To prioritize identified risks by combining | AIGP
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To prioritize identified risks by combining: What is the primary purpose of this probability/severity harms

AIGP Understanding How to Govern AI Development Easy

A probability/severity harms matrix prioritizes risks by combining likelihood and severity so mitigation targets the most significant harms.

The question

During the design of an AI system, a team plots each identified harm on a grid according to how likely it is and how serious it would be. What is the primary purpose of this probability/severity harms matrix?

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  1. To document the provenance of each training dataset so reviewers can trace where every data element in the pipeline originally came from.
    Plausible because provenance tracking is a real governance task, but it records data lineage rather than ranking harms by probability and severity.
  2. To prioritize identified risks by combining their likelihood and severity so mitigation effort targets the most significant harms first.
    Correct because a probability/severity matrix ranks risks by likelihood and impact, guiding where mitigation should be concentrated.
  3. To record the sequence of model versions released over time so auditors can reconstruct which build was live during any given period.
    Plausible because version history supports accountability, but it is a documentation artifact, not a tool for prioritizing risks by likelihood and impact.
  4. To measure the model's predictive accuracy against a labeled benchmark so the team can confirm it meets the agreed technical acceptance threshold.
    Plausible because accuracy benchmarking is essential, but it evaluates performance, not the relative priority of potential harms.
The trap
Confusing the harms matrix (a prioritization tool) with documentation artifacts like data lineage or version history.

How to remember it

A probability/severity harms matrix prioritizes risks by combining likelihood and severity so mitigation targets the most significant harms.

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