62 | Strategies for Bridging The Gap Between Personal & Organization AI Adoption with Amanda Bickerstaff

0:00Welcome, everyone, to a live episode of Leveraging AI, the podcast that shares practical, ethical ways to grow your business, your career, and we are here today to talk about AI. implementation. And AI implementation today has a very interesting dissonance in it. On one hand, you have a lot of people who are using it daily across multiple things, whether in their businesses, in education, on their personal lives. But from an organizational perspective, there's a huge gap as far as how to actually implement AI in an efficient way through the organization in a way going to be A, effective, and B, safe.

0:41I literally had two conversations in the last 24 hours with two potential clients that told me, yeah, we got started. We set up this group that are like the AI experts of the company, but they don't really know what to do, and they're not making any progress, and everybody's really frustrated. And they're actually a few steps ahead because they've actually set up a committee to do these kinds of things. Our guest today, Amanda Bikerstaff, Bikerstaff is an expert on exactly that topic. She is the founder and CEO of AI for Education, and she's been helping educational organizations understand how this whole AI thing works and how to implement it in a way that everybody will benefit from, right?

1:22So the educators, as well as the students and everybody in the organization. And the conversation is going to be not just about education, even though we're going to focus a lot about that, but on an organization in general. How should an organization approach the implementation of AI in a way that will be, as I said, effective and safe. So I'm really excited. I know a lot of people are struggling with this right now. And so, Amanda, I want to welcome you to Leveraging AI. Welcome to the show.

1:52In the next few years, AI technology will change our world dramatically. Whether you are a business executive trying to catapult your business forward or just somebody who refuses to be left behind and want to advance your career, this is the show for you. I'm your host, Isar Maitis, a serial entrepreneur and an AI enthusiast. You'll hear invaluable practical tips from innovative business leaders, AI practitioners, and some of the brightest AI minds in our world today on how you can leverage AI in ethical ways to advance your career and grow your business.

2:33Hi, everybody. Yeah, I'm happy to be here today. Like I said, I'm Amanda, the co-founder and CEO of AI for Education, and this is our world. We are fully focused on the responsible adoption of gender AI specifically in educational institutions, whether that's from the school level, the district, leadership, higher ed, but also working more and more with companies. So education companies, tech companies. And so it's been really interesting. Just had a good conversation today about thinking through like, how do you even think about using Genera AI to support content development? And how do you start to create some infrastructure for these tools?

3:10So happy to be here and looking forward to conversation. Awesome. I want to thank first of all those who have joined us on the chat. So feel free to, on the Zoom, feel free to write in the chat who you are, where you're from, what you're looking to get out of this. And for those of you who are hopefully watching us on LinkedIn live, thank you as well for joining us. We're doing this almost every Thursday. So Thursday noon Eastern time, we're doing these lives with experts like Amanda talking about AI practical implementation. So if you want to join us, just follow me on LinkedIn. There's always like a place to sign up.

3:42And if you're in the Zoom, then you can absolutely ask questions and we will try to relate to those as we move forward. So Amanda, let's really dive in and get started. What is the problem, right? It doesn't sound like such a big deal on paper, right? It's a new technology. We had new technologies before. We've been through change processes through organizations before. It's not the first time this is happening. And yet, literally across the board, people are struggling to deal with this and to understand how to move forward in a way that makes sense. Can you help us understand why there's such a big of a problem talking to so many organizations and helping them through the process?

4:23Sure. I think that while artificial intelligence has been around since the 50s, and we have been a few, 84 % of everyone daily uses some form of artificial intelligence. If you have one of these, 77 % of your apps, like your interactions will have something to do with artificial intelligence. if you've got your computer, if you're a big social media fan, or you're actually working with an organization that already has your own machine learning models. So we have had artificial intelligence part of our lives for a really long time, but ways that are not consumer facing, like we don't, it doesn't say TikTok powered by AI algorithms.

4:59Like that isn't something that happened, even though it absolutely is. It's going to get you to watch that cat video and learn about you every single time you interact with that technology. And so it's been this kind of underlying technology that has become a part of our lives. And it has driven a lot of technology development. And what we see is that there was the first like genre of AI that kind of hit the scene was IBM Watson. I don't know if anybody is a Jeopardy fan in the audience. That's almost a decade ago. And it did something pretty well. It beat Jeopardy, right? But it wasn't like making up new Jeopardy questions and answering and playing as three people.

5:33What we're seeing as being more possible with generative AI. And it took quite a bit of time. And what ended up happening is we had this like move towards more like deep learning and looking at how the brain works and creating these artificial neural networks, like a transformer model, which is the underpinning technology for chat GPT. And so there's a lot of development that happens between like 2018 and 2022 that allows us to see this really complex processing possible for the first time. and it shifts the way that we think about like technology. And, but really the reason why we're talking about this today is that OpenAI decided to put an experimental conversational AI tool into the world as an experiment and said, here you go.

6:19And November, 2022, Chattopiti 3.5 coming out like a couple of months later. And then we had four coming out in March. What happened is the world became OpenAI's guinea pig. and we say if it's free, you're the product, but that's what happened. And, but the thing is that this technology is like, unlike anything that has come before it. If you've used a Siri and predictive text and a terrible chat bot online that you can never get to a representative, that is not a step change from chat to BT. We're talking like this is a magnitude change in terms of capabilities, interaction, et cetera. And what happens is you have this acceleration that happens so quickly.

6:59And what we see is that if you look at Facebook hitting 100 million users, it takes about a decade. Even TikTok, everyone loves TikTok, it takes nine months. Even threads, which was like just Instagram, took months. Chattoot took five weeks. And so suddenly you have this massive new technology that is consumer facing in a way that has never happened before. It took decades for the internet to impact our lives. It took the quantum of weeks, days for ChatsVT. And that's why we're in this position today, just about a year change later, is that this is transformative, but also consumer facing in a way that's never been seen before.

7:38I love the way you framed it. When I talk to you, when I do this on stages and I talk about this topic, there's two things that are very different about this than any other transformational change we had in history. And there've been a few, right? You had multiple steps in history, but these steps get closer, like shorter and shorter in time. And as you mentioned, now it's within weeks and things are changing regularly. But the other thing is how wide it is, right? So the number of use cases this solves. So if you think about the agriculture change that we had, I don't know, okay, people built a tractor.

8:14so now a farmer could farm a lot more land with one person but that's all it could do it could go through his field then the internet came in the beginning it didn't do almost anything like the early days of the internet you had a browser it was very lame there was like landing pages like yahoo they could get information that's all he did and it was like this for a few years And now we have a tool that can do so many things across what seems to be an endless number of use cases. And new tools and new use cases are born every single day. And the speed. And I think the combination of these two things, like how wide it is and how fast it's happening, is what's overwhelming organizations.

9:00So now that we've framed the problem, what is the solution? Like how should I'm a manager, a leader, a CEO, a head of school, doesn't matter what I am. I'm in charge of the success of the organization that we're running. What do I need to do? Or maybe people underneath me, like what other people, I'm just a nobody in a large organization. What can I do? What's the right approach in order to actually start having a structured implementation of this thing? The best thing to say is that let's not throw out, you know, the things that work. And there's a change management process. If you're an organizational leader, and I see a couple here, then please do not think that this is somehow something so special that like we can't go through a change management process.

9:42And we think about change management, we're thinking about creating a couple of things. One is creating a common understanding of what we are talking about and what actually needs to change. And I think that's the most important first step is that because this technology is unlike anything that's come before it and is essentially you as an actor are going to be interacting directly with a computer interface, meaning like it's not you are now a programmer for using generative AI and you're using ChatGPT or others, right? that it's really important to think about that, that part of this is just learning what this technology is and isn't.

10:16So for example, if I ask a room of a thousand people, if you used it or not used it, there'll be a wide variance. And we're still in a very early adopter space, more and more people are using it for their own work, their productivity. Some of them are using it and not saying it because they don't know if it's appropriate or if guidelines will be changed. But we have a lot of people that have some deep insignificant misconceptions around things like thinking versus computing? Are these tools thinking? Is this like Skynet? Or is this like data from, or Janet from The Good Place, like one I recently heard.

10:48But I think that there's some big misconceptions, but some of this is just taking the time to learn. So if you look at Slack, for example, Slack took a week off, a week off to just focus on, they say AI, but really generative, right? And what does this mean for the organization, both internally and externally? So this is a moment where this cannot be another thing. Like when we talk about change management, you commit to a process and you know it's big enough. I promise you right now, if you have not committed to a process around adopting generative AI, you need to today or tomorrow or in a week.

11:19And the reason why I say that is because this is, not only is it not going away, but it will be deeply embedded in almost every part of our lives over the next 36 months. Google Maps will have a button that tells you where to go to dinner because you're like, you're fighting with your friends about who no one can decide. Google Maps will use generative AI to help you do that. So we're going to see it in this very deep way. And so I think that there is something you said about the change management process. So building that base of understanding, spending some time, making it a priority, and then starting to identify use cases in which you have a problem that can be uniquely solved by generative AI.

11:54So it's not like, I love that you said something about is this idea that it can do so many things and it absolutely can. And so this is where it's going to get really interesting is that this does have multiple applications, but it's not an end-all solution. It is something that needs to have a lot of different thought and approaches. And it needs to be something that is, you need to understand what your problem is and then look for a solution. And that's where a lot of people are living right now. And then it's time, like once you've done that, I'm sorry, I didn't find these use cases and looking at the ways in which you can potentially increase productivity for your team.

12:26You can create better experiences for your customers through better interactions, whatever it may be, the next stage is like innovation. What are you actually going to do to start bringing these technologies to drive real change in your organization? Because there is a technology that can do things that have never been done before. The only thing is like, you can't start there because you don't know enough about it to know what it's possible. Most likely you have to build towards that space. I agree. Two points. One, I want to summarize two of the key things that you The first thing is awareness and education, right?

13:00You need, you said that Slack stopped everything for a week. That's, think about it. It's a pretty big company and they've stopped everybody to do this. So you need to make it clear for everyone that this process is happening, right? We are going to work on AI. We're going to work on understanding it. You need to lay out what your process is going to be. And we're going to talk about this in a second. So this is step one. And something that I want to add to that actually Bob in the chat related to, it's not a one-time thing. And when I teach my clients or when I teach on stages or my courses, it's the number one thing that I tell people is continuous education.

13:38Like this thing is constantly evolving. Now, an organization, especially a large organization, cannot change every day or every week. They just cannot. But you need somebody or a few people that actually are paying attention, that are going to filter the stuff that actually makes a difference. that going back to what you said as the second thing, figure out where can this provide value easily and with low risk. Because then you can get quick wins, you can get people to start using it, you can get people to start understanding what this thing can do. And then, okay, then you go to the next thing and the next thing and the next thing.

14:10So having this mindset of this is going to be continuously evolving and we need to create a process that will allow us to evolve with it so we can benefit from it is the right way to do this. What are the practical steps or mindset that you help your clients define in order to do this effectively? Yeah. The first thing is let's create a space in where we have some time to learn and explore together. Let's actually set aside with an expert. It doesn't have to be internal. Someone that's good about it, like understanding the technology can explain it in ways in which you can understand it, but let's experiment.

14:48Let's hang out. Let's try this. These tools are fascinating and they could be super weird. and super funny and super, oh my goodness, like this is something that I didn't know was possible. But the thing is, this is not, if I go into my staff room and say, hey, everybody, gendered AI is gonna change the game and it could do all these things. Until you use it, until you see it, until you have the visceral reaction of doing it and seeing what's possible, it's very difficult to have that person's thing say that thing and then it be real to you. Because like how you mean it could do an entire front end of a website with like in 45 seconds now?

15:26No, you can talk about it, but until you show it, and of course it's not going to be perfect, but my goodness, what is that going to change for us? Or it can give me a pretty decent, like a GBT4 class model can give me a pretty decent starting place for a quick response to customer feedback or qualitative feedback. And it's not going to be perfect, but maybe like it just helps me to bounce that idea off and does it in a minute or less. And I think that's where there's just a really strong opportunity to have some dedicated time with the right supports in a scaffolded way to just get in there and start using this.

16:01So one of the ways that we do this with schools and as education institutions, we have our prompt library. Our prompt library, our prompts, so when you interact with ChatGPT or other tools, you're prompting. That's the way that we call the interaction, the questions that you ask. And while it's not like a computer program in the traditional sense where you create a prompt, it's always going to work. There are some best practices and some really good use cases that are commonly used. Like that email from a customer that you don't want to answer because you're afraid you might be a little bit snarky or not have the headspace or whatever may have you.

16:34Not using any personal item file for your patient, you can use a prompt pretty reliably to help you with refining a response or at least getting some talking points. And so I think that's something that we see. So you can collect and create that for your own team. Like maybe there are 10 really good use cases for productivity that you feel confident in that will really help drive some usability, some productivity, feel good, do it in a safe and responsible way. So you're using it in the way that your people aren't creating unethical moments or practices that they not realize potentially, and just get in there.

17:07And I think that we skip over that as part with something new, where if we even bring in a new technology, we don't have that time where you get to play around a demo. And sometimes like something like a new CRM is not going to be very fun to play around with. A GBT4 class model, right? Now, potentially Gemini Ultra and are advanced and now GBT4. It's a really good time. And so I think that's where we say is the first step is just giving that time to explore, have it be scaffolded, start to build some internal knowledge. And then when you go forward, you're talking from a space of shared understanding of common experience.

17:44And that is going to allow that next step to be a lot easier. So I love what you're saying on two aspects. One is the fact that if you don't experiment with this, you don't understand what it can do. And it's going back to what you said. It's the first time in history that a really highly capable software came with zero instructions. There is no user manual. There is no blog that tells you how to use it. Okay, it's okay. Go figure it out. I'm like, what do you mean go figure it out? Tell me how to use this thing. No, it doesn't exist. And the way you know how to use this thing is to follow the right people, see what they're doing, experiment yourself and figure it out.

18:21And so that's one thing that you said that I really like. The other thing that I love that I actually don't say a lot, but I think it's a very good idea is give people a solid starting point. If you give people a blank sheet of paper, it's very hard. Here are 10 prompts that you can use to do either this or that. Now they're like, oh, okay. Now I understand how I can use this in the context of a specific use case. And I can see what it's doing. And it's not a black box. I'm not clicking a button. I can actually see what's written. And they're like, oh, what if I change this? What if I do that?

18:56Which is what you call experimenting. You can then play with it. So I think giving people, like I said, a safe space, a good starting point, and a few use cases they can start using that you spoon feed them, right? It's not go figure it out. Okay, here are stuff that we, quote unquote, the organization, figured out that you can already start using. I have an interesting follow-up question to that. Who in the organization creates these initial use cases and problems and based on what? So I would say that there are probably some people in your organization already that are early adopters. These are the people that are like, it came out in the playground even before November.

19:33and they're like, oh my goodness, or the person that used it for the first time last spring and it changed their lives. And they use it all the time and they're really encouraged by it. They're engaged, they read, they understand. I would tap those people with potentially someone within your organization that's focused on operations. Someone that's focused on those kind of day-to-day tasks because these productivity gains are that great low risk entry point, right? Like where are the places in which we can help our team do something that is going to increase the quality of their work and is going to allow for it to be done in a more efficient manner and or to extend their work in terms of a creative partner, a brainstorming partner, whatever may have you.

20:16And so I think that what you do is you already, I promise you, you might, it might not be someone you know, but there is someone within your organization or many people in the organization that would love the opportunity to do this in a productive way. But make sure that you're now combining them with someone that's going to know that first of all, they're going to take into account the ethics and the protections of your organization. For example, the chat TVT is considered to be a leaky, it's a leaky model, meaning that sometimes the things that you think are private will randomly show up in someone's chat box in China.

20:52Like it doesn't happen, like it happens very small, but it can happen. There's also been experiences in which someone has entered something that is intellectual property that has now been something that was shared with someone else. And there are things like that. There are also questions around your privacy. If you're working with different organizations, you'll have different privacy components about identifiable information, et cetera. So you want to make sure that you're having that ethical consideration, as well as knowing that these models do not think. They are probabilistic models and they make stuff up.

21:22Literally, that's how they work is they are always making stuff up. And sometimes those made up things are wrong. And that's called a hallucination. So you want to make sure that you have those kinds of considerations and then do it. Then that's a great place. So, because you're not asking your operations or your compliance people, your cybersecurity people to do that on their own, but you're now partnering with those really excited people that are going to bring the energy that are going to be able to help you do that. And that would be my suggestion. Another suggestion that we see that's really interesting is that especially you have a risk or a change or a reverse group that you work with in one area, bring someone in that's an expert for that time too, to help you start figuring out those use cases.

22:01Because what will also happen is we see this all the time. Sometimes like you do have those early doctors, but just doesn't, they're just not being listened to because how does Terry from HR suddenly an A expert, right? And so I think that there's an opportunity also to think about if you do know this is a big barrier or you don't feel that confident, then bringing in an organization or a partner to do that work with you is a great way to get started and accelerate that too. You don't always have to do it on your own. I agree with you a hundred percent. I tell people, and that's what I do with my clients is first of all, let's build a committee.

22:36And the committee is aligned a lot with what you're saying. You preferably want a person from each department. So in schools, it will be different than in a company, but in a company, it would be somebody from HR, somebody from finance, somebody from operations, somebody from sales, somebody from marketing. Why? Because A, they will have different needs. B, then you'll have a champion in each of the departments that will help you do it. But the other thing that I tell people is you want the people who are geeks. You want the people that will actually spend 9 p.m. to midnight playing with this thing because they find it fun and cool and exciting.

23:08Because then they will give you solutions that otherwise will be work for people. And this is, oh my God, this is like the coolest thing ever. I can do this and I can do that. Then they're going to experiment and they're going to do the thing. But the other thing that you touched on, I think, is very important. And that's, to me, the number one thing that committee needs to do as far as education is really tell people what are the boundaries, the do's and don'ts of when you shouldn't, what you shouldn't, what you can do, what you cannot do. Because people don't know, like a lot of people don't know that the data you uploaded to it can be used for training of the model in some scenarios, people don't know that it makes stuff up completely in the same, by the way, in the same level of confidence as the correct answers.

23:49And sometimes we will mix the two together and some of it will be correct and some of it will be completely made up. And so the education, and if I make it even more extreme to a sales organization, salespeople are driven by results because they get paid commissions as a big part of their salaries. they might push the limits of what's acceptable or not acceptable from your organization's core values. Like, I'm not willing to do this and that in order to get additional sales, but some people now have tools to do stuff that they were not able to do before. You can literally create stuff out of thin air that looks completely real, whether it's reports, images, videos, testimonials, anything you want.