Ethical Considerations of AI →easyMultiple ChoiceObjective-mapped

AI Associate Ethical Considerations of AI Practice Question

{
  "bias_detection": {
    "enabled": true,
    "sensitive_attributes": ["gender", "race"]
  }
}

Refer to the exhibit. This JSON snippet is from the Einstein Trust Layer configuration. What is the purpose of this configuration?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

To detect biased predictions based on gender and race

The configuration enables bias detection on the specified sensitive attributes (gender and race).

Answer analysis

For each option: why learners choose it and why it is or isn't the right answer here.

✓
To detect biased predictions based on gender and race
Why this is correct
Correct. The bias detection feature checks for disparities along these attributes.
✗
To block all predictions involving gender or race
Why it's wrong here
It enables detection, not blocking.
✗
To anonymize gender and race data
Why it's wrong here
Anonymization is not indicated here.
✗
To remove gender and race from the model
Why it's wrong here
The configuration does not remove attributes; it monitors them.

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