Algorithmic bias in which a model systematically produces | AIGP
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Algorithmic bias in which a model systematically produces: Which of the following is an example of an

AIGP Understanding the Foundations of AI Governance Easy

Algorithmic bias producing discriminatory outcomes is an enumerated AI-specific harm (ethics and bias risk).

The question

Which of the following is an example of an AI-specific risk or harm that AI governance is intended to address?

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  1. A power outage in a data center caused by a regional storm, which interrupts service availability but arises from environmental infrastructure rather than the model.
    Plausible but wrong: a weather-driven outage is a general availability risk, not an AI-specific harm.
  2. Algorithmic bias in which a model systematically produces less favorable outcomes for a protected group, reflecting the ethics-and-bias category of AI harm.
    Correct: ethics and bias risk leading to discriminatory outcomes is an enumerated AI-specific harm.
  3. An accounting error in a manual spreadsheet that misstates a quarterly figure, which is a human bookkeeping mistake unrelated to any automated model behavior.
    Plausible but wrong: a manual spreadsheet error is a conventional operational risk, not an AI harm.
  4. A phishing email that tricks an employee into revealing a password, which is a social-engineering security incident independent of any AI system's operation.
    Plausible but wrong: generic phishing is a traditional security risk, not a harm specific to AI.
The trap
Classifying ordinary IT or security incidents as AI-specific harms.

How to remember it

Algorithmic bias producing discriminatory outcomes is an enumerated AI-specific harm (ethics and bias risk).

How many of these would you get right?

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