Module 01 · 16 minutes
Types of Harm
Map who is affected, what harm may occur, and how bias can emerge throughout an AI system's use.
Written and edited by Cahyanto Arie Wibowo. Last reviewed · version 1.2.
How does the idea of “Types of Harm” change the decision we make?
Use Types of Harm to inspect evidence in AI Ethics; identify who owns Types of Harm, then note what still needs checking. Look at Types of Harm through a decision: what information is available, who owns the result, and what happens if the assumptions are wrong. The goal is to use Types of Harm to clarify a decision, not simply add another term to remember.
After this lesson
- Use Types of Harm to inspect evidence in AI Ethics; identify who owns Types of Harm, then note what still needs checking.
- Use the idea of “Types of Harm” 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 model can look accurate overall while failing often for a smaller user group. This lesson uses the idea of “Types of Harm” to examine that situation without treating a single term as the answer to every problem.
Use Types of Harm to inspect evidence in AI Ethics; identify who owns Types of Harm, then note what still needs checking. Map who is affected, what harm may occur, and how bias can emerge throughout an AI system's use. 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.
01
Situation
A model can look accurate overall while failing often for a smaller user group. This lesson uses the idea of “Types of Harm” to examine that situation without treating a single term as the answer to every problem.
02
Decision
A model can look accurate overall while failing often for a smaller user group. Identify the part of the situation most closely connected to the idea of “Types of Harm”. Use the case as a thinking tool, not as proof that one solution fits every context.
03
Review
No single fairness formula fits every case. The decision context still matters. This mistake often appears when a label is used before the problem is understood. Write down your assumptions so another person can review them.
Do not rush the choice
Two ways to look at Types of Harm
Useful when
- Use Types of Harm to inspect evidence in AI Ethics; identify who owns Types of Harm, then note what still needs checking.
- Use the idea of “Types of Harm” to interpret one realistic situation.
- Use Types of Harm to inspect evidence in AI Ethics; identify who owns Types of Harm, then note what still needs checking. Map who is affected, what harm may occur, and how bias can emerge throughout an AI system's use. Connect the term to a decision someone genuinely needs to make.
Pause and check
- No single fairness formula fits every case. The decision context still matters. This mistake often appears when a label is used before the problem is understood. Write down your assumptions so another person can review them.
- Explain the limits of the concept and the information that still needs to be checked.
The stronger choice is the one whose evidence, owner, and limits can be explained, not simply the more sophisticated option.
Visual model
Map the parts before choosing what to do.
Read the diagram as a map of Types of Harm: begin with the context, follow the connections, and inspect the highlighted point before making a decision.
Pause for a moment
What evidence could change this decision?
Answer before opening the discussion. Name one fact and one assumption.
Open the discussion
Use Types of Harm to inspect evidence in AI Ethics; identify who owns Types of Harm, then note what still needs checking. Look at Types of Harm through a decision: what information is available, who owns the result, and what happens if the assumptions are wrong. The goal is to use Types of Harm to clarify a decision, not simply add another term to remember.
A tempting shortcut
A familiar term can still lead us to the wrong decision.
Why this can seem reasonable
No single fairness formula fits every case. The decision context still matters. 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
Look at Types of Harm through a decision: what information is available, who owns the result, and what happens if the assumptions are wrong. Begin with what can be observed, then separate facts, assumptions, and open questions.
Try it on your work
Try it with one small piece of real work.
- Choose one real situation related to Types of Harm.
- Separate what you can observe from what you are assuming.
- Write one decision, its owner, and the evidence needed to review it.
- Name the signal that would make you stop or change direction.
Choose a task you know. List what is known, what is still an assumption, and what must be tested before using the idea of “Types of Harm”. The larger module activity is: Create an impact map for one AI use case. Keep the first version small enough for another person to review in a few minutes.
Quick practice
Choose a task you know. List what is known, what is still an assumption, and what must be tested before using the idea of “Types of Harm”. The larger module activity is: Create an impact map for one AI use case.
Summary
- Use Types of Harm to inspect evidence in AI Ethics; identify who owns Types of Harm, then note what still needs checking.
- Use examples and evidence to test your understanding.
- Record the limits, risks, and conditions that should trigger another review.
Continue from here
- The Bias Lifecycle: Continue the idea from Harm, Bias, and Fairness with a closely related example.
- Ambition and Horizons: Connect this lesson to Leadership and test the idea in another context.
- Reading Uncertainty: See how the same decision changes when viewed through Future of Work.
Sources and further reading
- Recommendation on the Ethics of Artificial Intelligence: UNESCO · official-recommendation. Primary reference for the definition, evidence, or limits discussed in “Types of Harm”.
- OECD AI Principles: OECD.AI · official-principles. Further evidence and context for checking the explanation in “Types of Harm”.
- Artificial Intelligence Risk Management Framework: NIST · official-framework. Further evidence and context for checking the explanation in “Types of Harm”.