Responsible AI Essentials

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Key concepts in AI safety and ethics.

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Yusra Mukhtar

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Responsible AI Essentials


Responsible AI EssentialsVersión en línea Key concepts in AI safety and ethics. por Yusra Mukhtar 1 What is the primary goal of AI safety? a Increase profit margins b Prevent harm to people and property c Speed up coding only d Maximize model size 2 Which practice reduces bias in AI systems? a Relying on random sampling b Diverse, representative training data c Eliminating all tests d Using only a single dataset 3 Which is a risk of deploying LLMs in daily life? a Overfitting on tiny datasets b Misinformation and hallucinations c No energy usage d Always correct outputs 4 How can user privacy be protected with AI? a Share all inputs for accuracy b Use only public data c Disable all security measures d Minimize data collection and use strong anonymization 5 What is an ethical guideline for AI developers? a Never test with real users b Hide failure modes c Explainability to end-users d Prioritize aesthetics over safety 6 Which approach helps prevent misuse of AI? a Open publishing of all prompts b Publicly sharing model internals c Access controls and usage policies d Ignoring potential harms 7 Why is ongoing evaluation important for AI in daily life? a To detect drift and new safety issues b Because it looks impressive c To replace human judgment completely d It’s optional and rarely useful 8 What should users do when an AI output seems wrong? a Assume it’s always correct b Delete the data and move on c Ignore it if convenient d Verify with trusted sources 9 What does alignment mean in AI ethics? a AI aligns its coffee mug portals b AI sings to data for harmony c AI behavior matches human values d AI wears a tie to work 10 What is prompt injection in simple terms? a Tricking the model to reveal hidden behavior b Asking it to water the plants c Teaching it to juggle data d Giving it a smoothie recipe 11 What is AI hallucination? a AI grows a mustache on screen b AI sprinkles cinnamon on outputs c AI makes up false facts or details d AI learns to ride a bicycle 12 What should you do with sensitive data in training? a Share publicly to test bravery b Anonymize and minimize exposure c Photograph it for a yearbook d Translate it into pirate slang 13 What does explainability mean in AI? a The AI wearing sunglasses b The model writing poetry daily c The model giving a TED Talk d Being able to explain how decisions are made 14 What is responsible AI practice? a Always printing the outputs in comic sans b Only training with donuts nearby c Letting AI decide breakfast every day d Designing systems that are safe, fair, and transparent 15 How can you reduce AI misuse in daily life? a Install more fictional batteries b Use guardrails and user consent c Train it to tell sneaky jokes d Let it run your entire calendar without checks

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Responsible AI EssentialsVersión en línea

por Yusra Mukhtar

What is the primary goal of AI safety?

Which practice reduces bias in AI systems?

Which is a risk of deploying LLMs in daily life?

How can user privacy be protected with AI?

What is an ethical guideline for AI developers?

Which approach helps prevent misuse of AI?

Why is ongoing evaluation important for AI in daily life?

What should users do when an AI output seems wrong?

What does alignment mean in AI ethics?

What is prompt injection in simple terms?

What is AI hallucination?

What should you do with sensitive data in training?

What does explainability mean in AI?

What is responsible AI practice?

How can you reduce AI misuse in daily life?