01 / UNDERSTANDING
AI Fluency
What should people understand about AI before they rely on it? Explore capabilities, limitations, prompting, collaboration, and responsible use.
A space for curiosity and discernment
AI &
Learning.
The goal isn't simply to use more AI.
It's to understand the technology, ask better questions, test its claims, and decide when it genuinely helps people learn. This is a place for teaching ideas, thoughtful experiments, and lessons learned along the way.
On the desk
Four directions to explore
These interests overlap, but each raises a different question about the relationship between AI, people, and learning.
02 / JUDGMENT
Critical Thinking & Discernment
How do we know whether an AI response is useful or trustworthy? Examine evidence, errors, bias, uncertainty, and the importance of human accountability.
03 / TEACHING
Learning Experiences
How can AI support practice rather than shortcut understanding? Explore realistic scenarios, guided feedback, reflection, and active learning.
04 / BUILDING
Tools & Experiments
What happens when an idea becomes a working prototype? Try text-based learning assistants, interactive exercises, and small AI-supported applications.
The questions that matter
Keep the human in the learning.
AI can produce an answer quickly. Understanding, evaluating, and applying that answer are different kinds of work. These are the questions I want to keep asking as I experiment.
- Who is doing the thinking? Is the learner making sense of the material, or only accepting an output?
- What would count as evidence? Can a claim be checked against something beyond the AI's confidence?
- What is gained or lost? Does the tool deepen understanding, or remove the very practice the learner needs?
- Who remains responsible? What decisions should stay with the student, instructor, or leader?
Ideas worth testing
Experiments in progress
Possibilities for exploration, not promises of finished tools or scheduled courses.
A text-based learning guide
An AI assistant that asks questions, offers hints, and encourages students to explain their reasoning instead of handing over the answer.
Decision-making scenarios
Short leadership situations in which an AI recommendation must be examined, challenged, and justified.
Learning through play
Small simulations and interactive experiences that make abstract concepts visible and let learners test consequences.
A small thought experiment
A better question for AI
Instead of asking an AI system to explain a concept and stopping there, ask it to help you discover whether you understand it.
See an example prompt
"Help me learn this concept through questions. Start by asking what I already understand. Give me one question at a time, offer hints when needed, and ask me to explain my reasoning. Do not simply give me the final answer. At the end, help me identify what I should verify independently."
What should we evaluate afterward?
Did the questions match the learner's level? Were the hints accurate? Did the learner actually practice the skill? What should an instructor or another trusted source verify?
An evolving workspace
Learn. Experiment. Question. Refine.
Some ideas will become resources. Others will remain useful questions. Both belong here. The purpose of this space is to explore AI without losing sight of the people doing the learning.