Business
In This Episode we look at the question: When do I start trusting AI? Hi Everybody, welcome to another episode of click AI radio. My name is Grant. Alright, so been looking into this problem around trust. And what is it that gets in the way of us leveraging AI? Well, part of the problem comes from some reports. Right. So we'll look at a couple here. One of those was a report from Pegasus and the other was from pega systems, I should say, Now there was a Harvard Business Review report. And of course they they capture what people what we think about in terms of challenges around AI plenty of horror stories out there for sure. Can we actually trust this stuff? We all know about, you know, the Chinese board game go and how AI beat beat the Chinese board game player. kg. I hope I'm saying his name right? Back in 2017. ertainly machines can do a lot. And that's, of course, what we expect what we need them to do when we look at the Harvard Business Review. And what it is that they pointed out some of the challenges around this in in the Journal of marketing, they said based on data from over 3000 people who took 10 experiments, they provide some evidence, all right. And so here's here's the evidence, right, so there's the word of machine effect. And that stems from a widespread belief that AI systems are more competent than humans in dispensing advice. That's kind of an interesting viewpoint, especially when you really think about what it takes to build an AI model. It requires multiple layers of a network, typically, to help create decisions. Now, that's typically too much for us to think about as business owners. And generally, you don't want to have to get to that level of detail. One of the problems around AI, those are expectations of it, given all the hype that goes on out there, one of the best things I found that helps us to work through this is the mental model of viewing it as augmentation intelligence, rather than as artificial intelligence. I think sometimes that misnomer gets us into problem. And we expect it to do more than it than it really should. In fact, one of the best practices around this that I found is, as you're working through making decisions, and you're getting insights from an AI model, you need to compare it against reality. Certainly there are contextual things that the model designer may not have known. And of course, the more that you can get context into the brain of the model designer, the better it is for your business. But that doesn't always happen. So you need to apply the human cognitive sense and the sense of reality that the humans can pick up that the AI is not able to. So what what's critical to this as it becomes more of that collaboration, if we view AI as I'm going to spend time giving feedback into the model to inform it of ill advised insights, or things that just didn't work out. We need the models to be able to learn and grow and make adjustments over time. So coming back to this, to this HBr review, Harvard Business Review, one of the things that they pointed out was convincing a customer to give AI the benefit of the doubt. All right, so Okay, I think that might get a little bit too Ryan's talking about a moment ago, which is we need to look at AI as augmentation to our insights. And one of the key areas, of course, to think about is those ways in which AI can see things that's hard for us to see. That's really where we should should leverage the capabilities of AI itself. So I was working with a business owner recently who made the comment. Well, I'm not sure that my people will actually trust The insights from this, which I find interesting, and then there's this other group that I interact with and work with, they provide an AI platform that I strongly recommend. It's one that we've built and based our stuff on. And, and they made this interesting case study. Recently, they said that, that one of their clients had taken an AI model, and had deployed it and put it into production and hadn't actually told anybody. And what happened is, is over time, people started to notice this score, and the score was integrated into their system. So they were making these these selling decisions. And they started to draw a correlation between when a score was higher, the sales opportunities, they found out, were turning out to be better. Whereas when the score was lower the sales opportunities, were not as good. Rather than tell their employees, you must use this, they just put that into the system and let people start to observe it. And then they started to derive their own conclusions from it. And so rather than this top down approach of you must use this, they took this organic approach that said, let me let me put this in front of them, and then let them experience the results of it. and discover if if what the insights are giving reflect the reality and in fact, augment your reality in a way that it builds your confidence in that system. And so it's a critical way to approach AI. It's not to look at it in a dogmatic fashion, but rather look at and I love that case, study, look at it in a way that says, Let's, let's leverage and build on what we're already doing. And then let's verify is this augmented intelligence actually benefiting and restoring and building our growth and trust in AI itself? Simple example. But I think it's a very telling example, for sure. All right, trust is built over time. We know that certainly with humans, and I believe with AI as well. So though the approach here, get some AI going in your business, do it low key low cost, don't push or force it, and let the people in your team start to experience the benefits as well as the downsides of it. Learn together, refine it, over time, that trust gets built, and then he starts to see the results that will actually increase your business outcomes. All right, everybody. Thanks for joining and until next time, build your trust in AI. Thank you for joining Grant on click AI radio. Don't forget to subscribe and leave feedback. And remember to download your FREE eBook visit ClickAIRadio.com now.