AI AI Engineer: AI System Design and Ethics 1 — Questions and Answers
Question 1: What is 'algorithmic bias' in AI systems?
- Random errors in model predictions
- Systematic and unfair discrimination in AI outputs caused by biased training data or model design (Correct answer)
- High variance in model performance across runs
- Overfitting to training data
Correct answer: Systematic and unfair discrimination in AI outputs caused by biased training data or model design
Algorithmic bias occurs when an AI system produces systematically unfair outcomes for certain groups, often reflecting historical biases in training data.
Question 2: Which principle of responsible AI ensures that stakeholders can understand and interrogate how an AI system makes decisions?
- Scalability
- Explainability and transparency (Correct answer)
- Throughput optimization
- Data compression
Correct answer: Explainability and transparency
Explainability means AI decisions can be understood by humans, while transparency ensures the system's design, data, and limitations are disclosed.
Question 3: What is 'differential privacy' in the context of AI and data science?
- A method to compare two datasets
- A mathematical framework that adds noise to data or computations to protect individual privacy while enabling aggregate analysis (Correct answer)
- Encrypting model weights
- A technique for removing outliers from training data
Correct answer: A mathematical framework that adds noise to data or computations to protect individual privacy while enabling aggregate analysis
Differential privacy provides mathematical guarantees that an individual's data cannot be inferred from model outputs by injecting carefully calibrated noise.
Question 4: In AI system design, what is the purpose of a 'human-in-the-loop' mechanism?
- To replace AI with human workers
- To include human oversight and intervention in AI decision pipelines for critical or uncertain cases (Correct answer)
- To train models using human-labeled data
- To monitor server infrastructure
Correct answer: To include human oversight and intervention in AI decision pipelines for critical or uncertain cases
Human-in-the-loop keeps humans involved in reviewing, correcting, or approving AI decisions, especially where errors have high stakes.
Question 5: What is 'model cards' documentation in responsible AI?
- Business cards for AI engineers
- Structured documents reporting a model's intended uses, performance across subgroups, limitations, and ethical considerations (Correct answer)
- API documentation for model endpoints
- Training configuration files
Correct answer: Structured documents reporting a model's intended uses, performance across subgroups, limitations, and ethical considerations
Model cards, introduced by Google, standardize transparency by documenting a model's purpose, performance benchmarks, fairness evaluations, and known limitations.
Question 6: Which US federal principle guides that AI systems should behave reliably and safely across a range of conditions?
- Accountability
- Reliability and safety (Correct answer)
- Privacy and security
- Inclusiveness
Correct answer: Reliability and safety
Reliability and safety is a core responsible AI principle requiring systems to perform as intended under varied conditions without unintended harmful outcomes.
AI AI Engineer: AI System Design and Ethics 1
What is 'algorithmic bias' in AI systems?