the table as a tool. And the operative word is trust. And so the way that I build trust when I go into an organization and I'm talking about the dream of AI which I am very good about selling the dream of what you can do with all this cool technology, but trust only comes when I actually can deliver on the dream, deliver on the promise. And it ties directly what to what you said, right? As soon as an organization culturally understands what problem they're gonna solve and what tangible business outcome they want, that's becomes literally the way I build trust in AI. I build an AI system that delivers on that value. So oftentimes like simple, intelligent workflows, right? If somebody has a manual process, I can go in and just say, okay, I commit to improving your throughput of customers by 35% with the use of AI. Then, my job is to actually deliver on that promise, on that 35%, and as soon as I do, trust is built, but it's built in these like little small projects. Gartner even said like over the last five years, 90% of projects failed that had the word AI in them. And the reason why was exactly what Ariana said, that, we'd never identified the exact problem we wanted to solve, nor did we attach an actual value to that solution. And that's where AI is the most powerful. And so yeah, I'd say we build trust by delivering results on those business outcomes by building models that solve those very specific.

Andreas Welsch: 11:42

Fantastic. I really love that. And make it tangible. And put your money where your mouth is. With all the hypes still around AI and the AI whitewashing, it's it's so easy to claim there's AI in everything. And all the promises that we make, we better keep them.

Noelle Silver: 12:00

That's right.

Andreas Welsch: 12:01

Especially if you wanna be credible and win trust in AI. Excellent. So then maybe let's take a look at the next question here, and that is question number three: Why do businesses still want a human in the loop? And maybe that's something Totani that you can maybe help me with. I know you work a lot on RPA and intelligent document processing, but there is a lot of people still in the loop. Why do businesses still want to human it?

Tolani Jaiye-Tikolo: 12:30

I think I'll look at you from two different angles. And I'm probably gonna take you from what Noelle stopped. When we talk about business outcome and delivery on those business outcome, we still need to advise people that AI would never be a hundred percent in terms of predictions. So people would need to be wary of this and also acknowledge that with AI you might have 80, 90%, but you still need human in the loop to help refine the view of the world. And I'm probably gonna give a good example here particularly around if you have, let's say a child or if you have a nephew or a niece. So whatever the case might be. You take them to the zoo and they identify different animals. This is it's a lion, this is tiger, or wherever the case might be. Then tomorrow I come back and I tell the child I give them a picture of a fox and I tell them it's a dog. The first thing they're gonna do is argue with you and say, no, this is not a dog. Right? There are two things are gonna happen. Either I get convinced by that child that it's not a dog, or I convince that child that it's a dog. And let's say, because of who I am, I convince the child that it's a dog. What's happened is the view of how they see things is completely different. Every time they see a fox, it becomes a dog. Every time they say a dog, it's still a dog. And that's why I tell them that AI a hundred percent, you don't get that a hundred percent. But you keep changing the course of AI by refining, putting our human input into the system. And I think the second part of it is, again, I might probably just put it on the businesses because we can. Businesses fail to find good data sometimes. What I would always advise is, you want to build, let's say a good model. You need for documents, you probably need about 500 for good prediction, I tell you that. How many people in the organization can go into wherever they have it, into their lockers or wherever on the network, and give me 500 different samples. It's not gonna happen. But what we can do with human look is they keep in as much as we have a small sample, we can keep refining that over time. And AI becomes fresher than how it was yesterday. And this is where humans really change that course. But given the ai, the transparency it needs and the oversight it needs and it keeps improving over time, just not to take too much of your time, probably just stay on those two examples.

Andreas Welsch: 15:01

Thanks. The part around having that human in the loops even if you do have the data, you still need to label it and you need someone to tell you, what are maybe the bounding boxes around some of the text and all the manual and even still laborious tasks while you're trying to get rid of some laborious tasks. That's where people can help you already in the process today. If you augment it. If you make that step part of the process, build a good data set that you can then do your AI with. Perfect. Thank you so much. So that's awesome. Team, we did it. Thank you so much for playing What's the BUZZ? today! So let me summarize real quick. First of all, if you think about digital transformation, make sure you look at business value and business objectives first. That's where it all should start. Technology comes second. Then secondly, while you're building that talk track and getting that buy-in, whether it's from your customers or from your internal stakeholders, make sure that you also deliver on the promise to keep the credibility to build that trust and reinforce it. And one way to do that is to have a human in the loop for processes, especially where they're document based or where you can and should review something to make sure that your data set is built and gets better over time. Fantastic. So we're getting close to the end of the show today. Thank you so much for joining us and for sharing your experience with us. I really appreciate it.

Ariana Smetana: 16:32

Thank you.

Noelle Silver: 16:32

Thank you. It was so fun.