Everyday AI Podcast – An AI and ChatGPT Podcast - EP 53: How to Use AI to Teach Employees New Skills

Episode Date: July 7, 2023

It's time to level up your training and upskill your employees with AI. 🚀In our latest episode of Everyday AI, we dive into how to use AI to teach your employees new skills, guided by the incredible insights shared by our guest, Nancy Monroe, CEO of Verbal Transactions. For more, check out our Episode page. If you want to join the convo and ask Jordan or Nancy questions, go here and chime in! Time Stamps:00:00:17 Using AI to train and improve employees00:04:16 Focused on call center training using simulation, NLP, and bot.00:09:57 Talking, chatting, and observing with AI technology.00:14:14 Access to clean water and backup plans.00:16:53 Start small with Microsoft Teams, chatbot.com, and Alexa Skills.00:19:09 Leverage AI tools to automate and improve workflows.Topics covered in this Episode- Introduction to the episode and the use of AI to teach employees- Overview of Microsoft Teams and its bot creation feature- Information about Chatbot.com and its free trial for chatbot creation- Introduction to Amazon Alexa and its skills feature- Examples of skills that can be used to control devices- Discussion on the prevalence of automated features in consumer devices- Recommendation to start small and take advantage of free options like Alexa Skills templates- Speaker's recent panel discussion and what they can't live without- Concerns about potential water system attacks and the need for backup plans and independent learning tools- Examples of power outages in Texas causing freezing conditions- Concerns about risks associated with relying heavily on AI, bots, and machines- Speaker's personal experience installing smart technology and regret for not doing it sooner- Benefits of working with smart technology and advice for others- Question about using AI to train and upskill employees- Updates from OpenAI on GPT-4 API and Code Interpreter- Discussion on Google considering DeepMind's Sparrow as a competitor to chat GPT- Use of generative AI tools like GPT in Japanese schools- Introduction of guest Nancy Monroe and her company Verbal Transactions- Explanation of structured and unstructured data and their impact on productivity and decision-making- Description of software that tracks empathy and skills gaps in real time- Comparison between SCORM based learning and the software's scalable skill gap measurement- Acknowledgement of the importance of starting automation with existing workflow processes- Insights from Nancy Monroe about Verbal Transactions- Conclusion and invitation to visit everydayAI.com for more information and to sign up for the newsletter- Focus of Everyday AI in providing actionable next steps in using AI technology- Description of a simulation platform for call center agent learning- Implementation of natural language processing and bot technology for real dialogue in simulations- Comparison of one-on-one tutoring with traditional classroom training and peer-to-peer groups- Use of bots as tutors for observing and interacting with agents in real time- Utilization of NLP and bot technology for teaching new skills- Frustration with limitations of text-based communication compared to voice technology- Exploration of integrating voice technology into the enterprise- COVID's role in making voice technology more accessible- IllustSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

This is the Everyday AI Show, the Everyday Podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live and Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. Can you use AI to make your employees better and to train them?

That's what we're going to be talking about today on everyday AI. This is your daily livestream podcast and free daily newsletter, helping everyday people like you and me, not just understand what's going on in the world of AI, but how we can actually use it. You can spend countless hours a day trying to keep up with what's going on in the AI world, with news, with new tools and softwares and how to actually use it. Or you can tune in to everyday AI. That's what we do every single day.

So very excited to talk about that exact topic today. Can you use AI to train your employees, to have better employees? Before we talk about that and bring our guests on, let's first talk about what's actually happening in the world with AI. So some big developments. So everyone's favorite sidekick chat GPT, some big updates in the last couple of hours. So the parent company OpenAI is making, finally,

yay, GPT4 API available to all paying customers. So if you're not a developer, this might not mean a lot to you, but for the everyday person, this does mean a lot. So all of these, if you're using third party tools that use GPT for, you're going to start to see a lot better quality in these external tools. So more on that.

But another big thing with OpenAI is they finally also released Code Interpreter to all paying members as well. So a couple big developments there, and we'll have more in the newsletter in the AI and 5 section on Code Interpreter. All right. Let's move away from OpenAI. Talk about Google, right? So Google just reported that they use, that they may start using DeepMinds Sparrow as a chat GPT competitor. So we'll have more in the newsletter on exactly what that means, but an interesting development that Google is starting to look at additional models to come in and start

compete with chat GPT. So speaking of that chat GPT thing, all schools are using it, right? Students are using it. Schools are trying to see how to deal with it, at least here in the U.S. But in Japan, so a new report looked at how Japan is actually allowing and in some cases encouraging the use of generative AI tools such as GPT, all the way down to elementary and middle school as well. So I've been very fascinated with how the U.S. is struggling to deal with generative AI. And in most cases, just trying to ban it. So pretty interesting article today that we'll be linking to in the newsletter, talking about how Japan is actively and proactively just using it.

So that can help us all learn. So speaking of that, you can also use. AI to train your employees, just like students can use AI to learn. Right. So with that, let's bring on our guest for today and talk how we can use AI to teach employees. So very happy to bring on fellow fellow Chicago area person here. So Nancy Monroe is the CEO of verbal transactions. Nancy, thank you for joining us.

Well, thanks for having me, Jordan. Love to talk about this subject. You know, I'm sorry we only have 15 minutes. Yeah, that's, it's always true. You know, these conversations could go hours. So as a reminder, if you are joining us, thank you. So we already have a couple comments. But if you do have any questions for Nancy on how you can use AI to train your employees,

go ahead and drop a comment here and we'll get it answered. If you are listening later on the podcast, make sure to join us for these live streams, 7.30 a.m. Central Standard Time. So Nancy, just tell us quickly, you know, what is? verbal transactions and what do you all do? Yep. So verbal transactions is an enterprise learning company and we focus on right now call centers to help get those call center agents up to speed faster by using a hands-on immersive simulation platform and we're leveraging natural language processing to allow people to have real dialogue inside the simulator and then we're observing them

through automation and then a bot acts as their coach. You know, If they get off track to say, oh, you didn't type the zip code incorrectly or, oh, I didn't hear you authenticate the customer correctly. Let's try that again. And the reason that works really well is people in the learning space are probably familiar with Bloom's taxotomy of learning. But what people may not be aware of, he also does study around something called two sigma. He wanted to know what is the best way, best environment to teach someone how to learn something. So he tried traditional classroom training, which is still the dominant building. delivery mechanism today. Then he tried peer to peer groups. That didn't work so well. So he found out the

one-on-one tutoring was the best way to teach someone new skill because you can observe them doing something, give them feedback, let them kind of work their way through more complex skills. So I'm using the bot as the tutor. So the bot is observing what they're doing. The bot is interacting with them in real time. It's giving them real-time feedback versus delayed feedback. And so there's a lot other, you know, cognitive things that I could talk about. But that's how we're using NLP and bot technology to teach you a new skill. You know, when I hear you describe it, I think my brain thinks two things. At first, I think, oh, that's a lot to have a bot watching my every move, you know, almost

to feel like it's analyzing you. But then also, I think, what a great way to be trained, right? So how has the reception been? Because I know you've been doing this for a couple of years. But how was the reception been when you are using this technology to train employees? Well, the employees love it. I think sometimes just like any type of AI platform, you know, some of the trainers think, oh, they don't need me now.

I'm not going to facilitate this class, right? They're just going to go into the simulator. Well, I mean, you still need someone. So what happens is as we're delivering that simulation, if they mess up, where the person now can come into play, the person that used to be the instructor, they can look at the analytics that we spit out from the simulations to say, oh, they have this one area where they really got off track. This is where you need to then kind of intervene.

So it allows people to be more proactive in catching mistakes ahead of time versus reactive. Once they're talking to, you know, we've all had that bad customer service experience with somebody that didn't know what they were doing, right? Oh, gosh, yes. And statistics show that 70% of the time you leave a brand is because you had a poor customer service experience.

And you're having those poor customer service experiences is because there's 40% turnover in call centers. Yeah. So let's fix that problem. You know, pre-show, you kind of said it's flight simulator for call centers, right? So this, what you're doing at verbal transactions, it makes perfect sense for that use case. But if we hit, you know, if we zoom out a little bit and we look at these types of technologies and just AI learning in general, you know, what's your take on it? Because you were, you know,

verbal transactions was here before the recent, you know, AI wave, so to speak. But, but now it's, it's very commonplace. So where do you see kind of the industry going? Is it going in a healthy direction with, you know, AI assisted learning, bot learning? What are your, like, what's your take on that? Here's how I described it. So you think of structured data. You've got your HR records. You've got your test and assessments, all that structured data. You've got, let's say it's a tech support agent.

You've got how well they can handle tickets, right? All that is structured data. But now imagine if you can then take unstructured data, such as I'm wearing a device that measures my heart rate. while I'm doing some work task or I get up X number of times out of my chair during the day. Well, let's say you take that unstructured data and look to see, oh, at 10 o'clock, you know, you're not as productive as you are, so we're going to pump more oxygen into your desk. Or we're going to do something, you know. So where I see it going is taking all the structured data and unstructured data and kind of

comparing the two together so that you can make people more productive in an autonomous way, but then use that information to let the organization be much more strategic and proactive on how they're making decisions about the organization, but also how they're interacting with customers. Yeah, you know, even on the customer side, right? So you talked about how, you know, verbal transaction is, you know, specifically using, you know, your model to train call center employees. For the rest of us, right?

I think we're going to start to see a lot more interaction with with bots everywhere in general. So with your background with natural language processing in NLP, what should we as the everyday consumers on the internet everywhere else? Are we just going to be talking to only bots pretty soon? Yes and no. I mean, there's certainly, and when people say chat, I get a little frustrated because you're not literally talking. you're not literally talking to them most of the time. And so when you're typing things, that's, that's easy. That's easy.

For NLP engines to do that, it's easy. Where it gets really complex is when you are talking, physically talking, because there's a lot of other things that factor into that. But to your point, talking is the most natural thing in the world, right? And so I want to get to the point where in the enterprise, consumer products, they've nailed this. You know, we talk to our thermometers, we talk to our cars, we talk to, you know, I always say, the lady in the car is telling me where to go.

She knows that, you know, my husband doesn't trust those things. I'm like, the lady knows, right? So in the enterprise, we've got to cross that hurdle. But there's a lot of other complexities around the enterprise. You know, now everybody has a microphone. They didn't always have a microphone accessible to them. But because of COVID, everybody has a microphone and a camera now, right? So that's making my job a little bit easier.

But just imagine, let's say I have Salesforce. and I'm not at my quota and it's halfway through the month and I'm not halfway there. Workflow can be triggered so the bot starts to talk to you to say, hey, Nancy, you know, it's halfway through the month. You know, you're not where you need to be. I see you've made X number of phone calls because you can read that structured data. I've seen you send X, X, some emails out and the blah, blah, blah, right? And you haven't sent too many proposals out.

Let's go back and let's see if we can help you figure this out, you know. So it helps automate the observation, again, of somebody's work task. And you think of all the cameras that are around places today, you know, those cameras are observing people, you know, are you bending the right way when you're picking up a box in a warehouse? You know, so cameras and AI are going to help with some of those things too. Yeah. Wow. I just, I just thought of so many, so many different ways, right, that that AI can be used to teach new employee skills or just to, you know, prevent. accidents and all of those things. So we actually have some very specific questions. Sometimes on the show

we get general questions. We have a very specific one here from Amman. So hopefully you can take this one here, Nancy, because I can't. So asking how can AI be leveraged to identify skill gaps in an organization and recommend targeted learning? Yes. Okay. So in our in our simulator, we're tracking. Did they express empathy at the right time? Did they type? the zip code in accurately on the first attempt. And so our software spits out in very plain English, did this correctly or didn't do this correctly. And so we're identifying those skill gaps in real time so that you can coach them immediately

and be proactive versus there's this measurement of learning. There's four levels to it. Most organizations are using it. But you can't get to a level four or level five for months down the road sometimes. This accelerates the rate in which you can capture those skill gaps in hours versus days. And so that's, again, why aren't companies using technologies like this that are available? Because they've all got locked into something called SCORM-based learning, which only tracks when somebody attended a class or when somebody logged into something online, when they completed it, and if they passed a test. That's it.

There's no scalable way to measure skill gaps unlike our software. Yeah. And it's actually a great transition for this next question. So Rastafa asking, as we get more connected, should we be concerned of when systems go down or systems failures, right? So that's a great point, Nancy, right? Like if we are, whether it's for employee training, right, teaching, you know, teaching people new skills, if we become too reliant on AI, what happens, you know, and we're not saying verbal transactions, but what happens if a system goes down for employee training or even if we're just using it?

What's your thoughts? Right, right. No, we are so dependent on electricity. You know, I was on a panel the other day and somebody says, what can't you live without? You know, everybody's saying like some app or whatever, and mine is access to clean drinking water. You know, I mean, those things. And the fact that, you know, Ukraine's fighting these battles, hand-to-hand combat, which is ridiculous to me. There's so many ways that we could actually, you know, destroy people, you know, through water systems and things like that.

So it is a real concern. You need to have some kind of backup plan in place. You need to get people so they can learn independently somehow, you know, give them access to some kind of other tools so they can manage that on their own if there are some kind of shutdowns like that because it is a real threat and you think about power outages, you know, when Texas had that power outage and people were freezing in the middle of winter. These are very real problems. And the more we put into reliance on AI and bots and machines, there's a risk there. Absolutely.

Sure. Yeah. It's it's something I'm constantly thinking about, you know, because companies are, you know, being a little quicker now, I think, to start using generative AI to put it in every step of their every step of their business process. But then it's like, okay, you know, if before, you know, if Gmail went down or Outlook went down, you know, that just impacted one part maybe of your operation, a big part. But then, yeah, what happens when we have AI integrated front to back in every single part of our business and it goes down?

You need some kind of analog system to back it up. Yeah. Yeah. Yeah. That's It's not a bad idea, but I don't think anyone's going to be rushing out for typewriters anytime soon. So one other question that I had for you, Nancy, so, you know, verbal transactions is really, you know, focused on doing one thing really well. It's your training, you know, employees in call centers using AI, right? But for the rest of us, how can we work better with AI? Because I also believe that, you know, I've been saying this for years. the future of AI is you're going to have your own, you know, AI assistant on your desktop that follows you, quote, follows you around on your computer all day.

But I think there's a learning curve, right, to work better with AI. So you've seen it, I'm guessing through hundreds or maybe thousands of employees, but how can the everyday person prepare or get used to when that AI assistant comes? Yeah, get comfortable with technology. in baby steps. So if you're listening out there and you have access to Microsoft, Teams, teams has a way you can create your own bot and teams. There's lots of other, there's bot chatbot.com as a free trial and you can just play around with chatbot.com to figure out different ways to create an own bot for your own learning.

Amazon, Alexa, has something called skills and it's free. You can create your own skills. So if you have an Alexa device, you can turn it on and off your lights in your home. You can have smart plugs that you can use to turn things on and off when you're not home. So there's a lot of consumer devices out there that you can play around with that allow you to automate certain tasks in your home like thermostats are doing it. Refrigerators are doing it. You know, so I would say start off small and find there's lots of free. I'm the queen of all free things.

If you can do it free, just do it. But Alexa Skills is actually a very good way to start. and they have a lot of templates that you can use and customize. So I would start there. Yeah, that's a great point. It's actually crazy. Bring that up, Nancy. I've had a smart light bulb sitting in my closet for three years and I finally installed

it. I finally installed it like two days ago and I'm like, why didn't I do this, right? You know, having that smart. Yeah, just getting used to working with, you know, smart tech, I think is great advice. So I'll leave you maybe with the last question here for you as as we wind down. On the week, it's Friday, right? So maybe we'll end with a hard hitting one. How can maybe if someone's listening and they're a department manager or maybe they're a small business owner, CEO, what would be your advice on how they can use?

You know, because maybe verbal transactions is perfect for them. Maybe not, right? But how can they use AI to teach their employees, to train their employees? What would be kind of, and I know it's a hard question, but I think you could take this one. But how can everyone start to use the concept of AI learning to better their employees into upskill? Well, I mean, again, I would start with the like the Alexa skills and things like that because they're free. The downside to those things are they're not necessarily private. I mean, unless you pay a lot of money to have a Python programmer, you know, customize that for you.

So from an AI standpoint, spell check is AI, right? I mean, you think all those things that help your world make it better, spell check, things that automate in your world. So learn how to use Google or Microsoft has lots of tools to help automate workflows. Automating workflows is probably a very underutilized technology. In fact, SharePoint was a very underutilized technology from a loan. learning standpoint, you know, people had it, had accessibility to it. They weren't leveraging it the way they should. So look at the tools you have today and think, how can I leverage these? And does it already have some kind of AI component in it? PowerPoint has it. It helps you design

your slides. It's building the PowerPoint. So just educate yourself on what you have today. And if it has AI on it, learn how to use it. Yeah. That's great. That's great advice. you know, see what you already have in your workflow that you can automate. You know, you said Microsoft SharePoint presentations. It's fantastic advice. I think you just have to start. So Nancy, thank you so much for joining the show. It was great to have you share about verbal transactions and everything that you're doing.

Thank you. We appreciate all your time and insights. No, glad to be part of the show. Thanks for great. Yeah, absolutely. So as a reminder, if you want to know more about what Nancy's talking about, make sure that you go to your everyday AI.com. Sign up for our daily newsletter.

We're going to be linking to some of the cool work that Nancy and verbal transactions are doing, as well as some of the takeaways that she talked about, because I think it's great. That's what we're doing at Everyday AI. It's all about actionable next steps to help you use all of this AI technology that we're talking about every day. So we hope to see you back next week with Everyday AI. Thank you all. All right.

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