Bringing AI literacy directly into schools and community spaces.

The talk is structured as a journey from concrete to conceptual to embodied. Students don't sit through a lecture. They watch a working robot, write a line of real code, and leave with a method.

1. Know your tool. What AI actually is, what large language models really do, and why they sound so confident about things they have no way to know.
2. Promise. Four things AI does better than students would expect, framed honestly: a tireless tutor, a creative partner, a coding teacher, a career amplifier.
3. Pitfalls. Three concerns, including the one almost no school is talking about yet: when the photo, the audio, and the article can all be fabricated for almost nothing, how does anyone know what to trust?
4. The Resilience Toolkit. Four habits, drawn from the book: verification, humility, adaptation, metacognition. Demonstrated with a real classroom example.
5. Where this is all going. The pace of change, the shift from screens to embodied AI, and the careers that will reward the students who learn to think with AI rather than around it.
6. Meet Aiden (and Rose). Live demonstration of a Reachy Mini robot. Students see the robot's personality, written in plain English in a text file, get changed in real time.
7. You can do this too. One line of Python. One real shell command. A short conversation about vibe coding and why it only works if you can read what the AI wrote back.

The talk closes with five takeaways, a brief note for educators, and a direct invitation to apply for the Finley Robotics Scholarship for students in grades nine through eleven.

1. AI is a tool. A really good one. Learn it. Refusing to use AI puts a student behind. Using it badly puts them behind in a different way.
2. It sounds confident. Often it shouldn't. Hallucinations are a feature of how LLMs work, not a bug that gets patched tomorrow. Skepticism is the correct default.
3. Build the four habits: verify, humble, adapt, reflect. Thirty seconds of habit prevents years of being fooled by something that looked right.
4. Don't outsource your thinking. AI can do the writing. It cannot do the thinking. The thinking is the part that grows you.
5. Make stuff. Today's hardest tools are tomorrow's calculators. Every student in the room can build real software now. That was not true five years ago.

Format

• Standard talk. Forty-five minutes plus fifteen to twenty minutes of Q&A and live robot interaction.
• Assembly version. Thirty minutes, condensed for whole-school formats, with Q&A folded into the demonstration.
• Teacher in-service. Sixty to ninety minutes, with the educator's note expanded into a working discussion on assignment redesign and AI literacy across subjects.

Audience

• Best fit: grades seven through twelve. The framework works for younger audiences with light adjustment.
• Audience size: classroom (twenty to thirty), grade level (one hundred to two hundred), or full assembly (up to several hundred).
• In-person preferred. Virtual is supported when distance or budget requires it.

What the host provides

• Projector or large display with HDMI input.
• Wired or wireless microphone for audiences over fifty.
• Reliable internet for the live robot demonstration. A wired connection is preferred when available.
• A table at the front of the room for the robot.

Fees and access

The Initiative offers tiered fee arrangements. Title I schools, under-resourced libraries, and community organizations serving underserved youth are encouraged to inquire regardless of budget; sponsored visits are part of the program's mission. Standard institutional rates apply for schools and organizations with conference or professional development budgets. Travel within metro Atlanta is included; broader travel is reimbursed at actual cost.

One of the slides in Smart Tools, Sharper Minds is written directly to teachers. The summary, for educators considering whether to book:

• Banning AI does not work. Students will use it anyway. The question is not whether they will, but whether they will use it well.
• Detection is real, but not the goal. The deeper win is teaching students why doing the thinking matters, not just catching them when they skip it.
• Redesign assignments, do not just police them. Process portfolios, in-class drafts, oral defense, reflection logs. Work that reveals thinking is work AI cannot fake away.
• Use AI to teach AI literacy. Showing students a confidently wrong AI answer and asking them to break it is one of the most durable lessons in the talk.
• Model the resilience yourself. When you do not know, say so. When you check, say so. When you change your mind, say so. Students are watching.

The educator in-service version of the talk develops these into a working discussion with concrete assignment-redesign exercises.