Hello and welcome to another episode of the Working Conversations podcast where we talk all things leadership, business communication, and trends in organizational life. I'm your host, Dr Janel Anderson.

Imagine it's the late 1980s and the first wave of personal computers is making its way into offices. There's skepticism, fear and even some predictions that computers will make human workers obsolete. Fast forward to today, and it's clear that those predictions were not just off. They completely missed the mark. Computers didn't replace us. They amplified our abilities, allowing us to be more efficient and effective.

The same story is unfolding now with generative artificial intelligence, it's the latest wave of technology that has many worried. But the real story isn't about replacement. It's about enhancement.

Organizations, from tech startups to government agencies are cautiously yet undeniably beginning to integrate AI into their workflows. But with any tool, its effectiveness hinges on how wisely and creatively it's used. AI isn't just here to stay. It's here to help us do our jobs better, as long as we have the right mindset and skills to guide it.

Now if you heard last week's episode about writing prompts for generative AI, then you'll already know a thing or two about my position, and if you've been using generative AI in your work or experimenting with it, you'll know how powerful it can be.

But is it going to replace us? That's the fear mongering that we keep hearing in the news media. Is it going to wipe out an entire workforce? No way. It's very much like the wave of personal computers that swept through offices in the late 1980s now, of course, computing power has gotten so much more powerful over these last decades, so it maybe isn't a fair comparison that was maybe a new wave rolling in and generative AI is like a tidal wave rolling in, but it's not going to weigh about an entire workforce.

Now, I was there in the late 1980s the early 1990s with all the hype about computers taking people's jobs. And obviously it didn't. Now, I have a funny and interesting story. If you weren't there. Here's what it was like, and this was my real work experience.

Let me restart this anecdote over for those of you who weren't there in the 1980s and early 1990s. This is how it went down, and this is a story taken straight from my work life in the early 1990s I was a trainer for a company that did telephone systems for hospitals. So it integrated hospital telephone systems with patient information and all kinds of different databases within the hospital that had never been integrated before. And it did some very simple things, and it did some very complex things.

At its most basic, an example of a task would be to transfer an incoming call from a concerned friend or family member to a patient's room, a patient who was staying at the hospital. Now, prior to our system, here's how that would go down. The call would come in, the telephone operator would answer the call, probably then place the person on hold after they had told them the patient's name, the telephone operator would consult a paper directory, a census of the people who were in the hospital more or less at that moment, because it was never completely up to date, because there were new admits and new discharges all the time, and this paper directory, or census of hospital patients, was printed out probably just once a day.

So they would consult the latest census to see if they could find the patient's name, and then on that same patient census would be the patient's room number. They would then take the room number and consult with a different piece of literally, piece of paper, or maybe a three ring binder that had pieces of paper in it to match the room number with the telephone number of that room, and then they would go back and put the call through the system that the company that I worked for at the time was introducing. Did all of that with just a matter of a couple of keystrokes.

Now was the telephone operator still needed to do their job? Absolutely, could they handle more transactions and put the calls through faster without people having to wait on hold as long as they did before? Absolutely.

Now, at its most complex, this same system, integrated with the physician and nurses pagers and data from our system would log every time they got paged, and sometimes that information would be called up when there was a lawsuit. So if a doctor was being sued and he did get the page, didn't get the page, whatever, our engineers would occasionally have to go give depositions to the courts to explain how the system worked and all of the things behind it that date and time stamped everything anyway.

As a trainer, one of those populations that I worked with, in addition to doctors and nurses and various other hospital staff, was again those same switchboard operators. They were scared. They had done things manually, with all of these different pieces of paper and three ring binders for their entire career. They were scared. They thought that the computer was going to take their job and that it would render them obsolete.

Then when I got there, and I tell you what I mean, a big part of my job was press this key, get this screen, type this in, and, you know, complete the task. A big part of my job was yes, that, but an even bigger part of my job was reassuring these largely older women, not in all cases, but in many cases, these were later half of their career, again, largely women in these roles who thought they were going to be outplaced by by computers, and many of them didn't have a college education or many other skills besides being a receptionist or telephone operator to fall back on.

They were scared. They thought the computer was going to take their job. Then they learned that it wasn't. Then they learned that what it was going to do was make them more efficient. What it was going to do is have customers on hold less time. What it was going to do, I shouldn't say customers, I mean, they were callers, but what it was going to do was to increase their ability to give amazing customer service, and then they loved it, all right.

Now, I think the same is true for the threshold that we're crossing over now with generative AI, some are scared. They don't understand this new technology, and they're worried that it's going to, you know, take jobs away something. Some think that generative AI is going to do away with the whole human race. I think that's a little far fetched, because we have to remember that it is the human race who is creating the generative AI to begin with, and I don't think it's gone so far that it's going to develop a soul of its own and really take over the world.

But you know, some maybe think it will. We will all learn. We all learn what it's capable of, what it's not capable of. We will push it to its limits, and in the process, we will all learn, and we will grow to love it. Some of us already do, just like those telephone operators at the hospital, they grew to love the system that they were now using because it made their jobs so much easier, and again, they were able to give a much higher level of service once they were using this computerized system.

Now, lest you be concerned that people aren't really adopting generative AI. Let me tell you about a member of an audience that I was recently speaking with at the end of the presentation, I was chatting. I was talking about politeness in human computers and really maintaining the humanity in human computer interactions. That was the nature of my talk.

And I was talking with somebody afterwards about generative AI, and this was a person in a fairly conservative industry in get this legal department, who was telling me how he was using it in the for the analysis of contracts. So when they had a contract, a new contract, ready to go out to a vendor or somebody they were doing business with, he would run it through generative AI and compare it against similar contracts that had met all of the legal hurdles and approvals and so forth.

So instead of sending it off to the highly specialized people on the team who were already have way too much to do, what this person in the legal team was doing with the legal department's blessing, the chief legal officer knew exactly what he was doing again, cross referencing new contracts against old contracts, not necessarily that would be the final word, but it would catch anything that was maybe not anything that was missing, but it would catch a lot of things that were missing, or things that were duplicative, or maybe things that were different in this type of contract because of the entity that it was contracting with compared to the ones that were it was being carried against.

So it was doing a great job of maybe first and second round proofreading before it went off to the legal experts for the final, final blessing. And again, it was saving the organization tons and tons of time, speeding up the review process and getting their contracts with their vendors and their customers signed so much faster. So I asked him, Well, you must have tons of extra time on your hands. What are you doing with all this extra time? And he replied, What extra time? There's always a backlog of work to do, and that backlog of work is probably never, ever going to go away. It just means I can do my work faster, I can get more of it done, and there's more of my brain left to concentrate on the things that really need my brain.

So even in conservative industries and in operations like legal, we are absolutely seeing the uptake of generative AI. Now there are three key skills that we need in order to use generative AI well and really make the most of it. And these are more cognitive skills, as opposed to if you listen to last week's episode where I talked about the skill needed for writing prompts. So this is very, very different type of skill. If you didn't catch that episode, I strongly, strongly recommend that you go out and catch episode 178, where I talk about how to write really exceptional prompts from generative AI, so that it gets you what you need and you don't get frustrated and overwhelmed or it goes down a rabbit hole of the wrong thing.

But today I want to talk about the cognitive skills, the skills that we need as thinkers, as human beings, as we are engaging in work with generative AI. So I have three of them for you. The first one is discernment. We need to get really good at discerning when to use generative AI, when not to use generative AI, how much to use generative AI, and all of the rest of the things that go into whether or not we're using it, how much we're using it.

Now this comes up especially when we are in a hurry, when we are overworked and when we are stressed out, or all of the above, when we're in those types of situations, we tend to rush. We cut corners, and we do not engage in discerning whether it's the best choice, whether whatever it is the best choice. Do I send this person an email? Do I give them a call? Do I text message them? We need to pause in that moment and do some discernment and say, what's the best way to get a hold of this person? Because I need to convey an important message to them just like that.

When we are using generative AI, we need to use a strong dose of discernment. And again, when we are rushed, when we are overworked and when we are stressed, that is the time we are most likely to cut corners and make mistakes and not be discerning. So I really do want you to use a strong measure of discernment. Not only about is the time to use AI and is this the right type of task, and even across all of the AI tools that are out there, to ask yourself and discern for yourself which, which one of the generative AI tools that's out there is the best one for this task, or which one do I have access to that's the best for this task? Because, quite frankly, if you subscribe to all of them, it would get quite expensive quite quickly.

So I want you to be choosing your and again, this goes back to the previous episode, but choosing your top couple of tools and sticking with them. But even within those, you're going to be using some discernment. Which one should I use for this task? We also have to have some, a strong dose of discernment about the results that we get back from generative AI, because generative AI will be the first to tell you that sometimes it's wrong. So you do need to do some cross checking, some double checking. I like to ask it for resources. And sometimes I'll ask it for the resource that it's using as I write the prompt, and other times, after it replies with an answer to my prompt, I will ask it which sources it consulted to get that answer. And sometimes they're not credible for me, and sometimes I will ask it to look in academic journals, or I will look at to look, ask it to look at the Harvard Business Review, or specific places that I know as an academic myself are trusted resources, but we have to have some discernment about what generative AI puts out, because it's not always going to be accurate, and it's not always going to reflect our tone and our voice and our position.

So I also like to give it in my prompts, which, again, you may know this from last week, but I also like to give it my position on a particular issue before I ask it to do any research for me. All right, so discernment, that is your first skill.

The second skill is humility. We all make mistakes. AI will make mistakes. We will make content mistakes. We will make usage mistakes. We will make ethical mistakes. And of course, we've heard about AI making mistakes, getting the race of the founding fathers wrong in the quest for diversity. I mean, if you didn't hear about that one, you might have been living under a rock, but that happened. Let's see.

You know one time I asked generative AI, and this was fairly early on in generating images. I think it's gotten better since then, but I asked generative AI to create for me an image of a dark blonde haired woman with blue eyes wearing a blue sweater, drinking coffee from a white coffee mug. Okay, a fairly simple and straightforward request. Well, the thing that it produced had three arms, and so there were three hands reaching for the coffee mug, or holding on to the coffee mug from various angles. It was quite funny, but so AI makes mistakes in generating images college students, of course, we've heard about college and high school students getting essays written by AI without do, without the college student thinking of that as a first draft, just thinking of that as a final draft, and turning it in again, lots and lots of humans making mistakes.

Organizations have made mistakes as well. You probably heard about the fairly high profile case with Sports Illustrated creating fake journalists using AI generated images and AI generated names and possibly the articles too. Although that was up for debate, Sports Illustrated claims that these works were contracted to a vendor, these articles were contracted to a vendor, and that some of their authors used pseudonyms instead of their real names, and those pseudonyms may or may not have been made up by generative AI, as well as the pictures that go along with them. But without belaboring the details of that case, just let's leave it as mistakes will be made by generative AI, by humans and by organizations, and we do need to use a large humility when that happens.

We should not get defensive. We should not try to defend ourselves, or generative AI or whatever. We should just say what happened and what the result was and what we're going to do about it. So humility is our second skill, and our third skill is curiosity.

We need to be curious in learning, how to partner with generative AI, how to use it most creatively, how to use it most effective. So we need to be curious in our learning. We also need to be curious in using it. So again, whether it's prompt writing or thinking about the draft that it created, and if you want it to iterate any of those things as we're using it, we need to be thinking creatively, and we need to use our curiosity in order to do that. And in working with generative AI, we need to be curious about how can I best partner with it? Will this thing work? I'll try this idea as an experiment and see what happens.

But we just can't get too fixed in exactly what the workflow is going to be or how it's going to go down, because generative AI keeps changing. So need to stay curious, and we need to stay adaptable with it. Curiosity drives our effective adoption of new technologies and in a constantly changing world like we have right now, there is no constant other than change, and AI is right there at the forefront of it. So we really, really need to be curious, because curiosity gets us using generative AI in the first place.

Curiosity gets us learning how to use it better and better and iterating more and curiosity gets us to ask those ethical questions and engage in discourse that elevates the conversation and ultimately elevates the ethics of our use of generative AI. We can all make mistakes with AI, and we will, but it's important to remember that we make mistakes without AI too.

So here's a mistake that I made over 15 years ago in my corporate career, which also involves discernment, humility and curiosity. On my team, I had about half a dozen full time employees who reported directly to me. There wasn't a lot of room for advancement. There's a half a dozen people reporting to one director, and I did have a college intern. And so as I thought about the person who'd been on my team the longest and giving her some additional career growth, I thought, well, let's have her manage the work of the college intern. And in fact, I again, I saw that as a growth opportunity for her, because she was going to get some management responsibilities and the opportunity to lead the work of another person.

And so I handed off much of the responsibility, not everything, but much of the responsibility to her to supervise his day to day work. And there were some problems. First of all, part of the reason that I handed the work off to her to manage the intern, was that I was really, really busy, and so taking that piece of work off my plan somebody else do it, was a huge help for me.

Now, what I failed to realize was that she was really, really busy, and so was everybody on our team. We were a hot commodity in the corporation that we worked in, and I was finding new projects for us to work on all the time. And it was an exciting time to be there, but we were all just a little bit, to put it mildly, overworked.

Now, in her overworked state the employee who reported to me, she handed off the reins to a project entirely to the intern, and the intern, in short order, botched it. Well, maybe not in short order. It actually took a few weeks, maybe even a month to two months, to really, really botch it. So I showed up at the presentation to the client, which my employee had handed off to the intern, the whole project and the presentation. So I showed up as the supportive supervisors at the back of the room, and was horrified at that was unfolding before me and afterwards, in my debrief, first with my team, my apologies to the client and so on and so on.

I realized that I failed to use discernment. I failed to put clear parameters and be really, really discerning with my employee about what the intern could and could not do. It was ultimately my responsibility, so it was discernment on my part that this all got handed down to the intern to the degree that it did.

Then the next part is humility. Now this took tons of humility. Not only did I have to apologize to the client, because we were a client services organization, it was an internal client, but still, it was a client. I had to apologize to the client, take ownership and responsibility. It was my delegation gone bad that resulted in this. I had to apologize to my staff member, whom I had delegated too much to in a situation where she just didn't have the capacity to handle it the way I had hoped she would. But again, that was on me, so that was my humility. I also had to go to my boss, who was different from my client, and explain what happened. And usually my boss only ever heard about the amazing work my team was doing. So I definitely needed to hit head this one off of the past, because I was pretty sure he was going to hear, probably, from the internal client, that something had gone drastically wrong, and I absolutely wanted him to hear it from me first. So there was humility there as well.

The other thing is, I needed to be curious. I really needed to be curious about how did this happen. You know, of course, the discernment as well. But just how did this happen and how could I prevent it from happening again? Now I think there's some real valid comparisons here to this situation with my intern these many years ago and generative AI again. If you heard last week's episode, you probably heard compare generative AI to being like a whip smart intern. So my intern was whip smart probably still is. I haven't kept in close contact within all these decades. Got probably close to 20 years now, but he was whip smart again, probably still is. But in this case, he was mismanaged. It was ultimately my responsibility again, much humility discernment was missing because we were overworked.

The person I handed off the intern to was also overworked, and I took it on with curiosity about, how could we never, ever have this happen again? And so those three skills were at play, and there was no AI in the room. So we can make mistakes without AI as well.

But in using AI, I really want to drive home the idea that that discernment, humility and curiosity are your friends. These are your superpowers in an age of working with AI, and let's also take that curiosity in conversations with those who have different opinions about the future of AI now, as we move into a future that is further enhanced by AI, the key to thriving won't be about competing with machines, but about partnering with them and partnering wisely.

Generative AI will undoubtedly boost our efficiency, allowing us to automate routine tasks and focus on more creative and strategic work. And this is a good thing, but to truly unlock its potential, we meet we need more than just technical skills. We need the human qualities that make technology work for us, not the other way around.

Discernment will help us determine when to lean on AI and when to rely on our human instincts. Humility will remind us that AI, while powerful, is not infallible, and it's up to us to question its outputs. It's also up to us to own our own mistakes when we overstep with AI or with AI, and Curiosity will drive us to explore, learn and continuously adapt as the technology evolves, the organizations and professionals who master these three skills will be the ones who leverage AI not as a replacement, but as a powerful tool in their arsenal.

The future of work isn't about being replaced by AI. It's about embracing it with the right mindset and the right skill set.

Remember, the future of work is not only about technology. It's about the values we uphold, the communities we build, and the sustainable growth we all strive for. We need to keep exploring, keep innovating and keep envisioning the remarkable possibilities that lie ahead. As always my friends, stay curious, stay informed and stay ahead of the curve. Tune in next week for another insightful exploration of the trends shaping our professional world.

Now if you learned something today or you simply enjoy this content, please subscribe to my channel on YouTube, subscribe to the podcast on your choice and follow me on social media. These are all excellent, no cost ways for you to support me in my work over on YouTube. Make sure you hit the subscribe button and knock that little bell so that you get notified every time there's a new episode out, you'll find me @youtube.com/Janel AndersonPhD, wherever you're listening or watching, please leave a review or drop a comment. It helps other listeners find the podcast, and it also lets me know that you are along for the ride until next time my friends be well.