Practice Bias And Fairness In Algorithms (34.5) - 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 influences AI decisions.
Question 2.
Name one way to reduce algorithmic bias.
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Consider types of data used in training.
3Question 3.
What is the main issue with algorithmic bias?
- It results from too much data
- It leads to unfair treatment
- It improves decision accuracy
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Think about the effect of data bias.
4Question 4.
True or False: Using diverse datasets can help reduce bias in AI.
- True
- False
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Consider the variety of input data used.
Question 5.
Evaluate a real-world AI application in terms of its risk of algorithmic bias. Propose improvements.
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Identify cases like facial recognition systems and their downsides.
Question 6.
Design a bias-detection algorithm for a new AI product focused on recruitment. What metrics will you use, and how will you implement it?
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Consider tracking hiring rates across demographics.

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