Artificial Intelligence MCQ

Q: Which of the following is a genuine ethical risk of AI systems?

Correct answer: Amplifying bias present in training data. Models trained on biased historical data can reproduce and amplify discrimination — a documented, real risk.

Q: The three main drivers of the modern AI boom are:

Correct answer: Big data, powerful hardware and better algorithms. Abundant data, GPU computing power and algorithmic advances together enabled the deep learning era.

Q: Which question sequence best cuts through 'AI-powered' marketing claims?

Correct answer: What data? What prediction? Who acts on it?. Every genuine AI system reduces to data in, prediction out, action around it.

Q: Fraud detection in digital wallets is an example of:

Correct answer: Real-time prediction scoring transactions. Models score each transaction's risk in milliseconds — classic applied prediction.

Q: Most AI project effort is typically consumed by:

Correct answer: Data collection, cleaning and labelling. Data work dominates real projects; algorithms are the small visible tip.

AI concepts, machine learning, generative AI and prompt engineering.

Q11. Which of the following is a genuine ethical risk of AI systems? Medium

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Q12. The three main drivers of the modern AI boom are: Medium

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Q13. Which question sequence best cuts through 'AI-powered' marketing claims? Medium

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Q14. Fraud detection in digital wallets is an example of: Medium

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Q15. Most AI project effort is typically consumed by: Medium

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Q16. Before celebrating a model's results you should first: Medium

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Q17. A 99%-accurate model can still be worthless when: Medium

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Q18. Model 'drift' refers to: Medium

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Q19. What fundamentally distinguishes generative AI from classical (discriminative) AI? Medium

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Q20. In an LLM, a 'token' is: Medium

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