AI Literacy for the Rest of Us

Track Promise

Understand what generative AI can do, choose where it fits, use it with care, and check the results so you can decide what to trust, change, or decline.

Start with an ordinary need: organize something, understand an unfamiliar idea, compare possibilities, or evaluate a claim. Learn how to choose a useful task, protect information, work with a chatbot, and inspect what comes back. People remain responsible for the result and for what happens next.

This Track also welcomes people who need to take part in decisions about AI in a workplace, service, family, or community without operating a tool themselves. Curiosity, skepticism, and uncertainty are all welcome. No technical background is required.

Start Here

Begin with 🧩 Module · AI Without the Hype. It is this Track’s signature module: a calm first look at useful capabilities, limits, and human judgment.

Inside the module, use its signature lab 🧪 Lab · A Safe First Try. Work through a fictional task with a tool, a partner, a facilitator, or the supplied example. Notice what is useful, what needs checking, and which decisions remain yours.

The standalone 📓 Notebook · Lab Notebook contains the complete activity and places for your notes. You can use it without keeping the module or Activity page open beside it. Notes are private to the browser session; export anything you want to keep.

The AI Literacy Loop

Understand → Choose → Steer → Check → Decide

• Understand what the tool is being asked to do and where its limits matter.
• Choose a task and tool that fit. Set boundaries for information, safety, and what the tool may do before you begin.
• Steer with a clear request, relevant context, follow-up questions, comparison, or a fresh start.
• Check the result against sources, standards, and the needs of the task. Notice what worked and what you need to learn next.
• Decide whether to use, revise, verify further, seek help, or decline the result. Carry what you learned into the next attempt.

You can practice these choices through live use or by inspecting a supplied AI interaction. Reading another confident answer is not a substitute for checking a claim that matters.

The Five-Module Core

Follow this recommended sequence when you want a longer path. You can pause after a useful experience or choose a depth route without finishing all five modules. Only prerequisites stated by an individual module are required.

Each module teaches a part of the loop, with one featured lab for practice. Core describes its role in the Track; each resource’s About disclosure explains its current usability and review evidence. This is a curriculum under review, not a completed course.

1. 🧩 Module · AI Without the Hype
   Understand useful capabilities and limits; choose a safe first task.

   Featured lab: 🧪 Lab · A Safe First Try — inspect a fictional task and decide what remains human-owned.

2. 🧩 Module · Safety: Share Less, Notice More
   Choose what to share, sanitize, substitute, or keep out of the interaction.

   Featured lab: 🧪 Lab · What Else Came Along? — inspect a supplied file pair for information beyond what first meets the eye.

3. 🧩 Module · Prompting Is the Door, Not the Destination
   Make a useful first request, inspect the response, and repair what needs work.

   Featured lab: 🧪 Lab · One Task, Three Conversations — compare different conversation moves on one task.

4. 🧩 Module · Conversation Engineering
   Keep direction across turns; notice when to continue, steer, restart, or stop.

   Featured lab: 🧪 Lab · Stay, Steer, or Start Over — choose the next move in a conversation and explain why it fits.

5. 🧩 Module · Reality Check for AI
   Test your expectations about AI and revise them from what you observe and check.

   Featured lab: 🧪 Lab · Reality Check for AI: Six Experiments — predict, compare, inspect sources, and revise a working mental model.

Safety and checking begin in the signature experience and recur throughout the core. The later modules give those habits more depth. All five featured labs have their own standalone Notebooks, linked from the Activity pages.

Choose Where to Go Deeper

Choose a route when it serves something you want to understand or do. Developing previews remain available to explore. A complete route is not implied by the presence of a source page. Each module links to its own related labs and practice choices.

Optional depth

Understand and steer

Look more closely at what AI is, then learn to select and maintain the context around a task.

• 🧩 Module · What AI Is and Is Not
• 🧩 Module · Context Engineering

Optional depth

Privacy and relationships

Practice information boundaries, proportionate disclosure, and task-specific reliance on conversational systems.

• 🧩 Module · Before You Paste: Privacy and Data Boundaries
• 🧩 Module · Conversational Privacy
• 🧩 Module · Relationships with Conversational AI

Optional depth

Verification

Recognize unsupported claims, choose a suitable check, and decide whether a result is usable.

• 🧩 Module · When the Bot Sounds Right but Is Not
• 🧩 Module · Trust, But Check the Wires

Optional depth

Technology choices

Examine persuasive claims, changing communication, and the commitments that come with a tool or subscription.

• 🧩 Module · Pause Before You Pay: Scam Awareness Basics
• 🧩 Module · How Technology Changes the Ecology of Communication
• 🧩 Module · Becoming an Informed Technology Consumer

The consumer module offers an optional look at choosing tools and deciding where they fit.

Optional depth

Learning and making

Explore creative choices and ways AI might support explanation, practice, and learning.

• 🧩 Module · Creative Latitude
• 🧩 Module · AI for Learning: Tutor, Quizmaker, Simulator

The AI-for-learning source is a planning input. Dedicated AI-as-instructor modules and labs have not been created.

Optional depth

Communication

Use speaking and listening practice when explaining an idea would serve your next goal.

• 🧩 Module · Public Speaking — choose practice from the module’s related labs.

A public presentation or recording is not required.

Participation and Access

Live use and supplied-example routes are both complete ways to participate. You may operate an approved tool, direct a partner, observe and guide a facilitator, or inspect supplied scenarios and saved AI responses. In each mode, practice the same decisions: choose a task, protect information, inspect a response, and explain what should happen next.

No learner account, paid subscription, personal disclosure, recording, or public presentation is required. Learners may speak, listen, point, draw, dictate, or take notes. Adjust depth, vocabulary, pacing, and written load to the learner rather than assuming ability or comfort from age.

Use the fictional or low-risk materials supplied by each lab. A learner who uses a saved example can assess that example and plan a next move; they should not claim to have tested a current tool. An informed decision not to use AI is a valid outcome.

For Facilitators

Begin the first pilot with AI Without the Hype and A Safe First Try. Use the existing package’s facilitation and timing guidance as a starting point, then record actual time and any interventions needed. Do not attempt all five modules in one sitting.

Offer live and supplied-example participation from the outset. Ask learners to identify what was useful, what needs checking, and which decision remains theirs. Notes may be spoken or kept privately; a submission is not required.

During a facilitated pilot, note whether learners can find a starting point, understand the promise, find the status explanation, and choose a next route. Record missing or misplaced material and instruction changes with the facilitator. No online submission is required.

Use what learners encountered to choose the next core module or depth route. Actual learner evidence remains necessary before changing readiness or status.

Keep Learning

The optional tracks below remain in the earlier Learning Lab.

Return to the loop when tools, tasks, and claims change. Keep these practical ideas in mind:

• Artificial Intelligence (AI) · Generative AI · Chatbot · Prompt · Output
• Sensitive Information · Sanitized Information · Low-Risk Task · Safe Curiosity
• Human Review · Human Ownership · Verification

Follow a question through 🧭 Track · Invitation To Be Curious Again, explore Creative AI Makerspace (legacy Learning Lab) or Study Time (legacy Learning Lab), or consider the planning routes in AI Readiness (legacy Learning Lab), Zero-to-Hero Agentic Literacy (legacy Learning Lab), and Systems Thinking and AI Engineering (legacy Learning Lab). Each Track keeps its own scope and status.