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Question 1: What term describes AI producing false information presented as fact?
- Prompting
- Hallucination
- Bias
- Iteration
Answer: B. Hallucination
Explanation: AI hallucination occurs when a generative model produces false or misleading information that is presented as fact but lacks grounding in reality, requiring users to verify all generated outputs carefully.
Question 2: What is the text or instruction provided to an AI to trigger a response?
- Dataset
- Feedback
- Prompt
- Algorithm
Answer: C. Prompt
Explanation: A prompt is the specific text, question, or instruction provided to an AI system to trigger a specific response or action, serving as the primary interface for user interaction.
Question 3: What is the practice of refining instructions to improve AI output?
- Data mining
- Prompt engineering
- Model training
- Bias testing
Answer: B. Prompt engineering
Explanation: Prompt engineering is the systematic practice of designing and optimizing instructions to guide AI models toward generating more accurate, relevant, and meaningful responses based on the user's specific needs.
Question 4: Which information should you avoid sharing with generative AI tools?
- Social security numbers
- Public news
- Historical dates
- General trivia
Answer: A. Social security numbers
Explanation: Users should always avoid sharing sensitive personal information, such as social security numbers or financial data, when interacting with generative AI tools to protect their privacy and data security.
Question 5: What is the process of adjusting prompts based on AI feedback?
- Model debugging
- System auditing
- Iterative prompting
- Data scraping
Answer: C. Iterative prompting
Explanation: Iterative prompting is a systematic process of refining and adjusting prompts based on AI feedback to improve the relevance, accuracy, and depth of the outputs generated by the model.
Question 6: Why should users review AI outputs for fairness?
- To format text
- To avoid bias
- To check speed
- To save storage
Answer: B. To avoid bias
Explanation: AI models are trained on vast datasets and can inadvertently perpetuate biases present in that training data, requiring users to review outputs for fairness and potential inaccuracies or stereotypes.
Question 7: What is the best way to ensure the accuracy of AI-generated content?
- Cross-referencing sources
- Trusting the AI
- Using only one tool
- Ignoring the output
Answer: A. Cross-referencing sources
Explanation: Validating AI-generated content by cross-referencing it with reputable, independent sources is essential to ensure accuracy and prevent the spread of misinformation, as AI models can sometimes produce incorrect information.
Question 8: How should AI be used in an educational setting?
- As the sole teacher
- As a replacement
- As a complement
- As a grading tool
Answer: C. As a complement
Explanation: In educational settings, it is recommended to keep humans central by using AI as a complementary tool rather than a replacement for educator judgment, ensuring learning remains guided by humans.
Question 9: What should you review before sharing data with an AI tool?
- Privacy policy
- Marketing ads
- User reviews
- Software version
Answer: A. Privacy policy
Explanation: To protect data privacy, users should review an AI tool's privacy policy to understand how their data is collected, stored, and used before sharing any information with the system.
Question 10: What can generative AI create in response to a prompt?
- Biological cells
- Hardware parts
- Original content
- Physical goods
Answer: C. Original content
Explanation: Generative AI is a type of artificial intelligence that can create original content such as text, images, video, audio, or software code in response to a user's prompt.