Method note · Last reviewed

From source to answer: making AI explanations verifiable

An AI definition can change meaning when it is shortened. This note follows the path from primary sources to the lesson What Is AI?, then examines the sources, conceptual boundaries, related lessons, and structured data that preserve context. The aim is to improve understanding without breaking the link to the evidence behind the explanation.

Written by Cahyanto Arie Wibowo · 7 minutes

The question

How can a technical definition be shortened for non-specialist readers without losing its boundaries or original source?

A simple explanation should still show what that simplicity was built from.

Why it matters

Short definitions are easy to share and cite, but they can also lose their boundaries. Showing provenance helps readers check meaning, while relationships between pages reveal what was intentionally left out of the summary.

Method

  1. We selected the lesson What Is AI? because it is the entry point to the full Learning Series.
  2. The definition and boundaries of AI were compared with the OECD explanatory memorandum on AI systems and the Elements of AI introduction.
  3. We then checked how sources, review dates, related lessons, and LearningResource schema preserve context after the definition is shortened.

Evidence at a glance

main question
1
lesson sources
3
paths for deeper reading
3
visible review date
1

Findings

Separate definition from example

A definition explains what belongs to a concept. An example helps readers recognise it. When the two are mixed, readers may assume one example represents all AI.

State the boundaries plainly

AI can produce predictions, recommendations, or outputs, but its capability depends on goals, data, design, and use context. Those limits should sit close to the definition.

Connect the summary to its source

Primary sources give readers a path to check terms and scope. Source titles, publishers, and canonical URLs also give systems clearer provenance signals.

Preserve context through relationships

Related lessons answer follow-up questions about data, capability, and evaluation. Schema marks author, publisher, course, and citation relationships in machine-readable form.

Practical implications

  1. Separate the short answer, example, and conceptual boundary.
  2. Place sources as close as possible to the claims they support.
  3. Provide a path to the details intentionally left out of the summary.

Sources you can check

  1. Explanatory memorandum on the updated OECD definition of an AI system: OECD.AI
  2. How should we define AI?: Elements of AI · University of Helsinki
  3. Introduction to structured data markup in Google Search: Google Search Central

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