Which is NOT a core principle of Responsible AI?

• A. Fairness
• B. Accountability
• C. Transparency
• D. Optimization

Answer: (D)

This item tests recognizing which element isn’t a guiding value for guiding AI behavior. In Responsible AI, the focus is on how the system affects people and society: ensuring fairness so outcomes aren’t biased, assigning accountability so someone is responsible for AI decisions, and providing transparency so users can see how decisions are made and hold systems to account. These principles help build trust and governance around AI.

Optimization, on the other hand, is about improving performance metrics—making the model more accurate, faster, or cheaper to run. It’s a technical objective rather than a normative guideline about ethics or responsibility. While optimizing a model is important, it doesn’t by itself define how the system should behave with respect to fairness, accountability, or openness. In some cases, pursuing optimization could even conflict with those principles if not properly constrained, which is why it isn’t considered a foundational principle of Responsible AI.