1. What is AI bias?
A) AI making fair decisions
B) AI showing favoritism based on flawed data ✅
C) AI having no errors
D) AI being fully transparent
2. What is the main cause of bias in AI?
A) Poor internet connection
B) Biased training data ✅
C) AI’s own opinions
D) Lack of processing power
3. Which type of bias occurs when AI favors one group over another?
A) Confirmation bias
B) Selection bias ✅
C) Overfitting
D) Data compression bias
4. How can AI bias be reduced?
A) Using diverse and representative training data ✅
B) Reducing the dataset size
C) Avoiding transparency
D) Ignoring bias
5. What is the main ethical concern with biased AI in hiring systems?
A) AI may discriminate against certain candidates ✅
B) AI may work too fast
C) AI may require too much data
D) AI may favor all candidates equally
6. What is an example of AI bias in healthcare?
A) AI diagnosing all patients equally
B) AI misdiagnosing certain racial groups due to biased data ✅
C) AI improving medical accuracy
D) AI reducing hospital costs
7. Which ethical principle focuses on making AI accountable for its decisions?
A) Transparency ✅
B) Speed
C) Efficiency
D) Profitability
8. What is the role of fairness in ethical AI?
A) Ensuring AI treats all users equally ✅
B) Allowing AI to favor certain users
C) Hiding decision-making processes
D) Avoiding accountability
9. What is algorithmic transparency?
A) Making AI decisions clear and understandable ✅
B) Hiding AI decision-making processes
C) Making AI work faster
D) Reducing AI accuracy
10. What is one risk of AI in facial recognition?
A) AI may misidentify people of certain races ✅
B) AI never makes mistakes
C) AI cannot process images
D) AI eliminates all bias
11. What is the ethical risk of AI in predictive policing?
A) AI may reinforce racial biases in law enforcement ✅
B) AI makes law enforcement unnecessary
C) AI always makes fair predictions
D) AI has no role in law enforcement
12. What is one way to make AI decision-making more ethical?
A) Regular audits for bias ✅
B) Ignoring ethical concerns
C) Hiding AI’s decision process
D) Avoiding fairness testing
13. Which type of bias occurs when AI is trained on incomplete data?
A) Selection bias
B) Sampling bias ✅
C) Automation bias
D) Algorithmic bias
14. What is the main ethical issue with AI-powered loan approvals?
A) AI may discriminate based on race or gender ✅
B) AI makes loans faster
C) AI reduces paperwork
D) AI improves customer experience
15. What is a key principle of responsible AI?
A) Fairness and accountability ✅
B) Speed and efficiency
C) Profit maximization
D) Data secrecy
16. How can AI bias be detected?
A) Auditing AI models ✅
B) Reducing training data
C) Avoiding AI use
D) Limiting AI learning
17. Which of these is a form of AI discrimination?
A) AI favoring male job applicants over female ones ✅
B) AI treating all candidates equally
C) AI making unbiased decisions
D) AI reducing errors
18. Why is diversity in AI development teams important?
A) To reduce bias in AI models ✅
B) To slow down AI development
C) To make AI less accurate
D) To make AI decisions private
19. What is one ethical concern of AI in social media?
A) AI reinforcing filter bubbles ✅
B) AI reducing online engagement
C) AI slowing down internet speeds
D) AI promoting only educational content
20. What is data bias in AI?
A) When AI is trained on unrepresentative data ✅
B) When AI always makes correct decisions
C) When AI ignores data
D) When AI processes data equally
21. What is automation bias?
A) Over-reliance on AI decisions ✅
B) AI ignoring input data
C) AI failing to work
D) AI rejecting automation
22. How can AI bias be minimized in recruitment?
A) Removing sensitive personal attributes from AI training data ✅
B) Allowing AI to make final hiring decisions
C) Letting AI decide without audits
D) Using AI for all job positions
23. Why is AI explainability important?
A) It helps users understand AI decisions ✅
B) It slows down AI processing
C) It makes AI less accurate
D) It increases AI secrecy
24. What does fairness in AI mean?
A) AI making unbiased decisions ✅
B) AI working quickly
C) AI prioritizing profits
D) AI working without human input
25. What is one risk of AI-generated deepfakes?
A) Spreading misinformation ✅
B) Reducing bias
C) Making AI more ethical
D) Improving AI accountability
26. How can bias in AI-powered credit scoring be reduced?
A) Using diverse financial datasets ✅
B) Using only past loan approvals
C) Ignoring past discrimination
D) Avoiding data transparency
27. What is an example of confirmation bias in AI?
A) AI reinforcing existing stereotypes ✅
B) AI eliminating discrimination
C) AI improving fairness
D) AI removing bias
28. How can AI ensure fairness in decision-making?
A) Regular fairness testing ✅
B) Avoiding ethics
C) Reducing dataset size
D) Avoiding human oversight
29. Why is AI accountability important?
A) To ensure AI systems follow ethical guidelines ✅
B) To make AI more secretive
C) To reduce AI speed
D) To avoid responsibility
30. How can AI bias affect medical diagnosis?
A) Misdiagnosing certain groups due to biased data ✅
B) Making all diagnoses accurate
C) Improving healthcare
D) Reducing ethical concerns
31. What is one solution for AI bias in legal systems?
A) Regular audits of AI decision-making ✅
B) Letting AI make final decisions
C) Reducing AI transparency
D) Ignoring fairness concerns
32. What is one ethical concern of AI surveillance?
A) Privacy violations ✅
B) AI increasing security
C) AI reducing crime
D) AI improving fairness
33. What does ethical AI aim to achieve?
A) Fair and unbiased AI decisions ✅
B) Maximum profits
C) AI secrecy
D) Unregulated AI development
34. How can AI bias in news recommendations be minimized?
A) Providing diverse perspectives ✅
B) Limiting content
C) Avoiding transparency
D) Removing ethical guidelines
35. Why should AI decisions be interpretable?
A) To ensure fairness and accountability ✅
B) To hide bias
C) To make AI faster
D) To eliminate human oversight
36. What is the biggest challenge in AI ethics?
A) Reducing bias and discrimination ✅
B) Increasing AI speed
C) Avoiding AI regulation
D) Reducing AI transparency
51. What is the main goal of ethical AI?
A) Ensuring AI systems are fair, accountable, and transparent ✅
B) Making AI work faster
C) Avoiding human oversight
D) Hiding AI decision-making processes
52. What is the impact of biased AI in hiring processes?
A) AI may discriminate based on gender or race ✅
B) AI ensures fair hiring
C) AI makes unbiased choices
D) AI always selects the best candidate
53. What is the primary concern with AI in criminal justice?
A) AI may reinforce racial or social biases ✅
B) AI never makes mistakes
C) AI makes fair decisions
D) AI eliminates crime
54. How can AI bias affect financial services?
A) AI may unfairly deny loans to certain groups ✅
B) AI ensures equal loan approvals
C) AI makes banks more ethical
D) AI removes discrimination from credit scoring
55. What is an example of biased AI in education?
A) AI recommending different courses based on gender or race ✅
B) AI treating all students equally
C) AI ensuring fair grading
D) AI making education accessible to all
56. What is the danger of AI-powered social media algorithms?
A) They may create echo chambers and filter bubbles ✅
B) They increase diversity of opinions
C) They remove misinformation
D) They ensure fairness in content delivery
57. Why is human oversight important in AI decision-making?
A) To identify and correct biased AI decisions ✅
B) To speed up AI processes
C) To eliminate human involvement
D) To reduce AI transparency
58. What is the main challenge in AI-driven recruitment?
A) AI may prioritize certain demographic groups unfairly ✅
B) AI ensures diversity in hiring
C) AI cannot process resumes
D) AI never makes mistakes
59. How does biased AI impact healthcare predictions?
A) It may provide less accurate diagnoses for marginalized groups ✅
B) It improves medical decision-making
C) It eliminates human errors
D) It ensures equal treatment for all patients
60. What does AI fairness testing involve?
A) Analyzing AI decisions for possible bias ✅
B) Hiding AI errors
C) Speeding up AI processing
D) Reducing dataset size
61. Why is explainable AI important?
A) It allows humans to understand and trust AI decisions ✅
B) It makes AI more secretive
C) It removes the need for audits
D) It slows down AI development
62. What is an example of AI discrimination in banking?
A) AI rejecting loan applications based on biased historical data ✅
B) AI providing equal financial opportunities
C) AI improving financial fairness
D) AI reducing discrimination in banking
63. What role do ethical AI frameworks play?
A) They provide guidelines for developing fair AI systems ✅
B) They restrict AI innovation
C) They increase AI bias
D) They eliminate human oversight
64. How can AI developers reduce bias in machine learning models?
A) By using diverse and balanced training datasets ✅
B) By ignoring fairness concerns
C) By reducing the number of training examples
D) By hiding AI decision-making processes
65. What is a common form of unintentional AI bias?
A) AI reflecting biases present in historical data ✅
B) AI making fair decisions
C) AI ensuring equal representation
D) AI eliminating all errors
66. Why is ethical AI important in autonomous vehicles?
A) To ensure AI makes fair and safe driving decisions ✅
B) To reduce vehicle production costs
C) To remove human involvement in driving
D) To make cars faster
67. What is a key concern with AI-powered chatbots?
A) They may spread biased or harmful information ✅
B) They always provide accurate responses
C) They eliminate bias from conversations
D) They make ethical decisions on their own
68. How can AI bias in legal sentencing be minimized?
A) By using AI as a supporting tool, not the final decision-maker ✅
B) By allowing AI to replace judges
C) By making AI decisions unchallengeable
D) By avoiding AI in legal matters
69. What is the risk of biased AI in workplace monitoring?
A) AI may unfairly target certain employees ✅
B) AI ensures workplace equality
C) AI reduces bias in employee evaluations
D) AI promotes ethical decision-making
70. How can organizations ensure ethical AI use?
A) By implementing fairness, accountability, and transparency practices ✅
B) By prioritizing AI speed over accuracy
C) By limiting AI audits
D) By avoiding ethical discussions
71. What is the biggest risk of biased AI in law enforcement?
A) AI reinforcing racial or social discrimination ✅
B) AI reducing crime rates
C) AI always making fair judgments
D) AI improving fairness in policing
72. Why is fairness in AI decision-making important?
A) To prevent discrimination and ensure equal treatment ✅
B) To increase AI speed
C) To hide AI decision-making
D) To remove human intervention
73. How can AI bias be prevented in facial recognition?
A) By using diverse and representative training datasets ✅
B) By allowing AI to self-learn without supervision
C) By using only one type of dataset
D) By avoiding AI regulation
74. What is the ethical issue with AI-powered social credit scoring?
A) It may unfairly punish certain individuals ✅
B) It ensures fairness in financial systems
C) It eliminates human bias
D) It increases personal freedom
75. Why is diversity in AI training data important?
A) To reduce bias and improve fairness ✅
B) To make AI less efficient
C) To speed up AI decision-making
D) To increase AI profitability
76. What is one way to make AI accountability stronger?
A) By making AI decision-making processes transparent ✅
B) By hiding AI biases
C) By allowing AI to make independent decisions
D) By avoiding AI audits
77. What happens when AI lacks explainability?
A) Users cannot understand or challenge AI decisions ✅
B) AI becomes fairer
C) AI improves transparency
D) AI reduces bias
78. Why is AI fairness testing necessary?
A) To detect and eliminate bias in AI systems ✅
B) To increase AI complexity
C) To reduce AI efficiency
D) To speed up AI learning
79. What is the ethical risk of AI-driven hiring software?
A) It may reinforce gender or racial bias in recruitment ✅
B) It ensures fair job selection
C) It makes hiring completely unbiased
D) It eliminates all discrimination
80. What is an example of automation bias?
A) Over-reliance on AI decisions without verification ✅
B) AI ignoring data
C) AI making perfectly accurate decisions
D) AI rejecting automation
81. Why should AI be tested on multiple datasets?
A) To reduce bias and improve generalization ✅
B) To make AI more complex
C) To speed up AI processing
D) To increase AI’s ability to discriminate
82. What is a key ethical principle in AI?
A) Transparency ✅
B) Secrecy
C) Speed
D) Cost-cutting
83. Why is AI bias difficult to detect?
A) Bias is often hidden in complex algorithms ✅
B) AI is always fair
C) AI has no decision-making power
D) AI never uses biased data
84. What is the ethical concern with AI in advertising?
A) AI may manipulate users based on personal data ✅
B) AI ensures fair advertising
C) AI eliminates bias in marketing
D) AI cannot target specific audiences
85. What is an unintended consequence of biased AI?
A) AI may reinforce societal inequalities ✅
B) AI always promotes fairness
C) AI never makes mistakes
D) AI eliminates discrimination
86. What is ethical AI governance?
A) Setting rules and policies for responsible AI use ✅
B) Letting AI operate freely
C) Avoiding AI regulation
D) Eliminating human oversight
87. What is a risk of AI-powered resume screening?
A) AI may prioritize certain demographic groups unfairly ✅
B) AI ensures diversity in hiring
C) AI always makes fair selections
D) AI eliminates human involvement in hiring
88. Why is human oversight needed in AI-driven healthcare?
A) To ensure AI decisions are medically and ethically sound ✅
B) To slow down AI operations
C) To reduce AI accuracy
D) To prevent AI from working properly
89. What is an example of biased AI in finance?
A) AI denying loans based on zip codes associated with certain racial groups ✅
B) AI providing loans fairly
C) AI ensuring equal financial access
D) AI making completely unbiased decisions
90. How can AI bias be minimized in image recognition?
A) By training AI on diverse image datasets ✅
B) By using only black-and-white images
C) By avoiding AI in image recognition
D) By making AI models more complex
91. What is the ethical risk of AI in government decision-making?
A) AI may favor certain political groups or individuals ✅
B) AI ensures equal treatment in policies
C) AI always makes unbiased decisions
D) AI has no role in governance
92. What is one way AI bias can enter algorithms?
A) Through biased human input and data selection ✅
B) Through perfect training processes
C) Through AI’s inability to learn
D) Through AI’s strict neutrality
93. What happens if AI decision-making lacks transparency?
A) Users cannot challenge or understand AI decisions ✅
B) AI becomes fairer
C) AI improves trustworthiness
D) AI eliminates discrimination
94. What is a common issue with AI-powered loan approvals?
A) AI may favor wealthy applicants over lower-income individuals ✅
B) AI ensures fair access to credit
C) AI always makes unbiased financial decisions
D) AI improves fairness in banking
95. Why should AI systems be regularly audited?
A) To detect and correct potential biases ✅
B) To make AI work faster
C) To reduce AI accuracy
D) To increase AI secrecy
96. What is a risk of AI-driven hiring assessments?
A) AI may favor certain applicants based on irrelevant factors ✅
B) AI always selects the most qualified candidate
C) AI makes completely unbiased hiring decisions
D) AI ensures fairness in all industries
97. How can AI bias in criminal justice be addressed?
A) By using AI only as a supporting tool with human oversight ✅
B) By allowing AI to replace judges
C) By avoiding audits
D) By making AI the final decision-maker
98. Why is transparency crucial in AI systems?
A) It allows users to understand and challenge AI decisions ✅
B) It makes AI more secretive
C) It eliminates the need for audits
D) It reduces ethical concerns
99. What is a key ethical issue with AI-powered job interviews?
A) AI may misinterpret non-verbal cues from diverse candidates ✅
B) AI always understands human expressions correctly
C) AI ensures equal opportunity
D) AI improves diversity in hiring
100. Why should AI models be continuously monitored?
A) To identify and correct biases as they emerge ✅
B) To hide AI decision-making
C) To reduce AI efficiency
D) To eliminate AI in high-risk areas
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