A developer is proposing a new AI application for human resources systems.

Option B is correct because a human resources AI application processes highly sensitive employee and applicant information and may influence consequential employment decisions. Privacy and security therefore determine whether the system can be deployed responsibly. The design must address data minimization, lawful collection, access control, encryption, retention, auditability, secure model integration, and protection against unauthorized disclosure. It should also evaluate whether training data or outputs expose protected or confidential information and whether human review is required before decisions affect candidates or employees. Option A concerns friendliness and presentation, not the protection of people or organizational data. Option C may improve usability, but visual design cannot compensate for insecure handling of resumes, performance records, or identity data. Option D can make outputs easier to consume, yet brevity and summarization do not control privacy risk or system compromise. The NIST AI Risk Management Framework identifies privacy enhancement, security, resilience, accountability, and transparency as characteristics of trustworthy AI, making privacy and security the controlling considerations in this scenario.

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