Practice Data Bias (15.7.1) - Natural Language Processing (NLP)

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8 questions

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6 questions · about 4 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is data bias?
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Think about how your background can influence your understanding.
Question 2.
Give an example of how data bias can occur in hiring.
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Consider what kind of job applications are out there.
3Question 3.
What does data bias mean?
- AI is always accurate
- AI can reflect societal biases
- Data is always unbiased
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Think of examples where this could go wrong.
4Question 4.
True or False: Data diversity can lessen AI bias.
- True
- False
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Remember how different views can affect conclusions.
Question 5.
Consider a financial AI tool that suggests loans but is trained on data from a predominantly wealthy demographic. What bias might be present, and how would this affect outcomes for borrowers from different backgrounds?
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Think of societal impact and systemic issues.
Question 6.
Examine the role of transparency in AI usage. How can companies implement transparency principles to address data bias in their AI systems?
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Consider existing frameworks and reporting standards.

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