AI Basics
AI Mistakes
Bias in AI
Training AI
Ethics
100

What does AI stand for?

Artificial Intelligence

100

Can AI be wrong?

Yes

100

What does bias mean?

Being unfair or favoring one group

100

What is training data?

Information AI learns from

100

What does ethical AI use mean?

Using AI responsibly and honestly

200

AI systems primarily learn from what?

Data (Training Data)

200

What is an AI hallucination?

AI gives incorrect information that sounds great.

200

Where does AI bias usually originate?

Human-created bias

200

How does AI learn patterns?

By analyzing large amounts of data

200

Is using AI to check grammar ethical?

Yes (if works is your own)

300

What is Narrow AI designed to do?

Perform one specific task

300

Why should humans verify AI responses?

AI can be wrong.

300

How can biased data affect AI results?

Produces unfair or inaccurate outcomes

300

Why does data quality matter?

Good data = better predictions

300

Is copying AI work ethical?

No

400

Does AI think like humans?

No - it predicts patterns

400

Why can AI sound confident but be incorrect?

It predicts without understanding truth.

400

Give one example of AI bias.

Facial recognition errors/hiring bias/recommendations

400

What happens with bad training data?

Poor or incorrect results

400

Why does fairness matter in AI?

•Why does fairness matter in AI?

500

Why is AI considered a tool?

Humans control and verify it

500

What is the danger of trusting AI blindly?

You may accept false information.

500

Is bias an AI problem or human problem? Explain.

Human problem - AI learns from human data

500

Who is responsible for AI training?

Humans

500

Who is responsible for ethical AI behavior?

Humans

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