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Safe AI for HR Teams: Using AI in Hiring and People Decisions Without Breaking the Law

Where AI Already Sits in the Employee Life Cycle

Quiz: Where AI Already Sits in the Employee Life Cycle

Why Hiring and Promotion AI Counts as High Risk Under Annex III

Quiz: Why Hiring and Promotion AI Counts as High Risk Under Annex III

CV Screening Tools: What They Measure and How They Go Wrong

Quiz: CV Screening Tools: What They Measure and How They Go Wrong

Video and Game Based Assessment: Evidence and Legal Exposure

Quiz: Video and Game Based Assessment: Evidence and Legal Exposure

Bias Testing People Tools Before and After Deployment

Quiz: Bias Testing People Tools Before and After Deployment

Equality Act 2010, Indirect Discrimination and Reasonable Adjustments

Quiz: Equality Act 2010, Indirect Discrimination and Reasonable Adjustments

Candidate Notices, Consent and the Right to a Human Review

Quiz: Candidate Notices, Consent and the Right to a Human Review

UK GDPR Article 22 and Automated Decisions About People

Quiz: UK GDPR Article 22 and Automated Decisions About People

Data Protection Impact Assessments for HR Systems

Quiz: Data Protection Impact Assessments for HR Systems

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Quiz: Bias Testing People Tools Before and After Deployment

Safe AI for HR Teams: Using AI in Hiring and People Decisions Without Breaking the Law
Bias Testing People Tools Before and After Deployment
Quiz: Bias Testing People Tools Before and After Deployment

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Question 1 of 5

1. Question

What is the purpose of building paired test profiles with identical qualifications but different demographic characteristics?

To make the test set as large as possible
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To identify whether the system makes substantially different decisions for demographic groups
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To train the system on diverse data
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The lesson does not mention paired profiles
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Question 2 of 5

2. Question

What does demographic parity measure in a fairness assessment?

Whether the system trains on demographically balanced data
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Whether the system makes the same decision for all demographic groups
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Whether the system can explain its decisions
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Whether disabled candidates score higher than non-disabled candidates
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Question 3 of 5

3. Question

Why is post-deployment bias monitoring necessary even after pre-deployment testing?

Pre-deployment testing is meaningless without follow-up
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The system may drift over time; patterns true in training data may no longer be true in the live environment
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All systems become biased after deployment regardless of pre-testing
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The lesson states post-deployment monitoring is not necessary
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Question 4 of 5

4. Question

What is a reasonable adjustment that might be made to a hiring system that disadvantages disabled candidates?

Removing disabled candidates from the evaluation
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Providing a different assessment format, allowing more time, or requiring human review of borderline cases
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Stating that the system is unbiased and no adjustments are needed
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Instructing disabled candidates to hide their disability in applications
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Question 5 of 5

5. Question

What should be included in documentation of bias testing results?

Only the final bias metric scores
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Test set details, metrics applied, results, bias patterns detected, actions taken, and justification for accepting residual bias
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An executive summary with no supporting details
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Documentation is not required
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