Podcast featuring Dr. William Oliver Hedgepeth, Faculty Member, Transportation and Logistics Management and
Dr. Wanda Curlee, Program Director, School of Business
Artificial intelligence and robotics are revolutionizing forward and reverse logistics operations. In this episode, APU professor Dr. Oliver Hedgepeth talks to Dr. Wanda Curlee about the advancement of AI, why it’s so important for business leaders to understand AI, and how companies are using AI to make its logistics operations more cost effective. Also learn how AI is helping project managers understand data, make decisions, and the likelihood that AI will one day be considered a team member on a project management team.
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Dr. Oliver Hedgepeth: Welcome. Today we’re going to talk to Dr. Wanda Curlee. I’m Dr. Oliver Hedgepeth. I’m a professor of Logistics at American Public University. Both of us work at the university. First I’d like to have Dr. Wanda Curlee introduce herself and her background. And then I’ll come back and explain what we’re going to be discussion today about AI and some reverse logistics. Dr. Curlee?
Dr. Wanda Curlee: Thank you. Hello everyone. I am a Program Director at American Public University for Business Administration. I am a project manager by background, but I have worked in academia for at least 20 years. Program director has been fun because I get to bring AI into our classes, which I think should be done for everybody.
I also am very active with the Project Management Institute. I recently served on the ethics review committee, although I rolled off in December, and I am volunteering on some other things such as a fire department to become an EMT. And I’m amazed at how much AI is used there. But that’s a discussion for another day. I do research in AI. I have several grants from American Public University. And I work with Dr. Oliver Hedgepeth on classes where we incorporate AI and research. Thank you, Dr. Hedgepeth.
Dr. Oliver Hedgepeth: Thank you Dr. Curlee. Today we’re going to speak about or talk about artificial intelligence, as Dr. Curlee said. I said that’s really more than just adventurous to us. It is what we live with today. I’d like to ask Dr. Curlee several questions related to AI, and especially as it leads toward reverse logistics and sustainability and recycling of products that are normal that we go to the store and buy and throw away or return. First, let’s get started with how do you define AI, artificial intelligence, and robots today, in 2021?
Dr. Wanda Curlee: Well, AI has a lot of different names and a lot of definitions. But to keep it simple, I really like just call it machine learning, because that’s basically what’s happening. Is somebody programs a software because AI is software. It’s not something that just happens. It is, like I said, programmed and the person that’s programming it can make the AI learn in a different manner or learn in this manner. And also could even put ethics into it or not have ethics into it.
Initially, robots were just dumb robots. They would go back and forth, go here and there. They might deliver mail, but they didn’t really know what they were doing. Now they’ve incorporated AI into robots. And if you go back to the Jetsons, and yes, I’m dating myself a little bit here, that would be something that would have AI in it. When you talked about Rosey the Robot where she did all of the housework and cooking and took care of the kids. That would have to have AI. Probably a little more advanced than we have right now for AI, but we’re starting to do that.
If you go on to the internet, you can find dancing robots, you can find robots that look like a dog somewhat. And it can go from grass to hard rock to even mud and it understands that it’s going to different modes of walking to do that. And I see this happening with robots in reverse logistics because we have to have intelligent robots, which means we have to have AI in those robots to help us make reverse logistics more economical and make forward logistics more economical. And we’ll get into that a little later on.
Dr. Oliver Hedgepeth: All right, thank you. Thank you very much. In your opening, you talked about some issues that are important to humans, dealing with humans. And you did mention ethics when you started and dealing with each other, dealing with our students because we’re professors, there is an ethical consideration. And when we’re at work, different kinds of work, whether you’re at the grocery store, whether you’re an analyst with the Department of Defense. What do you mean by ethics and AI when do you mentioned that in your opening?
Dr. Wanda Curlee: Ethics and AI, it’s a complex thing. The person that is programming the AI has a certain set of ethics. Ethics might be that they see nothing wrong with murdering somebody. Let’s go to an extreme here. To them it’s, if that person gets in their way, they just murder them and go on. Would we want that to be programmed into a robot that allows it to, “Hey, you’re in my way, I’m going to just eliminate you.” No, we don’t want that.
We want something that helps do the mission and respects human beings. And that can be programmed into it. But what happens many times is AI, since I said it was machine learning, it is actually learning from its mistakes and things that it does well. But it goes into a black box, so to speak, and something happens there. So we feed it something, something happens, and something comes out.
It is incumbent upon us, the people that use this AI, to make sure that it’s doing what it should be doing and learning correctly. So if we feed it something, let’s say, put this box over on the third pallet, and the robot goes and puts it on the second pallet, we have to understand why it didn’t function correctly, and then make sure that it puts it at the correct place.
[Podcast: Will Anti-Robot Sentiment Harm AI Advancement?]
Did it do this because it was programmed incorrectly? Did it do this because that used to be the third pallet but now we’ve rearranged the warehouse, and it had to put it there? So it envisioned it as the third pallet.
Now that’s not really ethical, but what if that item in that box had something that was life or death? Could be a harvested organ that had to go to a hospital, and it needed to be on pallet three, because
Therefore, we need to make sure that we understand what’s churning in that black box when it comes to ethics or how its learning, because the ethics of the individual may not be the same ethics, and probably isn’t, the same ethics of the company. But the company that is using that AI better understand how that AI is doing ethics. I’ll just leave it at that.
Dr. Oliver Hedgepeth: Yeah. So ethics, it appears such as relearning or the machine, the robot, Rosey, maybe, is learning all the time. The ethics would be something that would be constantly changing or learning. For example, we are Americans, and we have ethical principles that we use in our country. But what if Rosey happens to be transferred with you to Afghanistan, or Italy, or Japan, or Tokyo? And now Rosey is helping you out and there may be some ethical concerns over there. The ethics may be a little different. Do you see that as a problem with Rosey learning ethics over there?
Dr. Wanda Curlee: Let’s say Rosey goes to Japan or like you said Afghanistan. Yes, those Eastern countries have different ethical, not issues, but have different ethics than we do in a Western world. For example, in many Eastern countries, a child is not as valued as an elderly person.
There were some studies showing that if an autonomous vehicle comes to pedestrians in the road. And it has to decide whether to hit a child or hit an elderly person. In Western countries, it was hit the elderly person and leave the child. In Eastern countries, it was hit the child and possibly kill it and leave the elderly person. That’s a nuance that every country has.
Our ethics, even though we’re a Western country, may be slightly different than say, Germany or Canada or Sweden. But those big moral issues are basically the same within Western countries versus Eastern country. Is one better or worse than the other? No, it’s just the culture of that organization.
Dr. Oliver Hedgepeth: Okay. All right. Very good. That’s a very good analogy overall of what AI is about, robots are about. It can be one and the same. AI and robots are kind of one and the same in many cases. One of the issues we have to look at these days is businesses. Walmart, Target, Amazon, they’re using robots in their warehouses to move goods from one point to another. And those robots seem to be moving boxes from one pallet to another.
How do you see robots being used in what we call forward logistics? Forward being you have placed an order on Amazon and the order goes in and a robot is going to pick up that box and move it to another point in the warehouse where a human does pick it up. And eventually it’s processed and put on a truck that gets to your house and it’s delivered. That’s forward logistics. How do you see robots and AI being used in our logistics world, our forward logistics world?
[Podcast: The Future of Humanoid Robots using AI]
Dr. Wanda Curlee: Well, there’s AI at different aspects of the forward logistics. There are some warehouses that have incorporated AI into the pallets themselves in the stacks and stacks of boxes. I was talking to Dr. Robert Gordon and he was telling me he was actually in a warehouse, where as you walked, the stacks and stacks would open up or close if somebody was there. And this actually left more room, but the AI within those pallets, I don’t know what else to call it, it’s not really a pallet, but the stacks, they would have to be programmed to not crush people if there was somebody in there. So it couldn’t close if somebody was in there. But it would make all kinds of room when there was nobody around because it would shut so things could go back and forth, the robots could go back and forth.
Another thing I see with logistics is, yes, maybe the human goes and gets the box off the pallet, but let’s say it’s 20 feet up in the air, it’s very dangerous for somebody to climb up the ladder, even if they’re young and spry. We all have accidents.
But to send a robot over there, and to send an arm up there to go get it, or even a drone at some point to go get it. Then let’s take it, it gets out and it gets on to the truck. And the truck might be autonomous, that truck maybe, we have autonomous trucks driving on the highways now. Kind of scary, but it’s happening. And it gets to the place that it’s delivering quickly. Then we have drones taking it that last little step.
The drones can pick up the box. For example, I live way out in the country. GPS doesn’t even get you to my house. It drops you off about a third of a mile before my house. But a drone could have a picture of my house and have coordinates. But when it gets to that coordinate, it will say, “There’s no house here.” So it could go and look around. And then if it has that picture of my house, it will then come and deliver it.
That is much better for me because right now I have to go down the mountain because I live up on the mountain to go to a central place where FedEx and DHL and Target and all those other places deliver their boxes. With a drone, it will bring it right to my area. And again, we’re freeing up people to do the value-add, not to do the common mundane things.
Dr. Oliver Hedgepeth: Okay, very good. That’s part of the forward logistics area. Now let’s flip the coin there. There is something called reverse logistics, where you have a product you bought. And you open the box and it’s like, “No, that’s not what I wanted. I ordered something else.” And you call them and say, “Come get this.” That’s reverse logistics. You’re reversing the flow. Can you speak about reverse logistics and how AI or robotics might be part of that reverse logistics operation?
Dr. Wanda Curlee: Absolutely. Reverse logistics starts, as you said, when somebody opens up their box, or they have a piece of clothes that they ordered and it doesn’t fit. And so it needs to be returned. What could happen is many things.
For example, we can use the drone in reverse. I could put the box out on my porch, I would call or send an email or whatever. The drone would pick it up, take it back, but now what do we do with that when it comes back? Whatever it may be. That is something that adds to the cost of that product. If we can figure out a way to make reverse logistics economical, then the price of the product should go down. So how can we use AI to do that?
Well, there’s very many ways we can do that. AI could predict what’s going to be returned based on my buying habits. If I always buy a pink dress, and I always return it, then AI can tell Amazon or Target or whomever, that she bought a pink dress, it’s going to be returned.
Also, it could say, the pandemic happened. When the pandemic happened, online buying soared. It absolutely soared because many of us couldn’t go to places that we were used to going, or were too scared to go into a Target or to an essential other retailer. In 2020, there was an increase of returns of 41% from the year before, at Christmas time. That can be catastrophic to a company to have all these returns, they don’t know how to handle it.
So with the returns. You’re in the store, you’ve returned it, or you returned it via online. What do you do with that stuff? Well, again, analytics can help you. Analytics might say, “Well, Wanda returned that pink dress again. We’re just going put it on the shelf for somebody else to buy it.”
Or I buy a new phone and I want to return the old one. What do you do with that? Companies, let’s say a Verizon or an AT&T, send these old phones back to companies that have robots that are able to sort those phones. They’ll look through the phones and say, “Oh, this is an Apple phone that has three models back. Yes, we want to keep it. And yes, it’s in good shape.”
The robot then pulls it out, takes it to the bin where it goes. Another robot would look at it and wipe it clean, and then open it up and make sure that it has everything that it needs, puts the correct background on it for AT&T or Verizon or T-Mobile, any of those. And then it’s wrapped back up and sent back out. That helps make reverse logistics more cost effective, because we can now resell that and offset some of the cost.
It would also sort out things that say, laptop computers. There are precious metals in laptops. The robot can take out the precious metals, and it would understand, it would start learning on the different types of models of laptops. I would assume Dell does something of that sort.
It would also take out components that are doing well, or it might just refurbish the laptop. Let’s say it’s a brand new laptop, but a key fell off. That robot would be able to put the key back on and fix it and it will be put back on the shelf to be sold as a refurbished model.
But let’s go a different route. AI can use analytics, and it’s very good at analytics. Not too long ago, SpaceX launched the first NASA astronauts into space. And I think it was on the first one, there was a purple dragon that started floating. Well, everybody wanted that purple dragon.
AI would be able to predict what will be the next big thing, but with that comes the forward logistics, but it also has the reverse logistics. Because AI should also predict, “Well, based on how its manufactured and the type of people buying it, there might be 5% that are faulty, maybe the stitching’s not correct, or there may be another 10% of the people, their children hate the color purple or are scared of dragons.” It’s learning from all of this and it would then tell the retailer, “Expect to have this many return.” That can then be incorporated in what the people do.
Now, I’m not saying that people are going to be replaced. People should be doing the value-add. You could retrain somebody that restock shelves to, for example, take customer calls to help with customers that are calling in for whatever reason. You can have these people maybe become cashiers if AI hasn’t taken over that. But there’s jobs there for people, whatever they’re doing in there. So retailers are not just wholesale getting rid of people and replacing them with robots. Absolutely not. It’s working in conjunction.
Dr. Oliver Hedgepeth: You raised some very good points here as we’re talking about forward logistics, reverse logistics, and logistics in general using this AI and robotic technology. This machine intelligence.
But you also discuss analytics and analytics as part of project management. Program management and techniques like Six Sigma where people are trained to analyze lots of data. And there’s a lot of data coming at us these days, 24/7. Sales of items or operations or equipment or companies are working and the data is being collected. There is visual data as we’ve seen in cities where police are monitoring visual data, and just millions of pieces of data per second coming to large databases for us humans to analyze.
So when you think about training people in project management or Six Sigma with these analytics, how do you see training them to go beyond: here’s the textbook, here are the principles of Six Sigma, here are the principles of project management, here’s how we add numbers and look for deviations in analytics? How is AI going to assist?
We go a little deeper in terms of how would you train somebody and say: here’s project management, here’s Six Sigma, learn these things. But you got to tell them AI and robotics could do something, but I’m not sure what it’s going to do. And also address how far in the future do you think it’s going to be where AI is going to be partner with that person, you, for example, as a project manager, or a Six Sigma expert. Please.
Dr. Wanda Curlee: Many companies today have AI. And project managers today are overwhelmed with data, especially if they’re on a large program or project. I mean, there’s projects and programs that are billions and billions of dollars. Think about constructing an aircraft carrier or a submarine.
PMI, the Project Management Institute did a study on how AI and project management should be coupled. And it was found that those companies that used AI in conjunction with project program and project portfolio management saved about 20% to 30% on the cost of the project. Why is that?
Because the AI can take all the data from previous projects and programs and see where the issues were, where the risks were, where the stakeholders may not have helped, and feed this data to the project manager or the team, whomever it needs to go to.
The project manager needs to understand how to ask questions of AI, and understand what data AI has. Now, AI as I said is machine learning. It is learning. So the AI provides the data on let’s say, a scheduling issue that’s come up and tells the project manager, “On 15% of the projects in the past, this has happened. On 20% of the projects, this has happened. And on 65% of the projects, this has happened. None of them resulted in a good outcome.”
The project manager now knows that there’s an issue with his or her schedule. The AI may provide, depending on how sophisticated the AI is, may provide a recommendation saying, “This is the route that some projects took, and this was the least of the issues that resulted.”
The project manager may decide to take the recommendation of the AI, or it may say, “No, I’ve got a better solution and this is what we’re going to do and it doesn’t involve any of the ones that were done before.”
The AI will then go back and look at the scheduling technique that that project manager has done. And if it was successful, or at least mitigated the risk better than all of the others, the AI now learns and understands that, “Hey, this is a good way to do it.” I’m sure it doesn’t think like that, but if you get my gist, that’s a good way to do it.
The same thing with Six Sigma. You get loads and loads of data. And even if you had hundreds and hundreds of people to look at all that data and crunch the numbers, you have to get everybody to communicate. And you can’t get hundreds and hundreds of people to communicate effectively.
AI can take all of that, crunch it in probably seconds, and provide the data to whomever it needs to go. And then of course that project manager or whoever’s doing the Six Sigma, or Lean Six Sigma or whatever it happens to be, has to feed it back into the AI.
The problem that project managers are saying is the companies don’t understand why project managers need to have access to the AI. And that’s true probably with many people. Reverse logistics manager, logistics manager, they have to make a business case to get to that AI. And that can be an issue, especially if leadership is not seeing the value-add.
Dr. Oliver Hedgepeth: Dr. Curlee, that was very informative in terms of AI and I say analytics, AI and project management. And I do believe that given the next five or 10 years that there will be more use of AI for project managers.
In my day I was a project manager and the slide rule was one of my tools I used. I also have a pencil and piece of paper. I can add numbers. I knew how to use an adding machine. But like you said, there’s a lot of data coming, and you’ve got to coordinate and communicate with people.
You did mention that there was a certain percentage that the AI would be, let’s say AI is correct. Project managers got all these millions of pieces of data for a project, such as, let’s build the ships for the United States Navy. Okay, there’s somebody in charge of all the data for every boat, every platform, every window, every weapon. There’s somebody in charge of all that data, and it’s coming 24/7. And there are problems and issues 24/7. You have to communicate and coordinate with people, as you said.
But you mentioned AI could be providing a correct answer. And if so, and I can look ahead, can you see a time where AI would be hired, the robot would be hired to do project management for this project? Could there be a certain size of a project? Projects are large. Could there be a certain part of the project where AI would be 100% in charge of project management of the analytics? Of the Six Sigma data being produced to be pumped down into a piece of paper, or screen, not paper anymore, for the overall project manager to use of the overall project? Can you see that happening or comment on whether it should happen?
Dr. Wanda Curlee: I can see AI in the future running a small project, that’s short and small. But there always needs to be somebody overseeing it. It’s just like with a team on a project, you have the team doing it, but the project manager ultimately is responsible for it. The project manager may not understand what’s being done. I did many technology projects in software, and I couldn’t code you a one or a zero. But I knew the questions to ask and knew what should be the goals and objectives of the project.
AI would be the same thing. I would see it as a team member doing the mundane. So I see them even doing on big projects, maybe doing the scheduling, maybe looking at the risks, maybe doing costing, maybe forecasting the budget, which is cost control, which combines the cost and the scheduling, which can be very complex. I can see AI doing that.
But, again, the AI is not doing it in a vacuum. The project manager is overseeing it, but the project manager is allowed to go do more value-add instead of crunching the schedule every week or every month and producing all of the cost schedule information that leadership wants to know. What is the schedule performance index? What is the cost performance index? That’s all something AI can do.
And AI can be learning, because the project manager if they’re doing their job, they’re going to see that sometimes the AI is correct, and sometimes the AI is wrong, just like on our teams. It’s another team member. So we need to understand what the AI is doing. We can’t just let it run amuck. As I used to say with my teams, “I’m not going to like to run a mock. I’m going to give you the independence you need but I will be overseeing it.”
Dr. Oliver Hedgepeth: Okay. And as a team member, watching your team members, and I was a project manager, I had many projects in which I would have what I called the 15-minute meeting every week. The eight o’clock in the morning, Friday morning. I come in with a cup of coffee, all the sub-teams come in, and all I want to know is: “What’s the issue that’s brewing right now? And how are we going to fix it before Monday gets here?” And we’d have our 15-minute meeting. If there was no issues this week, because everything was going smoothly, it’s like, drink a cup of coffee go away.
You would have an AI team member in there in the future maybe. How would you run such a meeting? Can you see everybody sitting around a table and all of a sudden the computer is talking, “Oh, here’s what’s going on,” as a team member, “and I see an issue.” Can you see AI being a part of your human team?
Dr. Wanda Curlee: Sure, not right now. But in the future. We’ve got Sophia, the humanoid robot that might be that AI is programmed to project a hologram or to just speak. Maybe it might be an Alexa or a Google that’s sitting on the table that talks to us and ask questions and responds to questions.
We’re not quite there yet, but yes, I see that happening, especially on very complex projects. And I see it reaching out to other team members saying, “Okay, what’s your schedule like this week? What did you accomplish? What didn’t you accomplish? When will it get done?” So it can incorporate all of that information, or sending emails.
Dr. Oliver Hedgepeth: Very good, very good. Now, we’re talking about AI and robotics and we’re talking about forward logistics and reverse logistics. The subject of analytics and project management and Six Sigma is part of forward logistics, it’s part of reverse logistics. And one aspect of reverse logistics that’s coming out of England, and it’s over here in America in many places, is called sustainability or circular economics.
Circular economics and sustainability are just different words in terms of reverse logistics where a company, such as Coca Cola, being involved in circular economics and sustainability. They are really experimenting with designing glass bottles and plastic bottles for their drinks that are winding up in the trash heaps. They’re winding up in rivers. We have miles of floating islands of plastic bottles, and we’re trying to get rid of them.
So Coke and others are trying to learn how to take the plastic or build the plastic, or the glass, such that it can either go into the environment and not hurt it, it just evaporates. It’s like throwing out a chicken leg, and eventually it will rot into the ground and is part of the ground, no big deal. Chicken leg’s not going to be there in 50 years or 100 years. Right now, your water bottle is going to be there in 50 years or 100 bottles.
So they’re looking at circular economics of that water bottle so the parts can be broken down and put back into a new water bottle. And you buy that water bottle over and over again, basically. It’s going to be all the elements come together. You mentioned this about other technology. Can you talk about all of this AI and sustainability or circular economics? What do you see happening in there?
Dr. Wanda Curlee: When I lived in Europe many, many, many years ago, I was kid and I didn’t understand it them, but I do now. In Europe, they don’t have massive amounts of land where they can do landfills, like we do in the United States.
And I was always amazed how everything was reused and redone. The packaging on different items was minimal. Whereas here in the United States packaging takes a lot. I bought some dog collars the other day, and the packaging was more than the dog collar, which is stupid in my opinion. But that’s what it is here in the United States.
And Europeans still to this day, reuse things. They might decide, “Okay, I have this Coke bottle. That’s good to store my oil in,” for example. They might use that. The packaging, whatever the butcher wrap their meat in, they’ll reuse that paper until it falls apart. They’ll reuse the string.
I think that those in the United States from the World War II era and the Depression era got very good at doing that. I remember my mother-in-law saying that she used to take flower bags, and she would make her husband and her kids underwear from it. She was very good at sewing. So to me, that’s circular, you’re reusing it until it can’t be used anymore.
And how do robots fit into that? Well, as I mentioned with the cell phones, they take cell phones and reuse them and repurpose them. If there’s plastic in there, it’ll melt down and use it for another cell phone. If there are circuitry on there that can be used, they will reuse the circuitry. And again, robots are used for that.
Sustainability of using our precious resources. We are limited on the earth as to what our resources are. So we’ve got to reuse that. Laptops, the robots will come and take circuitry off the laptops or precious metals on the laptops and reuse it again for a new laptop. Same thing with the plastics on there. They’ll reuse it for plastic. We don’t want to send all this stuff to landfills because eventually our landfills will go away and sometimes it’s bad for the earth these landfills.
So as you said, Coke and all the major manufacturings are developing robots to help bring out things. For example, if it’s sorting out all the different plastics because there are different plastics, the robots would say, “Okay, this plastic is filthy dirty. It needs to go into this bin because it needs to be cleaned.” Or, “This is an X, Y, Z plastic. It needs to go into that bin.” Or, “This is a color plastic. It needs to go to that bin.” And it understands what these plastics can use.
The European Union has passed some very stringent laws on what can be used for foods. So if you have a plastic that was used for a food, it can be recycled for a food. If you have a plastic that was used to wrap something and it wasn’t food, then you can’t use that plastic for foods. That will have to be built into the AI. And right now we don’t have that there. We need to use the imaginations of our great coders that do AI to help them understand what’s needed for reverse logistics because we just aren’t there yet.
Dr. Oliver Hedgepeth: Okay, that’s very good. I really appreciate your discussions with everything as we wind down today. We’re both in education, we’re both professors, we both create courses and teach courses. Switching gears a little bit here. I don’t see a lot of courses in artificial intelligence. I see courses in analytics, project management, logistics. I see all these great things, got textbooks about how to move a box from here to there.
For just a moment, do you see a reason for planning artificial intelligence as a course? Maybe take a course or develop some courses or maybe in a bachelor’s degree or something in artificial intelligence and uses in the fields we talked about? Can you speak about what’s there or maybe what’s coming?
Dr. Wanda Curlee: Professionals in business need to understand AI. They don’t need to know how to code it. They need to know how to work with it. Therefore, it behooves us as educators to make sure that we have incorporated into our courses, whether it be the American Public University or University of Maryland or Notre Dame. Those that are creating and have business courses need to understand what business professionals need to understand about AI on that topic.
For example, if you’re teaching a reverse logistics course, there needs to be a section on what AI can do for that reverse logistics person at that point. If you’re teaching a course in project management, AI needs to be incorporated in there as to what is available for project management and push the student to use their imagination on where we can go with AI.
Because unless the coders know, they won’t code it. So the Microsofts, the big ones need to know that as well. And they need to know it from a business perspective, not from the coder’s perspective, because those can be two vastly different ideas.
So it’s just the imagination that we can use AI in classes. But we as educators need to understand what business needs about AI and also educate business leaders on what AI can do for different functions within their company. So it doesn’t necessarily need to be students at the bachelor’s, master’s, or even doctorate level. We can have business level, executive level AI for your company, which are non-credit courses. And we in education need to develop those as much as we develop for the bachelors, and the masters and the doctorate level.
Dr. Oliver Hedgepeth: Wow. Okay. So if we have courses in economics or accounting or say hospitality, where you have to run a hotel or restaurant, do you see that some aspect of AI would be part of hospitality or accounting? I’ve taken accounting courses and oh, boy, I couldn’t see AI anything a part of it. It’s just a lot of numbers and paper and a lot of numbers. Do you see adding AI to some of those courses like economics and accounting and hospitality?
Dr. Wanda Curlee: Absolutely. Let me take hospitality and I’ll address economics and accounting in a minute. But hospitality, there’s actually a hotel in Japan that’s run by robots, intelligent robots, so that includes AI. What was interesting was that the hospitality industry found out that individuals checking into the hotel would rather deal with a human face-to-face than being checked in with AI. That is good to know for the hospitality industry.
But they had no problems if AI gave them suggestions for meals based on what they are used to eating. Didn’t mind AI or robot bringing them a toothbrush if they forgot their toothbrush. But on check-in, they were very much wanting a person. But on check-out, they wanted to check out with the AI because it got them going quickly and out the door. So that’s something that hospitality industry needs to know where they can use AI.
Accounting and economics. That’s number crunching, especially economics. It can forecast what might be going on, for example, it could have forecasted and how economics would happen in the pandemic. It could have told us, “Hey, these industries need to stay open, these industries will shut down, these industries will have a catastrophic disaster because they can’t open.” Look at our restaurants and bars. “These will end up being very good. This will happen to people because they can’t go out anymore,” and so forth. And so AI can play a very big part especially in economics and the pandemic.
Accounting. Accounting laws change, especially here in the United States all the time. The IRS changes what we can and cannot do based on what the legislature has done. And AI is there. Look at TurboTax. That’s got AI in there if you buy that software to do your accounting. It will get you to where you need to go to do your taxes. So accountants use AI all the time. They wouldn’t be able to keep up if they didn’t.
Dr. Oliver Hedgepeth: Okay, very good. Thank you for that very much. That summary in terms of how it can be used in normal everyday business and the college courses and education that we have. I’d like to thank you again for spending time with us discussing AI, robotics, sustainability, reverse logistics, the business side that’s really important in having AI as part of a tool set for us humans, as well as there may be a time where the AI may be doing something by itself like you said in the hotel, checking you out. I can understand that.
This is Dr. Oliver Hedgepeth. I’d like to thank Dr. Wanda Curlee. She’s a wonderful person in terms of her teaching abilities. I’ve known her for a while. Teaches at American Public University and we have been discussing one of the topics that she is most interested in, in terms of AI and robotics. I thank you very much, Dr. Curlee, for being with us today and hopefully have a wonderful day.
Dr. Wanda Curlee: Thank you.
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