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Podcast: How Artificial Intelligence Is Changing the Workplace

Podcast: How Artificial Intelligence Is Changing the Workplace

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Podcast with Dr. Linda Ashar, J.D.
Faculty Member, School of Business, American Public University

and Dr. Wanda Curlee
Program Director, Business

Artificial intelligence (AI) is changing how companies operate. AI is being used in ecommerce, medicine, transportation, logistics management and a host of other fields.

Start a management degree at American Public University.

In this podcast, Dr. Linda Ashar talks with Dr. Wanda Curlee, the Program Director of Business at APU, about the influence of artificial intelligence on the workplace today and in the future. Learn how AI is changing the way companies interact with customers, manage projects, assess risk, collect and manage data, and much more. As AI is integrated into more work functions, learn why it’s so important for organizational leaders to understand the technology, train employees so they can effectively use the technology and plan for the future implementation of AI into more business operations.

Read the Transcript

Dr. Linda Ashar: Hello, everyone. This is Linda Ashar, your host for Politics in the Workplace from American Public University. In this podcast series, we explore a broad range of topics of timely interest to both employers and employees. Today, we are exploring the impact of artificial intelligence on the workplace.

Artificial intelligence, we will be referring to as AI. Once a phenomenon of science fiction, AI is very much now a feature woven into our actual way of life in many ways from the algorithms of a Google search to your smartphones, speech recognition, and now driving our cars. So AI is very much a presence in the workplace.

We are privileged to be hearing more about this subject today from Dr. Wanda Curlee. Dr. Curlee is the Program Director for Business Administration in the School of Business at American Public University. She has a Master in Technology Management and a Doctor of Management in Organizational Leadership. She has been teaching online for over 20 years.

She currently researches artificial intelligence topics, and also has a podcast where this is explored further here at American Public University. Dr. Curlee is active with the Project Management Institute. She currently serves on that Institute’s Ethics Review Committee and has several certifications to the Institute. Wanda, welcome.

Dr. Wanda Curlee: Thank you very much. I’m excited to be here.

Dr. Linda Ashar: Well, thank you for sharing your time with us. This is, really, always a fascinating topic. If we were to pick it up next month, there would probably be new things to talk about. I’m looking forward to this discussion today. But before we get into details and the ramifications of AI as it impacts the workplace, please explain for us all listening, what is artificial intelligence when we talk about it?

Dr. Wanda Curlee: Well, when people think of artificial intelligence, many times they think about the “Terminator” or they think about Data from “Star Trek.” We are not there yet.

But in a nutshell, artificial intelligence is machine learning. So it’s a machine that can learn based on the way that it’s programmed. Notice I say it’s programmed. It’s not something that just happens. A machine doesn’t all of a sudden become smart and learning. It’s coded. So there’s a bunch of ones and zeros in there. So that’s what artificial intelligence is. It’s a software that helps us do many things in our lives. As you mentioned, it’s all around us. I’m sure we’ll get into more detail on that, but artificial intelligence, I think, is here to stay.

Dr. Linda Ashar: Thinking about it in terms of the workplace. What are some key changes that AI has brought to the workplace since the mid-20th century approximately until now? Without holding down to dates, but over the last 50 to 70 years, we’ve seen a lot of changes. Can you tell us what some of those are?

Dr. Wanda Curlee: Yes, of course. Technology changes the way we work, and AI is doing that. I would like to say that AI is probably in its infancy, not a brand-new baby, but maybe one that’s starting to learn how to walk.

But AI started probably around in the 1950s. It was a huge, huge computer that filled several rooms, warehouses, as a matter of fact and all it did was calculations, one plus one or two plus two. But as we slowly understood how that worked, we then were able to make it so it would learn from itself, not how it learns today, but the scientists could see and grasp how things worked.

So what we have slowly migrated to — and I’m going to date myself a little bit here — is it used to be that when you were in the university, you had to use punch cards and you had to have them in the correct order. You would feed those into the computer, and the computer would do whatever you asked it to do on those punch cards. So as you were giving different punch cards, it wasn’t really learning at that aspect, but if it wasn’t programmed in there, it didn’t know how to do it. So the scientists started telling it what to do and how to calculate things. S that’s how it started.

Now, as we roll forward, I’m also going to date myself again. When I first started in the workplace, there were no desktops, there were no laptops. We did everything by the telephone, which was considered a wonderful thing to do, because that’s how you get ahold of people or you walk to their office.

Nowadays, we have laptops, we have desktops. Some people still use desktops, especially if they’re gamers or doing heavy graphics. But our laptops are AI, and people don’t think of that as AI. But think about it, when you do a MS Word document and you see all those red and green things on there. That’s AI, because it’s learning how you write and how you do things.

So for example, if you constantly spell okay as “O-K,” it’s going to start to understand that that’s how you use it. It’s not going to say spell it with an “O-K-A-Y.” It might recommend it, but it’s not going to force it.

So there’s all kinds of things like that that you can do with your laptop. Think about going out and searching on the Internet, your laptop is learning how you search. So if you search for a product that would help you in your house, you would then all of a sudden start getting all these ads whenever you went out to the internet for that product or something similar.

So those are the algorithms that are out there. There’re smart algorithms. Amazon knows how to use them beautifully. They’re used all over social media, Facebook. Google uses them for their analytics. So it’s all over the place now.

When you use Google or Siri or one of those items in your house, it’s learning from you. So if I ask Google or Siri to play the news, and by default, it uses BBC or NPR. And I constantly tell it several times that “No, I want NBC News,” it will then start bringing me NBC News first.

Same thing with your music. If I constantly ask Google or Siri that I want country, it’s not going to bring hip-hop. Or if I asked for hip-hop, it’s not going to bring country, but it’s got to learn. So it is learning. It’s almost scary how much it learns.

Think about driving your car, as you mentioned before, Linda. GPS is a form of AI. It’s got to be. It’s got to learn that if you make a wrong turn, how to get you back to where you’re going. So it’s going to quickly calculate how to get you back. But again, that’s all programmed.

So we’ve talked about Internet searches. Think about data and the mega amount of data that we have in business. I mean, it’s just unfathomable in my opinion these days. It used to be that people looked at all that data. Well, we couldn’t have all those people looking at all that data right now. They would have hundreds and hundreds and hundreds of people looking at the data. And then if they’re not communicating with each other, what is missed? What opportunity did you give away in the marketplace?

So all those things are just amazing to me that we have out there. We’ve got translation services that will do it on the fly. So if I’m talking to you and somebody wants to translate it into French or German or Spanish, it can do it immediately as they’re listening to it.

We’ve got chatbots. Those pesky things when you call into a company or you get a receptionist, and they try to direct you to the different things. Those are chatbots, and they learn as well.

We have self-driving vehicles. In fact, I just read an article just this week about two companies, believe it or not, in Texas that are testing right now autonomous 18-wheelers to actually go on the highways and deliver goods. So think about that. You’re going to have 18-wheelers out on the highway, and there’s nobody in them. So that’s kind of scary.

Robotics, we’ve got robotics in healthcare. You’ve got robotics in manufacturing. They’re not just your dumb robots that take something off of a pallet and put it down or pick it up and put it back.

There’re robots that think. So, for example, in Japan, they have robots that help children learn in the classroom. They provide them scenarios. If they’re having problems in something, it will help them understand what they can do.

It’s not replacing the teacher. I don’t want anybody to think that teachers are going away. They’re not. It’s helping. It’s an adjunct to the teacher.

Think about healthcare. It used to be that surgeons did all the cutting on a person. That’s not true anymore. We’ve got robotics, again that are doing that now. The surgeon has the overall control of the robotic. If the robotic is doing something wrong, then it’s the surgeon’s responsibility to make sure that it happens.

We have other types of AI that are helping doctors make a diagnosis. Again, it’s not the AI making the diagnosis. It’s the doctor. And the AI is learning from that. So for example, if it comes back with the diagnosis and the doctor says, “No, that’s not correct,” or diagnoses something else, the AI will learn from that, because now it’s got more data.

In manufacturing, you can have rows and rows of stacks of equipment. There is a place in Europe, and I can’t remember exactly which country it is, but they’re all closed. But as you walk by if you’re heading down into that row of stuff that you want, it senses that you’re going to make that turn or as soon as you make that turn, that row opens up.

So if you’re working in there, you see rows closing and opening. It’s got to be intelligent enough to know if somebody’s coming, because obviously, it doesn’t want to close on somebody. It’s got to be intelligent enough to understand. Maybe it will understand as time goes on which rows are accessed more, so maybe it will keep it a little bit open.

But it’s fascinating to understand that those things happen. So those are just some of the places we’ve gotten to in AI. So I hope I haven’t hogged this too much for you.

Dr. Linda Ashar: Oh, no, not at all. That’s an excellent narrative on how we have changed so quickly in so many ways. I have a feeling that some of these things you’ve mentioned are very recent. Is that right?

Dr. Wanda Curlee: Oh, yes, well, the autonomous vehicles are something that had been in the news quite a bit, but not the 18-wheelers. Although they’ve had 18-wheelers that are autonomous, I believe it’s Walmart that’s using them, that’s using them on their warehouse areas. So they are driving themselves. If they need to take this pallet over to the other warehouse, then it’ll move that.

But we haven’t had them out on the open highways yet. Yes, we’ve had cars out on the open highway and up in cities, but there’s always been a person behind it.

So it’ll be interesting to see how people will react if they see a vehicle like an 18-wheeler driving on the highway, and there’s nobody behind the wheel. Yes, for some of us, that would be very scary. The stuff in healthcare, I would imagine healthcare is just going to expand by leaps and bounds. What we see for the employers and the employees, it’s just amazing what you can do.

Dr. Linda Ashar: On the 18-wheelers situation, is that, to your knowledge, meant to decrease in employment of truck drivers?

Dr. Wanda Curlee: Interesting that you mention about employment, as each type of technology has come out and people were advocating that humans would no longer have jobs. That has been far from the truth. It’s actually as new type of technologies come in, it’s created more jobs than what they were having previously.

Now, will truckers still be driving trucks? I’m going to guess it’s going to be a little bit of both. But, yes, I think some truckers will be displaced. But understand that those displaced truckers may now be in a control center that’s monitoring where all of these are at and making sure that they’re going to the right place. or making sure that they’re working properly.

Because remember, just because it’s not driving with a human, there is all kinds of data that’s going back to the command center — I use “command center,” I don’t know what it will look like — that people will have to monitor these.

You can’t have one person monitoring thousands of 18-wheelers out there, that’s going to be more than one person. So I can see where these truckers, they’re going to have to be provided training, could come in and say, “Oh, wow, this one’s running low on air in four of its tires. We need to get it to pull off and go to this place where we can take care of it.” So that’s another thing that when you think about it.

There’s going to have to be areas where these trucks can pull off to get maintenance, especially if it’s critical. So you’ll see all those things now popping up along the interstate or in towns or wherever it needs to be. So I see it creating more jobs than it will displace. If people are willing to learn, they will be able to find a job.

Dr. Linda Ashar: That’s a good answer, and it’s a comforting one for people, I would think. This part of the discussion raises another question in my mind and that is, how organized labor responds to these changes. If you haven’t seen a lot on this, I understand because I haven’t either. But do you have any insight as to how organized labor was in place collective bargaining agreements are responding to changes like this?

Dr. Wanda Curlee: Yeah, I actually do have one example. I’m going to thank Dr. Robert Gordon for this, because he actually brought it up in one of my podcasts, and I thought it was fascinating.

I think it’s the Port of San Francisco, which is one of the busiest ports, if not the busiest port, in the United States. Although with COVID, I’m not sure if that’s entirely true anymore, but there is AI there and it’s a very unionized area.

They actually embraced it once they understood what it did for them. It decreased the amount of people that got hurt every year and maybe disabled for the rest of their lives, because a container fell. It now allowed the port to be 24 hours a day, whereas previously, it wasn’t.

So now, people could work on the shifts that they wanted to. It actually created more jobs for the people, because again, you have to monitor all this AI that’s going on. They’ve got forklifts running by themselves. They’ve got cranes that are taking the pallets on and off. So all of those things have to be monitored. The cranes understand when a ship is docking and knows where to go to load or unload that ship. So yeah, they actually embraced it.

Now, I’m going to guess that when it was first brought to them, all they could think of was, “No, people were going to be displaced.” But once there was training and learning, they understood that it’s actually creating jobs.

Dr. Linda Ashar: That’s an excellent example to use, because most of the docks are heavily unionized. It’s a good example to show collective bargaining response, because that in turn sets a precedent for other places. I know that the automobile industry moved into robotics. The unions came to accept that, but there’s always resistance to change.

You mentioned a component of training, which brings to mind a case that I had… I practice law. I want to say this was somewhere in the 1990s. I had a discrimination case in a situation where an employer laid off an older worker who lacked skills for a new office system they installed. Everything had been manual from desk operations to production in their production capacity.

They were installing this new system that was computerized. This person did not have any of the skills in present tense for this system. Many of the other employees or most of them were younger and did have some native computer skills that they had acquired through school, or at that time, people were into desktops if they wanted them and laptops were out.

So many of the other employees had some skills that already in hand, but not on this system certainly. So the employer made a decision, prematurely as it turned out, to lay off this older worker with a job elimination.

The court came back and said that the employer was discriminatory in its action, because training was not first provided to this employee. The employee was not given the opportunity to learn the system.

So that was an object lesson certainly at the time and probably since, that making assumptions about what people can and can’t do is not the right avenue to take. So training is important.

What do you see employers doing for training? Is there an organized approach to this? How did they do it when they make such changes?

Dr. Wanda Curlee: It’s interesting that you asked that. I’m a project manager for many years, and I still practice it on the side. But in the 1990s, I was actually implementing things that were drastic changes to a company.

In one company, they went from green screens to laptops. I mean, that was the jump. It was interesting, because this was actually an example of a good one. The company had already told the employees that nobody would be laid off. That’s the only company that I’ve ever heard say that.

They provided just-in-time training. I mean, there were employees that had been there 30, 40 years. Like I said, they were used to green screens where they had to type everything in. So they were working with a mainframe, and now they were going to laptops. Many didn’t even have desktops at their homes.

So what this company did was that they communicated. They probably overcommunicated. They had newsletters. They had town halls. They did everything. They constantly were bringing people up to date on what was going on, who would be affected first, who would be affected second. Like I said, they were provided just-in-time training.

Then when they went to their laptops, if they… I mean, there were people that didn’t know what a mouse was. They thought a mouse was something that crawled on the floor. If they were still having problems, they had mentors and coaches that were available all the time to help them out. So this company went way beyond what was needed.

Many companies in the 1990s just decided they would eliminate jobs because they were under the false impression that this new technology would eliminate jobs. But they kind of did it just in the wrong manner, instead of looking at what it would bring, what processes it would help, what processes it would eliminate, what processes would now be automated. I was caught up in one of those. I was laid off and come to find out later on somebody with my exact skills was brought back in.

So companies have to understand what they’re implementing. With the AI, they truly have to understand what they’re implementing. So they have to understand what processes this is going to eliminate and how can they use the value-add of a human.

Remember, AI is software. It’s ones and zeros. Yes, it learns, and it gets smarter, but there still has to be a human with it. So it has all this data; it can give you trends in analysis, but what do you do with that unless you have a human making the decision and looking at all of this?

Because maybe the AI looked at the wrong information. Maybe the AI didn’t know that this was out there. The AI is learning, just as much as the human is learning to work with the AI.

Dr. Linda Ashar: Oh, that’s an excellent answer. Thank you. I’m very interested in that employer that went seemingly above and beyond; two points there. One was communication. They kept the employees in the loop throughout the process. The other is the training, of course. I think that the case I had was an object lesson in that, and also, that’s an everlasting message is to not underestimate your human capital.

Dr. Wanda Curlee: Oh, absolutely. They’re the ones that have the value-add. They can do the higher reasoning that AI can’t do. Remember, I said back to “Terminator.” We’re nowhere near as bad or data. Even then, it was still an algorithm. All that has to be input into that machine.

Dr. Linda Ashar: Given the way that this impact has affected the workplace, we’ve talked about a lot of examples and it’s certainly continuing. We’re by no means going to, as you pointed out right at the very beginning, stop with AI.

How should workers or potential employees be reacting to this? We’ve been talking about what the employer should do. What does a savvy employee think about with way AI is progressing in society in the workplace? What kind of skills are employers looking for that employees should be thinking about in getting education and training and retraining?

Dr. Wanda Curlee: Many employers are looking for people that are comfortable working with technology. It doesn’t mean you have to know how to code it. It doesn’t mean you know the ins and outs of it, but you know how to extrapolate the data that you need to get your job done. So you can’t be scared of it.

What I tell people that are asking me about that, especially older individuals that may be a little bit scared of technology, I tell them to go and find out as much as they can about an AI. Go out into the Internet and do searches. Subscribe to magazines on the web that are free of charge that are technology that have AI. There’s many, many out there that are written in layman’s terms.

Take some college courses in AI. I know in our university at the MBA level, we’re writing AI into many of our courses. In fact, we have some courses just written on AI. Again, it’s not telling you how to code. It’s not telling you how it works. It’s telling you how to use it, how to be a leader of this technology, how to help your employees, what the processes are. So that you understand, and you are comfortable with it.

It doesn’t mean that when you go into your first job where you’re using AI or your current employer where you’re using AI, that it won’t take some training. It’s going to take training on your part and the AI’s part. Remember, the AI is learning. It’s learning you, as well as you’re learning the AI.

So try to get as comfortable as you can with it. Go to a community college. They have AI courses, or go to a university if you want to actually get a degree that uses a lot of AI.

We are human beings, and we’re constantly learning. In fact, our brains change as we learn. People thought that our brain stopped developing several years ago when you were in your 20s. That’s not true. They have found that your synapses within your brain change as you’re learning things, so you become more flexible. That’s called brain plasticity. So, it’s amazing.

I mean, we’ve got 80-year-olds and 90-year-olds that are using their laptops and probably can do searches better than I can. We’re constantly learning, and we’ve got to be comfortable with it, because it’s not going away. If you’ve got Google in your house or Siri or one of those items in your house, that’s AI. So don’t be scared of it. When you say, “Hey Google, find me so-and-so,” that’s AI. It’s learning you.

Dr. Linda Ashar: Well, I mentioned at the beginning that it’s become part of our fabric of life in ways that we probably don’t think about consciously at all anymore, because we use it all the time and don’t think about it as being AI,  most likely.

But your comment about Siri or Alexa is a good one. I have a friend who is very active user of as it happens Alexa. That AI really knows her preferences and almost anticipates sometimes what she’s going to ask for, because she uses it all the time.

Dr. Wanda Curlee: Yeah, I don’t have one of those, but my son does. When I go and visit him, I stayed at his house one time for four months. Within three weeks, whenever I would say something, Google. They have a Google adaption of it, would come back and say, “Good morning, Wanda.” It got to know my voice.

Dr. Linda Ashar: That’s kind of fun. How is the AI changing how businesses and their employees interact with customers? You mentioned the chatbots. We certainly know about those, most of us, but clients and customers respond at various levels of acceptance to AI answering their questions or interacting with them in some way. What can you tell us about that?

Dr. Wanda Curlee: Some of us love chatbots. Some of us hate it. I think it depends on how the chatbot has been coded. As you mentioned it, most companies use that now. When you go out to the internet and you go to a company’s website, you usually see something down at the bottom that says, “May I help you?” Well, that’s a chatbot.  And it possibly can.

If you’re just having a hard time finding something, it can help you very well. It’s available 24/7. If I had to call the company and I’m searching at midnight because I can’t sleep, I don’t want to have to wait until tomorrow. We’re [a] society nowadays that we want our answer right now. Give it to me now. So, in that perspective, it helps.

From that chatbot, what you probably don’t know or many people don’t know is, it’s collecting data, not necessarily personal data, when you’re on the website on how their clients and customers and how their employees are searching on the website. When they go to this page, what is the next page that they normally go to? If an employee is looking for something on benefits and they have to click 15 times, maybe there’s an issue there with how it’s put together. So now the company knows how to redesign the website and possibly can even do it quickly. Think about scheduling.

For those companies that still schedule manually, that’s a nightmare, especially if you have five or more people on a project. You may have hundreds of people at a stakeholder meeting where you have to bring everybody together and they may be outside of the company as well. Well, if you have AI that can go and look at everybody’s calendars and bring back to the human or maybe even go ahead and schedule it for the best time, can you imagine the amount of hours that saves everybody for you to go do more value-add work?

While it’s not here quite yet, I think it’s probably just around the corner. Think about how many PowerPoints we have to put together for clients or for the C-suite. AI can possibly start to learn how you put together your PowerPoints. So, instead of me having to create a PowerPoint from scratch, I can tell AI, “I need a PowerPoint on the next status meeting for my project.” It puts it together for me, based on the latest data.

Of course, I am responsible for going in and making sure that it’s all right. I may tweak it a little bit because I don’t like this item here or I don’t want this in my status report. So AI will start to understand my wants that I want on a PowerPoint.

Same thing with risks. Risk is big to a company in every area. So that you’re seeing customers that are all of a sudden drifting over to another competitor, AI will pick that up before anybody else will. So, for example, if you had a customer that ordered things from you every month like clockwork, and all of a sudden, they’re not ordering it like clockwork, well, that should send up a red flag and maybe you have several. AI is going to pick that up before you do.

AI may say that this customer always orders at 11:00 AM on Tuesdays, the last Tuesday of the month. Now at 11:02, that is not in there. Guess what AI is going to do? It’s going to send up that red flag and send you that risk. Maybe you now pick up the phone and you call that person, or you send them an email, or you have the chatbot go out and reach out to them. So those are all different ways that we’re going to be handling clients.

Think about in healthcare: the patient is a client to the doctor or to the hospital or you’re a patient in the hospital. AI is working through robots in the hospital, believe it or not, that’s delivering medicines. It’s delivering food, especially for those that might have communicable diseases like we have now with COVID. We want to keep the healthcare worker safe. So why not have robots go do that?

These robots have to be able to understand what the patient’s doing, what the patient will do. Do I need to put it up onto the tray table for the patient, or does the patient always grab it from me, or do I need to hand a glass of water to the patient, or does the patient have the ability to do that themselves? So those are all things.

These robots also know how to get out of the way of people that are walking in the hallways, so they’re smart. They understand if somebody’s coming towards them, and they need to stop or move away or move to the side or hurry up. We’re seeing all of these things happening.

In healthcare, also, it’s helping doctors as I mentioned before with diagnoses. It’s helping put together all the data we’ve got out there in healthcare. Think about all the patients that we have with cancer, it can go and look at all the data on what’s worked, what’s not worked, and help doctors understand what needs to be done. I’m very hopeful that through AI, we’ll eventually find a cure for all cancers.

COVID, it’s already looking at x-rays of lungs. It can tell the radiologist fairly quickly, “Hey, this looks like a COVID patient,” or “No, this is pneumonia,” or “This is a COVID pneumonia,” or some other things or I could look at the heart. So all of those things are coming around, and I think it’s touching every industry.

Supply chain, when COVID first started, everybody started buying all this toilet paper and we had no toilet paper, no paper towels. Now, supply chain, well, even then, supply chain knows when they’re having a glut on something or a run on buying something. So it can start starting up the manufacturing process again in those areas to try to meet demand.

Or look at all the companies that retooled to do ventilators or masks, that was helped through AI because you just don’t change robots overnight. Most of these were robotic companies. So that was AI learning how to do something different. Now that it’s learned how to do both, it might be able to do during the hours from 12:00 to 12:00, it does ventilators. From the other 12 hours in the day, it does car manufacturing, for example. So AI is going to change how we work.

Think about us that work remote. That was before COVID something that many employers said, “Oh, no, no, we can’t do our work remotely.” But we can. They found out that with everything that we have out there and the AI that we have, most employees can work remotely.

Look at even in healthcare, telemedicine, insurance companies were pushing away telemedicine. I’m not sure why, I don’t know that aspect of it. But now, because of COVID, telemedicine I think is here to stay. How convenient is it if you’re not feeling well to be able to call your doctor and get a quick call and they say, “Oh, yeah, you’ve just got a cold” or “No, you need to come in for X?”

I think even in the future, we’ll be able to call emergency rooms and say, “I’m having these kind of pains. Should I come in or is it just indigestion?” So those are things that we’ll be able to see in the future with medicine and AI.

Dr. Linda Ashar: Those are all very exciting things to think about, in my opinion. Another aspect of all of that with human interaction with AI is something I saw on a documentary not too long ago was the robots that look like, sound like, and talk like people.

How soon will it be that if I walk into a hotel or a business that the receptionist will be the equivalent of a Data rather than a human being receiving me into the business?

Dr. Wanda Curlee: Interesting that you should say that. There was actually an experiment in Japan. Japan is really ahead in the robotics area, where they, whatever company it was, put a hotel that was almost all AI, very few human employees there: receptionists, the restaurant, everything was done with robotics and AI, even in checking in.

What they found within a couple of months was that people didn’t like that. Most people didn’t want that. They wanted the human interaction. So that was quite interesting. For example, if I called down to the desk and I wanted toothpaste because I forgot mine, you will be talking to AI. And then it would be put onto, AI would put it on a robot. The robot would bring it up. It would come to the door, knock on the door and hand you the toothpaste.

We’re social creatures, we do like some interaction. So they abandoned most of these robots and AI and went back to humans. I would like to think that what might have been good to do, especially at the reception desk, is to have humans there. So those people that wanted to go to humans could wait in line and go to humans; or if those that were in a hurry or just had a quick question, they could be offered to go to the AI and they could decide what to do.

It would be interesting to see how that adjunct would work if those two were put together. If the AI couldn’t answer, then another human would come in and help that AI with whatever it needed to do.

But it’s funny because also in Japan, in nursing homes that they have in Japan, they have robots that go around and talk to people with dementia. Now think about that, people with dementia ask probably the same question again and again and again. The robot doesn’t care. The AI doesn’t care.

So, for example, if the person with dementia asked, “What’s the weather outside?”, this AI system could tell it. And then two minutes later, the person with dementia again asks, “Well, what’s the weather outside?” Again, the AI doesn’t care. It will continue to answer the questions. In fact, it will get to know that person with.

Anne, let’s say, is the person’s name. It might come up to Anne and say, “Hello, Anne. The weather outside is so and so.” So nurses and the people that are helping people with dementia don’t have time to just sit there and chat. Many times, these people are lonely. In any nursing home, they’re lonely, especially now with COVID. So having these robots around could give them an opportunity to talk and use their mental faculties.

Dr. Linda Ashar: What does this robot look like?

Dr. Wanda Curlee: It doesn’t look at human. I mean, it’s got sort of a face. It’s got what appears to be two eyes and a mouth and the mouth moves. Although it doesn’t move with it. I don’t know if you remember Rosie on “The Jetsons.” I know I’m dating myself on that one, but she looks a little bit like that.

You can make it have a male voice or a female voice. I think you can even put different dialects in there. So the person speaks a different type of Japanese, and they can do that as well. So it doesn’t look human, but it doesn’t seem to affect the patients that much because they have somebody to talk to.

Dr. Linda Ashar: You mentioned face, so it does have some affect about it that has some personableness to it, it sounds like, even though it’s still a machine look. That to me sounds better than if a box is moving around that talks by comparison.

Dr. Wanda Curlee: True. I agree.

Dr. Linda Ashar: Well, this has been a fascinating discussion. We’re about at the end of our time here. What else can you add on this topic? We’ve been talking about insights for employers and employees with artificial intelligence.

Dr. Wanda Curlee: I just want to say that artificial intelligence, we shouldn’t be scared of it. We do have to monitor it. We do have to make sure that it’s ethical. We didn’t touch on that, but ethics plays a big part in AI.

So companies that are using AI must make sure that the correct ethics are put in there, and that it’s obviously not to harm humans. But we will see it train employees. AI now trains employees. If you’ve ever gone out there and had to learn a new software, there’s little avatars that go out there and show you how to do different softwares. So, you have a software training a human how to use a software, which is mind-blowing.

It can automate processes on legacy systems. We have all these different computer systems out there that are so old, but we rely on them, especially in the U.S. government. Well, now they have found that they can put an AI layer on top of it. They can automate some of those processes within that old legacy system. So think about the amount of money that that’s saving you and me as a taxpayer. It can help with customer service. It can correct responses. So if it’s answering something or it’s telling the agent what to answer and it’s not quite correct, it will learn from that.

It’s helping with 9-1-1 services. They have AI on many 9-1-1 services that are capturing not only what the person that is calling in, but what’s going on in the ambient noise. It can detect if there’s people shooting. It can detect if the person that’s calling in if the effect is right. It can hear the patient if the person calling in is not the patient. It can automatically sense if you’re calling from a phone, the cell phone, where it’s at. So it can start to send out emergency services. The 9-1-1 operator doesn’t even have to transcribe anything. It’s doing that all for them.

So now the 9-1-1 operator can think about what they need to do to help the patient that’s in the background. I think it’s only our imagination that will stop us as to how we use AI. Like I said, we’ve got smart robots. They’ll just get smarter. They’ll think about education.

I mentioned that there was a robot in Japan that’s being used in Japan within the classrooms. Even in online learning, we can use AI. They have found that AIs that grade paper do just as well as the professors.

So wouldn’t it be better if professors instead of having to grade all these papers, they provide more one-on-one interaction with the student? That’s what students crave. They want to have the knowledge. They want to take out the knowledge from the professor. So, if you don’t have to grade the papers that’s so much, it doesn’t mean that the professor is not responsible for it because they are. They should go and check it, make sure AIs doing all right.

There’ll be drugs made for you as an individual. So, for example, if you have a heart condition, you won’t have to go and get a normal heart medication. They’ll take some blood from you. They’ll create a drug based on your genetic makeup for your heart condition.

So it’s going to change every aspect of work, the pharmaceutical industries, the traditional HPs or Amazons or all those big companies. It’s going to change social media. It’s going to change every way, and it’s going to change how we look at the world around us. I can’t even fathom what my children and my grandchildren will see in the future.

Dr. Linda Ashar: That’s a great summary. Whether we like it or not, the bottom line here is it’s certainly here to stay. To me, it sounds like the biggest challenge is going to be how humans control and process how we use AI and respond to what it can do for civilization.

You mentioned ethics. I think I might have you back for another podcast just on that topic. The downside, people want to talk about the downside of AI, but it seems to me that the element of downside in AI is going to be the human factor. Is that too simplistic of [a] statement?

Dr. Wanda Curlee: It’ll be the human factor. It’ll also be people that can code AI correctly and for businesses to understand how their AI is learning. They have already found that some AIs are learning, and they don’t understand how they’re learning. So that’s kind of scary. So we need to make sure we control the AI.

Dr. Linda Ashar: Well, that is a good statement on where we need to close up, because the relentless clock is telling us that we need to be done. Wanda, I can’t thank you enough. This has been a fascinating discussion. We could probably go another two hours and not run out of things to talk about on this topic. I very much appreciate your time.

Dr. Wanda Curlee: Thank you very much. I’ve enjoyed this immensely.

Dr. Linda Ashar: Today, we have been exploring the impact of artificial intelligence in the workplace with Dr. Wanda Curlee. This is Linda Ashar for Politics in the Workplace thanking you for listening to our podcast. Please check back for more broadcasts here at American Public University.

About the Speakers

Linda AsharDr. Linda Clark Ashar is a full-time associate professor of business, law and ethics in the School of Business at American Public University. Having practiced law in federal and state courts for more than 30 years, Dr. Ashar continues to manage her own law practice part-time.

An experienced litigator, her practice focus is employment and labor law, agriculture and equine law, public interest, and management consultation for businesses and nonprofit organizations. Dr. Ashar has represented both employers and employees. She has a bachelor’s degree in English from Muskingum College, a master’s degree in special education from Kent State University and a Juris Doctorate in law from the University of Akron.Wanda Curlee

Dr. Wanda Curlee is a Program Director at American Public University. She has over 30 years of consulting and project management experience and has worked at several Fortune 500 companies. Dr. Curlee has a Doctor of Management in Organizational Leadership from the University of Phoenix, an MBA in Technology Management from the University of Phoenix, and an M.A. and a B.A. in Spanish Studies from the University of Kentucky. She has published numerous articles and several books on project management.

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