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Session 6 Quiz

Test What You Learned!

8 questions about Session 6: Data and Fairness. Get 6+ right to pass!

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Progress

1

Is data always objective and fair?

  • Yes — numbers cannot be biased
  • No — human choices in collection and analysis can introduce bias
  • Only government data is fair
  • Data is always fair if a computer processes it
2

What happens when certain groups are missing from data?

  • Nothing — missing data does not matter
  • Decisions based on that data may ignore their needs and harm them
  • The data becomes more accurate
  • Missing groups chose not to participate
3

How do algorithms become biased?

  • They cannot — computers are neutral
  • By learning from historical data that contains past discrimination
  • Only if programmers are biased
  • Algorithms are always fair
4

What is Amana in the context of data?

  • A type of database
  • The principle that information is a trust to be handled with care and honesty
  • A data collection method
  • A software program
5

Who is responsible when an algorithm makes an unfair decision?

  • Nobody — it is the computer's fault
  • The humans who designed the system, chose the data, and deployed it
  • The people affected by the decision
  • The government
6

What does transparency mean in data use?

  • Making data invisible
  • Showing your methods openly so others can check your work
  • Using transparent colors on graphs
  • Keeping methods secret
7

Can algorithmic bias be fixed?

  • No — it is impossible
  • Yes — through awareness, diverse teams, fairness testing, and ongoing monitoring
  • Only by stopping all algorithms
  • It fixes itself over time
8

What should a responsible data user always ask?

  • How can I make the data look good?
  • Who might be harmed by how this data is collected, analyzed, or used?
  • How can I finish faster?
  • What data should I hide?