Ethics

Data Science Ethics Q&A

1Why ethics in DS?
Answer: Models can affect people, rights, fairness, and trust.
2What is algorithmic bias?
Answer: Systematic unfair outcomes for specific groups.
3Fairness metrics examples?
Answer: Demographic parity, equal opportunity, equalized odds.
4What is explainability?
Answer: Ability to interpret and justify model decisions.
5Why privacy matters?
Answer: Protects sensitive user information and legal compliance.
6What is consent in data usage?
Answer: Transparent user permission for data collection and purpose.
7What is model transparency?
Answer: Clear documentation of data, assumptions, limits, and risks.
8How reduce ethical risks?
Answer: Bias audits, governance reviews, monitoring, and human oversight.
9What is responsible AI?
Answer: Building AI that is fair, safe, accountable, and beneficial.
10One-line summary?
Answer: Ethical AI combines technical quality with societal responsibility.