A security team is conducting an AI risk assessment for a new AI-powered hiring tool. They discover the model produces statistically different outcomes for candidates from different demographic groups. Which ethical AI principle is violated and what is the required remediation approach?

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A. Fairness — the model exhibits bias that must be addressed through bias auditing, dataset rebalancing or debiasing, and ongoing fairness metric monitoring. Statistically different outcomes by demographic group indicate algorithmic bias, violating the fairness principle of ethical AI. Remediation requires bias auditing, addressing root causes in data or model design, and implementing ongoing fairness monitoring. The SecAI+ objectives include ensuring responsible AI use and applying ethical guidelines. Confidentiality, availability, and integrity are CIA triad concepts related to information security, not the bias issue described.

A security team is conducting an AI risk assessment for a new AI-powered hiring tool. They discover the model produces statistically different outcomes for candidates from different demographic groups. Which ethical AI principle is violated and what is the required remediation approach?

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