A bank's compliance team is rolling out an automated loan-decision system and sets two requirements: first, the system must be able to give each applicant a clear, understandable reason for its decision that they can review and contest; second, the system must keep working correctly and safely even when it receives unusual or edge-case applications it was not explicitly trained on. Which two Microsoft responsible AI principles do these requirements most directly reflect? (Select TWO.)

The correct choices are the transparency principle and the reliability and safety principle. Transparency is the principle that AI systems should be understandable, including providing explanations for decisions that affect people, which directly matches the requirement that applicants receive a clear, contestable reason for each decision. Reliability and safety is the principle that AI systems should perform consistently and safely across the range of conditions they may encounter, including situations not explicitly covered in training, which matches the requirement that the system keep functioning correctly on unusual or edge-case applications. The fairness principle is incorrect because fairness concerns whether the system treats individuals and groups equitably and avoids reinforcing discrimination, which is a distinct concern from explaining decisions or handling edge cases robustly; the scenario does not mention comparing outcomes across demographic groups. The privacy and security principle is incorrect because privacy and security concerns protecting applicants' personal data from unauthorized access or misuse, which is unrelated to either explaining a decision or handling unfamiliar inputs safely. Because the two stated requirements map specifically to explainability and to robust, safe operation under uncertainty rather than to equitable treatment or data protection, transparency and reliability and safety are the principles being described.