Mapping the AI Landscape
AIF-F01 · Foundation level · ~75 min
Capabilities
- C1AI Mental Models and Ecosystem Literacy
- C8Learning Agility and Tool Transfer
Source
- OECD-AI-PRINCIPLES
Profiles: explorer
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Activity: Three-Lens Classifier
Classify each system with the three lenses. When information is missing, choose "Cannot determine" and note what you would need. Then reveal the suggested answers and check your automation-vs-AI calls.
| System | How it operates | What it does | Where it sits |
|---|---|---|---|
| Mail merge | |||
| Spam filter | |||
| Recommendation engine | |||
| Chatbot | |||
| Rules-based approval | |||
| Tool-using agent |
Activity: AI Landscape Map
Pick one AI product you use or have observed. Fill in the eight dimensions. Then export your map — it becomes the core of your checkpoint submission.
Activity: Task Scorer
List up to ten recurring tasks. Score each 1–5 on potential value (would AI plausibly improve the net result?), risk (consequence of error, data sensitivity), and verification effort (cost to confirm the output is right). Reject at least two tasks — an honest rejection is part of the method, not a failure.
Scoring: 1 = very low · 3 = moderate · 5 = very high. For verification effort, 5 means it would cost a lot to check the output.
| Task | Value (1–5) | Risk (1–5) | Verification effort (1–5) | Decision |
|---|---|---|---|---|
The three lenses — look at any system through all three
How it operates
Rules someone wrote, patterns learned from data, or a hybrid.
What it does
The action: predict, classify, detect, recommend, generate, retrieve, act.
Where it sits
The layer: model, data source, application, connected tool, workflow, human checkpoint.
One chat box can hide all three at once. Separate them before judging the system.
Worked example — "The AI answered the ticket" is five components
Classify
request type
Retrieve
policy doc
Draft
reply
Route
rules
Human
checkpoint
Five different components, each a place where incorrect data or weak oversight can cause harm. The sentence hides all of them.
The equation that decides
Low verification cost → good first use
Summarizing your own notes. You already know what's right — checking is cheap.
High verification cost → avoid first
Summarizing unfamiliar legal terms. You'd have to verify every claim — the checking is the real work.
An unpleasant task is not automatically an AI-suitable task. Run the equation first.
Review · flashcard
Flip each card, say the answer out loud first, then check.
Your takeaway card — what to keep from this module
- 1"AI" is an umbrella — separate how it operates, what it does, and where it sits before judging any product.
- 2Automation follows written rules; AI learns patterns from data. Say which part does which.
- 3Assistant, copilot, and agent are product labels, not technical categories — ask about actions, tools, approvals, and failure.
- 4"The AI answered it" hides many components and many places for harm. Name the human checkpoint.
- 5When information is missing, write "cannot determine" and state what you would need.
Try it yourself · Interview your AI tool
Open the AI tool you actually have — any free tier works. Run these questions and then classify the tool with the three lenses using what it tells you (and what it does not).
Pick your tool (to confirm what's available — the method works with any)
Tip: open ChatGPT (free) (chatgpt.com — free tier, no login needed for most use) in a new tab to begin.
Open your AI tool in a new tab.
Run this first question — copy it exactly. Then note the answer in the observations below.
What kind of AI system are you? Describe how you produce your answers — which components (model, retrieval, rules, tools, human approval) are involved?
Run this second question and note the answer.
What actions can you take? Which tools or integrations can you access? How long can you work on a single task? What approvals or limits apply?
Run this third question and note the answer.
What are your main limitations? Describe a situation where you are likely to be wrong or where you would need a human to verify the result.
Challenge one claim the tool made. Ask it to show the source or reasoning for one specific statement it gave you. Note what happened.
One of your answers made a claim. Show me the specific source or reasoning behind it, or tell me clearly if you cannot.
Record what you observed