The Ethics of AI Ethics -- An Evaluation of Guidelines

There is significant consensus on core AI ethics principles across guidelines. The paper identifies substantial overlap in ethical principles across multiple AI ethics guidelines, suggesting broad agreement in the field on fundamental values like fairness, transparency, and accountability—though the specific interpretation and implementation of these principles varies.

Major gaps exist between ethical principles and actual practice. The paper finds a critical implementation gap: while guidelines articulate clear ethical principles and recommendations, these are often not effectively translated into the actual research, development, and deployment of AI systems in practice.

Current guidelines have notable omissions that limit their comprehensiveness. Beyond areas of agreement, the paper identifies specific gaps and omissions in existing guidelines, suggesting that current ethical frameworks may not adequately address all relevant concerns or stakeholder perspectives in AI development.

Implementation effectiveness requires more than principle statements. The paper emphasizes that simply publishing ethical guidelines is insufficient; improving the real-world impact of AI ethics demands concrete mechanisms to ensure principles are actually followed during the development and deployment phases of AI systems.

The field needs clearer pathways from ethics to practice. The paper suggests that closing the gap between ethical ideals and implementation requires better frameworks, accountability structures, and practical guidance for translating abstract principles into specific organizational and technical practices.