Page 424 - AI Ver 3.0 Class 11
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8. Why is fairness critical in the context of AI ethics?
a. To accelerate the development of AI technologies
b. To ensure equal distribution of AI resources
c. To maximise AI's impact on environmental sustainability
d. To prevent bias and ensure equitable treatment of individuals
9. What is the purpose of the Moral Machine?
a. To develop autonomous vehicles
b. To explore ethical dilemmas in AI
c. To create interactive decision-making scenarios
d, To quantify societal expectations about AI ethics
10. How do AI and data collaboration benefit decision-making?
a. By replacing human judgment entirely
b. By automating all decision-making processes
c. By identifying patterns and providing insights
d. By increasing the complexity of decision-making tasks
B. Fill in the blanks.
1. AI improves forecasting, helping people prepare for major weather events.
2. The harm from AI isn’t always ; it can be less obvious, like unfairness or discrimination.
3. is a crucial aspect of ethics in AI because it ensures that AI systems treat all individuals and groups
equitably and without bias.
4. in AI is crucial for ensuring that the decisions made by AI systems are understandable to humans.
5. in AI means being open and clear about how AI systems are created, how they work, and what
effects they might have.
6. involves individuals having control over their personal information and avoiding unwarranted
interference in their lives.
7. in AI ethics refers to the capacity of AI systems to perform reliably and accurately across various
conditions, while minimising unintended consequences.
8. AI systems learn to make decisions based on data, which may include biased human decisions or
reflect historical or social inequities.
C. State whether the following statement is true or false.
1. AI systems are incapable of making ethical decisions.
2. An ethical dilemma arises when there is no conflict between moral principles or values.
3. The Moral Machine is a platform designed to explore ethical dilemmas in AI through interactive
decision-making scenarios.
4. Bias testing and auditing should be conducted irregularly to identify biases in AI systems.
5. Training data bias can result in AI systems that do not perform well for underrepresented groups.
6. AI bias can lead to both unethical and unfair consequences in decision-making processes.
422 Touchpad Artificial Intelligence (Ver. 3.0)-XI

