1. . AI ethics is:
(A) Backup only
(B) Encrypting AI systems only
(C) Compressing datasets only
(D) The study and practice of ensuring AI systems are designed and used in a morally responsible way
2. . Bias in AI refers to:
(A) Compressing bias
(B) Encrypting bias
(C) Systematic errors or unfairness in AI predictions due to skewed data or algorithms
(D) Backup only
3. . Fairness in AI aims to:
(A) Backup only
(B) Encrypt fairness
(C) Compress fairness
(D) Ensure AI decisions do not discriminate against individuals or groups
4. . Explainability in AI means:
(A) Backup only
(B) Encrypting explanations
(C) Compressing explanations
(D) Making AI decisions understandable to humans
5. . Transparency in AI involves:
(A) Encrypting transparency
(B) Being open about how AI models make decisions, including data and algorithms used
(C) Compressing transparency
(D) Backup only
6. . Privacy in AI focuses on:
(A) Encrypting privacy
(B) Protecting personal data from misuse or unauthorized access
(C) Compressing data
(D) Backup only
7. . Data anonymization in AI is:
(A) Encrypting anonymized data
(B) Removing personally identifiable information (PII) from datasets
(C) Compressing anonymized data
(D) Backup only
8. . Adversarial attacks on AI are:
(A) Compressing attacks
(B) Encrypting attacks
(C) Attempts to manipulate inputs to deceive or mislead AI models
(D) Backup only
9. . AI robustness refers to:
(A) The ability of AI models to perform reliably under various conditions, including attacks or noise
(B) Encrypting robustness
(C) Compressing robustness
(D) Backup only
10. . Security in AI includes:
(A) Encrypting AI only
(B) Protecting AI systems from cyber threats, data tampering, and unauthorized access
(C) Compressing AI models
(D) Backup only
11. . Differential privacy ensures:
(A) Individual data cannot be identified even when used in statistical models or machine learning
(B) Encrypting data
(C) Compressing privacy
(D) Backup only
12. . Accountability in AI means:
(A) Backup only
(B) Encrypting accountability
(C) Compressing accountability
(D) Responsibility for decisions and actions made by AI systems
13. . Human-in-the-loop AI ensures:
(A) Backup only
(B) Encrypting oversight
(C) Compressing AI decisions
(D) Human oversight in AI decision-making to prevent errors and unethical outcomes
14. . Ethical AI frameworks guide:
(A) Backup only
(B) Encrypting AI ethics
(C) Compressing frameworks
(D) Development, deployment, and governance of AI to ensure fairness, transparency, and privacy
15. . AI model auditing is used to:
(A) Evaluate AI for fairness, accuracy, security, and compliance with regulations
(B) Encrypt audits
(C) Compress audits
(D) Backup only
16. . Data governance in AI refers to:
(A) Encrypting governance
(B) Policies and practices to manage the quality, privacy, and ethical use of data
(C) Compressing governance
(D) Backup only
17. . Explainable AI (XAI) helps to:
(A) Backup only
(B) Encrypt XAI
(C) Compress explanations
(D) Understand how AI models reach decisions to build trust and accountability
18. . AI security threats include:
(A) Backup only
(B) Encrypting threats
(C) Compressing threats
(D) Data poisoning, model inversion, adversarial examples, and unauthorized access
19. . Regulatory compliance in AI ensures:
(A) AI systems follow laws and standards related to privacy, security, and fairness
(B) Encrypting compliance
(C) Compressing compliance
(D) Backup only
20. . The main purpose of AI ethics, security, and privacy is to:
(A) Ensure AI systems are safe, fair, transparent, accountable, and respect human rights
(B) Encrypt all AI models
(C) Compress datasets
(D) Backup only