Ética de la IA
Definición
La ética de la IA cubre principios (equidad, transparencia, responsabilidad, privacidad) y gobernanza for diseñoing and deploying AI. It includes codes of conduct, impact assessments, and regulation.
Se conecta con AI safety (risks, alignment), bias in AI (fairness), and explainable AI (transparency). Regulation (por ej. EU AI Act) is making ethics and impact assessments mandatory for high-risk applications. Organizations and practitioners need to operationalize principles into diseño, evaluation, and deployment practices.
Cómo funciona
Organizations adoptan directrices (por ej. principios de IA responsable) and review processes (por ej. ethics boards, impact assessments). Regulators set requirements (por ej. EU AI Act: risk tiers, transparency, human oversight). Practitioners use checklists (por ej. data provenance, fairness metrics), audits (por ej. bias, safety), and stakeholder input to align systems with ethical norms. Flow: identify use case and risk level → assess impact (who is affected, what could go wrong) → implement safeguards (data, model, explainability, human-in-the-loop) → monitor and iterate. Documentation and accountability (who is responsible for what) are part of governance.
Casos de uso
La ética y gobernanza de IA se aplican cuando se necesita alinear sistemas con normas, regulación y responsabilidad (impacto, equidad, privacidad).
- Impact assessments and governance for new AI products
- Aligning with regulation (por ej. EU AI Act) and sector codes
- Privacy, fairness, and accountability in diseño and deployment