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The Marketing Architects
The Truth About AI in Marketing with Shelly Palmer
00:35:53
AI won't replace humans. But it will dramatically change how we work. And brands that don't commit to AI will eventually find themselves struggling to keep up with savvy competitors, according to tech expert Shelly Palmer. So what’s really at stake...
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- [00:00]
Shelly Palmer
You will never add a column of numbers faster than Excel will add a column of numbers. Why would you try? You have to separate creativity and execution. And we have to separate the magic of being human from the calculation capability of AI.
- [00:14]
Angela Voss
Marketing Architects.
- [00:16]
Alena Jasper
Hello and welcome to the Marketing Architects, a research first podcast dedicated to answering your toughest marketing questions. I'm Alena Jasper. I run the marketing team here at Marketing Architects. And I. I'm joined by my co hosts, Angela Voss, the CEO of Marketing Architects, and Rob DeMars, the chief product architect of misfits and machines. And we're joined by a guest today, Shelly Palmer. An expert across technology, media and marketing, Shelley is the professor of advanced media and residence at Syracuse University's S.I. newhouse School of Public Communications and the CEO of the Palmer Group, where he advises Fortune 500 companies on emerging technologies, media and marketing. Recognized as one of LinkedIn's top voices in technology, Shelley regularly shares insights on CNN and Good Day New York and runs a very popular daily business blog. He's a best selling author, award winning composer, TV producer and much more. So this conversation today could be wide ranging, but we'll try to keep it focused on advertising and marketing. Welcome, Shelley.
- [01:16]
Shelly Palmer
I think I just need you to say that every time I go anywhere, it's a mouthful.
- [01:20]
Rob DeMars
Now I have to ask a bit more though about the music because I definitely have known you for of your thought leadership that you've done, but the London Symphony Orchestra at Abbey Road Studio, I mean, how cool is that? And as a product of the 80s, I've watched more television than anyone else on this podcast and it sounds like you've done a lot of TV jingles. Give me one. I know, Shelley, give me one.
- [01:44]
Shelly Palmer
I know. Oh, they're gonna be written on my tombstone. But I've worked on things like Meow Mix and, and Seagram's mixers and Burger King and the CBS news theme, msnbc, tnt, AP Radio, going back, did all the music for Spin City, Regis and Kelly, Regis and Kathy Lee, Regis and Regis and everything Kelly and everything, Kelly and Mark. Now I just have a ton of TV show themes on the air and news themes.
- [02:08]
Rob DeMars
So how did you go from this music prodigy to technology prognosticator, if you will?
- [02:16]
Shelly Palmer
I don't even know how I describe myself. Now look, mom and dad, they met at Juilliard. They own music stores, so they were my first music educators. I grew up with parents who owned a half a dozen small retail music stores and a piano shop. And I earned my allowance tuning guitars on Saturdays sometime around When I was, I don't know, maybe 12 years old or so, I got to see my very first ever Moog synthesizer in person. And it was really a lot of money. My father's like, it'll never sell. Like no one's ever going to spend that money on a piece of technology that no one understands. And I started to play this thing and I gotta have it now. When I was about 17 years old, I was walking through Radio Shack and I still have the book. It was 79 cents. It was a book about VCFs, VCAs and VCOs. Voltage, voltage controlled amplifiers, oscillators and filters. And I asked the guy behind the counter if they were the same voltage controlled oscillators, voltage controlled amplifiers and filters that were in my synthesizer. And he had no idea what I was talking about. The reason I wanted to understand it is that these were integrated circuits on the COVID And the synthesizer was all hand wired with printed wiring boards and component parts. There were no integrated circuits in it whatsoever. Fully analog device. And I ended up buying that day about $50 worth of parts. And I took the whole bit of kit the back of the music store where I dumped everything on the bench. And I said to Walter, we're going to computer control the synthesizer. He goes, how? I said, I don't know. I bought a couple books, let's see what we can do. And so that's my technology career in a nutshell. 17 years old, I start to figure out a way to digitize the patches that you'd need to make an analog synthesizer, have a sound and store it so you could get it back without having to like make yourself crazy. Ultimately, my very first patent claims were written around that technology. And over time I was composing pretty regularly. Even as a 17 year old, I was writing music for commercially. As I got into the business and got my degree in film TV production out of nyu. My first job out of school was working for an amazing, unbelievably talented guy named Don Elliott, who was a super famous jazz musician and owned a jingle company. I started working literally playing jobs for him as well as repping his reel. Like you'd go around to agencies, try to get work for him. And then when I got work for him, I was allowed to write a demo and was able to throw in my own, see if I could get any work, which I did. It was kind of fun. I left Don and got my own production company. Now we're in the early 80s. So by 86 we had put the very first ever totally tapeless Recording studio online. And it was really expensive to do, and it took a lot of tech. So the early part of my career, I was blessed to have mechanical problems to solve, but actual real world problems to solve and enough aesthetic understanding of what I was trying to accomplish to. To be able to pursue this in a pretty rigorous way. So by 86, I was lucky to do a lot of really good work for a lot of big agencies. One of the agencies, and I won't mention which, they have their research department, we had a very big control room, and we had really good audio chain. And I had invested in an extremely expensive television monitor. It was a 16x9 cathode ray tube. Now, this is before anyone had a flat screen. We're talking the 80s now. So this was a 16 by 9 format, which everything was 4 by 3 back then. Everything was analog. This was a color correction monitor, a Sony color correction monitor that literally cost $40,000. But if you were an ad agency, the best place in New York City to see your spot finished, to show your client was in control room A at Creative Audio. Like at my place. Because the monitor was the best TV monitor you could buy for money. And the soffit mounted Westlake speakers were the end of days from a sonic perspective. So they'd never sound that way again, we'd never look that way again. So we used to let the agencies come for free to at night to like, have playback parties for the finished spots was just like a thing we did. If we worked on the spot, you could come and play your stuff for your clients. Anyway, there was an argument going on between one of the agency leaders and their research group about some optimization. And I couldn't help but overhear, and I laughed and I said, oh, my God, that's such an easy regression. I don't. What are you guys talking about? And they're like, what? We have enough computational power in the. In the machine room to do that right now. We're doing that a couple thousand times a second to make this work on each of these machines. They're like, what? I was like, yeah, yeah, yeah. No, we could definitely do that. That. It's like, come on, that's silly math. And so we did this media optimization algorithm for them, which I literally coded while they were sitting there. I got them their output and I printed it out for them. And they're like, oh, my God, this is amazing. Like, we need this. It's like, well, you need a computer. I mean, you literally just need a computer. Like, you shouldn't be Doing this on a spreadsheet, you should just code this. It's easier. We became the darling of that whole group because the math is the same math as we were using for the sampling. We were doing regressing lines and like looking for R squared is looking for R squared. It's just not it's right thing. I mean, it is what it is. So anyway, it was really, there was a very funny moment. A bunch of people who were not mathematically gifted talking math in a room filled with people who did math 24 hours a day.
- [07:29]
Angela Voss
Oh my God, you just blew their minds. That's amazing.
- [07:32]
Shelly Palmer
It was just like a different thing. So anyway, that put us into one place that we didn't know we were ever going to be. Because all of a sudden we started getting much deeper into the mathematics and the mechanisms of distributing advertising and marketing materials. And then what really took it over the edge was in right around 2000, I had patented a lot of my tech and the Disney organization decided they wanted some of it. And they, in a very stealthy way, tried to buy it without letting us know it was Disney. And we weren't fooled easily. So that's when my career really changed. Because I've been doing music since I was 4 years old, sort of grown up with it, as I told you. But when Disney came knocking, here was an opportunity to see a patent that I had sort of created in 93, which was it taught this thing called the Open Cable Application Protocol ocap and it basically turned set top boxes and head ends into client server networks and allowed you to do data distribution, interactive television, basically on set top boxes. So Disney had this thing they wanted to call enhanced tv. This ability to do things like play who Wants to Be a Millionaire in sync with the broadcast through your set top box or on your PC. My patent covered all of that. And it was the earliest patent in the space. And they wanted this patent because they didn't really want me to sue them. They wanted to buy the patent. So we made a deal and ultimately I went to consult for them and I couldn't resist. So I closed my production company. I was really, really excited to go consult for the Imagineers and watch my technology get reduced to practice. I thought that was super cool. And so I wrote a book called Television, Disrupted the transition from network to network to tv and started getting on the speaker circuit. And in less than a decade it went from no one knowing what any of this was to fully invented. I've just been enamored with and immersed in all of the tech around advertising and marketing. And we've been using artificial intelligence, what they're calling AI today. We've been using machine learning since the late 70s to do the work that we're doing. Real neural networks, probably for the last 15 years or so, transformer networks, maybe since 2018 or 19. Somewhere in there, everyone thinks AI was invented on November 30, 2022.
- [09:45]
Rob DeMars
Right.
- [09:45]
Shelly Palmer
It really wasn't. It really wasn't. I mean, it's been around a long, long time. So, yeah, that's how I got in the tech side. I got the tech side by doing, which is the way I think you should get into anything in your life. You just do it in so much.
- [09:56]
Rob DeMars
Of what you just talked about there, it almost sounds like you're talking about today. Right. When you think about creativity interweaving with technology and, you know, it's obviously the headlines now. It's how does it get applied in a way that everybody can accept? So, gosh, that's a great story. Thank you for sharing.
- [10:15]
Shelly Palmer
It has the unusual attribute of being the story of my, my journey, but there's so many other ways to have gotten where I got. But everybody always does ask, how did you go from a composer producer to a tech consultant? And the answer is practical application, applied engineering. From theoretical engineering to applied engineering is how you get there.
- [10:34]
Alena Jasper
Well, thank you, Shelley. I think that those stories probably helped make it clear to the listeners that this was not an easy interview to plan for because you have so much expertise and so many things we could talk about. But I do want to kind of focus us on recent marketing news. We try to always root our opinions in data research and what drives business results when we can. And I like to introduce our interviews with a piece of research or an article. And I found one that I really like for you because it's a summary of the talk that you gave at the ANA event that also happens to be where you met Ange. This is an adage article, it's by Brandon Dorer and Jack Neff and it's titled How CMOS Agencies and Consultants are Clashing over AI Usage. They describe your discussion there where you urge brands to take AI adoption seriously or risk falling behind. You explained how AI is transforming, how we search, how we shop and how we advertise. Brands who don't fully commit to AI will soon find themselves margin deprived, struggling to keep up with more savvy competitors. But despite this work you and others do pushing for AI adoption, there's still some skepticism from marketers. Many Agencies say clients are unclear on the AI goals. Some CMOs are concerned about privacy and security, and others just believe we're caught in an AI hype cycle. So there's a lot we could talk about when it comes to AI and marketing. So it wasn't easy for us to pick a place to start, but I wanted to begin here. You were pretty direct in your talk there about the risks for brands who lag in AI adoption. So could you share why you see AI as such a game changer, a big deal for marketers today?
- [12:05]
Shelly Palmer
It's not just marketers. We're in a sociological transition we have not experienced ever in our lifetimes when the written word was invented. There is plenty of writing about how this is going to be terrible for humanity as you will no longer need to use your mind to store things. You'll be forgetful because you can write things down and you people will become stupider because they can write. This was the prevailing wisdom as writing started to happen 5,000 years ago. A couple things are going on right now you have to respect. First of all, in business, productivity is the key driver of economic success. You really don't have a lot of choices about your sale price. You can be the high cost provider if you want. You can be the low cost provider if you think you can be more aggressive. But ultimately the market sets the price you will sell your goods and services for. Markets are funny that way. Where you do have some control is over your margin. If it costs you less to create your goods and services and your margin is greater, then you will profit and you will profit less if it costs you more. And so you have some control over productivity, whereas you have very little control over market pricing. So if you think about what people do for a living in our industry, marketing, research, advertising, production, for the most part, we execute the vision of others. Someone says we're going to make a spot that includes the following things. We need a script. This is our strategy. This is what we're going to do. Let's realize it in the best possible way. And people who are both artists and artisans will get on the project and they will execute. People come in all different flavors at all different prices. If you go through the entirety of the workflow and process that is creating an advertising campaign start to finish, there are dozens, if not hundreds of places where what, forgetting all jargon you could just call super automation would take care of it. Now I can try 25 different things against the target that no human could ever do it that speed or at that Cost. Oh, the blue button doesn't work. Could I replace it with a green button? Does the red button work better? Any level of marketing incrementalism. If you believe that incrementalism is of fundamental value to the marketing business, forget about hyper personalize. You've never been able to channel personalize at a price. You're running the same spot on WE versus USA Network versus CNN versus Fox News Channel because you couldn't afford your non working media budget just didn' allow you to make five commercials. You can only make three and so two will get two networks are getting the same commercial and even though they not quite right, they're the closest one you have. I can bang out something that's spot on now at nowhere low cost and near real time. Am I going to do that? What's the law of diminishing returns versus the incremental benefit? Well, at some point I will hit a law of diminishing returns, but I've got so far to go on incremental opportunity. These kinds of little tiny subtle things in a business like a CPG business where somehow every analyst knows what the margin of your business is against all your competitors. Everybody knows what your non working media budget is and your working media budget is and how you're using it. So if I can get a couple basis points better at everything across the board, I'm going to destroy my competitors. I'm not going to beat them. You have to know that this is now the biggest problem and the pushback we're getting from everybody is that everyone is trying to compare AI to human capabilities. This is so stupid, it's almost unbelievably stupid. AI as it sits today, Generative AI is not human. What it does is it calculates the next best most probable token, whether that's words or pictures, soon to be video, audio. It's the next most probable token. To think of it as words is okay at the most macro level, it's not how it works. But if you think about the next note or the next word or the next sentence, knock yourself out. Whatever mental model works for you, it's taking the average of everything it's ever ingested. Remember, GPT stands for pre trained transformer, General pre trained. So that means you're going to have to post train in some way, which is some fine tuning and possibly some other constraints and some other technologies that you might want to use to constrain the model. But one way or the other, you've got a tool set here that is capable of doing better than average work all of the time. I'm running a factory, and in my factory I need the lowest possible cost for the goods I have to deliver. So if it is acceptable and the audience doesn't hear or know the difference, there is no difference. And. And for anyone to think differently, there's some human arrogance involved. It'll never be this. It's like, you're right, it'll never be that. But 90% of the production things we need to do are resizing that graphic, respecting the type, color, grading. I have to sweeten this, I have to add that. I have to build like I'm doing worky work that a human must do right now. Must do right now. But the machine can do at a level that is close enough, but at almost no cost and nearer at real time. You will never add a column of numbers faster than Excel will add a column of numbers. Why would you try? You have to separate creativity and execution. You have to. And we have to separate the magic of being human from the calculation capability of AI. Human beings are magic. They do magic things. But most of us aren't employed to do magic. Most of us are employed to do others bidding where we're told what to do. And then we are judged on our ability to execute against someone else's vision. And people don't want to be honest about that. They don't need to be honest about it. But people who are honest about it are going to Elena, in no uncertain terms, kick ass and take names.
- [18:06]
Alena Jasper
So I need to recover from that for a second.
- [18:08]
Rob DeMars
So pumped up right now. I mean, forget Tony Robbins, run through a wall.
- [18:13]
Shelly Palmer
It's just I hear this argument so much from people who literally don't know what they're talking about. And I'm telling you, more than half the stuff I wrote in my career, AI is capable of writing. Suno or Udio are capable of writing now. And they're not even good at it yet. Three years from now, two years from now, a year from now, this stuff, if you're not using it, you're going to wonder why you're not using it. It's a fun thing to play with on like Chubbs Baby Wipes, stackable boxes commercial that needs a childlike underscore that is not actually Mickey Mouse to the scenes, but needs to evoke a feeling of blah, blah, blah that the creative director spent three hours thinking about one night and basically just showing you the spot. And you'd have known as someone who does it for a living. But it's like, okay, you had to write me a long brief. That's great. I'm sorry. If you spend $50,000 today to get that underscore. And I loved charging that 30 years ago. Now you should press a button and get that underscore. It's just what it is. Is that terrible for composers? Am I saying something terrible for humans? No, it is what it is. What are you gonna do? You're gonna stop the technology? How?
- [19:17]
Angela Voss
It's not going back in the tube. I think what we're dealing with, it's like someone telling me my daughter's drawing is not beautiful. It's such an emotional topic.
- [19:25]
Shelly Palmer
People have very big feelings about it. They do.
- [19:27]
Angela Voss
You mentioned before, there are currently dozens, if not hundreds of places or opportunities for automation. And early this year, we hear Sam Altman say that 95% marketers use agencies and strategists and creative professionals for. Is going to be done instantly at almost no cost.
- [19:43]
Shelly Palmer
Except he doesn't understand that that's not the part that they pay for.
- [19:47]
Angela Voss
Right?
- [19:47]
Shelly Palmer
He's right, but he's wrong.
- [19:49]
Angela Voss
Totally.
- [19:50]
Shelly Palmer
This is a leadership problem. This is not a technology problem. He's right. The tech is going to do all of that. You know what's not going to happen? There's no CMO that I'm aware of who's going to take responsibility for anything that they can have an agency take responsibility for. Because you can fire an agency, but you get fired when you screw up. I mean, remember Star Trek, the Original series?
- [20:09]
Rob DeMars
Yes, sir.
- [20:10]
Shelly Palmer
Remember Captain Kirk and all the commanders wore gold tunics. And then all the science officers and medical officers wore blue tunics. And security. Right. And engineering wore red tunics. Remember those? Everybody had like the different shirts. Mr. Scott wore a red shirt, but the security guards did too. If you're a security guard and you beam down to the planet and you're not. Mr. Scott, it was a one show contract. The alien was killing you. You were getting killed by the alien. And in fact, there's a wonderful T shirt you can buy that looks like a Star Trek original series tunic. And in Star Trek type, it says expendable on the right on the front. Because that's like everybody. That's the joke of the original series. Star Trek. Okay, they're beaming down. We never heard of these three guys before. They're carrying phasers and they're in red shirts. They're doomed. Something bad's gonna happen. It was like watching a Law and Order. You just knew it was gonna happen anyway. That's exactly how CMOs treat agencies, they're all wearing red shirts. And when something bad happens, the PR agency, the experiential agency, the digital agency, the like, they go into review. It's like oh well, because they're not going to take responsibility. You think because AI exists somebody's going to risk their Christmas bonus or their car payments or their kids private school? Why? Because technology happened? Never. The sociology of this is so stable. The inertia, the bureaucracy is so stable. You would need an entire generation of chief marketing officers to go, I know, I'll do it. Are you kidding me? In what world does that actually like, what planet would you need to. Speaking of Star Trek, would you need to visit for this to be true? Never happening. So yes, Sam, I agree. All the marketing functions will be completely super automatable right by your own tools. Then what? That is not happening. What will happen is we're going to see point solutions happen. We're going to see data come together because brands have some data, but they don't have enough. Agencies have the ability to synthesize and process data that brands don't. So external signals, cultural insights, long term and short term insights. The loneliness epidemic. Okay, what does the brand do to interpret loneliness epidemic data into their workflow and process for their AI? The answer is probably not much. They're buying it from somewhere. Where are they buying it from? Where is it synthesized? What are they doing with short term insights? What do we think is going to happen and how will that impact go down the list of every single thing? You need to go down the list of who's going to amass and accumulate those insights and who's going to wait and score them against decision trees that you'd use for marketing campaigns. Like the agency has a role and they're going to build agentic systems or they'll build point solutions that allow them to do what they do at a much more efficient rate. The headbutt is guaranteed to come in the way that agencies sell to brands because now they sell FTEs full time employees or full time equipment equivalents and they're going to have to sell outcomes or some other, there's got to be some other way of remunerating or, or compensating these relationships because agencies are capable of staging large systems that will be very specialized based on the amount of media they're buying, based on what they've understood about the media they buy, based on efficacy, all the things the brands don't have. Retailers in the retail media will have a fair amount of data that are Unique data sets. And then the brands themselves will have unique data because they know their supply chain, they know it's an inventory, they know what they've sold, which they don't tend to share. So because these data sets are by default separated, you're not going to see one AI system do all of this. You're going to see there's still roles for different agents to do different things and different people are going to be better at keeping those agents current because of their access to the data. That's, to be fair, proprietary. So yeah, a large language model, which I think is a race to the bottom, will speak languages better than anything else. And the reasoning engines may reason, they may get them to reason, but at the end of the day, the unique data sets are the stock and trade. That's where the differentiators come from. And so yes, if you could build a synthetic employee of proctor and gambler of Unilever that literally had every single ounce of this, the these data sets available to it, there's a chance that you could get rid of everybody that had to do with marketing and advertising. But it's unlikely that those data sets will become freely available to all of the models that need it. You still have to post train with some kind of human feedback. Could you teach self supervised learning to assist? Of course you can. You can build dynamic systems, but they're not set it and forget it, you're constantly tuning them. Who is going to do that? You have to understand the way the business works to make a bold statement like Sam made. And it's like anybody who's in the business for more than five minutes starts to laugh and go, man, you just don't know who you're dealing with. Yes, you're right, the tech can do it. But tech has never been the problem. I'm not scared of artificial intelligence, I'm scared of artificial control. So is everybody else. No one wants to be controlled by this nonsense. Nobody.
- [25:11]
Rob DeMars
Is that why people are freaking out as much as they are in terms of just, you know, you see Toys R Us or the cocoa Coca Cola spots and people love to hate on them. And is that just because it's people that aren't early adopters freaking out?
- [25:23]
Shelly Palmer
No. You know, Rob, I, I think that's still human arrogance. I still think that's human beings thinking, oh, a machine is never gonna be as good as us.
- [25:31]
Rob DeMars
Right?
- [25:32]
Shelly Palmer
And again, it's a point of view and I respect it. And people say it to me every day. It's like every day someone tells me well, you're so high on AI, but it's never going to do this, this and this. Like, A, I agree. And B, it doesn't have to for. For it to have a dramatic financial impact on how everybody I know spends their day in business. Like my entire client base, everyone that we work with. It does not need to be much better than it is right now. Data sets need to get better. So workflow and process needs to be like. Things need to be orchestrated and plugged together in ways that they aren't now. Like, if I say to you, let's Google something, you know exactly what I mean. Well, there are no phrases like that in anywhere in the world of AI. But when we get there, when I can say, let's AI something, whatever the hell that's going to mean. And you. And we all know, like, we know it as well as we know what to Google something is. We're going to be in a different place. We're nowhere near that. But when everything is wired together, if it was just as good as it is right now, the economic impact would be stunning. So to compare this to people capability, why People are people, Machines are machines. Yeah.
- [26:35]
Angela Voss
It's just that transition and maybe fear of what's to come, not knowing. But then there's different sides of this debate, right? There's ethical, there's legal. You've got some artists like Imogen Heap telling the world she's going to empower her songs to go make love with other people. She's going to create an AI twin. Then you've got artists that are just absolutely losing their minds over what's going on. And I think you've called this the fight of the year, the fight over IP and copyright. I've heard you favor thinking from fairly trained. You know, what do you think is going to happen here? How do you think the world of copyright and IP are going to change?
- [27:10]
Shelly Palmer
It's going to get adjudicated in the courts. And so it doesn't matter what I think. It matters what the judges who are involved think. Look, it goes this way. AI is trained on everything. So was I. Everything I could hear, everything I could find in the world. But the difference is not in degree, but in scale. And so it's already ingested. Everything ever written about whatever subject you're thinking about, you haven't. No matter what you've read, no matter how well read you are in a subject you know you want to read about the impact of the Weimar Republic on the advent of World War II, okay, it's read everything ever written by everybody on the public Internet and you've read six books on the subject and taken one semester in college about it. In the history of European thought, you think you're a match for the GPT cabal that has existed here. You're not. So this is the problem by itself. What's ethical? Who. Who do you pay and. And, and if so, what gets paid? And the problem is it's not stored. The data is not stored in a way where they can tell you flat out that it's learned from you. Here's something you can do as a test. You ask any of the models, ChatGPT, the paid version, who Shelly Palmer is. It'll tell you. Ask it if it can write like me. There's one or two answers it'll give. Now, depending on which version you're using, it'll either say, while I can't write directly in his style, he writes in the following way and I can write in that style, or it'll just start writing in my style. When it does, depending on the version you have, I can't tell that I didn't write it. Who do I go see about that? Now, I'm not famous, but like, if I was, I'd be pissed. I've written 2.2 million words according to ChatGPT that it's read. I write a blog every single morning, as you know, since 1996, literally five days a week, I write a rant, I write a thought leadership piece on Sundays, now Saturdays, it's a recap of the week. But ultimately I write over 4,000 words every single week, closer to six. And it's read them all. And it can write in my style. Now, for me, I don't think anybody's really going to go do that. But what if you're Michael Crichton's estate? What if you're Aaron Sorkin right now? What if, if you're Michael Lewis? I mean, these guys are alive, they're kicking, they're amazing writers. And when you ask ChatGPT to write like Aaron Sorkin, it kills. It kills it. So who do you go see about that and what would you do to stop it? I don't know the answer to any of those questions and I think the courts will decide. We're not going to get this. The copyright office tried listening sessions and they invited everyone to comment and they, Shira Perlmutter, the copyright registrar, they were really good about asking everybody to come on down and give their opinions. I was asked by Paul Williams to moderate The AI symposium at the ASCAP annual members meeting. And I was basically booed off the stage for telling the truth. Like, nobody wants to hear this. Nobody. It's going to get worse because right now it's doing the simple stuff, which is it's training off of other people's work. But the reasoning engines are going to learn to reason and nobody knows the following. What's going to happen? This is a really hard problem to solve. And people are going to fight this from the core of their souls. They're not. You're going to rip people's bodies apart to get them to give up on this. There's no way in the world anybody gives up on this. Yeah, you're right. Never happening. And so this is going to be a big fight and everyone should prepare for it. There's one line in the Constitution that talks about ip and it's granted to humans, not to machines. So now I can use a machine to infringe on your copyright, but I can't copyright the work product that's infringing. So I just built something that you can sue me for, but what I just built, I can't copyright because the machine did it. Oh, my God. This is a hot mess. And it's going to be a hot mess. Like, I think I can fairly. I could argue both sides of this because I'm on both sides of it. Sure. And it's. And it's terrifying to me because it's not going to end well.
- [31:05]
Alena Jasper
Yeah. Let me, let me move us to a lighter note to end the episode. We appreciate you giving your point of view on that. I know you said you didn't have an answer, but I have questions, Elena.
- [31:13]
Shelly Palmer
I literally don't have. I. I have a billion questions about it. And I have a point of view because I've lived. It's my lived experience. But that doesn't make me more qualified than anybody else to talk about it. It just means I have a deeper point of view and this is going to be a fight, trust me.
- [31:27]
Alena Jasper
Well, to wrap up the show, Shelley, we have kind of a fun question for you. Outside of marketing, what's one world changing task that you're most excited about AI solving or AI helping with in the.
- [31:39]
Shelly Palmer
Future outside of marketing?
- [31:41]
Alena Jasper
Yes.
- [31:41]
Shelly Palmer
I love to debate with it. Love to. It is fabulous to argue with. So you give it a personality. You're acting as Stephen Hawking, and I want to dispute your assertion that Hawking radiation exists, and then you have an argument with it. You are acting as a group of physicists including Marie Curie, Isaac Newton, and Albert Einstein. I want to talk about. And you fill in the blank and this thing will go at you. It is so fun. Like, it's like you invent your own games so you literally can invent any scenario. I did one the other day for somebody that I thought was really fun. I was trying to build a playlist building tool for Spotify. I wrote a prompt that said, you are taking on the Persona of a genre of music known as bebop. Do you know what bebop is? And I said, yes. I said, great, Now I want you to become bebop as a character. And we are going to go listen to jazz in the 1950s and we're going to talk about what this music means and who's like. And all of a sudden, I'm talking literally to the genre of music.
- [32:57]
Angela Voss
That's amazing.
- [32:58]
Shelly Palmer
And we were having so much fun. To me, that kind of nonsense. It's not like a synthetic companion. It's turning this into things that. That can't exist in the world. How could a genre of music be alive and have a personality and talk to you? Except bebop has a point of view musically, and music is a language. So it interpreted what it felt like that would be like as a personality.
- [33:23]
Angela Voss
What's your go to platform to do that on?
- [33:26]
Shelly Palmer
You do it on anything you can do. You don't meta AI. You can do it on. Claude's good at it. GPT4 is good at it. Does almost. Doesn't matter. Each one's slightly different. I play with all of them. There's about 150 foundational models out there. You go to Huggington Face and pretty much get access to all of them. They're all over the place. And each one will do something slightly different. But my favorite thing to do with AI is push its boundaries, to push my boundaries to think of something that literally cannot exist in the universe without this tool. It's easy to apply it to a productivity problem. It's easy to apply it to a thing that you do every day, to anything that's automated. Where you get to have fun with it is where you push this word calculator to calculate words or sounds or art. Doing crazy mashups is my favorite thing to do with this. Take that as far as you can. I want to mash up to William Shakespeare doing Lin Manuel Miranda. Like, I mean, just that kind of thing. To me, that this is the most fun you can have. Stretching your own imagination and having it do the realization for you because it can realize things. It allows you to stretch what is in my mind, a little misty idea that I kind of think I understand to some concrete, real thing I can look at or hear or see and go almost that. Yeah, that's my. That's the funnest part. Like, I love that part.
- [34:47]
Alena Jasper
So cool. That's great. I think we all know what we're going to be doing after this recording. I've got a couple of people in mind that I want to. I want to pit against each other. Shelly, thank you so much for joining us. That was an episode I'm probably going to listen to multiple times, if I'm being honest.
- [35:01]
Rob DeMars
That was a blast.
- [35:02]
Alena Jasper
Yeah. Do you have anything to plug? We'll include your LinkedIn, your newsletter website. Anything else?
- [35:06]
Shelly Palmer
Well, I'd love people to subscribe to the newsletter if they can. That would be great. We do have a course, the free course, generally I. For brand marketers. Anyone can take it. It's about an hour and a half, two hours to get through it. It'll make you a prompt crafting monster. We update that course on a regular basis, so it's the latest stuff. Usually newsletter subscribers. Again, it's free. They'll get opportunities to come to our events and learn what we're doing. So that. That's probably the best to plug. Appreciate it.
- [35:30]
Alena Jasper
Will do. Thank you so much for your time.
- [35:32]
Shelly Palmer
All right, all the very best.
- [35:35]
Alena Jasper
That's it for this episode of the Marketing Architects. We'd like to thank Taylor de Los Reyes for producing the show. You can connect with us on LinkedIn. And if you like the podcast, please leave us a review. Now go forth and build great marketing.
- [35:49]
Angela Voss
Marketing architects.