Practice Transparency And Accountability (32.17.2) - , AI-Driven Decision-Making in Civil Engineering Projects

Practice: Transparency and Accountability

Lesson 32.17.232, AI-Driven Decision-Making in Civil Engineering Projects

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9 questions

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4 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does transparency in AI mean?
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Think about how well we can see the reasons behind decisions.
Question 2.
Define accountability in the context of AI.
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Who is responsible if things go wrong?
3Question 3.
What is Explainable AI (XAI)?
- A AI model that functions without human oversight
- AI methods for understanding decision-making
- An AI that predicts outcomes
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It clarifies the workings of AI.
4Question 4.
True or False: Accountability ensures there are no consequences for AI mistakes.
- True
- False
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Think about who is responsible for AI outcomes.
Question 5.
Provide a detailed explanation of how failure to implement transparent AI could impact a civil engineering project.
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Think about the effects on communication and trust.
Question 6.
Analyze the effects of having insufficient audit trails in an AI-driven project.
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Consider what audit trails are meant to accomplish in terms of decision-making clarity.

5 more questions in this section. Enroll free to practise them all.