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The Evolution of Ethical Standards and Guidelines in AI
Abstract
AI ethics focuses on the systematic study of what is right and wrong, with the aim of providing principles to resolve ethical dilemmas. AI products, such as deepfakes, have raised concerns about their potential to disrupt traditional industries, devalue human work, and threaten intellectual property rights. AI ethics are intertwined with the need for an understanding of potential risks and benefits. We can categorize AI ethics into principles-based, processes-based, and ethical consciousness approaches. Key themes emerging from AI ethics include transparency, justice, fairness, non-maleficence, responsibility and accountability, privacy, beneficence, freedom and autonomy, trust in AI, dignity, sustainability, and solidarity. The development of AI ethics requires defining universally applicable guidelines and promoting global collaboration. Collaboration between industry, academia, and the public is critical for detecting and evaluating AI-generated content, addressing the social and economic impacts of AI displacements, and building public trust in AI technologies.
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