AI’s Future: What You Need to Know Before VOE

This is a special edition of the VOE Podcast, designed to serve as a primer for our next in-person speaker series: “Voices of Experience: Denver’s AI Future.” That discussion will cover the future of AI through a Denver-centric lens. City and county leaders will share how they’re using emerging technologies to address the most pressing issues in the Mile High City. That includes things like immigration, housing, infrastructure, workforce development and the economy. It takes place on Monday, May 20, on the University of Denver’s campus.

Leo Dixon’s love of artificial intelligence began years ago with Star Trek and the hologram, and has since blossomed alongside his professional and academic career. Dixon is a teaching assistant professor in the Department of Business Information and Analytics at Daniels and an expert on artificial intelligence. His research and teaching expertise spans entrepreneurship, AI, computer programming, databases and analytics. On this episode of the Voices of Experience podcast, Dixon dives deep on the core principles and transformative potential of artificial intelligence.

Show Notes

Leo Dixon is a teaching assistant professor in the Department of Business Information and Analytics at Daniels and an expert on artificial intelligence.

Table of Contents

1:24 The early days of AI
2:17 Star Trek holograms and a computer being
2:45 The expansion of AI
4:52 Assist, augment and automate
Uncommon AI applications
8:02 “A different way of computing”
9:34 Predicting the AI future
11:33 ChatGPT asks a question
14:24 How to learn more about AI
15:19 Show notes and credits

In this episode:

• Q&A: How AI Fits in Entrepreneurship
• Voices of Experience: Denver’s AI Future
• Register for VOE in-person

Related articles and information:

• IOC unveils plans for using artificial intelligence in sports – ESPN
• AI for Earth: How NASA’s Artificial Intelligence and Open Science Efforts Combat Climate Change – NASA
• Google Maps Will Use Artificial Intelligence to Help You Find EV Chargers Everywhere – CNET
• Lights, camera, algorithm: How artificial intelligence is being used to make films – The National

Transcript

Nick Greenhalgh:
Today, on the Voices of Experience podcast. What exactly is artificial intelligence and how do you weave it into your work?

Leo Dixon:
You can’t just say, I’m going to integrate AI into my business. You still have to think about what are your current processes and where do you want AI to be in that process?

Nick Greenhalgh:
On this episode, we’re joined by Leo Dixon, a faculty expert at the Daniels College of Business, to dive into the core principles of AI and its transformative potential. Join us as we explore advancements, ethical considerations, and the future landscape of this technology. Oh, sorry, I forgot to mention, that part of the intro was written by AI… actually, from ChatGPT. Back to me for a moment. This is a special edition of the podcast designed to serve as a primer for our next in-person Voices of Experience event on Monday, May 20. That discussion will cover the future of AI through a Denver-centric lens. We’ll host leaders from the City and County to share how their using emerging technologies to address the most pressing issues in the Mile High City. That includes things like immigration, housing, infrastructure, workforce development and the economy. You can register for that online at daniels.du.edu/voe. But first, Leo, welcome to the show.

Leo Dixon:
Thank you. I’m happy to be here.

Nick Greenhalgh:
So I want to jump in here and talk a little bit about your academic career. You’ve recently started research on AI’s applications, specifically around entrepreneurship, and we’ll be sure to link that Q&A in our show notes where you talk a little bit more about that. But taking a step back, where did your fascination with AI begin?

Leo Dixon:
Well, it really began with just computer intelligence, I would say. When I was in school, they called it mainly decision support systems, so building database applications with Microsoft Access, and then eventually SQL Server, Oracle and so forth. And that’s because I looked at storage or memory as one of the key components that AI, I knew would kind of grow to be… Why it became so successful. Because really what it is, the ability for a computer to remember why it’s doing something or what it’s trying to do. So I would say the fascination began there, but the spark that happened around November or so of 2022, I think for all of us is really would’ve really touched home, if you will.

Nick Greenhalgh:
And did I read something about an interest in Star Trek back in the day too?

Leo Dixon:
Yeah, I mean the hologram, right? I mean, being able to walk in and that’s where you mix in some of those other fourth industrial revolution and technologies, where they all kind of come together with the virtual reality, mixed reality, and then being able to interface with that computer being, or whatever we want to call it. Yeah, it’s very exciting to me. So I’m looking forward to really being a part of that in real life, and I think we’re getting closer and closer to that.

Nick Greenhalgh:
Great. When we hear AI, I think a lot of people think IBM’s Watson and more recently things like ChatGPT, virtual assistants, Siri and Alexa, and even autonomous vehicles. So how has AI expanded in recent years and how would you describe what it is at this point?

Leo Dixon:
Yeah, I think it’s a paradigm shift is what’s happening because technically, AI is underneath what everyone would call, for the most people, for the most part, machine learning. But now that’s kind of swapped places because that I think wasn’t as marketable. So now you have AI and then you’ve put a whole bunch of things that already existed underneath that. So when we talk about machine learning, technically all of AI is machine learning, but AI as a subcategory is about predicting. So that could be the weather, that could be for a restaurant, maybe how busy you may be on certain days of the week. From a medical perspective, it could be do you have cancer or not? But again, these things already existed before, but now that is a category underneath AI. And then we also have computer vision. Another thing that already existed, computers have been able to see for quite some time, but now that’s also kind of underneath AI. Then we have natural language processing, which also existed before the computer’s ability to either speak or understand what’s being spoken and then translate languages back and forth. Again, that’s another thing that did exist before, but now it’s just better if you will. And some of this is because of big data, cloud technologies and the powers of computers. And then what’s most exciting is generative AI. So the computer being able to create new things, whether that’s images, videos, or text. And so that’s kind of the breakdown. But as I’ve been mentioning throughout, even that breakdown, it’s really about taking technology that already existed and making those better. So if you can imagine at some point AI be more integrated with robots, and then that kind of brings more talk about Star Trek, more things like that happening. So that’s kind of the breakdown of AI when people say it’s really a nest of things.

Nick Greenhalgh:
Great. And in that story about your research, I think you mentioned three buckets you place AI in and that was assist, augment, and automate. What does that look like on a practical sense?

Leo Dixon:
Right, it’s about strategy because you can’t just say, I’m going to integrate AI into my systems and it’s going to do what though? And do it with who and to what degree? And that’s really what that breakdown is trying to explain. Sometimes you may want to have AI and it has its own role in terms of what you’re trying to… Get those words together. Sorry. Sometimes you want to work with AI where the human, for example, they have a role that they play. AI plays its own separate role, but together the task gets accomplished. But it’s still two separate things. The human doing something and then the AI’s doing something. But again, together the task is accomplished. But then there’s other times where it’s the human’s job to do it, but it’s AI that can help the human do that better. And my research partner, he likes to use Iron Man as an example, when you want to put on a suit to kind of help you accomplish something, just like basketball people, they’re like certain shoes or so on and so forth. So it’s kind of like you want to wear AI so you can 5 or 10 X what you’re normally capable of. And then with the last one, sometimes you want the AI to just do its own thing, but the human still needs to be there just in case, maybe we need to pull the plug or be able to make that final decision. And the example we like to use is autonomous cars. While they may be able to drive on their own, we still want you to be attentive. So that way, if it’s about to make the wrong decision, the human can step in time to make the right decision. So it comes down to strategy. When we talk about it from business perspective, you can’t just say, I’m going to integrate AI into my business. You still have to think about what are your current processes and where do you want AI to be in that process?

Nick Greenhalgh:
We’ve talked about some common applications of AI, and I think largely most people know about those. Are there some other applications of AI that we may not even realize are AI?

Leo Dixon:
Well, I would say just what I think is most exciting about AI that’s somewhat different is the ability for it to take on personas. So if you want to have a conversation with five people let’s say, you can go to a ChatGPT, Anthropic or some of the other ones, and you can say, I want you to be five people from five different backgrounds, and just really go into detail who those five people are and then start having a conversation with that virtual or that AI group. I think that’s where a lot of things are headed, pretty much AI being the agent. So I would say instead of what we’re used to now is buying a computer, we own it. Think of it now as you’ll be hiring AI, which is kind of a different way of thinking about it because this was a psychology problem to understand humans, and we kind of stumbled upon AI. So while it’s not human, it is human-ish of where it is now mimicking human cognition. And so it’s about really now how do you hire AI? And it’s really your imagination when it goes from there. As I mentioned, when I’m breaking down the fundamentals of AI, it’s things that already existed, but it’s what can we do now though that didn’t exist? And like I said, you couldn’t have had an AI conversation with five people, what you type instantly. And so when you start doing that, you could do better design thinking. You want to make sure that you are thinking about your customers, come from a business perspective, and the degrees of customers you may have. Now you can chat with those people ahead of time. So you can really have that product and design planning, that could be different. It’s a lot of use cases with that.

Nick Greenhalgh:
Yeah, can you provide just a little bit of context on what quantum is? Is that just a really powerful computer?

Leo Dixon:
It’s a different way of computing. So right now we’re used to off and on, but there are more combinations of off and on. There’s off, there’s on, and then there’s on-on or off-off. So all quantum is saying is that there’s more states that exist, and if you take advantage of those, now the computer can think more at once. That’s as far as I can really go right now. I’m still trying to learn how to best communicate that myself, but because you now have more states that exist, again, the computer can now do more, but that’s very expensive. And so we haven’t gotten to the point where AI was at in November of 2022 where it was like, okay, now it’s useful, practical, cheap enough. So it’s still trying to get to that point, and that’s why even I’m still trying to wrap my head around it, because that’s going to almost be a similar phenomenon to AI where we’ll be doing the same things we were doing before, just the computer will be more capable. And all of this is trying to get the computer to be like us. So I want to keep that in mind because a lot of times people want to get afraid of AI and say, oh, well, it’s going to take over the world, it’s going to enslave us, it’s going to do this, it’s going to do that. And I’m not saying those things aren’t possible at some point, but look at how much energy we have to put in just for it to be a fraction of who we are. So I think we have a long way to go, but I think we have to enjoy the ride as we get there. But it’s not going to… Technology’s going to keep doing the same thing, just better.

Nick Greenhalgh:
That’s a great segue, and I want to have you play Nostradamus for a moment. If you could predict the future, what’s one area or application of AI that you believe is going to grow significantly, and what’s one area that you think might fade away or become less relevant?

Leo Dixon:
AI is going to be a citizen of society. That’s where it’s going. We’re going to want to be able to have it with us almost like a pet, I would say.

Nick Greenhalgh:
Interesting.

Leo Dixon:
That’s where it’s going. It is straight out the movies to science fiction or what have you, because that’s what makes the most sense. We already have AI, customer service agents. We already have computers or whether robots getting better in terms of their joint movement and everything, so on and so forth. Faster internet. Internet’s everywhere, we’re connected all over the place, and so just put it all together. So the other human or the mock human will definitely be here. I think what’s going to fade away… I think it’s all going to be the same. Honestly, we’ve evolved over time. So no, we no longer live in huts. We no longer use horses to get us around, but we are still driving, we still travel, we still do all these things. So I think we’re always going to be human. I don’t think it’s going to take over so much that all of a sudden we’re going to be in some dystopian world. I just don’t think that’s possible. Not yet at least, I think we have some time because if the AI doesn’t have a purpose beyond the human, then we are going to be the ones always driving. And we’re so complicated that we’re not just something that you can just solve quick. Computers like to do things quickly. We’re just not that simple. So I don’t think anything’s going to go away. I think things will just get better, but there will be more computerized beings around, and I think that will be the shift, if anything is just getting used to that.

Nick Greenhalgh:
So normally on the VOE podcast we have a student question, but given the fact that we’re talking about AI, I figured we’d use it to our advantage here. So let’s check in with our friend ChatGPT. I prompted it for this conversation and asked to give us a question or two. So the AI chatbot wants to know what ethical considerations and potential challenges should society be prepared to address, and what measures can be taken to ensure the responsible development and deployment of AI technologies?

Leo Dixon:
I think we have to be ready for the mirror. AI is trained on data, just like humans we’re trained on society. The thing is, with us humans, we like to debate what is and what isn’t. AI is going to tell us what’s in the data. And so we have to be ready to accept that and then just make a decision on to what degree do we need to alter that for whatever it is that we’re trying to accomplish. Because some things we can fix immediately, some things we cannot, but we just have to be ready to admit what the data says, and then from there, figure out how can we best make sure we’re protecting humanity and being as fair as possible. And certain applications of AI needs to be more sensitive than others, like the more that’s used for law enforcement and so on and so forth like that. It’s going to have to require a lot more effort to get out some of the bias and some of the other things that can be ethical concerns. But if you’re just trying to detect if your customer’s happy or not while they’re waiting for food, then there may not be too many things there other than just how you store the data and making sure that doesn’t get leaked out. So some of those things are going to have to kind of come up because the privacy aspect of it, but then our data’s already out there anyway. Just learned that AT&T got hacked and a whole bunch of stuff is out there, and then something about Facebook sold something about messages to somebody else and whatever. So our data’s there, but we do want to limit how much more of that is available, especially when it comes to AI.

Nick Greenhalgh:
Yeah, it seems like the rollout of AI is happening faster than the sort of government oversight or larger body oversight is happening. Is that okay?

Leo Dixon:
That’s just what’s going to happen. That’s the role of technology anyway, to be honest with you. And that’s just the innovative power of AI. And it’s out now. There is no putting it back, and this is just what we see on the surface. I’m assuming some of us may be familiar with the dark web and some of the other things. If you try to limit it now, you’re going to make it explode even faster. The way that I see it, it’s best for them to keep this… Let’s see what’s happening, every now and then have a conversation, but I think this is what we need to propel forward anyway. I think if anything, per the Jetsons, we should have had some of this in the year 2000. So we’re about 24 years behind from at least how I was growing up thinking what the year 2000 was going to be like, so I think we’ll be okay.

Nick Greenhalgh:
No flying cars quite yet.

Leo Dixon:
No, not yet. I’m disappointed.

Nick Greenhalgh:
Before we wrap up, I want to remind our listeners to join us for Voices of Experience on May 20th at 6 p.m. for a deep dive on Denver’s AI future. But my last question for you, for those that aren’t well versed in AI, apart from listening to this podcast and attending our event on May 20th, how do you become more fluent in it?

Leo Dixon:
I would say if you have the time, aim for a certification. Microsoft, Amazon, Google, they have different types of self-paced modules that you can go through for free. Well, a certification may cost some money. But I would say just do that and just be careful not to overwhelm yourself. Because as you mentioned, there’s too many changes happening where you can get just overwhelmed. The thing is, I would say just maybe every two weeks, see what’s happening. Check out the news, check out a YouTube less than five minutes, and you should be good enough.

Nick Greenhalgh:
Great. Well, Leo, thanks for joining the show. I really appreciate it.

Leo Dixon:
Thank you.

Nick Greenhalgh:
I hope that answers some of your questions on where AI is today and where it’s headed. And we hope that you’ll continue your learning journey at our in-person Voices of Experience event on Monday, May 20 on the University of Denver campus. It is completely free to attend, but you need to register online at daniels.du.edu/voe. If you enjoyed this episode and are not one of our regular listeners, become one! Click subscribe on your favorite app and catch a new episode of the Voices of Experience podcast every month. Also, delve into our extensive library of content, where we chat with high-profile business leaders to explore topics at the intersection of business and the public good. Sophia Holt is our sound engineer. Joshua Muetzel wrote our theme. I’m Nick Greenhalgh and we’ll talk again soon.