Practice Algorithmic Bias In Automation (34.5.1) - Ethical Considerations in the Use of Automation

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9 questions

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6 sample questions

Question 1.
What is algorithmic bias?
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Think about how data can influence outcomes.
Question 2.
Why is diversity in datasets important?
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What happens if the dataset is only one type of data?
3Question 3.
What is the main cause of algorithmic bias?
- A) Poor AI design
- B) Biased training data
- C) Lack of funding
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Think about what the AI learns from.
4Question 4.
True or False: Algorithmic bias can result in discriminatory outcomes.
- True
- False
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Consider the implications of AI making decisions.
Question 5.
Analyze a case where biased algorithmic decisions led to negative outcomes. Discuss the implications for ethical AI development.
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Look for recent news stories or academic papers discussing bias in algorithms.
Question 6.
Propose a strategy to audit AI systems for bias and discuss how transparency would improve public trust.
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Consider how existing companies handle transparency and what practices they follow.

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