AI Bias Quiz

What is AI bias?

• When an AI tool makes a decision that is wrong or problematic because it learned from training data that didn't treat all people, places, and things accurately

• When an AI tool makes a decision that is always correct

• When an AI tool makes a decision based on random data

• When an AI tool makes a decision based on testing data

What is training data?

• The information used to test the AI's speed

• The information used to confuse the AI

• The information given to an AI to help it learn how to do a specific task

• The information used to check whether the AI that was created is reliable and accurate

What is testing data?

• The information used to confuse the AI

• The information given to an AI to help it learn how to do a specific task

• The information used to test the AI's speed

• The information used to check whether the AI that was created is reliable and accurate

What are some ways to reduce the AI bias of the fruit detector?

• Show it more examples of things that are NOT fruits so that it can become better at identifying what IS a fruit

• Show it more examples of other kinds of fruits (e.g. mangoes, kiwis, watermelons, grapefruits)

• Show it pictures of fruits at different stages (different size, ripe vs. unripe, etc.)

• All of the above

What kind of images would you include as a part of the training data for an AI tool that can identify weather conditions?

• Sky conditions: blue skies, partly cloudy, mostly cloudy, overcast

• All of the above

• Times of day: sunrise, morning light, afternoon life, sunset, night

• Seasons: spring, summer, fall, winter

What is the key to reducing AI bias?

• Creating random training data

• Creating biased training data

• Creating as little training data as possible

• Creating as diverse and complete a set of training data as possible

What is the purpose of the AI tool you had to create at the end of our lesson?

• To identify different types of vehicles

• To identify different types of animals

• To identify different types of fruits

• To identify weather conditions

What is the best way to limit the chance for AI bias in an AI tool?

• Creating as little data as possible

• Creating random data

• Creating biased data

• Creating as complete of a data set as possible

What was the main bias the AI had when identifying fruits?

• It confused apples and bananas.

• It mislabeled fruit.

• It thought every red fruit was an apple.

• It misspelled the fruit names.

What data would you put into the AI if you were training it to identify weather conditions?