In this short article, I want to explain how and why I let people know about my usage of AI for the content that they are reading or watching from me in my new Digital Brain.

What's my digital brain?

It's now roughly 10 years since I wrote and created content focused on learning Service Design. This content is spread out in multiple books, templates, articles, etc.

A good friend of mine told me one day:

"It feels as if you're trying to create the Bible of Service Design"

In fact, in some way, that's not totally wrong. I try to learn as much about Service Design as possible and then share it.

But one of the big problems that limits me in reaching this goal of having a library of all things Service Design is that my content is spread around too many formats, and there is not one way to search through all of it easily.

So, over the last months, I've been prototyping several ways to get there, and I've finally decided to go with one format. A knowledge base specialized on Service Design with a powerful search feature.

See the related articles about this experiment

• Why I’m migrating my content to a knowledge base built with Intercom

• A short review of SiteGPT

• Ask AI: Why I'm trying to create a specialized AI in Service Design

• Early exploration of 8 apps to create a specialized Service Design ChatGPT tool

• Why I re-committed to Podia for the next few years

Why an AI label?

Today, AI is another tool many of us use to create content. But as it's pretty new, there are a lot of questions that come with it. So instead of using it without letting people know, I now try to let people know when I'm using AI. And if it's the case, I also explain what tools I've used and how.

Inspired by the website ai-label.org I'm categorizing my use of AI as follows:

• Made with AI: When something is totally made with AI

• Assisted by AI: When I use AI to help me in certain tasks

• No AI used: When this is the case, I don't put any label

How does this AI label look like?

What's the goal of this AI label?

Sure, having that label is a good transparency practice. Especially as today, there are groups of people who really have a problem with stuff that is made with AI.

But for me, the more important aspect is to offer my readers a look at the backstage of how my service is built and let them discover the tools I use. And maybe this motivates them to say to themselves:

"Oh after all it doesn't seem so complicated to share your knowledge, I'll do that too! Plus now I have a tool that helps me to do so!"