DSE Ethical Considerations in AI 5 — Questions and Answers
Question 1: The concept of 'value alignment' in AI safety refers to:
- Aligning model weights to minimize loss functions
- Ensuring AI systems pursue goals consistent with human values and intentions (Correct answer)
- Synchronizing model versions across distributed systems
- Matching feature scales before training
Correct answer: Ensuring AI systems pursue goals consistent with human values and intentions
Value alignment ensures that as AI systems become more capable, their objectives remain consistent with what humans actually want and care about.
Question 2: Which scenario best illustrates the 'dual-use' ethical dilemma in AI?
- A language model used for both Spanish and French translation
- Facial recognition developed for accessibility tools also enabling mass surveillance (Correct answer)
- A recommendation algorithm deployed on both mobile and desktop
- Transfer learning applied from image to text tasks
Correct answer: Facial recognition developed for accessibility tools also enabling mass surveillance
Dual-use dilemmas arise when technology developed for beneficial purposes can also be repurposed for harmful applications.
Question 3: Participatory design in AI ethics involves:
- Allowing users to download and modify model weights
- Including affected communities in the design and evaluation of AI systems (Correct answer)
- Running A/B tests with user subgroups
- Publishing model benchmarks for public comment
Correct answer: Including affected communities in the design and evaluation of AI systems
Participatory design brings in the perspectives of people who will be affected by an AI system during its development, improving relevance and reducing harm.
Question 4: A hospital uses an AI triage tool that performs well on average but poorly for elderly patients. Releasing it without disclosing this gap primarily violates which principle?
- Model compression standards
- Transparency and honesty about model limitations (Correct answer)
- The principle of parsimony
- Software licensing requirements
Correct answer: Transparency and honesty about model limitations
Transparency requires disclosing known performance gaps so that clinicians can make informed decisions about when to trust the model.
Question 5: Which of the following best describes 'algorithmic recourse'?
- A method for reverting model updates after deployment
- The ability of individuals to appeal or change outcomes produced by automated systems (Correct answer)
- Automated rollback procedures for ML pipelines
- Legal action against algorithm developers
Correct answer: The ability of individuals to appeal or change outcomes produced by automated systems
Algorithmic recourse gives individuals a meaningful path to contest or reverse automated decisions that negatively affect them.
Question 6: When evaluating fairness in a recidivism prediction model, which of the following is a documented real-world criticism of the COMPAS system?
- It used too few features to make predictions
- It produced higher false positive rates for Black defendants than white defendants (Correct answer)
- It was trained on synthetic data without real criminal records
- It ignored socioeconomic features entirely
Correct answer: It produced higher false positive rates for Black defendants than white defendants
ProPublica's 2016 analysis found COMPAS had significantly higher false positive rates for Black defendants, flagging them as high-risk when they did not reoffend.
Question 7: The principle of 'beneficence' in AI ethics requires that AI systems:
- Operate within defined computational budgets
- Actively promote the well-being of users and society (Correct answer)
- Be open-source to enable peer review
- Minimize the number of model parameters
Correct answer: Actively promote the well-being of users and society
Beneficence obligates AI developers to design systems that do good and improve human welfare, not merely avoid harm.
DSE Ethical Considerations in AI 5
The concept of 'value alignment' in AI safety refers to: