As AI takes center stage in critical sectors, there is a need for strong ethical policies to assure trustworthy and responsible use of such technologies. This chapter will describe the main features of the current global landscape for AI ethics, introduced by leading frameworks, for example, the UNESCO agreement among 193 countries and the new AI law from the EU by comparing policy documents, implementation reports, and industry surveys from Europe, the United States, Singapore, China, and international organizations. Thus emerged five shared principles: transparency, fairness, human oversight, data protection, and security. There is commonality around these principles. Implementing them is an issue. The rise of generative artificial intelligence adds layers of complexity, demanding updates to existing arrangements so they can better tackle issues like synthetic content and dual-use risks. Strong ethical principle consensus worldwide is found herein while gaps in the implementation persist. Findings give a direct path toward action to professionals who work in the field of AI ethics.

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Ethical Principles and Global Guidelines for Trustworthy AI Systems

  • Latha Ramamoorthy

摘要

As AI takes center stage in critical sectors, there is a need for strong ethical policies to assure trustworthy and responsible use of such technologies. This chapter will describe the main features of the current global landscape for AI ethics, introduced by leading frameworks, for example, the UNESCO agreement among 193 countries and the new AI law from the EU by comparing policy documents, implementation reports, and industry surveys from Europe, the United States, Singapore, China, and international organizations. Thus emerged five shared principles: transparency, fairness, human oversight, data protection, and security. There is commonality around these principles. Implementing them is an issue. The rise of generative artificial intelligence adds layers of complexity, demanding updates to existing arrangements so they can better tackle issues like synthetic content and dual-use risks. Strong ethical principle consensus worldwide is found herein while gaps in the implementation persist. Findings give a direct path toward action to professionals who work in the field of AI ethics.