Augmenting Humans with AI: A Learning Professional’s Perspective
Augmenting humans with AI is becoming the way of the world. Over the next few blog posts (and an upcoming webinar), I’ll be diving into how AI can be integrated into learning—specifically within learning transfer.
This topic feels incredibly relevant right now. It’s timely, it’s pressing, and—if I’m honest—some good friends in Europe insisted I needed to talk about it. But beyond their encouragement, a personal experience recently pushed me to explore this idea further.
The Strange Case of the AI-Generated Podcast
I have a bit of an unusual media habit. I don’t subscribe to any paid TV services, but I do have a YouTube subscription—and I spend a lot of time learning and enjoying content there.
A few weeks ago, there was a lot of buzz around Google NotebookLM—a tool that could generate AI-driven podcasts, seemingly voiced by humans but entirely synthetic. I was intrigued by this breakthrough and its implications.
Then, something unexpected happened.
I clicked on a YouTube video that sounded interesting from a channel I don’t typically follow. As soon as I hit play, I recognized the voices—not as real people, but as AI-generated ones. The video, however, made no mention of this. It was presented as a conversation between two humans.
Cue an emotional rollercoaster.
Was I imagining it? Could these actually be real people? I felt a sense of unease, even betrayal. There was no transparency, and it left me questioning everything I was hearing. But here’s the twist—the content was excellent. The tool was impressive. The learning was solid.
Yet, despite all of that, I wasn’t enjoying the experience.
Why? Because trust was broken. Instead of fully engaging with the content, I was distracted by feelings of distrust, frustration, and even anger at the lack of transparency. It was a powerful lesson as a learning professional.
The Need for Transparency in AI-Augmented Learning
So, where does this leave us when it comes to augmenting humans with AI in learning?
First and foremost, it reinforces the need for transparency. At Coach M, we’re intentional about making sure learners always know when they’re interacting with AI versus a human.
For example:
• A “Rescue” Command – If a learner ever needs human support, they can type “rescue” to be instantly connected to a person.
• Explicit Human Signatures – Any time a human joins a conversation in Coach M, the message always begins with: “Hi, it’s Emma (human) here.”
No guesswork. No ambiguity. Just absolute clarity.
This isn’t just a courtesy—it’s fundamental to maintain trust in learning environments. If learners are distracted by concerns about whom (or what) they’re engaging with, it interferes with their ability to focus on the content itself. And when learning is about transferring knowledge into action, that’s a serious problem.
What’s Next?
In the next few blogs, I’ll be sharing practical strategies for augmenting learning with AI—how we’re doing it, what’s working with our clients, and how we’re embracing this shift in learning design.
If you’re as fascinated by this topic as I am, I’d love to have you along for the journey. Keep an eye out for the upcoming blogs—and if you want to dive deeper, book your spot in our webinar, “Augmenting Learning Teams with AI Coaching”
I can’t wait to share more. See you there!
PS – This blog post was created with the help of ChatGPT. Full transparency. To learn more about how, read about it here.