AI Today Podcast #001: Why Does AI Matter?

The AI Today podcast, produced by Cognolidica, cuts through the hype and noise to identify what is really happening now in the world of artificial intelligence. Learn about emerging AI trends, technologies, and use cases from Cognolidica analysts and guest experts. Welcome to Cognolidica's AI Today podcast. I'm your host, Kathleen. I'm your host, Ron Chmelzer. This is our first of multiple podcasts we're doing on a topic of what is happening today that is relevant in the field of artificial intelligence. What you're going to be hearing from us over the course of multiple podcasts is upcoming topics, features, things that are newsworthy, information, and of course our focus and feedback and opinions on the topic of artificial intelligence. Great. Our first podcast is going to be on, why does AI matter? The part of the reason why we're doing this as our first topic is because we believe that the question is not necessarily being asked enough. We're doing all this artificial intelligence stuff before what reason, right, Kathleen? Correct. That's what we're going to answer today. This is our opinions on why AI matters. I think let's get things started a little bit. People are really thinking about AI and they think about all the great technologies and things that can be done. But first and foremost, the real applications of AI that we're starting to see make impact for businesses today have to do with improving the way that companies serve their customers, make it more reliable, make it more efficient, and especially what we're seeing in the realm of chatbots. I've had some pretty good experiences talking online to some customer solutions that I was actually talking to about, but it served me at three o'clock in the morning when they phone services down and didn't have to wait until next morning and go through that long and knowing call center and to reach somebody who didn't really know what the problem was and I can get that solved immediately. So for me, even though that's a very narrow, as they call, weak focus of AI, it was very helpful. I don't know, Kathleen, what do you think about that approach to using AI to really improve the efficiency and effectiveness of business to customer communication? Yeah, and I like how you brought up that you had it at 3 a.m. Because I think that one challenge company space right now is always being there for the customer and call centers have a limited window of maybe eight to five every day and then not open on the weekend where a chatbot can be available 24/7 and they might not be able to answer all of your questions right now, but they're pretty good at getting most of them answered. So I do think that the ability for businesses to help serve their customers and help be there for their customers 24/7 is definitely improving with AI. Of course, you know, one of the downsides of that people say that it's pretty obvious right now when you're talking to a bot, especially when you're having conversations that may not necessarily be complete English sentences if you're using a chatbot or talking about things that may be a little off topic or even like things that are on topic, but require like you're not communicating all the information like, oh, my system is down like, okay, what does that mean? You know, so there definitely are some not necessarily optimal implementations of AI right now, but I think from what we're seeing, the sole chatbot conversational interaction with something that's pretty intelligent, it seems to be effective use of AI. Right. And I think that we have a ways to go, but you know, this is definitely a good starting point. And I think that everybody acknowledges that that's what this is. So another point that I have is to why AI matters is that it's allowing people and companies to deal with a lot more information than they could possibly handle on their own right now, sort of like an intelligent assistant, where it allows people to take information that they would never be able to read on their own or take weeks or months and compile it into a short period of time and be able to use that effectively. And I think this is applied in few instances where an account, for example, might not be up to speed on all of the latest policy changes that are taking place or not know exactly how to apply it. The intelligent assistant can help with that. I think that this was also shown during the election with taking all of the polling data and being able to under process and understand it in a much faster time. Yeah. That is definitely the case. I think that's really the big difference there where AI is being applied instead of just search, right? Because right now, yeah, Google and Microsoft and all these folks have really mastered the idea of search, but all it's giving you is just pages and pages of information, especially if it's internal to the company like, well, I really wanted to answer to this question. So the whole idea of that smart assistant to say, well, I know that all the information is here, but we'll get a lot of the answer to my question, how does this apply to my job, or how does this apply to this problem that I'm trying to solve? AI seems to be tackling that problem pretty well. So I guess the challenge is really about, how do you make sure those systems are smart enough to be able to have the information necessary to answer that question, right? Right. And I think that we're still figuring that out, but we're getting there. And I think that some applications have been shown to be very effective. And like I said, it's an assistant. So it's not supposed to be replacing right now. It's supposed to be augmenting. Exactly. So I think sort of like piggybacking on that, one of the other great uses of AI, but also to answer the question like, why does AI matter is it's really trying to help people in organizations make better decisions, right? And fewer mistakes. So it's not just about, you know, having this information at your fingertips, but, you know, especially this idea of the intelligent assistant, you know, really helping guide people say, well, you know, in this case, this AI is not going to make the decision for you, but really help you make that decision. So starting to see that a lot of especially in medicine, you know, with AI assisted for treatments and for diagnosis and things like that, for a lot of applications, especially in military and government applications for our decision making, especially if you're in a situation like say a battlefield environment where just stuff is coming at you from all over the place, you know, humans were pretty good at making decisions, but actually, you know, that's the whole idea of analysis paralysis. You have too much information. You can't actually make effective decisions. So, you know, why does AI matter? You know, it's not just helping you get information, need a lot of a haystack, but it's really about helping you make, you know, better decisions. And I think the better we can build AI systems to do that, the more useful it'll be. Right. And then I think that it also, you know, to go along with that AI can help do tasks that are too dangerous for people to perform. And by too dangerous, I mean, it's a situation that we'd rather have a robot in or a drone in than a human being. Right. So, you know, war, for example, or maybe a fire situation, we'd rather have a robot or a drone go in than a human. Let's get into it. You know, I know a lot of people are really thinking about, you know, AI and they think about self-driving cars, right? They're thinking about, you know, robots are thinking about drones, right? This is one of those things people talk about. Yeah, of course, there's some fear about that, but what do you think, Kathleen? You know, there's a whole idea of AI has applied to all this autonomous stuff. Right. I mean, I am very excited to see where self-driving cars are going. I think right now it's in its infancy and I know that laws need to catch up with it, which is another, you know, to answer why does AI matter? I think we need to be talking about this because we need to make sure that people are understanding what this means and that, you know, we make sure that we have things and systems in place. Self-driving cars is one of them. So, we need to figure out in the short term how human drivers and autonomous drivers can be on the same road and be safe. Yeah. And, you know, that's actually making a lot of use as I have speaking of AI today. You hear this sort of little bit of on-going. I don't want to call it a feud, but this conversation happening between Elon Musk on the one side saying, "Hey, guys, let's sort of slow down this rapid adoption of AI because we have cars and they're going to be making decisions about should they speed up, should they slow down, should they avoid this collision and, you know, systems are, you know, not necessarily mature enough to be able to necessarily make the right decision. You know, if you're driving fast and then like there's this person walking across the street and then you can sort of avoid that person, but at the same time you might run into another vehicle, you know, the AI systems may not be smart enough to make the same kind of rational decisions that a human might make. So, I think that's sort of one of the fears about a lot of this autonomous stuff. And of course, people watch too much Terminator and everybody's afraid of SkyNet, so, you know, right. You don't like that sort of stuff, but at the same time, I'm with you, you know, like what can you do in a universe where you can call a card anytime that shows up at your doorstep, take you to where you want, you get on, you get off, just as totally autonomous. I mean, that's a future that we're still trying to figure out. Right. And I had recently read an article where people, you know, we're talking about self-driving cars, for example, and you have to be careful about what you tell the car to do versus what you've been for the car to do. So, if they say, take me to the airport as fast as possible, does that mean the fastest route within, you know, obeying traffic laws and speed limits? Or does that mean literally get me there as fast as you can go? So, we need to constantly be thinking about that when we are building and implementing AI systems. Mm-hmm. And so, sort of piggybacking another sort of usefulness of AI and YA matters that has both a positive and a negative side to it. The whole idea of artificial intelligence system removing the repetitive, the boring tasks, the tasks that people are doing over and over again, they're absolutely necessary, but, you know, they're completely boring. You see this even today. I mean, you walk into a McDonald's and they're already getting the kiosks and operation, you know, Olive Garden, you could see these kiosks. And well, maybe those systems are not necessarily AI. They may just be, you know, e-commerce at your fingertips. And it's obviously not that hard to sort of see the evolution of AI, making it impact into a whole lot of white collar and service jobs that are occupied by people. And you can, like, walk down the street and go into a stormy, like, yep, that job's going to be AI, that guy, that guy, that's going to be AI. Is that a plus or a minus? You know, you could see both sides of the coin here, but we think it's an inevitability. It's just a lot. The ability for artificial intelligence systems to do these tasks reliably, efficiently, without tire and, of course, cost effectively, is there. So that's something we're seeing. Right. But going back to the point that I had made before that this is an intelligent system and it's used to augment, not replace, in all cases. So we need to figure out and see where that's going to because while it might be easy to go into the local coffee shop or Starbucks, for example, and have it be all autonomous, is that really the right experience for the customer that there's no human interaction? You need to take that into consideration too. People might go into the Starbucks in the morning so that they can talk to a human before they go into work and replacing the cashier with a bot or a robot. It might have an adverse effect that Starbucks didn't think about. Part of the reason why people are going into the coffee shop is to have a human experience. Another thing that it does is that humans are taught to upsell and robots may not be. They're just taught to do the task and so maybe Starbucks sales of pastries start going down because of that. So, you know, AI matters and then you always have to think about the actual implications of it as well. So just because it may make the tour more cost effective, it might actually have an adverse effect. Yeah. I think you know, maybe this is a good sort of place to wrap it up because we've been talking a lot about ways that AI matters. And you can even just make sure the general case that the reason why people care so much about AI is like the same reason people care about space exploration. They may not see necessarily the immediate impact on their day-to-day lives today. But so much has come out of the process of exploring space, things that we use on a daily basis, whether it's thermal blankets and, you know, baby formula even came out of the stuff that came out of the appell program, even microchips, right, that the the process of exploring space, the technology, and similarly we could say that just the process of thinking about how smart can we make our systems and make our computers and machines. If we just pursue that, it might just improve everything else we're doing. And that might really be the strongest reason why AI matters. I agree. It would be very interesting, you know, and it's very exciting that we're this early into artificial intelligence to see where things go. Okay, so I think this is a really good place for us to start. You know, this is obviously, you know, our first podcast of many that we're doing the subject. We're going to continue to explore this idea of why AI matters dive deeper into each of these segments. Look at how AI is really being implemented in practice. Talk about some of the cutting edge applications and thinking about really how can it apply to my day-to-day life, even if I don't necessarily see the application of this today. I think this is really a good basis for the conversations that we're going to be having over the next few years. I agree. All right, listeners. Well, I hope that you've enjoyed this podcast and we'll catch you at the next one. Like this episode of Want to Hear More, with hundreds of episodes and over 3 million downloads, check out more AI-Today podcasts at AIToday.live. Make sure to subscribe to AI Today if you haven't already on Apple podcasts, Spotify, Stitcher, Google, Amazon, or your favorite podcast platform. Want to dive deeper and get resources to drive your AI efforts further? 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