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Computer Chapter 5 : Topic 2.6
AI Discrimination
1 / 9
A recruitment system automatically shortlists job applicants but consistently prefers candidates from one gender despite equal qualifications across all applicants. What type of decision issue does this represent?
Reasoning: If one group is consistently favored or rejected without valid reason, the system is showing bias.
2 / 9
A loan approval algorithm gives higher approval rates to applicants from wealthier neighborhoods while rejecting equally qualified applicants from poorer areas. What is the main concern with this behavior?
Reasoning: Decisions influenced by income level or location can create unfair socio-economic discrimination.
3 / 9
A facial recognition system performs well on light-skinned individuals but frequently fails to correctly identify darker-skinned individuals. What is the likely problem?
Reasoning: If training data is unbalanced, the system becomes less accurate for underrepresented groups.
4 / 9
An AI hiring tool ranks candidates lower if their resumes contain names associated with a specific ethnic group. What ethical issue does this indicate?
Reasoning: Using personal attributes like names to disadvantage candidates leads to unfair discrimination.
5 / 9
A school performance prediction system tends to underestimate students from rural areas regardless of their actual marks. What is the main problem?
Reasoning: When predictions unfairly depend on location rather than actual performance, it reflects bias.
6 / 9
A medical AI system recommends less aggressive treatment for patients of a certain age group without strong medical justification. What issue does this represent?
Reasoning: If decisions unfairly depend on age without medical reason, it is age discrimination.
7 / 9
A social media content algorithm shows fewer job advertisements to users from a specific region compared to others. What is the main concern?
Reasoning: Unequal exposure to opportunities based on region is a form of bias.
8 / 9
A credit scoring system consistently assigns lower scores to applicants from a particular school, even when academic records are similar. What is the likely issue?
Reasoning: Judging individuals based on the institution rather than personal merit creates unfair bias.
9 / 9
A hiring AI model trained mostly on male employee data performs poorly when evaluating female candidates. What is the root cause?
Reasoning: When training data is not representative, the system becomes biased against underrepresented groups.
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