Almost Timely News, September 24, 2023: AI and the Rise of the Ideapreneur

Almost Timely News: AI and the Rise of the Ideapreneur (2023-09-24) :: View in Browser

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Almost Timely News: AI and the Rise of the Ideapreneur

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What’s On My Mind: AI and the Rise of the Ideapreneur

This week, let’s talk about the rise of the ideapreneur. I can hear you saying now, “the rise of the what?” And yes, it’s a word I made up. I suppose you could call it a neologism if you want to be specific, but it really just is a little silly – and that’s kind of the point.

What is an ideapreneur? It’s someone who undertakes ideas. To get all word nerd, the original term, entrepreneur, means to undertake an enterprise, from Latin’s entre and prendre. Instead of undertaking enterprises, we’re talking about undertaking ideas.

Okay, and…? Here’s why this has been on my mind all week. It’s about – no surprise – generative artificial intelligence, generative AI. The technology is no longer the differentiator for generative AI; nearly everyone has access to some form of generative AI, be it big public models like GPT-4 and PaLM 2, open source models like the LLaMa family, and all the interfaces we know. ChatGPT, Google Bard, Google SGE, Claude, Microsoft Bing, and this week Microsoft’s announcements that Office Chat and Windows Chat will be ubiquituous in all its upcoming products. We also saw Bard and Bard Extensions launch this week which puts generative AI in your inbox, Google Docs, YouTube, and more.

So technology and access to it is no longer a competitive advantage in any way. And by competitive advantage, I don’t just mean at the corporate level, I mean at the personal level. I’ve said forever that AI won’t take your job. A person skilled with AI will take the jobs – plural – of people who aren’t skilled with AI. When we’re talking about competitive advantage, that’s specifically what I’m referring to, your ability to be competitive in the work force.

What about prompt engineering? There are definitely tips and tricks to prompt engineering that make it work better, faster, but the reality is that if you’re willing to have a conversation – a real conversation, like you’d have with an intern – with generative AI, you’ll get to the output you need sooner or later. That’s not to say you should disregard prompt engineering entirely, but it’s becoming less and less important over time as the AI models get better and better at understanding us.

For example, with Stable Diffusion, you used to have to write these arcane prompts filled with weird buzzwords and put subjects, objects, and descriptors in a very specific order to get it to generate what you want. With the newest version of its model, Stable Diffusion XL, you now can use much more natural sounding prompts, like “A photo of a black and white pit bull wearing eyeglasses, sitting at a desk with a cup of coffee and typing on a MacBook Pro in an open office with the morning sun”.

Dog and Stable Diffusion

Prompt engineering isn’t your competitive advantage, either. Even those who are skilled at prompt engineering have to acknowledge what a rapidly moving target it is. Prompts that worked yesterday deliver sub-optimal results today. Prompts that work in one environment don’t work as well in other environments. It’s an important skill, but it’s a skill that will be ubiquitous very shortly, in the same way that spreadsheet skills are ubiquitous today (comparatively).

Okay, so access to tech won’t differentiate you and prompt engineering won’t differentiate you. What will? Your ideas – hence why I’m talking about the ideapreneur. The quality of your ideas will differentiate you in the age of generative AI more than any other skill, because the limitation of bringing ideas to life – at least in knowledge work for now – is no longer skill.

Machines are capable of writing. They are capable of composing songs, creating images and motion pictures, analyzing maps and spreadsheets, mimicking empathy in conversation… the list goes on and on of what machines can do, growing daily. But they still have no agency. They still have no innate sense of self, no self motivation, no ability to simply decide to do something. A generative AI system like ChatGPT just sits there waiting for you to talk to it before it can take any kind of action.

If you have no ideas, if you have no prompts, nothing to say, then it doesn’t either. There’s no output of note or worth. Generative AI is no better than a word processor you never type words in, or a spreadsheet you never enter any data into.

Suppose you have ideas, but they’re just bad. Generative AI follows the eternal axiom of computer science: garbage in, garbage out. If you ask it to write a blog post about B2B marketing with no other input, you’re going to get a super generic, boring, unimaginative, non-creative output because your input was equally generic and boring. If you ask it to write a blog post with a huge list of specifics and creative ideas, it’ll generate something that is equally specific and creative.

Why? Under the hood, large language models and diffusers are simply libraries of probability, and creativity is in many ways data that is low probability. Think about every corporate brainstorming session you’ve ever been to. Most of them sucked, didn’t they? “Innovate something!” people are told with no other guidance, and what teams often come up with is the opposite of innovative. Why? Because in a situation like that, you’re just drawing on your own libraries of probability – and in a group setting, it tends to be a monoculture.

What makes an ideapreneur different? The ideapreneur is someone who has learned to harness and control their creativity, to generate better ideas that they can then ask machines to bring to life. That’s the differentiating skill, the X factor – your ideas beget your machines’ output, and the better your ideas are, the better your machines’ output is.

This then begs the eternal question, okay, how do I become more creative? How do I generate more and better ideas, so that I can be an ideapreneur? The answer to this question is fairly straightforward and simple (but NOT easy, simple and easy are not the same thing): you have to know how creativity works.

Creativity is strongly bound to memory, to our memories, which makes logical sense. We can’t invent or create things we don’t know about. If I asked you to create a modern day variation of a Kalahari kirikata, and you have no knowledge or memory of what that is, you can’t do anything creative with the task. Your brain has nothing to draw from. If you know what a kirikata is, if you can remember it, then you can start the process of creativity.

Thus, if we have more to remember, if we have more experiences to draw from, we have the capability for greater creativity. Again, this mirrors our machines (or more accurately, our machines mirror us). A large language model trained on a small number of tokens and parameters will be less capable than a model trained on a large number of tokens and parameters.

Not all memories are created equal. Quick, what did you have for lunch on Tuesday, May 24, 2022? I have no idea. You probably don’t, either – unless something happened on that day’s lunch that was incredibly memorable. Yet if you ask me what I had for lunch on a certain day in May of 2001, I can tell you exactly what was for lunch, because it was the lunch served at my wedding.

Part of memory is emotion; the more emotional the memory in any capacity, the better we remember it. And the better we remember it, the more likely it is to influence our future creativity, because those memories pop to the surface faster.

The second aspect of idea generation is disruption. We are creatures of habit, and as such, we tune out a tremendous amount of information. We simply no longer see or hear things that are customary and familiar. We do remember anomalies. We do remember the atypical, especially if there’s also emotion involved. It’s one of the reasons vacations are so important – they break us out of routine and change our level of perception.

In 2022, a meta-analysis of creativity by Courtney Gerver and her team at Pennsylvania State University found that semantic memory – memory that associates concepts and meaning – was most strongly associated with creativity. Again, this is no surprise – if you understand concepts and how they link together, it makes it easier to be more creative, to generate more ideas.

For example, if you’ve ever felt like the drive to get somewhere unfamiliar takes longer than the drive to get back (even when the driving time is identical), it’s because your cognitive perceptions on the way there are heightened. You’re capturing a lot more information because you’re not sure what is and isn’t important. On the way back, you’re storing much less because you’ve been that way at least once, and you’re headed back to familiar surroundings. You’ve linked your new understanding with your existing understanding in your semantic memory of where you are.

So when it comes to being an ideapreneur, you have to take control of your idea generation processes. You have to put yourself in different circumstances, break up routine, and subject yourself to heightened emotional states so that you’re capturing more information, associating it with existing ideas, and making it available for creation.

Generative AI systems have access to massive amounts of information about humanity, like the world’s largest library of ideas and concepts. If we want these systems to generate creative, inspiring, and differentiating outputs, we have to be the ones to feed them the ideas we want brought to life. Like a mirror, they can only reflect what is put in front of them. The faster you become the idea powerhouse, the ideapreneur, in your organization, in your collective of friends and loved ones, in your life, the more powerful an ally generative AI will be.

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ICYMI: In Case You Missed it

Besides the newly-refreshed Google Analytics 4 course I’m relentlessly promoting (sorry not sorry), I recommend the piece on why open source large language models matter. It’s critically important to understand the implications on how AI can and cannot be regulated.

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Folks who post jobs in the free Analytics for Marketers Slack community may have those jobs shared here, too. If you’re looking for work, check out these recent open positions, and check out the Slack group for the comprehensive list.

What I’m Reading: Your Stuff

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Events I’ll Be At

Here’s where I’m speaking and attending. Say hi if you’re at an event also:

  • ISBM, Chicago, September 2023
  • Content Marketing World, DC, September 2023
  • Marketing Analytics and Data Science, DC, September 2023
  • Content Jam, Chicago, October 2023
  • MarketingProfs B2B Forum, Boston, October 2023
  • AImpact, Online, November 2023
  • Social Media Marketing World, San Diego, February 2024

Events marked with a physical location may become virtual if conditions and safety warrant it.

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Required Disclosures

Events with links have purchased sponsorships in this newsletter and as a result, I receive direct financial compensation for promoting them.

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My company, Trust Insights, maintains business partnerships with companies including, but not limited to, IBM, Cisco Systems, Amazon, Talkwalker, MarketingProfs, MarketMuse, Agorapulse, Hubspot, Informa, Demandbase, The Marketing AI Institute, and others. While links shared from partners are not explicit endorsements, nor do they directly financially benefit Trust Insights, a commercial relationship exists for which Trust Insights may receive indirect financial benefit, and thus I may receive indirect financial benefit from them as well.

Thank You

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See you next week,

Christopher S. Penn


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