Ética em IA
Definição
A ética de IA cobre princípios (equidade, transparência, responsabilidade, privacidade) e governança for projetoing and deploying AI. It includes codes of conduct, impact assessments, and regulation.
It connects to AI safety (risks, alignment), bias in AI (fairness), and explainable AI (transparency). Regulation (por ex. EU AI Act) is making ethics and impact assessments mandatory for high-risk applications. Organizations and practitioners need to operationalize principles into projeto, evaluation, and deployment practices.
Como funciona
Organizações adotam diretrizes (por ex. princípios de IA responsável) e processos de revisão (por ex. comitês de ética, avaliações de impacto). Regulamentors set requirements (por ex. EU AI Act: risk tiers, transparency, human oversight). Practitioners use checklists (por ex. data provenance, fairness metrics), audits (por ex. 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
A ética e governança de IA se aplicam quando é necessário alinhar sistemas com normas, regulamentação e responsabilidade (impacto, justiça, privacidade).
- Impact assessments and governance for new AI products
- Aligning with regulation (por ex. EU AI Act) and sector codes
- Privacy, fairness, and accountability in projeto and deployment