Hum_EDU Secondary
Secondary ⏱ 20-30 minutes

Exercise 1 — Fact, opinion or hypothesis?

Learn to distinguish three types of statements that AI can produce — and why this distinction is essential.

Objectives

  • Distinguish a verifiable fact from an opinion
  • Identify an unverifiable hypothesis
  • Analyze an AI response using these three categories

Before you start

When you ask an AI a question, it gives you a response that often mixes three very different types of statements. Knowing how to distinguish them is the first step toward using AI intelligently.


The three types of statements

A fact is something verifiable. You can look for sources to confirm or refute it. Example: “The Earth orbits the Sun in 365 days.”

An opinion is a point of view. Reasonable, well-informed people can disagree. Example: “Solar energy is the best solution to climate change.”

A hypothesis is an assumption that cannot yet be verified. Example: “In 50 years, AI will be more intelligent than humans.”


Exercise — 3 steps

Step 1 — Without Hum_ID

Ask this question to an AI of your choice:

“Are social media harmful to the mental health of teenagers?”

Copy the response you receive.

Step 2 — Analyze your response

For each statement in the response, classify it in a table:

Statement →Fact / Opinion / Hypothesis→ Why?

Step 3 — With Hum_ID

  1. Go to humanity.net/en/hum-id
  2. Select rule R1.1 — Distinguishing facts from opinions
  3. Generate your profile and download your humid-your-profile-name.json file
  4. Submit the file to the AI + the following activation message: Here is my Hum_ID ethical profile. Apply these rules to the following question: [Paste your question here.]
5. Compare the two responses

Reflection questions:

  • Is the second response easier to analyze? Why?
  • Which statements changed between the two responses?
  • Does it change the way you see the first response?

Going further

The same question asked to two different people can yield very different answers — depending on their values, culture, and experience. AI is no different: it reflects the data it was trained on.

Hum_ID allows you to explicitly ask it to be honest about what it really knows — and what it does not.