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Will AI Make Marketers Dumber? (Thinks Out Loud Episode 419)

Picture of young worker tutored by robot to demonstrate the question: Will AI make marketers dumber?

AI has the potential to make our teams faster and more effective. But will this power also make marketers dumber? Will it hurt their ability to learn and to grow?

Turns out the answer depends entirely on how we use it. We learn by doing, by thinking, and, yes, by sometimes failing. Senior marketing leaders — and business professional of all kinds — need to think about how they and their teams are using AI to ensure we help our teams get smarter while they’re also getting faster. Because, otherwise, their effectiveness will only exist for a short while.

How can you use AI to make your marketing team smarter? How can you help them grown and learn and build expertise? That’s what this episode of the Thinks Out Loud podcast is all about. Want to learn more? Here are the show notes for you.

Will AI Make Marketers Dumber? (Thinks Out Loud Episode 419) — Headlines and Show Notes

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You might also enjoy this webinar I recently participated in with Miles Partnership that looked at "The Power of Generative AI and ChatGPT: What It Means for Tourism & Hospitality" here:

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Recorded using a Shure SM7B Vocal Dynamic Microphone and a Focusrite Scarlett 4i4 (3rd Gen) USB Audio Interface into Logic Pro X for the Mac.

Running time: 18m 17s

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Transcript: Will AI Make Marketers Dumber?

Well, hello again, everyone, and welcome back to Thinks Out Loud, your source for all the digital expertise your business needs. This is episode 419 of The Big Show, and thank you so much for tuning in. I very much appreciate it. I think we have a really cool show for you today. I, I’m really happy about what we’re talking about today because it’s something that is very, very important to me.

And I recognize that this is primarily a marketing and e commerce and digital strategy podcast. That’s most of what I talk about here. At the same time, I’ve had a weird career. I have not had a traditional career path, and I suspect I’m not alone. We all collect a ton of experiences over the course of our careers.

We’re much more than just our job titles. While I’ve worked as a marketer for more than 25 years, I also have a fairly broad background in training and education. I am an educator. I have taught at Rutgers Business School Executive Education for almost 11 years. And I also taught at New York University’s School of Continuing and Professional Studies for several years.

I’ve worked as a trainer in private sessions and for other companies for more than 25 years. I even have a certification in instructional design, though to be fair, I haven’t kept that up because it’s not where I spend most of my time these days. The reason I do that work, though, on top of the other things that I do, is that I care deeply about the future of business, Of our community, and frankly of our world, our businesses and our community and our world only gets better if the people who follow us are smarter, more thoughtful, kinder than we are.

We all benefit in the long run by a smarter, more thoughtful, kinder world. Group of people. That is one of my most core beliefs. I, I think it’s just one of the most critical things we can do is prepare our teams and our people for the future. And that brings us to artificial intelligence. I’ve long said that AI won’t take our jobs, but smart people who use AI might.

The question is, will AI make us smarter, or will it make us dumber? The answer appears to be almost entirely within our control. I feel pretty strongly about that. And one of the things that leads me in this direction is that I’ve been reading Wharton professor Ethan Mollick’s outstanding new book, Co Intelligence, Living and Working with AI.

You should read it. It’s very much worth your time. One chapter in the book in particular caught my eye and felt a little thin to me. Not because it’s bad, not because I think he’s wrong, but because I think it’s early. The chapter is called AI as a Coach. And Malek opens the chapter by saying, The biggest danger to our educational system posed by AI is not its destruction of homework, but But rather, it’s undermining of the hidden system of apprenticeship that comes after formal education.

He goes on to say, For most professional workers, leaving school for the workforce marks the beginning of their practical education, not the end. Education is followed by years of on the job training, which can range from organized training programs to a few years of late nights and angry bosses yelling at you about menial tasks.

Many of you have lived through this, right? I know I have. You know, he says, people have traditionally gained experience by starting at the bottom. The carpenter’s apprentice, the intern at a magazine, the medical resident. These are usually pretty horrible jobs, but they serve a purpose. Only by learning from more experienced experts in a field and trying and failing under their tutelage, Do amateurs become experts?

He then lays out the problem. He said as much as an intern or a first year lawyer doesn’t like being yelled at for doing a bad job, their boss usually would rather just see the job done fast than deal with the emotions and errors of a real human being. So they will do it themselves with AI, which, if not yet the equivalent of a senior professional in many tasks, is often better than a new trainee.

He goes on to offer some evidence that this is already occurring, and that points to the risk. As he writes in the book, he says, Even as experts become the only people who can effectively check the work of ever more capable AIs, we are in danger of stopping the pipeline that creates experts. I share Mollick’s concern that that could be a big problem for your business in the longer run.

We’ve seen how other technologies have Hurt the time it takes for people to get better at what they do in some ways. And I’ll explain what I mean by that in a moment. Obviously, things like YouTube and things like your ability to text your boss or text someone more senior are enormous benefits. A clear case where the value of the ship outweighs the risk of the shipwreck.

What’s also true is that some of the opportunities, some of the risk behind those harder learnings is going away. I remember having to make a number of tough calls when my boss was traveling in the era before cell phones. She couldn’t be reached because she was on a flight or in a meeting overseas, or rarely given how hard she worked, on a beach.

But, but in those cases, something might come up that forced me to make decisions. As the only available, and I’m going to use this term loosely, expert, sometimes those decisions worked out great, and I got a feather in my cap, you know, yay me. Occasionally those decisions worked out less well, and I got direct and, you know, frequently less pleasant.

Feedback. Right? I was exactly like Ethan Mollick’s example of the apprentice carpenter or the magazine intern or the medical resident getting yelled at by angry bosses. Happily, this didn’t happen very often, but that doesn’t mean it didn’t happen. And in both cases, I learned. I learned what worked, I learned what didn’t work, and I got better at what I did.

What’s potentially different with AI. is that younger workers might not get the same opportunities. If you, the more senior person, just turned to AI to do the work, you might be killing the pipeline of smart people who could help you in the future. Now the thing is, I said I think this is pretty much within our control though.

We can fix this. We need to give our teams the opportunity to fail, because that’s how you learn. I mentioned I had a weird career. I was a music major. I did not go to school initially for business. I didn’t go to school initially for marketing. I went to school for music, music management, the business of music.

But I wanted to be a musician. I wanted to be a record producer. And one of the things I learned from that activity was that there’s a way to practice. There’s a way to improve. Uh, Professor Stephen Bryant, my, my old teacher, used to say, Practice doesn’t make perfect. Perfect practice makes perfect. This is such an important idea to me that I did an entire podcast episode about this, uh, episode 217 a few years ago.

Malek talks about this same reality in his book, too. Now, I want to be really clear. Perfect practice doesn’t mean you get it right every time. It’s not perfect every time. After all, if you could do it perfectly every time, you wouldn’t need practice. Instead, it’s about the process you follow. You timebox your practice session to work on a specific piece of music.

This is the music version. Obviously, you can see the business implications here. But you play your piece, and when you’ve finished, you take note of what went well and where you need to improve. Then you play it again, paying attention in particular to address the issues you identified during your first practice performance.

Afterwards, you again note what went well and what still needs work, and then you do it again. And again, and again, and so on. And you periodically meet with your teacher, who then reviews and gives you even more feedback on what’s going well and what’s not going so well. As it happens, AI can help with this.

As is so often the case, though, it’s not an either or situation. It’s a both and situation. One on one tutoring is proven to help people learn better and faster. Again, it’s the perfect practice situation. A tutor can point out where your mistakes are and offer guidance on how to improve them while they’re happening.

They have more expertise and can better recognize any mistakes than you could. Because you’re not an expert, right? The AI can work as a tutor, too. They can tell you when you’re doing a good job and when you’re not. What you then need to do, though, is have your team member meet with you and review what they’ve learned so that they are also getting true expert guidance and oversight.

As it happens, Malek has a chapter called AI as a Tutor in his book that talks about how this could work. The key point here, though, is that you need to commit to having your team learn hard lessons and get it wrong sometimes. The ideas behind test and learn, the ideas behind methodologies, take it as a given that not every idea pans out, that sometimes you fail.

So here’s an idea of what you could do. You, your team could use AI to brainstorm ideas. You could assign them tasks that you might actually have an AI do, but let them use AI. They’ll get it done faster. They also should exercise judgment and provide you with a recommendation based on what the AI offered.

They shouldn’t just come back with three or four options and say, you pick. They say, this is the one I would pick, which idea did the AI generate that they thought was best or that they worked with to hone into something that’s really good? Then make your team show their work. How did they get the answer?

What other options did they consider? Why did they think the one they’ve offered was the best one? That’s how they’ll learn. This becomes a both and. You’re using AI to a degree, you’re letting the people learn, and you’re also providing your expert guidance and oversight. We’ve all had weird careers. I started by saying I had a weird career.

Our younger marketers and salespeople and other business professionals will too. Preventing younger team members from using AI is a little bit like preventing kids from using calculators or computers. We want our younger workers to learn how to use these tools. I mean, you’re not going to have them revert to using an abacus or a typewriter, are you?

That’s just ridiculous. They need to learn how to use the tools that exist so they’re prepared to use them as they go forward. What’s also true is that they need to improve their critical thinking. They need to learn to become experts for themselves. And AI can help with that. It can help them improve.

It can help them hone their expertise. But only if, A, you provide feedback on their work and the specific reasoning they used that led to the choices that they did. And B, that you give them the opportunity to fail. You provide them the opportunity to get it wrong so that they can learn. By the way, they’re going to surprise you.

Most times they’re going to get it right. Because you hire smart people, right? But when they do, you’re there to provide additional guidance beyond what they got from the AI. Anything else, anything less, ensures that the education crisis Ethan Mollick talks about occurs. That the expertise crisis occurs.

And that’s bad for your business in the long run. I’ve said many times on this show that AI won’t steal your job. But smart people who use AI might. Turns out, the more I thought about it, maybe I was wrong. Because if you don’t let your team become smart people, AI will take your job, and your customers, and your business.

The choice is yours. I can’t wait to hear where you go with it.

Show Wrap-Up and Credits

Now, looking at the clock on the wall, we are out of time for this week.

And I want to remind you again that you can find the show notes for this episode. As well as an archive of all past episodes by going to Again, that’s Just look for episode 419.

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Show Outro

Finally, and I know I say this a lot, I want you to know how thrilled I am that you keep listening to what we do here. It means so much to me. You are the reason we do this show.

You’re the reason that Thinks Out Loud happens every single week. So please, keep your messages coming on LinkedIn. Keep hitting me up on Twitter, sending things via email. I love getting a chance to talk with you, to hear what’s going on in your world, and to learn how we can do a better job building on the types of content and community and information and insights that work for you and work for your business.

So with all that said, I hope you have a fantastic rest of your day, I hope you have a wonderful week ahead, and I will look forward to speaking with you here on Thinks Out Loud next time. Until then, please be well, be safe, and as always, take care, everybody.

Tim Peter is the founder and president of Tim Peter & Associates. You can learn more about our company's strategy and digital marketing consulting services here or about Tim here.

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