Ethics & Principles
9 resources in this section
AI Transparency — Disclosure and Documentation Requirements
Definición técnica AI transparency is the obligation and practice of providing clear, accurate, and accessible information about AI systems — their…
Algorithmic Bias: where structural inequality enters the model output
Algorithmic bias creates unfair outcomes for specific groups. Zertia audits bias detection under ISO 42001 + EU AI Act Articles 10 and 14.
Disparate Impact — Algorithmic Discrimination in AI Decision Systems
Definición técnica What is disparate impact in AI decision systems? Disparate impact is a legal and analytical concept describing the situation in which…
Explainable AI (XAI) — AI Decision Transparency and Interpretability
Definición técnica Explainable AI (XAI) refers to methods, techniques, and design principles that make the decisions, predictions, and behavior of AI…
Fairness in AI — Equitable Outcomes and Non-Discrimination Requirements
Definición técnica Fairness in AI refers to the requirement that AI systems treat individuals and groups equitably, without producing discriminatory…
Human Oversight — Genuine AI Supervision Requirements
Definición técnica What is human oversight in AI systems? Human oversight in AI refers to the requirement that AI systems — particularly those making…
Responsible AI: where principles become operational practice
Responsible AI operationalizes ethics. Zertia audits under ISO 42001. Definición técnica Responsible AI is a structured governance and ethical framework en…
Trustworthy AI — Seven Requirements for AI Systems
Definición técnica Trustworthy AI refers to AI systems that exhibit properties that make them worthy of human and institutional trust: they are lawful…
Watermarking (AI) — Content Provenance and EU AI Act Article 50 Compliance
Definición técnica What is watermarking in AI-generated content? Watermarking in AI is the practice of embedding a detectable signal in AI-generated…
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