Computational Thinking and Ethics Quiz - CBSE Class 12 Computer Science

Free practice quiz: Computational Thinking and Ethics (CBSE Class 12 Computer Science). 12 multiple-choice questions with answers and explanations. Play online, no sign-up needed.

This CBSE Class 12 Computer Science practice quiz has 12 multiple-choice questions on Computational Thinking and Ethics, and 12 of them come with an explanation. Try the 5 sample questions below (tap an option to check yourself), then play the full quiz online. No sign-up needed.

Sample questions

1. Which of the following is NOT a core principle of computational thinking?

   1. Decomposition
   2. Pattern Recognition
   3. Abstraction
   4. Randomization
   Show answer

   Answer: D. Randomization

   Randomization is a technique used in programming, but it's not a core principle of computational thinking. Decomposition, pattern recognition, and abstraction are fundamental aspects.

2. Explain the ethical implications of using AI in decision-making processes.

   1. AI is always ethical
   2. AI is never ethical
   3. AI's ethical implications depend on its design, implementation and use. Bias in data can lead to unfair or discriminatory outcomes
   4. AI's ethical implications are not relevant to decision making
   Show answer

   Answer: C. AI's ethical implications depend on its design, implementation and use. Bias in data can lead to unfair or discriminatory outcomes

   The ethics of AI are complex and depend heavily on how it is built and used. Bias in data or algorithms can result in unfair or discriminatory outcomes.

3. Discuss the concept of algorithmic accountability and its importance in ensuring ethical AI.

   1. Algorithmic accountability is unimportant
   2. It is not possible to ensure accountability
   3. It means holding developers and users accountable for the consequences of AI systems, promoting transparency and fairness
   4. It is a concept that is not yet defined
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   Answer: C. It means holding developers and users accountable for the consequences of AI systems, promoting transparency and fairness

   Algorithmic accountability is crucial for ensuring that AI systems are used ethically and responsibly.

4. Evaluate the potential impact of AI on employment and the economy, discussing both positive and negative aspects and potential mitigation strategies.

   1. AI will only have positive impacts
   2. AI will only have negative impacts
   3. AI may lead to job displacement in certain sectors but can also create new opportunities; reskilling and upskilling are crucial
   4. AI has no impact on employment
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   Answer: C. AI may lead to job displacement in certain sectors but can also create new opportunities; reskilling and upskilling are crucial

   AI's economic impact is complex, requiring proactive strategies to address potential job displacement and create new opportunities.

5. Discuss the challenges and opportunities related to the regulation of AI, considering its global nature and rapid evolution.

   1. AI regulation is unnecessary
   2. AI regulation is impossible
   3. Global cooperation and adaptable regulatory frameworks are needed to address the challenges and opportunities posed by AI's rapid evolution
   4. AI regulation is only needed in specific countries
   Show answer

   Answer: C. Global cooperation and adaptable regulatory frameworks are needed to address the challenges and opportunities posed by AI's rapid evolution

   Regulating AI requires international collaboration and frameworks that can adapt to the technology's rapid advancement.

More questions in this quiz

Answers and explanations are in the full quiz.

1. What does abstraction mean in the context of computational thinking?
2. How can we mitigate bias in algorithms used for decision-making?
3. Describe a scenario where the use of AI could lead to a significant ethical dilemma. Analyze the potential consequences and propose solutions to mitigate the negative impacts.
4. Analyze the role of intellectual property rights in the context of software development and AI.
5. Critically examine the concept of 'explainable AI' (XAI) and its importance in building trust and ensuring accountability.
6. Develop a framework for evaluating the ethical implications of a novel AI application, considering factors such as fairness, privacy, transparency, and accountability.
7. Compare and contrast different ethical frameworks applicable to AI development and deployment, such as utilitarianism, deontology, and virtue ethics, and discuss their strengths and limitations in guiding AI decision-making.

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