Shane Lester ChatGPT, Learning Goals

AI Doesn’t Reward Knowing

We're surrounded by advice about which AI tools to learn, which prompts to master, and which skills will remain valuable. Those are useful questions, but I think there's a more important one: What kind of learner do I need to become? In my latest Learning Frames article, "AI Doesn't Reward Knowing. It Rewards Learning," I revisit ideas that have shaped my thinking for years: Carol Dweck's work on growth mindset and learning goals, and Judson Brewer's research on curiosity and behavior change. AI gives those ideas new urgency. The tools we're mastering today will change. The workflows will change. The skills organizations value will change. Trying to permanently "know enough" may be the wrong strategy for a world moving this quickly. The third part of the AI Adoption Learning Frame is Stance, which asks: How will I intentionally engage with AI? My answer begins with curiosity. Not resisting every change. Not blindly embracing every new tool. And not using AI merely to appear more productive. Instead, using it as an opportunity to learn, experiment, challenge what we think we know, and continually become more capable. Knowledge matters. But in an age of accelerating change, the ability to keep learning may matter even more.

Shane Lester ChatGPT, learing

Humans Change When AI Enters the Room

We spend enormous amounts of time asking whether AI is accurate, safe, capable, or ready for deployment. I think we're missing another important question: What happens to human judgment when AI enters the room? A 2023 study involving radiologists provides a fascinating example. When researchers intentionally introduced incorrect AI recommendations, clinicians sometimes moved away from decisions they had previously made correctly. Even more interesting, changes in how the AI recommendation was presented influenced their behavior. That's not simply an algorithm problem. It's a human factors problem. In my new article, "Humans Change When AI Enters the Room: Preserving Human Agency in the Age of AI," I use the study to explore Sight, the second part of the AI Adoption Learning Frame. Sight asks: What is actually changing? Sometimes the answer isn't merely the technology. It's us: our attention, confidence, assumptions, willingness to disagree, and ultimately our judgment. If we're going to intentionally adapt to AI, I believe learning to notice those changes will be just as important as learning how to use the technology.

Shane Lester ChatGPT, learing, learning how to learn, Uncategorized

C:\HUMAN\RUN.EXE

Every week there's another article about AI. New tools. New models. New prompts. New predictions. But I think we're missing the most important conversation. As AI changes what it means to work, how do we remain fully human? This article introduces Anchor, the first step of the AI Adoption Learning Frame—a framework designed not to teach people how to use AI, but how to intentionally adapt to it without outsourcing the very qualities that make us human. If you've ever wondered where human value fits in an AI-powered future, this article is for you.