Ethical Considerations in Al — Flashcards
ICSE · Class 9 · Robotics & Artificial Intelligence
36 flashcards for Ethical Considerations in Al (ICSE Class 9 Robotics & Artificial Intelligence) to test yourself on key terms and facts.
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What is ethics in AI?
Answer
Ethics in AI means using artificial intelligence in a way that is morally right, fair, and responsible. It focuses on right and wrong behavior, human values, and the effect of AI on people and society…
What are the three major ethical concerns in AI?
Answer
The three major ethical concerns are privacy and surveillance, bias and discrimination, and the role of human judgment. These are important because AI can affect personal data, fairness, and human dec…
Why is privacy important in AI?
Answer
Privacy is important because AI systems may collect, store, or use personal information. If data is misused, people can lose control over their own information. Good AI should respect privacy and use …
What is bias in AI?
Answer
Bias in AI means unfair preference or unfair treatment caused by the data or design of the system. AI can repeat human prejudice if it is trained on biased data or developed without care.
Why can AI become biased even though machines do not have feelings?
Answer
AI can become biased because it learns from data created by humans. If the data contains unfair patterns, the machine may repeat them. So the bias often comes from people and data, not from the machin…
What is the role of human judgment in AI?
Answer
Human judgment is important because AI should not fully replace human thinking in sensitive decisions. In many situations, people need to check, explain, and correct machine decisions.
What does it mean for AI to be socially beneficial?
Answer
AI should help society and improve life in useful ways. It should support areas like healthcare, education, safety, transport, and farming, while keeping risks lower than benefits.
What does it mean to avoid creating or reinforcing unfair bias?
Answer
It means AI should not treat people unfairly because of race, gender, religion, income, ability, or other sensitive traits. A fair system should not increase existing inequalities.
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