In today’s episode, I discuss where businesses rely too heavily on AI to generate content. While AI can be helpful, overreliance leads to mediocre, generic content. I explain why detailed prompts and preserving your unique authorial voice are key to creating compelling content with AI. Tune in to learn strategies to leverage AI tools effectively!
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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
In today’s episode, Ashley asks, “Where do you see the biggest overreliance on AI in business today? How can businesses address this issue?” This is a real straightforward question to answer, at least in the context of marketing, which is where I work the most. People are using generative AI to crank out reams of mediocre content. It’s boring. It is dull. It is not special. And that is certainly not what people are hoping for, which is thought leadership content. And the reason for this is that people have a fundamental misunderstanding about how large language models work, right? They assume that these are these magical devices that just make stuff, they’re they are literal machines that just guess the next word, the next sentence, and so on and so forth.
Behind the scenes, when you type in a prompt into a chat GPT or a Claude, or Google Bard, or any of these tools, what it’s doing is it’s looking at those words and saying, “Okay, what is the most mathematically related terms to this pile of words you’ve given me?” There’s actually a feature called top K, which you don’t need to know about because you don’t see it in consumer interfaces. But mathematically on the back end, there’s a number called top K. And this is the top 40 most probable tokens that would be used next in whatever sequence you’re guessing.
That’s what these machines are. They’re probability machines that are guessing, okay, if you if you gave a prompt, like, “write a blog post about b2b marketing,” right? What are the 40 most probable next words that would be associated with a prompt like that? You know, you’re going to get dry, boring, generic content, because this is a dry, boring, generic prompt. You will get mediocrity because you’re asking for the mathematical average of a very small amount of words.
That’s why these tools don’t generate great content, you know, magically. You have to prompt them to do so with very, very detailed prompts. And if you’re writing up a page long blog post, your prompt should probably be about a third of a page, right? If you are writing longer form content, you might have a prompt that is a couple of pages long, and tools like chat GPT and Bard and such are capable of handling longer prompts. But it’s people tend not to do that and not to provide enough data so that these models can come up with something new.
Because remember, we are trying to we’re using these tools to find averages. If you give a small prompt, it’s going to find the average of a very large number of words, right? “Write a blog post about b2b marketing.” That’s a big category. There’s a lot of words in that concept. If you were to say “write a blog post about b2b marketing in the industrial concrete sector with a specific focus on direct mail marketing to key executives in who are high net worth individuals.” You’ve now given many more words and the number of candidates the likely next words are going to be very different mathematically, because you’ve given more data and therefore more probability conditions in the prompt.
You need to have beefy prompts. How do you fix this? It is about educating people and educating your content creators in your company how to best use these tools. One of the best uses for them is not to generate content at all. Which is like, so what do we do? What we’re doing right now, right? I’m talking, I’m I am using my intellect and my skills to to say words, but they are my words, they are unique. And I’m recording this, obviously, that audio can then get transcribed and then put in a tool like Claude or GPT four or Bard, and you give the instructions “fix grammar spelling punctuation and formatting, but don’t rewrite the words, preserve the author’s voice.”
When you do that. Now instead of having to ask it to generate mathematically probable averages, you’re really just asking it to clean things up and remove things that mathematically don’t matter, right, with the ums and the uhs and the you know, ending sentences with “you know,” that sort of thing. You are therefore preserving what is unique. Thought leadership is all about unique, a unique point of view, right, a unique perspective on things.
If you’re using large language models to generate content, you cannot be unique with short, bland prompts. There’s no way to do that. They’re not going to spit out something that is unique because they’re mathematically averaging a lot of stuff you have to have either really detailed prompts, or you have to have your unique voice and your unique content in some other format that you then ask these tools to transform into a blog post, a newsletter, social media posts and things but it preserves your unique point of view, your unique way of using language that is yours alone and that is not other people’s.
That’s how you fix this problem this over reliance on AI. Yes, there’s going to be a lot of generic content, there’s a great ton of generic content out there you and in some ways that’s not a bad thing. Because if you master the use of these tools, and you master the use of these tools to highlight and elevate your unique voice, you’ll be head and shoulders above your competitors that all sound exactly the same. So really good questions and important questions, a question that we need to have more people to be thinking about in the AI industry. Thanks for tuning in. We’ll talk to you next time. If you’d like this video, go ahead and hit that subscribe button.
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