AI Ethics is a branch of applied ethics focused on ensuring artificial intelligence systems are developed and used in ways that are fair, transparent, accountable, and beneficial to society. It addresses the moral implications of AI decision-making, bias, privacy, autonomy, and the broader societal impact of AI technologies.
Core principles commonly included in AI ethics frameworks include: Fairness and Non-discrimination (AI systems should not perpetuate or amplify biases), Transparency (AI decision-making processes should be understandable), Accountability (clear responsibility for AI system outcomes), Privacy (respect for individual data rights), Safety and Security (AI systems should be reliable and secure), Human Oversight (meaningful human control over AI decisions), and Beneficence (AI should benefit humanity).
Organizations implement AI ethics through ethics boards or committees, ethical impact assessments for AI projects, bias auditing and fairness testing, explainability requirements for AI decisions, stakeholder engagement processes, and whistleblower protections for AI-related concerns.
Major AI ethics frameworks include the OECD AI Principles, UNESCO Recommendation on AI Ethics, IEEE Ethically Aligned Design, and various corporate AI ethics guidelines.
