This set of norms aims to integrate ethics into the entire life cycle of AI, to promote fairness, justice, harmony, safety and security, and to avoid issues such as prejudice, discrimination, privacy and information leakage.

This set of norms aims to integrate ethics into the entire life cycle of AI, to promote fairness, justice, harmony, safety and security, and to avoid issues such as prejudice, discrimination, privacy and information leakage.

This set of norms aims to integrate ethics into the entire life cycle of AI, to promote fairness, justice, harmony, safety and security, and to avoid issues such as prejudice, discrimination, privacy and information leakage.

This set of norms aims to integrate ethics into the entire life cycle of AI, to promote fairness, justice, harmony, safety and security, and to avoid issues such as prejudice, discrimination, privacy and information leakage.

(2) Promoting fairness and justice.

(2) Promoting fairness and justice.

Adhere to shared benefits and inclusivity, effectively protect the legitimate rights and interests of all relevant stakeholders, promote fair sharing of the benefits of AI in the whole society, and promote social fairness and justice, and equal opportunities.

Adhere to shared benefits and inclusivity, effectively protect the legitimate rights and interests of all relevant stakeholders, promote fair sharing of the benefits of AI in the whole society, and promote social fairness and justice, and equal opportunities.

Adhere to shared benefits and inclusivity, effectively protect the legitimate rights and interests of all relevant stakeholders, promote fair sharing of the benefits of AI in the whole society, and promote social fairness and justice, and equal opportunities.

Avoid bias and discrimination.

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.

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.

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.