Actively participate in the formulation of international, national, industry, and organizational standards related to artificial intelligence. Enhance the measurability of ethical principles such as security and controllability, transparency and explainability, privacy protection, and diversity and inclusiveness; and simultaneously build corresponding assessment capabilities.

Published by Artificial Intelligence Industry Alliance (AIIA), China in Joint Pledge on Artificial Intelligence Industry Self-Discipline (Draft for Comment), May 31, 2019

Published by Cyberspace Administration of China in Global AI Governance Initiative, October 18, 2023

Principle: AI system designers and builders need to apply a user centric approach to the technology. They need to consider their collective responsibility in building AI systems that will not pose security risks to the Internet and Internet users. Recommendations: Adopt ethical standards: Adherence to the principles and standards of ethical considerations in the design of artificial intelligence, should guide researchers and industry going forward. Promote ethical considerations in innovation policies: Innovation policies should require adherence to ethical standards as a pre requisite for things like funding.

Published by Internet Society, "Artificial Intelligence and Machine Learning: Policy Paper" in Guiding Principles and Recommendations, Apr 18, 2017

　　10. Strengthen the awareness of self discipline. Strengthen self discipline in activities related to AI research and development, actively integrate AI ethics into every phase of technology research and development, consciously carry out self censorship, strengthen self management, and do not engage in AI research and development that violates ethics and morality. 　　11. Improve data quality. In the phases of data collection, storage, use, processing, transmission, provision, disclosure, etc., strictly abide by data related laws, standards and norms. Improve the completeness, timeliness, consistency, normativeness and accuracy of data. 　　12. Enhance safety, security and transparency. In the phases of algorithm design, implementation, and application, etc., improve transparency, interpretability, understandability, reliability, and controllability, enhance the resilience, adaptability, and the ability of anti interference of AI systems, and gradually realize verifiable, auditable, supervisable, traceable, predictable and trustworthy AI. 　　13. Avoid bias and discrimination. During the process of data collection and algorithm development, strengthen ethics review, fully consider the diversity of demands, avoid potential data and algorithmic bias, and strive to achieve inclusivity, fairness and non discrimination of AI systems.

Published by National Governance Committee for the New Generation Artificial Intelligence, China in Ethical Norms for the New Generation Artificial Intelligence, Sep 25, 2021

Published by Republic of Serbia in ETHICAL GUIDELINES FOR THE DEVELOPMENT, APPLICATION AND USE OF RELIABLE AND RESPONSIBLE ARTIFICIAL INTELLIGENCE, Febrary, 2023