Practice Understanding Bias In Ai (2) - AI Ethics, Bias, and Responsible AI

Practice: Understanding Bias in AI

Lesson 2AI Ethics, Bias, and Responsible AI

Practise this section

10 questions

Flashcard drill
4 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
Sign up to start the exercise
Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
Sign up to start the quiz

6 sample questions

Question 1.
What is data bias?
Show hintHide hint
Think about how data representation affects AI.
Question 2.
Name a type of bias that occurs during the labeling process.
Show hintHide hint
Consider who is annotating the data.
3Question 3.
What is data bias in AI?
- Bias introduced by algorithms
- Skewed or incomplete data
- A type of human error
Show hintHide hint
Focus on how data representation matters.
4Question 4.
True or False: Algorithmic bias can arise even from well-intentioned data.
- True
- False
Show hintHide hint
Remember that good intentions do not eliminate the risk of bias.
Question 5.
Design a strategy to mitigate each type of bias discussed. How would you ensure the AI system remains fair and accountable in its decisions?
Show hintHide hint
Think about proactive measures you can take at each stage.
Question 6.
How do real-world implications of these biases affect how AI is perceived by society? Explore the potential consequences of ignoring these issues.
Show hintHide hint
Consider societal trust and fairness in technology.

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