Governance

AI Ethics

Definition

The application of moral principles—fairness, accountability, transparency, non-maleficence, and human dignity—to the design, development, and deployment of AI systems. AI ethics provides the normative foundation that regulations like the EU AI Act translate into enforceable obligations.

Related Terms

AI Governance

The framework of policies, processes, roles, and controls that ensure AI systems are developed, deployed, and used responsibly and in compliance with applicable law. AI governance spans ethics, bias, privacy, security, and regulatory compliance across the model lifecycle.

Algorithmic Bias

Systematic and repeatable errors in algorithmic outputs that create unfair advantages or disadvantages for individuals or groups based on protected characteristics. Algorithmic bias can arise from biased training data, proxy variables, or flawed evaluation metrics.

Fairness (AI)

The property of an AI system that ensures its outputs and decisions do not systematically disadvantage individuals on the basis of protected characteristics such as gender, ethnicity, or disability. Multiple mathematical definitions of fairness exist and may be in tension with one another.

Knowing the Terms Is Step One. Applying Them Is Step Two.

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