The LeadG2 Podcast
The LeadG2 Podcast is dedicated to helping sales organizations grow. Each week host Dani Buckley (VP/GM at LeadG2) discusses proven sales enablement strategies and real-life examples with experts and thought leaders from across industries.
The LeadG2 Podcast
AI and Content Creation with Megan Skalbeck
In this episode, we’re exploring the ever-changing role of AI in content creation. Are the current capabilities of AI tools all that they are cracked up to be? Is AI a boon to the content creation industry or a disruptor? Will ChatGPT replace us all?!
Joining Dani to break it all down is Megan Skalbeck, Head of AI Projects at Verblio.
Megan brings so many amazing points to the table, like:
- How AI tools, while far from perfect, are capable of performing truly incredible tasks
- Why you should keep a watchful eye for factual inaccuracies when using tools like ChatGPT – Spoiler alert: these programs can speak a little too confidently about wrong information
- And finally, why content creators shouldn’t be treating AI as a silver bullet for their every task or, conversely, grabbing their pitchforks in defiance
Links:
Megan Skalbeck:
linkedin.com/in/megan-skalbeck-75251466/
The Best AI Detection Tools of 2023 - Or, When the Turing Test Won't Cut It:
verblio.com/blog/ai-detection-tools
Dani Buckley:
linkedin.com/in/daniobuckley/
LeadG2:
leadg2.thecenterforsalesstrategy.com/
TIMESTAMPS:
(02:53) Megan's experience and background with AI
(05:45) When you think about what AI is actually doing and what it's capable of, it is incredible
(07:35) You should be playing around with and testing new AI tools, but keep humans in the loop
(11:24) One of the biggest risks is the factual accuracy
(12:45) AI is that it is not capable of generating novel, original thinking
(14:42) The biggest general mistake is treating AI as either a silver bullet or condemning it outright
(17:38) If AI is using information intelligence, data and content on the internet, at what point do we know that what these tools are producing isn't regurgitated AI content that may be incorrect?
(19:22) People are slapping AI on everything nowadays
Dani Buckley: (00:15)
Welcome to Sell Smarter Sell Faster, a podcast dedicated to helping sales organizations grow. Each week, we discuss proven sales enablement strategies and real life examples with experts and thought leaders from across industries. I'm your host, Dani Buckley, Vice President and General Manager at LeadG2, a sales performance agency.
Dani Buckley: (00:43)
In this episode, we're exploring the ever-changing role of AI in content creation. Are the current capabilities of AI tools all that they are cracked up to be? Is AI a boon to the content creation industry or a disruptor? Will ChatGPT replace us all? So many questions to answer. Joining me to break it all down is Megan Skalbeck, head of AI projects at Verblio. Megan brings so many amazing points to the table, like how AI tools, while far from perfect, are capable of performing truly incredible tasks. Why you should keep a watchful eye for factual inaccuracies when using tools like ChatGPT Spoiler Alert, these programs can speak a little too confidently about wrong information. And finally, why content creators shouldn't be treating AI as a silver bullet for their every task or conversely grabbing their pitchforks in defiance. Welcome, Megan. I am so excited to have you here. How are you doing today?
Megan Skalbeck: (01:41)
I am doing great. How are you?
Dani Buckley: (01:42)
I'm good. Yeah. I'm, I'm really, really looking forward to this conversation with you. Um, I know we've met before and talked about it, and I immediately was like, I want you on the podcast. So I'm glad that it worked out, , and
Megan Skalbeck: (01:53)
I'm happy for any excuse to talk about ai. So, great. Thanks for having me.
Dani Buckley: (01:56)
Great. Yeah. So I mean, AI that, you know, not a surprise that we're talking about this on this, uh, our fifth season here at Sell Smarter, Sell Faster. It is all the buzz. I always like to remind people, you know, AI is not new. Um, we've been u either, AI is all part of our world and has been for a long time, but there have been recent innovations, um, like ChatGPT and now Bard and, and so many others, um, that are really putting this like in the forefront and everyone's talking about it and everyone's asking the questions, right? Um, do we use ai? But I think the real question is how are we going to use AI and what are the best ways to use it? Right. And I know we're gonna get into that with you today. So, um, yeah, I'm excited to talk to you about AI in general cause you are an expert, but also we're gonna really dive into it when it comes to like using it for actual, like content creation, um, especially copywriting for marketing and sales, for those that are listening. So how's that sound ready to jump in?
Megan Skalbeck: (02:45)
Sounds great. Absolutely.
Dani Buckley: (02:47)
Cool. Okay. So just to go kinda get everyone on the same page, can you tell our audience a little bit just about your background, um, your experience with AI and kind of what you do at Verblio, just so we can kind of understand, you know, who you are?
Megan Skalbeck: (02:57)
Absolutely. So, uh, until about six months ago, I was a content marketer for Verblio. We are a content creation platform that uses our network of freelance writers to create content for brands. So think blog posts, eBooks, landing pages, things like that. Um, and prior to that, I had actually been a freelance writer for several years. Um, eventually writing for Verblio, which is how I joined them. And, and they convinced me to join full-time, uh, back in 2020. Um, so that's kind of the, the writing content creation side. Long before that, though, I was a math camp kid. I did some programming in college. I interned for a summer programming there, started seeing code in my dreams, the whole, you know, nine yards of a, of a techie mind. . Yeah. And at the time, I ultimately decided against going down that route because coding was, um, honestly like a lot of fun, but just a little bit too deterministic for my taste. You know, you write a piece of code, it does something, and it's gonna do that same thing every time you do it. And you can do all sorts of cool stuff, but it's more predictable. And I had too much appreciation, I think, for the randomness and unpredictability of humans to wanna work exclusively with computers.
Dani Buckley: (04:07)
Yeah.
Megan Skalbeck: (04:07)
Well, fast forward to now, and we've got tech that is so much closer to mirroring that randomness of humans and like the large language models that AI writing tools are based on, and we'll talk more about this, but, you know, they're, they're probabilistic. They're not gonna do the same thing every time that you give them the same prompt. And so they do all kinds of weird and strange and unpredictable things. I find that really fun. So over the last year or two, I've been digged back into that tech side of things, both from my own technical curiosity, but also like my professional interest and frankly, self-preservation instinct as a writer and content creator. Right? Yeah. Um, and so about six months ago, that became my full-time job at Robo. Um, essentially had a mandate to figure out where and how we should be using ai, experimenting with it, learning about it, iterating on it, um, eventually kind of building out a new product with our CTO or head of engineering, essentially our entire ops team at this point. Um, and what we've come up with is kind of a, a hybrid method of creating content that uses ai, but also uses our community of professional writers. So that's where I've been with all this. Yeah. Um, deep, deep in it from both sides, the writer side and the, and the technical side.
Dani Buckley: (05:15)
Awesome. I love it. I think that's really very valuable and helpful that you have both of those kind of, uh, perspectives coming into this. So let's jump, let's kind of dive right into the, the, the big questions here. So how do you view the current capabilities of ai? Um, especially when we're talking about copywriting for marketing, for sales, um, yeah, like what are, what are you kind of seeing there?
Megan Skalbeck: (05:35)
Yeah, so it is, it can do incredible stuff to be perfectly frank. Like, I mean, we can get down on it for the, the mistakes. We've all seen screenshots of crazy things that it generates, but like when you, when you think about what it's actually doing and, and what it's capable of, it is incredible. Mm-hmm. . Um, it is far from perfect, and it is not to be like left to its own devices, but, but it can do, do some cool stuff and can absolutely help with copywriting and content writing. So, um, like it is, it is absolutely changing the content creation industry. I'm, I mean, that's, that's why I was put to work on this full-time, was like, okay, this is gonna change everything that we do. How should we be using it? Um, and, and how should we be using it? Well, it's really easy to use AI right now.
Megan Skalbeck: (06:18)
It, I mean, it's free , it's essentially, right. You can go create content with it. But what we wanted to know is like, okay, how can we be doing this more responsibly, creating content that still meets our quality standards, um, creating content that is factually accurate, um, you know, free of bias that adheres to brand guidelines, all of those things, um, that actually provides value to readers. Um, so that's what we've been working on, and that's, I think, what's the really critical piece, um, that is missing from everyone, just again, doing screenshots of their ChatGPT . Yeah. Text
Dani Buckley: (06:51)
. Totally. And I, I think before we even hit record on this podcast, we were talking a little bit just about, um, you know, we, we prerecord these episodes, and so this is gonna air like, uh, maybe a month or a little bit more after we're talking today. And so I think it's important to note that like a lot can happen in a month, . Um, we've seen that. So the questions I ask you today, we won't hold against you if we, if, if they've, you know, improved your change in in the coming weeks. Um, but I still think it's really valuable. And, and so with that being said, I'm curious right now for those that are listening, um, and you know, we specifically talked to a lot of, um, business leaders, sales leaders, marketing leaders. What are some of the specific things that you think those folks can and should be using AI for right now when it comes to content creation? Like some specific stuff?
Megan Skalbeck: (07:35)
Yeah. So, uh, you should absolutely be playing around with some AI tools if you are doing, you know, trying to create say like one off pieces of content, whether that's for sales enablement or something like that, like play around with a tool, whichever one. It's interesting. Um, I've, I've looked at a lot of AI tools and they all change their pricing and their plans every month or so it seems, I'm sure one of them is currently offering a free trial that you continue
Dani Buckley: (07:59)
Use
Megan Skalbeck: (08:00)
, um, but play around with it and see kind of what, what it can do and get a sense of what it's capable for, um, for a, like a salesperson, for example, like, uh, something like, you know, if you have an internal writeup after a sales call and you send that around to your team, oh
Dani Buckley: (08:17)
Yeah, I love that. You could u well,
Megan Skalbeck: (08:18)
You could use that internal writeup, feed that into an AI and it could probably generate a, a pretty decent follow up email for you. Right? Yeah. Um, it's, it's great at things like that. Um, so it's great for, you know, it's great for summarizing, it's great for coming up with ideas for, you know, coming up with 10 different email, uh, uh, subject line ideas for you. Right. If you wanna say test different things in, in your cold emails, um, it's great for kind of coming up with different versions of text, right? Yeah. So if you kind of have your version, but again, you wanna maybe test it again against different things, um, it's, it's got a lot of applications, like kind of narrow applications like that. And then for larger content creation, like what we do, um, the most important thing that we've found is, is having a human in the loop.
Megan Skalbeck: (09:03)
Mm-hmm. . So it's not, okay, the AI generates this full article, you give it to the human and they, you know, spend a little bit of time polishing it, and it's also not okay. The human writes the article and you give it to the ai and the AI does it thing, it's, it's a true back and forth. That's the way to get best results. I love that. Um, so we've done a lot of playing around with our prompt engineering and, and all of that, um, to figure out really the best way of blending those two. And it's been a lot of work , and if you are wanting to do this at scale, I, you know, just know it's either gonna be a lot of work, uh, or you're gonna wanna work with somebody who's, who's already done the work. Yeah. Um, but it's, it's important to know, again, for any sort of longer content, having the human involved throughout that entire process is, is crucial. But for one-off things, shorter copy things, play around with it, um, just again, see what it can do and, and also know that you're gonna need to review every single thing it produces.
Dani Buckley: (09:57)
Yes, yes. Yes. Very key. And just to kind of add to that list, you know, some of the stuff we're seeing salespeople and sales, you know, leaders use, you said email templates or different kind of like different types of emails. Love that. We're seeing that really helpful. Um, those that are listening that, that use valid business reasons or coming up with, you know, a piece of, of something to draw in a prospect When you're doing that initial outreach, we found that a great thing to find, um, any kind of brainstorming or like list creation, um, creating outlines for stuff like PowerPoints or articles or different, um, coming up with questions for your discovery call, right? I mean, there's a, and you know, again, there's varying levels of editing that's needed, but um, but yeah, we're, we're seeing a lot of different parts of the sales process that you can kind of like trial and error and kind of see, hey, does can this help with this?
Dani Buckley: (10:41)
Can this help with this? And it's really, um, recapping meetings, um, yeah, like transcribing notes and calls. I mean, there's a lot of really cool stuff, so, yeah. Yeah. Great. Um, so with, you know, uh, with ChatGPT, you know, where we're seeing like students are using it's right essays, , others are prompting it to create poems and full length novels. I mean, there's all kinds of stuff beyond business that's happening. Um, you know, and, and I think the possibilities are certainly endless and we're gonna continue to see this, you know, evolve. Um, but, and we've touched on a little bit of this, but I wanna like really just make sure we cover anything that you wanna be sure is said. What are the gaps or shortcomings of this that we need to be really being sure folks are aware of? So you talked about making sure there's a human involved in the whole process. That's a big one. What else?
Megan Skalbeck: (11:22)
? Yeah, so the, I mean, I would say the biggest, one of the biggest risks of this is the factual accuracy piece, right? Mm-hmm. Because AI will say things and, and the tricky, the hardest part of it is it will say it with such confidence, right? . Yeah. We'll write it out and it will sound good and it'll sound like something you've read before and you know, the number it includes, or what it says is simply false. Yeah. So that is the, the single biggest, um, kind of risk to be aware of. You know, anytime it's some, the AI is making a claim of any kind, you need a human checking that. Um, and citing the source source to make sure that it's accurate. Um, because again, also the AI won't be providing its sources either. Um, so that's the citing sources is another key piece of that.
Megan Skalbeck: (12:01)
Um, the other thing is, uh, you know, right now ChatGPT is free. So it's easy for people to think that, okay, this is totally free tool. Um, be mindful of the editing time and the review time that you're gonna have to spend editing that. Yeah. Um, you know, if you're used to working with a freelance writer and you're like, well, okay, now I don't need a freelance writer, I can get my content from chat g p t, like, know that you're gonna be spending a lot of time reviewing that. And it's also like much higher stakes editing and that, you know, if your freelancer submit something and you miss a few things editing, whatever, it's, it's a slightly more mediocre article. Yeah. If you don't review what Chad g p t says, you could be putting completely false information out there. Right?
Megan Skalbeck: (12:40)
Yeah. So the, the stakes are very different. Um, and then the other, the other big gap obviously of, of AI is that it is not capable of, of generating new novel, original thinking, right? I mean that's, and that's simply cuz it was trained to predict the next word based on what Epstein Right. It was designed to write stuff like what has come before. So by definition it's not gonna be appropriate for your thought leadership article. Right. Um, yeah. So, but again, the factual accuracy is just the biggest one because that's brand risk. That's, you know, misinformation, that's, there's whole Yes. Can of worms
Dani Buckley: (13:16)
There. Yeah. We've been doing a lot of testing on our own here at LeadG2 and we've definitely seen some like things being written that are, like you said, completely factually incorrect and you gotta make sure you have the up the right person reviewing this stuff that can catch it. Um, and it's really important . Um, we've seen some people publishing things that aren't factually and then we're pointing them out and, and so that's a big one. Um, and I like that you mentioned the, the, the kind of, how, how new is the information that you're asking them to write about. Right. You know, I, I was reading an article that was talking about make sure it's like, like, I don't know what their rule of thumb was. Their recommendation was like nothing that is like just come out like today, like a current trend that just was announced or something because there's just not enough there. Right. There's not enough intelligence to back it up. Um, this is more for stuff that has like the data, the, the information available some time has passed is right. Is that what you're saying?
Megan Skalbeck: (14:08)
Yeah, absolutely. Because again, remembering that like, this was trained on existing content on the internet, if something super new, it hasn't read anything about it, it's not gonna be able to speak intelligently about it. Um, it could, you know, potentially summarize a new story that you give it. Right. It could kind of learn that way, but it's not, if you just ask it for a new article on some new topic, some new, you know, technology that's come out, it, it won't be able to do
Dani Buckley: (14:30)
That. Yeah. Got it. So we touched on like shortcomings and stuff. Is there any like big mistakes that you're seeing folks using AI for right now that, that you wanna point out? ?
Megan Skalbeck: (14:39)
Yeah.
Dani Buckley: (14:40)
Um, well
Megan Skalbeck: (14:41)
The biggest, I mean, I guess the biggest general mistake I see is, is treating it as this black and white issue, right? I see so many people who either think AI is this free silver bullet that's gonna solve all my needs for free, or AI is uni universally bad, I'm not gonna touch it with a 10 foot pole. Right? Neither of those views in, in my mind is correct. There are times to use it. There are times not to, um, for us, for example, even within a single client's content, there are types of content where our hybrid approach is appropriate. And there are types where actually no, we still need it to be only our human writers, so, you know, within a single person's, you know, workflow or that there could be different parts that are appropriate for ai, different parts that aren't. Um, but I, again, I think every, every single person probably has some use cases where AI can help them out. Um, but nobody can be using it for everything. Yeah. And so it's, there's a lot more middle ground there and I think it's easy for people to, um, take a black or white
Dani Buckley: (15:38)
Approach. I love that. I'm glad you said that because yeah, that's what we're seeing with our clients even, it's like, no, we don't want to, we have no, like, this is scary or this is like too risky or whatever, or why do we need anybody, we can just do everything through ai. It's like there's there's somewhere in the middle . Yep. Um, cool. So I know you're really passionate about this stuff, so tell me or tell us, what are you just like most excited about right now? Just as a chance for you just to like, yeah, whatever, whatever is getting you really pumped up about ai.
Megan Skalbeck: (16:08)
Well, the first thing that's so cool is just how quickly it's changing, right? Yeah. I mean, and that makes, means like probably in a week I'll be excited about something that at this point didn't even exist. Yeah. You know, we, we surveyed marketers last winter and already the results have, you know, are are pretty out of date, right? That was pre chat G p t, um, even with chat G B T now, Bing has already advanced that a lot by being connected to the web. Um, so the pace of change is really cool. One somewhat nerdy problem that is cool and fascinating to me is just the idea that, um, you know, it's trained on existing content from the internet, we're actually gonna run into a problem where we run out of content to train our models on, which is a wild thought, right? If you think about how much content is out there, like that is gonna be one of our biggest limitations in like new and improved AI models, is just not having enough content to train them on.
Megan Skalbeck: (17:04)
And we don't wanna train them on AI content, right? Like, yeah, that would just kind of be turn into this game of telephone where we get further and further from the original, like human writing content. Um, but I think that's gonna be cool. Cause I think that's gonna probably require some, like, changes to the architecture of the models and how we actually build them out in order to like get around that limitation of like, we just don't have enough data. Um, so yeah, on the tech engineering side, that's just a cool, a cool problem to me. Okay.
Dani Buckley: (17:32)
I'm gonna throw in a question that is pretty techy, but I'm curious, so maybe there's someone else listening that's curious. So, okay, that is a question I have. So if AI is using, you know, information intelligence, data content on the internet, at what point do we know that like, yeah, it is an AI content that may be incorrect, that's feeding ai. Like how do we know, how does it not become this like, loop is there Yes. Safe. Yeah. Like what is that
Megan Skalbeck: (17:56)
? Yeah. So that is why, um, AI detection has really gained the prominence and that's why you're, you've probably seen some tools out there around that. Um, I am publishing an article today actually on this topic, on like, uh, tools that can detect when something has been created by AI. Um, and so that's important for a lot of people, right? For us in content creation, we wanna know that we're publishing something that was, you know, written by a human. Um, we think maybe Google, maybe Google is gonna potentially care at some point and penalize, uh, you know, AI generated content down the line and rankings. Yeah. Um, so there's, there's kind of those immediate business reasons, but there's also this, this task of keeping AI generated content out of future training sets. And so that's why like Open ai, uh, recently released their AI detection tool. And that's why I think they've been working really hard on that is so that, you know, when they train future models, they can run this AI detection tool on the content they're giving it and make sure that they're not feeding it something that is produced by ai.
Dani Buckley: (18:56)
Got it. Got it. Very interesting. I could sit and talk about this all day, but we won't . Um, so just to close this out, is there anything else that we haven't touched on that you wanna be sure that, um, you mentioned or address to our audience? Uh, any closing thoughts on this?
Megan Skalbeck: (19:10)
Yeah, I will just say, um, obviously I'm super excited about AI and think people should try it with, you know, try it out with, with all the caveats of like, yeah, you need to be reviewing everything. I also wanna just point out though that people are slapping AI on everything nowadays. Um, so, um, and I know, cause I've, again, I've been looking at a lot of these tools and experimenting with them, and the number of times when I go to a website and try to find anything in their information about like the actual tech behind it or, or what they're doing with the model or anything like that, it's just nothing. Um, and so it's easy to, again, just to say something's AI when it's really just, you know, maybe you've just put an interface on, you know, basically on top of Jasper or, or something like that, or you're just, or maybe you're just using the algorithm and calling it ai.
Megan Skalbeck: (19:57)
Um, look for the, if you, you know, if you want to dig into these tools, look for the people who are actually talking about the tech and the experiments that they've done and what they're trying with it and what they're learning. Nobody has all the answers to this, right? And nobody's, you know, everyone's iterating as we go and, and that, but, um, do just be mindful of like what tools you're using and, and if they're actually, um, if it's real AI and if they're really doing something cool with it, or if again, they're just kind of flapping that on their, their website.
Dani Buckley: (20:24)
Yeah. So I love that. Look, look for the, look for the real deal . Be aware of what we're using and doing, and yeah, just know your stuff, do some research. I love that. That's a good tip, good reminder. Um, great. Well, Megan, thank you so much. Uh, it was so nice to get to talk with you more and thank you for joining. Yes. Love having you. Um, and I, I'm, we're gonna try to add that blog post that you just shared, that you're, you're publishing, we'll probably no notes for those listening. Um, and we'll also have Megan's contact information in the show notes as well as mine. Um, always love hearing from folks if you have questions. And, um, thank you everyone for joining today. Looking forward to the next episode of Sell Smarter, sell Faster. Until then, happy selling.
Megan Skalbeck: (21:07)
Thanks
Dani Buckley: (21:07)
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