Together Digital Power Lounge, Women in Digital with Power to Share
Digital is a demanding and competitive field. And women are still grossly underpaid & underrepresented. But we are not powerless; we have each other. Together Digital Power Lounge is your place to hear authentic conversations from women in digital who have power to share. Listen and learn from our amazing guests along with host Amy Vaughan, Owner and Chief Empowerment Officer of Together Digital. Together Digital is a diverse and collaborative community of women who work in digital who choose to share their knowledge, power, and connections. To learn more, visit www.togetherindigital.com.
Together Digital Power Lounge, Women in Digital with Power to Share
Getting Started with Gen AI
Welcome to The Power Lounge, where women leaders in the digital realm share their expertise. In today’s episode, “Getting Started with Gen AI,” host Amy Vaughn, chief empowerment officer of Together Digital, converses with Lexi Trimpe, Director of Digital and AI at Franco and Detroit chapter ambassador.
Lexi leverages her background in journalism and digital strategy to navigate the evolving landscape of generative AI. She provides actionable insights on building human-centered AI strategies, ethical considerations, tool selection, and promoting education over fear. Her guidance is valuable for both AI newcomers and professionals looking to enhance their organizations.
At Franco, Lexi leads digital strategy for B2B, automotive, and SaaS clients while spearheading the AI adoption task force. A former journalist with contributions to Eater Detroit, Thrillist, and Hour Detroit, Lexi blends storytelling with data-driven approaches, fueled by her passion for technology since her first Gateway computer.
Chapters:
00:00 - Introduction
02:05 - Digital Obsession Rooted in 1999
03:08 - Curiosity Driving Digital Journalism Shift
08:54 - "Embracing AI: A Tool, Not Fear"
10:03 - "Choosing the Right Tools Wisely"
14:17 - Start with Needs, Not Tools
16:00 - "AI Task Force: Becoming the Magician"
20:35 - AI Reveals Bad Marketers
23:06 - Embracing Mistakes to Improve Communication
28:34 - "People-First AI Integration"
31:08 - "Embracing Educational Tools Effectively"
35:24 - AI for Creativity and Everyday Life
38:11 - Healthcare Innovation Excitement
40:16 - AI Manners Debate
44:03 - "Connect and Learn with PowerEdge"
45:10 - Outro
Quotes:
"Education turns fear into empowerment by fostering curiosity and focus."- Amy Vaughan
"Embracing mistakes and continuous learning drives progress in AI and personal growth."- Lexi Trimpe
Key Takeaways:
Curiosity Fuels Innovation
Mindset Over Tools
AI Is Not Magic
Efficiency Before Innovation
Human Touch Is Essential
Ethics Are Practical, Not Just Policy
Inclusion Drives Adoption
Everyday Life Hack
Embrace the Imagination Age
Connect with Lexi Trimpe:
LinkedIn: https://www.linkedin.com/in/lexi-trimpe/
Instagram: https://www.linkedin.com/in/lexi-trimpe/
Website: https://www.linkedin.com/in/lexi-trimpe/
Connect with the host Amy Vaughan:
LinkedIn: http://linkedin.com/in/amypvaughan
Podcast:https://www.togetherindigital.com/podcast/
Learn more about Together Digital and consider joining the movement by visitinghttps://togetherindigital.com
Hello everyone and welcome to our weekly power lounge. This is your place to hear authentic conversations from those who have power to share. My name is Amy Vaughn and I am the owner and chief empowerment officer of Together Digital, a diverse and collaborative community of women who work in digital and choose to share their knowledge, power and connections. Join the movement at togetherindigitalcom All right. Today, friends, we are excited to welcome one of our own Together Digital member and ambassador at our Detroit chapter.
Speaker 1:Lexi Trump is the Director of Digital and AI at Franco, another amazing agency that I have loved getting to know your coworkers over the years. It seems like such a phenomenal place to work. I know you've been there for a while, lexi. We'll get into that here soon. She leads the digital strategy for B2B automotive and SaaS clients and heads Franco's AI Adoption Task Force and brings her a background as a formal journalist with bylines in Eastern Detroit, thrillist and others. She's the perfect guide for this conversation.
Speaker 1:Lexi and I had the pleasure of meeting Actually, I was just thinking back to that. The last time I was in Detroit was our panel and you were on our panel. I don't think you were a member yet, but I remember sitting there listening to you going, oh my gosh, this girl. She knows what she's talking about, so I am so thrilled that you're a part of the community. You helped champion together digital and our members. So we're excited to champion you here today and give our listeners a little bit more insight onto how they can start with generative AI.
Speaker 1:Obviously, you can't spend a day without hearing that term If you're in digital marketing and advertising. Everybody's kind of on a different spectrum to kind of know where we are and what you're doing in that space. There's a lot of overwhelm right Within the landscape of AI, from everything from tools to applications. Lexi's approaches you are all going to find very practical, easy to use hopefully not overwhelming on how to build an intentional AI strategy that preserves the human touch. So we're excited to have her here with us today. Thanks, lexi, for joining us.
Speaker 2:Thank you so much for having me. I'm excited Absolutely.
Speaker 1:Right, all right. Before we dive in and start nerding out about all things AI and generative AI, I would love to hear about your journey from journalism to leading digital and AI. Now, like I love how you're just like acquiring all this amazing work, what sparked your interest in becoming what you call a professional nerd?
Speaker 2:Yeah, so I always use the same, probably corny analogy that all of this started when my parents got me a gateway computer in 99.
Speaker 2:But, really, I think from that moment on on I've been kind of obsessed with the internet and all things digital, mostly for the reason is it allows me to kind of do this self-discovery and the self-exploration and as somebody who loved the library and loved reading, it was always a way that I could kind of hear stories from all sorts of different sources and learn so much. Um, and journalism really allowed me to do that too. Right, kind of amped up a little bit. My favorite thing was just getting to talk to people and then they would recommend me do research into something and I could spend all this time putting the story together. I hated transcribing and I hated deadlines, but I really loved learning all the things.
Speaker 2:So that kind of natural curiosity kind of led myself more into that digital realm. And that was right around when digital first content started to come up as well, and real social media strategy, which maybe I'm dating myself now, but that was an entire other kind of build the plane as we fly it kind of time. I think. In journalism specifically short form journalism, digital first that offered kind of both that challenge and that learning curve they've always been looking for, which then agency life, I think all I mean also the joke that all journalists, when you reach like mid 30s you make that agency life jump. But for me personally, I think it was the natural next step, because I get to look in so many different industries across so many different types of clients and figure out, you know, what makes sense for them and their individual audience.
Speaker 1:I love it. Yeah, you are like the quintessential TD member in that sense of like that insatiable, like curiosity and always wanting to learn. And it's interesting because a lot of our members kind of fall within that 15 to 20 year experience. And I do think it is because we all have had the chance like let's go ahead and date ourselves, that's okay, let's own it. We should be proud of that fact.
Speaker 1:We got to see the birth of the digital era and how fast it's come along. You have to be curious and willing to be open to learning and exploring and as you were describing yourself on your gateway computer back in 99, totally reminded me of something my mom would always say whenever we had a question. She'd be like look it up, look it up, and it was this like little definitive, you know 26, you know for all the letters of the alphabet encyclopedia set. That was probably done in like the 70s. That didn't really have a ton of data.
Speaker 1:So for us it's like we remember what it was like when you had to spend all of the time at the library or poring over books and encyclopedias, and now it's like all at your fingertips and so I don't think we take that for granted as much as kids who have been born right, kids these days that basically have all of that right at their fingertips. So I do think that appreciation of it is such a good thing and I think it's definitely shown as to like how and why although I'd love for you to color that a little bit too is like how you've been able to evolve your role right to kind of find their place within the workplace as far as like what's that next role, what's that opportunity, what does growth look like? But you know, knowing you for how, for the few years that I've known you, lexi, I feel like you've done nothing but ground like what's what's some of your thoughts and advice on that.
Speaker 2:So I've been particularly, I guess, lucky or had the opportunity that I've been kind of put into this intersection where things are changing in a really big way but they're also becoming much more accessible at the same time in multiple different assets, one being obviously the technology boom and you can be able to have a home computer. When I did early on, way before my siblings who were in high school who probably, like that, would have been a game changer right, I had it through, you know, middle school all the way through high school, which was an incredible opportunity. But it also allowed me to access more information and kind of continue feeding that hunger for knowledge and that curiosity. I had Same thing right when journalism. Everything was changing very rapidly but it was also becoming much more accessible. We didn't need a full camera crew anymore to do anything. We had our phones and we could go out and do live feeds. We were telling live stories, right. I was able to record really high quality footage and people expected that now it didn't have to be so polished and now it was more accessible and more exciting.
Speaker 2:But all of these times times we very much had to fly the plane or build the plane. As we fly it. I always say so. There has to be a little bit of that nimbleness and, I guess, not being afraid to fail. There is no wrong way to do any of this. We're figuring it out as we go right. We may stumble and evolve, but I think it's that willingness to be wrong and see what happens and learn from it.
Speaker 1:Yeah, and that leads so nicely into my next question, because you know, in this kind of AI overwhelm that a lot of folks are feeling, you know you even referenced this in a recent blog post that you did is that you know people's first question is often about what tools are you using? It's all about the tools and I'm curious, you know why do you think our focus tends to gravitate towards the tools rather than what you're talking about, which is more mindset, more strategy?
Speaker 2:Yeah, I mean, the most easy answer to that is there's just so many. I tried to look up studies the other day to how many like hundreds and thousands of tools have been released, but it is asinine. Um, there's actually a really interesting story about the dot ai domain that I won't go into and how that's exploding. Yeah, but there's so many of them and every day I think my inbox is filled with another cold email with a tool that says it can do x, y or z, all super targeted towards me, right, my particular needs, yeah, and all of them feel very much like that easy button that we're all looking for.
Speaker 2:Everyone is just looking for something that will just work right, especially because these things maybe take a little bit of that thought and risk out of it. When something is, you know, a little bit uh, being built as we fly it, yeah right. But the problem is is when we start kind of chasing these tools without that strategy, it kind of leads more to that wasted time, because these tools can only really matter if we're using them to first solve our really real problems, or else we're just going to be shoehorning solutions in where it doesn't make sense, and now it's more time being spent.
Speaker 1:I agree. I agree I've got an upcoming event that I'm really excited about to talk about AI without fear for small, namely small business owners, because I think it can be, like you said, a great, like a great tool I mean a great democratizer but if you're not using it in the right way. The analogy I came up with with my presentation was like it's kind of like finding scissors for the first time. You've been like ripping paper and trying to do it really well for years and all of a sudden, you find this new tool, aka scissors that are AI, but then you're running. It's like running with scissors. Right, you're just running around looking at what can I cut? I'm going to cut everything now, but scissors aren't the tool for everything, right, if you've got a big honking piece of wood, if you've got something know, something else, it's. Scissors aren't the answer for everything, and neither is AI. And it's like, when you're running around like that, acting a fool, it is kind of like running with scissors.
Speaker 2:This is my analogy, you know. Imagine it's a Swiss army knife and it's all the other things that we aren't using it for that it could be good for in addition to that.
Speaker 1:I am adding that to my presentation. Extended metaphor. Thanks, lexi, you're the best. I love it 100. I am adding that to my presentation. Extended metaphor. Thanks, lexi, you're the best. I love it. A hundred percent.
Speaker 1:That's so, so true, because you're right, I think people are chasing I mean we hear it all the time right, chasing the shiny object. You know, looking for that easy button. But you know the wrong tool and the wrong place could be disastrous. So really making sure that you have a sound strategy and then determine the tools that are the right tools for the job, really making sure that you have a sound strategy and then determine the tools that are the right tools for the job, really the best way to go about it. And when you think about it in a practical kind of physical world sense, it makes all the sense in the world. It's just I don't think we think about it that way. But I love your multi-tool reference too, because I agree there are a lot of things people are not using AI for that it's actually really made for more so than just generative all right you.
Speaker 1:All right, you've done some more writing. I love that you're continuing to write Like clearly your journalistic chops have not left you, so be sure to go onto Franco's website and check out some of Lexi's blog posts. We'll include them in the show notes. But you've written about the importance of understanding the foundational technology behind AI tools, right. So it's not just understanding what's the right tool, when is it the right time to use it, but like what is the technology behind it? For those of us who aren't very technical, what's the minimum we should try to understand about how large language models which is really what AI most AI tools are based on work?
Speaker 2:Yeah, and again, I think it's so important again, just even if it's that basic understanding for that exact thing that we had just talked about, it's using it for the right solution, right.
Speaker 2:Using the tools correctly, and when you understand what they are inherently, that's going to be so much easier. So again, breaking this down in a way that I, as a very much non-engineer do for the rest of my agency, I like to describe them kind of as giant statistical engines. These like math driven stats machines and they're not sentient, but they're really good at spotting patterns, which means they don't understand language like you and I do. They don't read letters, they don't read words or sentences, but they're really good at predicting what chunks of letters will come next. Right, they're really good at predicting what numbers will likely come next, but they don't really understand the data like you and I would, and that becomes really important to understand for some of the things that you're using it for, because it's just looking for patterns based on its training data and what you feed it.
Speaker 2:And if you aren't feeding it a good input, you're not necessarily going to get a great output back. Right, you're just kind of hoping it figures it out from his eye, guys, anything that it pulls to put together. The more intentional you can be with that input in your, what you're putting into the model, how you're asking it, the better that output is going to be when you get it out. And then you can use it across tools. Right, you're not being shoehorned in necessarily to this one specific solution. Those skills can be applied across models.
Speaker 1:Right, yeah, I love it.
Speaker 1:That's. I love that. I love the way that you just described it it is. It's highly predictive. It is literally just looking for patterns. It doesn't. It doesn't have a brain. It's not like understanding and processing everything the way we would. It's literally looking at large sets of data and saying, oh, I can predict what's next, which is what you know again, what machines are good at and humans maybe not always so much, and that's great, but that's really like the mindset you need to have when you're starting to use them, right.
Speaker 1:But, yeah, I think you know, I love that we're talking to you today, because I think a lot of our listeners and members are people who are advocating for the use of AI and you know newer technology and tools and sometimes it's a challenge, right, because there's a lot of fear, there's a lot of misinformation, misunderstandings, you know, and really trying to get people to kind of embrace these things, it can be a challenge, you know. And so for those who are listening, who are leading small teams with those limited resources, and you're spending your time not just trying to implement but also trying to educate, you know you're doing this and you've been doing this at FrankL how could they approach AI adoption intentionally, maybe, without getting caught into what you call, what we're calling like this AI overload?
Speaker 2:So the biggest advice that I can give anybody is don't start with the tools. Again, they seem like easy buttons. It's the first thing you can do. You see something in your inbox. You've heard really good things, you know it. It can help. You've heard of another agency or company that uses them. Don't start with the tools. Really start with your needs.
Speaker 1:And ask yourself.
Speaker 2:Why are you exploring using AI? What do you need it for? What's not working right now with your current processes and what are your goals? Because, ultimately, if whatever you're implementing isn't supporting your goals, why are we using it right? So if we can start by first identifying real pain points, then we can evaluate if and how we can use AI to solve them. And it might not be right in that one way, the scissors right. It's a whole Swiss army knife of things that we can do to maybe solve that problem in a way that works best with your workflow.
Speaker 1:Do to maybe solve that problem in a way that works best with your workflow, and by doing that you're going to be able to kind of keep your work focused right on what is again, eyes on the prize, what's at the end of the rainbow here, without getting kind of pulled into all these various tools and then trying to shoehorn them into your process Absolutely, because I think people are going to feel and sense that, right, like if you're if you're just kind of trying to force a new tool without a rationale or a why you're just you're really going to struggle, right, because that's what we all gravitate towards is the why I do want to call out that we've got our live listeners here with us today, so we're so thrilled that you're here and we want to hear from you as well.
Speaker 1:So, if you have questions throughout the conversation, drop them into the chat and I'll be sure we get them asked before we wrap things up here today. Because, like I know, everybody's unique circumstances are here. Although we've got a good list of questions for you, lexi, I want to make sure we're helping our listeners as much as we possibly can. All right, the next question I have for you is in another one of your articles, you mentioned the relationship between AI literacy and our perception of AI as kind of magical, and how has demystifying AI changed your own approach to implementing this? So this is a nice build to our last question.
Speaker 2:Yeah, so we've been now, as in, I guess, our AI task force, been working for about 10 months doing this exact process I just described.
Speaker 2:Right, we're starting with analyzing the what are we trying to improve and then again, how can we use AI to do that? And really, what we've learned throughout, you know, these 10 plus months. A, we've learned it's not magic, right, but we've also learned what AI is really good at and what it's not good at, and I think by doing that alone, we've kind of taken it that we're again no longer a spectator, we are now the magician. I like to say we can be a little bit more intentional with our usage, versus being reactive and trying to experiment with different things that aren't necessarily working. We're kind of thinking that AI first, now mindset, and with that too, we're starting to think about that a lot more holistically within our own processes right, it's not after the fact looking at this whole thing and figuring out okay, now where can? Throughout the entire process, now we're looking at ways that we can make it more efficient and that we can improve our time usage.
Speaker 1:No, that's fantastic. I mean, you put it so simply, but I don't take that lightly. That kind of change management is never an easy thing, right, when there's just a ton of concern and fear, security, people's jobs, all those different things in mind. To guide an entire company along to taking a mindset of an AI first approach is no easy feat, and especially in 10 months. Girl, that's impressive, that's really impressive.
Speaker 2:And we have so many different types of clients, too, and different processes, and all of our services are different, right? So trying to figure out a this is how we do this task approach wasn't necessarily going to work for us, right? We really had to get into the heart of what. Are we spending time doing that we don't want to when?
Speaker 2:do we want to improve our time. What do we want to do more of? We really focus, and you'll hear me say efficiency privately too many times, but we really intentionally focused on that first, yeah, doing optimizations before innovations, because optimizations pay the bills.
Speaker 1:Love it Optimizations before innovations. I'm sorry, I'm just going to say, like we have to quote that Take it right, but it does, it helps.
Speaker 2:you know, that's that ROI that you're looking for, which can be hard when you're also trying to invest in new tools and invest your time of figuring out how to use them.
Speaker 1:Right and we do get. We get so excited. I love don't get me wrong, I am all for innovation, but if things are not optimized first, like what is the point? You're just, you're just. You're just innovating to innovate You're actually not improving upon anything. So I love that and I want to get a little more practical here too. If you could walk us through, like, your process for determining whether an AI tool is actually worth adopting because you've given us a little bit of guidance, but maybe, like a case in point example, would be helpful for our listeners as well. And what questions should we ask beyond? Okay, what can this thing do when it comes to implementing AI tools?
Speaker 2:Yeah. So if we're going to get down to any kind of situation task, whatever it might be fitting into it First, I think we've done this a lot. What is the problem that you're solving? What do you want to do and what are you trying to achieve at the end of this? Making sure it's measurable right at the onset, I've learned throughout, this entire process has been so so valuable. Again, not only is it allowing us to show that ROI, but now we're actually able to see if, whether or not, this is working.
Speaker 2:Second, from that asking yourself, how will this tool actually help us achieve that right? Will this tool make us better, faster, more strategic? What is it doing for us? How does it integrate in the work that we already do? Right? Is this going to create more friction? Because if we're implementing a tool to improve our processes and now we're just creating more friction, right, we can start to see ahead on where you know there's going to be problems there, and then can we trust the output? What is our plan for validating it? I say this with everything, because hallucinations are a bug. They're just destined to happen with the way that AI works right. So we need to be having a process in place for any of these things to really guide our ethical usage right and making sure the content that we're putting out is accurate and correct.
Speaker 1:Yeah, yeah, no, definitely, human in the loop is absolutely essential, and a lot of marketers, I think people, are sometimes afraid like, oh, it's going to take our jobs.
Speaker 1:It's like, no, no, it's the people who know how to use AI that are going to take your jobs, not AI itself, because you can't just run on AI alone. It's not possible. It's you're going to get and that's another phrase I heard recently too, somebody put out there it's like marketers are not going to get replaced by AI, but it's going to expose the bad marketers, because people who don't understand marketing are going to try to use it in place of people who actually know what they're doing and there's no check the balance there, right, and so they'll just put up something and it's total garbage or it's bias, right, because we know there's bias in the code. So therefore there will be a bias in the output, and so not having that human checkpoint absolutely essential. I think that's a good call. Let's dig into ethics a little bit more, because that comes up often in AI discussions. Although I need to clear my throat, give me a second.
Speaker 2:I love the mute ahead of time. You're a pro Right.
Speaker 1:Done this a few times and I can like feel it coming, so I'm like all right, all right, let's get practical here. Could a little bit more, and I'm going to focus on ethics and how it comes up so frequently with AI discussions. What ethical considerations specifically should digital professionals be mindful of when implementing specifically generative AI in their workflows?
Speaker 2:Yeah. So when we talk about ethics, I think it's important to specify that ethics isn't just about having a policy right. It's ultimately about protecting trust. So when we're figuring out about what is our AI ethics policy, or how should we be writing this, we need to first assess what is our responsibility right, and not just our responsibility to our team, but also to our clients, to our audiences, anyone who's going to be impacted by your AI use cases. For example, no AI generated content should be going live from any of our brand channels without human review, because we know that our audiences we have a responsibility to them to build their trust, that they know that the content coming from us is accurate. These sorts of things of first analyzing who will be protecting what is our responsibility to them is really key to that sort of mindful application and setting up the right guardrails and vetting processes.
Speaker 1:I love it and that's so great. And there's a lot there, obviously, that we could kind of expound upon. And you know, and it's, this is one of those situations, like you were saying earlier. It sounds crazy, but like AI and ethics, like that's, that's a plane we're building while we're flying it.
Speaker 1:It's one of those things where it's like you just have to stay vigilant, right, and you have to think about your use cases and just know there's going to be slip-ups.
Speaker 1:But, like, when there's slip ups or there's instances where it's like, okay, this didn't really align to what our values, our morals, our standards, our ethics are, well then you gotta put it on in writing, you gotta train, you know things differently.
Speaker 1:You have to communicate across your team that this is not how things get used or done. I think, early and often and as soon as kind of the slip up is made, but at the end of the day, like during this time, like that's just what's going to happen, right, because that's how we're going to figure it out is by falling on our faces a little bit. So I think that, too, hopefully helps alleviate some of that fear, right? That is like you said, when you stay vigilant, when you're on the lookout and you're keeping humans in the loop. Ethics becomes an easier thing when you kind of understand, too, that this is something we're figuring out as we go and there's not a lot of regulation out there either, which I know is terrifying. We're having a whole one of our Together Digital Cincinnati. In-person events is all about unregulated tech in a highly regulated industry like healthcare right.
Speaker 1:I can't even imagine. I mean, I worked on automotive, I worked on Ford, I know what that legal department's like, any and easy to get stuff through there. So I can only imagine with AI it kind of just compounds, like you were saying. It almost creates maybe more friction sometimes. So finding the right places to use AI makes a whole lot of sense and generative to me. To me seems to be the most tricky right, because it's a thing you're going to take and then you're going to put it out into the world. Versus take and use for analyzing, yeah.
Speaker 2:Yeah, and again this is. I did a presentation on this out in Grand Rapids earlier in the year and again, like you said, we're very much building the plane as we fly it on this, so it is continually changing.
Speaker 2:But I use the analogy it's really easy to lose sight of the forest amongst all the trees. Right, when it comes to ethics, we're kind of pulling out these individual things that we need to focus on, versus first analyzing what is it that we're doing and who again do we owe that sort of moral responsibility to? And I think when we have that compass in mind, it's much easier to look at all the individual processes we have in place through that lens and see, okay, where could there be an opportunity that we could let somebody down?
Speaker 2:and be able to kind of proactively assess that risk.
Speaker 1:That's great. I think that's a good way to look at it too. It's just being mindful and vigilant throughout the whole process, even at the very beginning, to say like what could go right, what could go wrong? Right, yeah, exactly. And so what are some ways in which you are trying to kind of balance the convenience that AI brings while maintaining the control of the outputs that AI maybe is creating for some of the work that you guys might be doing?
Speaker 2:Yeah. So when it comes to AI tools, specifically to when we talk about third party tools and things, a lot of them are designed for ease, right. But with that ease and convenience, there's often that cost of understanding exactly how they work. That's that secret sauce. But that abstraction can obviously limit your understanding and also limit your control. That's always why I like to try to make it a point to really understand how these tools work and how they handle data. That way again, you're not being shoehorned into one specific process, but it can be taken across as these again, there's going to be a lot more new tools that come out right With that in mind. These tools are kind of continuously changing, right. There are risks involved. There's evolution involved. When you're working with third parties, you're putting your trust in them. Now, that.
Speaker 2:A they're staying up to date and that they are keeping your data private, right, right. So the more layers of kind of abstraction there are, the more kind of, you know, viability there is. Just inherently, and a lot of the. I mean, all of these tools are working on the same handful of models. That's also the other thing. That was just the eureka moment of realizing core models versus, like, third party models. If you can understand kind of the basis of that, it gives you so much power to kind of be tool agnostic, which is very cool.
Speaker 1:No, definitely. Yeah, I think there's some things interesting too. So I don't know if we talked about this yet, but my husband recently made a transition from academia to a startup and it's an AI company and he's head of AI research, and one thing I have taken from him that I think is fun, that you reminded me of as you were speaking. There is, as I'm trying, a new tool. I kind of try to break it. I try to see where the fallacies are, how it will start hallucinating if it'll start making up information, anything like that. Because as a head of research for AI, that's his job is. He just gets to sit around not all day, but sit around and try to find ways to basically get the AI to do something it's not meant to do or not supposed to do.
Speaker 2:So I would say, yeah, test the limits. My prompts are abysmal, Like if you look at my prompts, compared to what I tell people to prompt with on my team. Again, for that exact reason, if I'm always trying to test it to be okay, what would say the person that's going to use it the worst? Right, they break it. That sort of proactivity is so important too, as we're trying to be. Again, we know there might be some resistance to some of these things, right? So if you can kind of be proactive and figure out where doesn't it work and put some of those I guess that's all that transparency right up front with your team.
Speaker 1:It's really going to again prevent some of that resistance to change and I was kind of curious like what resistance have you encountered when introducing, you know, either AI or any of these technologies, and how do you address the concerns that are coming from your team members, because I can imagine we've got a lot of folks listening that are kind of in a similar situation.
Speaker 2:So when we, when I first came into this our whole team well, we developed people, a people first approach, right, even based off of our AI task force that we put together. Um, there's only, I think, two members of our digital team are actually on that task force and the rest are from other you know, members of our agency who we do integrated communications for context there. So a lot of members of our team are more heavily involved in media relations or influencer work, um, so having all of those seats at the table was a really important as we develop their processes, because it's not just how I'm using the tool. That can often, you know, lead to some biases and, you know, misunderstandings about what would be easy, what are our processes. So, I think, putting that first and making sure that we had everybody at the table right, and then from there, we just asked our team exact things that again that we're talking about what are you guys challenged with right now? Where are you struggling? What do you want to do more of? What do you want to do less of? Um, and from there, we were able to really look at all that through the lens and figure out okay, where could we maybe use ai to do some of this, right, yeah, um, so we were directly answering their questions, we were directly solving their problems, um, and with that there's inherently less resistance, right, I love it.
Speaker 2:The other thing is just knowledge. Knowledge is very much power in this way, that same explanation of kind of what I gave earlier. There's a reason again that I came up with the statistical math machine analogy because it makes it a lot less. Yeah, especially when you know that if you're putting your content in, you're inherently getting a version of your content back. Right, makes it a lot less scary. Knowing how it's trained makes it a lot less scary. I always say if you're planning on putting something publicly online eventually, like a press release, that's fine that you use AI with it, because eventually it's going to end up back in that model anyway. If it's going out on the wire, it's going to be in chat, gpt in like six months max. It's getting faster and faster, right. So understanding some of these things just make them a little bit less scary and prevent some of that resistance early on.
Speaker 1:Yeah, I agree, education is the antidote to fear, for sure, and I think exactly what you said at the very beginning of the podcast.
Speaker 1:It circles from the so nicely right back to now, which is, you know, when you're working with a team and you're trying to implement something such as AI or any other technology tool like focus on the needs Cause, then you're like I got this paper, I got stacks and stacks of paper, I got to get cut, and how are we going to do it? Oh, look, I have scissors. Yay, all of a sudden you're not questioning any of it. But I agree, understanding education, even just finding ways to kind of simply explain so that people aren't feeling so fearful, is a great way to get them to embrace those tools. So, yeah, I can definitely see why you've done such a great job implementing it and I love that you have, like you know, an identified task force within the agency to help kind of own this and you know steer and guide and having, I imagine you have that support too, right From the top down, which also is a huge difference, right.
Speaker 2:Absolutely Well. We again we knew with an agency of our size we're about 30 people, a little bit over. Now we're right at that sweet spot too that we're like boutique agency size, but we have the clients right, we have a large workload. We've always very much worked in that sort of way, so the innovation and optimizations that we were going to potentially unlock with AI were so particularly valuable for us that it became a really big priority for us early on. When we saw that power, I got to again give it to our leadership on that, because that can be a little bit scary, right, because, like you said, we're making this up as we go and the only way to do it is by trying things and sometimes failing and figuring it out. But we knew that if we weren't kind of like first to market on one of these things, we're just going to be learning from other people and our agency is unique in that way that we knew that we wanted to kind of forge our own way.
Speaker 1:Yeah, I love it. I think that's the way to do it. It seems really smart and I love that you've embraced it and again, that your leadership team is like aligned, because that really helps. If you don't have that alignment from the top down, it just makes it hard for anybody.
Speaker 2:It's that women-owned agency. We're getting stuff done. Go, ladies Well done.
Speaker 1:Franco, folks Love it All right. Looking ahead, how do you see the relationship between human creativity You're at a creative agency right and AI evolving in the market and marketing and communications field over the next few years? I mean, we can even tie this back to your experience as a journalist, you know.
Speaker 2:Yeah, yeah. No, this one is such a fun question and I gotta say I think it was last year where we had helen todd um at the illuminate and I just fell in love with her and her entire presentation.
Speaker 2:Um, so I will say I've taken a bit of a note of that sort of optimism, and I do have a little bit of I mean definitely optimism in the way that we, as creatives, can use it. I think, like with all tools, like with the internet, like with everything, we're going to have this phase, a kind of shallow, surface level AI use, and that's normal. I think that's where we're very much in right now. There's a lot of risk right now. We're still figuring a lot of things out, but I hope I'm inherently optimistic that, as our understanding continues to deepen, that we can start to use AI more as that sort of creative co-pilot that you were talking about.
Speaker 2:The ability to improve our ideation without needing an entire roundtable of people and its ability to free us up for new thoughts is something that really, really excites me. The ability to look at mass amounts of data and look for trends in a way that previously we weren't able to do at this sort of scale is incredible, right? So I don't think it's going to replace human creativity. It can't. Inherently it can. It's regurgitating. Again, it's a math machine. It's just giving us back what we put in, exactly, Exactly, but it can make us more creative by giving us so much more capacity that we were never able to before.
Speaker 1:Yeah, I love it. I'm so glad that Helen inspired you. Yeah, her talk last year at our national conference was phenomenal. Y'all should check out her podcast as well Creativity Squared. She's been on this kind of you know role with talking about AI and creativity for about a year, two years now, I think. The podcast is actually two years old, so she pre-ordered the book.
Speaker 2:Did you? Yeah, I'm excited about it.
Speaker 1:So good, yeah, I'll have to let her know that she's got some pre-orders coming in. She's writing a book and she really talks about you know this like a lot of times. Uh, I think it's. Sam altman calls this, like this time point in time, the innovation age, and she's like, no, it's the imagination age.
Speaker 1:Like this is really not about, again, like you said, innovating without optimizing, like there's just we do. We need more innovation right now. No, because, honestly, it's hard enough for us to keep up with it. But how can we start to be more imaginative? How can we use AI to actually enhance our ability to be creative? And I will say too, just like as a small business owner you know, on the flip side of things, I know it's different for agencies like trying to adopt and figure out what are the right tools, what's the right conversations, what are the right ways in which we could use it, how do we talk about using it with our clients? Like so tricky.
Speaker 1:But I have to say, as a small business owner and, honestly, like one of my other favorite podcasts that we've had on AI recently is with Sarah Dooley, talking about AI, empowered moms and how it's such a phenomenal tool, just even like a little life hack in ways in which you can like I have gone and asked for like tips on meal prep and things like that based on like food allergies and concerns. I've used it as like a little book in the moment therapist for things when I'm like in a moment and I need somebody to like help, because it just rationalizes and it's got all the CBTs, so cognitive behavioral therapy like trained up on it. So, yeah, no, it's not just not going to replace your therapist. However, in a moment like, honestly, it at least gets you to slow down and think. And so there have been.
Speaker 1:I've used it to plan parties for my kids. I've used it for so many different wild things that I would like it. That's the Swiss army knife moment right, that's the unlock is when you start to realize that you know, yes, it is a great tool and, yes, that's something we should be working to champion and educate those at work to be being aware of. And how do we use it, when do we use it? All of that. But also, I think another way to maybe drive down that fear is just kind of start finding fun ways at home to use it. And you might be surprised because, like you said, that pattern recognition is real and it's new, like deep research capabilities have just been wild.
Speaker 2:I always try to show a couple of personal use cases whenever we do a rollout or things on those lines, just because again it gets us using it. But the mobile app of Chad GPT the number of times that I just take pictures of things and ask it to tell me about it. I'm a thrifter, I love to thrift.
Speaker 1:I love it.
Speaker 2:A bunch of weird old patches and pins and things. The number of times I've told it to do deep research on it for me and tell me all the history, stuff like that. Just it takes the ability of something I couldn't google before. Yeah, again, just finding those real use cases. What do you want to know? What do you want to do? I coded my first, uh, my first JavaScript app in my life the other day. I'm not an engineer, but I got rid of 26,000 emails, right.
Speaker 1:Oh my gosh, I need this.
Speaker 2:I spent two hours making the app, but I cleared out all the emails. Oh my gosh, that's amazing, opening up new avenues of creativity that just previously weren't even possible, which is so cool.
Speaker 1:That is so cool. Yeah, I'm excited to see kind of where it goes, also within healthcare. Like, I'm excited there just because there's so much just for diagnosis and things like that. There's so much complexities behind like a series of like tests and conversations and symptoms over the years, months, whatever, that don't get tracked, that don't have pattern, that anything that the human brain can like, recognize and realize. I think we're going to see a lot of innovation, I think, in the healthcare space too. For that Cause I think about that. That pattern recognition is essential in understanding how our minds and our bodies are working.
Speaker 1:There was another example I was thinking of too, actually, as you were talking, and then it left my I left my non-AI powered brain. If I think of it, I'll bring it back up. But yeah, there's so many cool and fun and interesting use cases out there and I do think it's you know, what are the things that you find belaboring that you would rather off put to. You know, like you said, a co-pilot oh, that's what it was. Tech support I have used it for tech support, where I'm like I am struggling with this thing. How do I create, like, even like setting up zaps? I'm like I want to set up a zap for this and that and the other and I'm like how do I even do that? It is like a super powered search engine, right? Because instead of just giving me general search results, it's actually specifically answering my question. So yeah, tech support's been another kind of lifesaver for me.
Speaker 2:That's my life hack, I swear it's. My biggest hack is if you were looking up which I hate Facebook questions. Stop asking me Facebook questions. But the meta AI. I ask it every Facebook question that comes into me because I know it's direct knowledge base. Similar thing Bing owns or I'm sorryrosoft owns uh, copilot. Microsoft also owns linkedin. Go ahead and ask uh, that copilot? Any of your linkedin questions. I try to match them up where it makes sense.
Speaker 1:Yeah, just knowing that they're going to have way more access to those knowledge bases and, like you said, like having that understanding helps you know how to use the tools smarter, because you're asking the right tool to do the right job.
Speaker 2:Google ads questions go to Gemini. Right, You're able to kind of ask the right ones.
Speaker 1:Oh, that's great tips. I love that. I know some people are going to take that home for sure. I have a fun little bonus question before we move on to our power round questions, unless we get questions from the audience. I am curious and this is like latest breaking news right, and AI is now. We're being asked not to say please and thank you. Have you seen this on AI? Because apparently we're like burning down the world and all of the power and energy that it takes for all of this stuff to compute. We're being requested not to say please and thank you. Will you continue to say please and thank you to AI, and do you already?
Speaker 2:Yeah, here's the deal. I'm always going to phrase my input the way that I want my input to come back out, and if I don't want it to be a but, I'm going to be nice to it. Right Beyond that, I think if we're worried about the data processing, we probably should stop making Studio Goodly images. But it's fine. There are probably bigger concerns than the please and thank you. Yeah, I agree, but it's fine, there are probably bigger concerns, right, please and thank you. Yeah, but I think this is where that intentional usage really goes far. I love it. I love that answer.
Speaker 1:That is so great. Yeah, can we attack some other things other than just genuine, like just courtesy?
Speaker 2:you know it went down for all of last week because of the image generation. So we can stop that first.
Speaker 1:It'd be great, right oh, I hear you there, friend. All right, let's get to these power round questions. I had to ask because it just keeps coming up and I'm like you know, I'm just curious.
Speaker 2:All of my coworkers have asked me this week if I had a can. I won't lie.
Speaker 1:I believe it All right. What is one AI tool people tend to overlook, but shouldn't?
Speaker 2:I hear it a lot, but maybe not this feature but notebook lm from google for deep research. Um, but also that podcast ability. Within the last couple of months they introduced the interactive ability. So you can interrupt them and ask them questions now and like direct the conversation. That's super useful for me. Um, and all that, live again. You live person to bounce ideas, off of which is so cool.
Speaker 1:No, it is really. It's like the best little intern ever. I love it. All right, fill in the blank.
Speaker 2:The biggest mistake people make with Gen AI is Starting with the tools instead of understanding what they're trying to solve for I love it.
Speaker 1:Yep, exactly, all right.
Speaker 2:What's your favorite aha moment you've witnessed when introducing AI to someone else? Lately it has been basically any of the ways outside of content generation, specifically the deep research, when people get to see everything that comes back and then all of the citations for it. They're blown away every time and it is super cool.
Speaker 1:It's my little encyclopedia set. They're just exploding and becoming infinite website.
Speaker 2:It's right there for me it's so nice.
Speaker 1:Oh, it's amazing. I love it. Yeah, it's gonna help a lot with a lot of things. All right, last one um, what is one thing about ai? You wish everyone understood, uh, but most don't halluc.
Speaker 2:Hallucinations are not glitches. They're ultimately baked into how the models work right. So validating your output is always going to be a non-negotiable before you put it outwards.
Speaker 1:Yeah, I love it. That's a great frame of reference for us to kind of keep in our little back pockets there as we continue. Lexi, this has been amazing. Thank you so much Again. All these insights have been really helpful the tips, just the practical advice, just really kind of helping build out and navigate the AI landscape with some intention and purpose. You know it's just really helpful because you know it's all moving fast, it's all moving furious and it can feel a little overwhelming, but it doesn't have to. I think your measured approach, your open mind about it, I think all of it's, you know, a really great example for those who are trying to do the same out there in the world. So thank you so much for sharing with us today.
Speaker 2:Thank you so much for having me. This was super fun.
Speaker 1:Absolutely. Yeah, long overdue, but, you know, at the right time right? We're all sitting in the thick of this right now, so everyone who's listening be sure to check out our past recordings. All of our Power Lodge sessions are available on YouTube. Also, anywhere that you stream and listen to your favorite podcasts, you can stay updated by subscribing to any of those channels. Definitely, if you have felt like you've learned something here today, you're feeling a little less alone and you're looking to meet and connect with more amazing women like myself and Lexi, who are just really here and excited to again just nerd out together, you know, and come together and nerd out and also are just really wicked, smart and generous. Definitely, check out and learn more about Together Digital togetherindigitalcom. Lexi, I'm excited to come up to michigan and see you next month. Um right, yeah, absolutely.
Speaker 2:Come to our events again together. Digital ones are typically open as well, if you're looking to dip your toe in absolutely, absolutely.
Speaker 1:Yep, we're excited to have you all here. We'll be back next friday, so we hope you join us then. And until then, everyone, keep keep giving and keep growing.
