undermining the credibility and reputation of organizations committed to human rights advocacy. 〈Section 2-2) Critical Review of Bias and Stereotypes〉 addresses guidelines aimed at reducing these risks. Fourth, the use of generative AI must not compromise personal data protection or security. Issues of privacy and security are critical across all digital activities, and the use of generative AI is no exception. In particular, when relying on external commercial generative AI services, data entered through prompts is inevitably transmitted to the service provider, giving rise to potential security risks. Moreover, data provided to AI companies in this way may later be used for AI training purposes and, as a result, could be exposed through outputs generated for other users in the course of deploying AI products. 〈Section 2-3) Data Protection and Security〉 sets out specific guidelines to address these risks. In addition, each organization’s existing data protection and security policies should be reviewed and updated to take into account the use of generative AI. Fifth, where generative AI has played a substantive role in producing an output, or where its use may cause confusion, it is necessary to transparently disclose whether and how generative AI was used. In the context of AI, the concepts of transparency and explainability encompass multiple dimensions. First, people should be able to recognize when they are interacting with an AI system. Second, AI-driven decisions should be traceable and explainable. Generative AI Guide for Civil Society