Rules, Prediction, or Generation

What does “Rules, Prediction, or Generation” mean in practice?

For Applied AI, think of Rules, Prediction, or Generation as a way to organize a decision, not as a label that settles the answer. Use Rules, Prediction, or Generation as a thinking tool. If the evidence, owner, or limits are unclear, pause and ask a better question. Try Rules, Prediction, or Generation on one small task, then write down what still needs to be checked.

After this lesson

• For Applied AI, think of Rules, Prediction, or Generation as a way to organize a decision, not as a label that settles the answer.
• Use the idea of “Rules, Prediction, or Generation” to interpret one realistic situation.
• Explain the limits of the concept and the information that still needs to be checked.

Start with the situation

Understand the situation first. The label can come later.

A rule can validate an invoice number. Extracting information from free text may require an AI model. This lesson uses the idea of “Rules, Prediction, or Generation” to examine that situation without treating a single term as the answer to every problem.

For Applied AI, think of Rules, Prediction, or Generation as a way to organize a decision, not as a label that settles the answer. Compare simple rules, predictive AI, and generative AI, then decide whether to build or use an existing service. Connect the term to a decision someone genuinely needs to make.

See how the decision unfolds

Move from the situation to a choice others can review.

Visual model

Map the parts before choosing what to do.

Read the diagram as a map of Rules, Prediction, or Generation: begin with the context, follow the connections, and inspect the highlighted point before making a decision.

Do not rush the choice

Two ways to look at Rules, Prediction, or Generation

The stronger choice is the one whose evidence, owner, and limits can be explained, not simply the more sophisticated option.

Try it on your work

Try it with one small piece of real work.

1. Choose one real situation related to Rules, Prediction, or Generation.
2. Separate what you can observe from what you are assuming.
3. Write one decision, its owner, and the evidence needed to review it.
4. Name the signal that would make you stop or change direction.

Write two examples that fit Rules, Prediction, or Generation and one that does not. Explain the difference in your own words. The larger module activity is: Use a decision tree to choose an approach for three different cases. Keep the first version small enough for another person to review in a few minutes.

Pause for a moment

What evidence could change this decision?

Answer before opening the discussion. Name one fact and one assumption.

A tempting shortcut

A familiar term can still lead us to the wrong decision.

Why this can seem reasonable

The largest model is not always the cheapest, fastest, or safest choice. This mistake often appears when a label is used before the problem is understood. Write down your assumptions so another person can review them.

How to check it

Use Rules, Prediction, or Generation as a thinking tool. If the evidence, owner, or limits are unclear, pause and ask a better question. Begin with what can be observed, then separate facts, assumptions, and open questions.

Quick practice

Write two examples that fit Rules, Prediction, or Generation and one that does not. Explain the difference in your own words. The larger module activity is: Use a decision tree to choose an approach for three different cases.

Summary

• For Applied AI, think of Rules, Prediction, or Generation as a way to organize a decision, not as a label that settles the answer.
• Use examples and evidence to test your understanding.
• Record the limits, risks, and conditions that should trigger another review.

Continue from here

• Build, Buy, or Combine: Continue the idea from Choosing an Approach with a closely related example.
• Opportunity Mapping: Connect this lesson to Product Thinking and test the idea in another context.
• Examples and Constraints: See how the same decision changes when viewed through Prompting.

Sources and further reading

• Rules of Machine Learning: Google for Developers · official-guidance. Primary reference for the definition, evidence, or limits discussed in “Rules, Prediction, or Generation”.
• Data on the Web Best Practices: W3C · web-standard. Further evidence and context for checking the explanation in “Rules, Prediction, or Generation”.
• Artificial Intelligence Risk Management Framework: NIST · official-framework. Further evidence and context for checking the explanation in “Rules, Prediction, or Generation”.