(preamble)

Thomson Reuters will adopt the following Data and AI Ethics Principles to promote trustworthiness in our continuous design, development, and deployment of artificial intelligence (“AI”) and our use of data:
Principle: Data and AI ethics principles, 2023

Published by Thomson Reuters

Related Principles

(Preamble)

The following principles aim to foster both innovation and trust in the design, development and deployment of artificial intelligence (AI) in Aotearoa New Zealand.

Published by the Law, Society and Ethics Working Group of the AI Forum,New Zealand in Trustworthy AI in Aotearoa: The AI Principles, Mar 4, 2020

(Preamble)

This set of norms is formulated in order to deeply implement the “New Generation Artificial Intelligence Development Plan”, to refine and implement the ” Governance Principles for the New Generation Artificial Intelligence”, to enhance the ethical awareness on Artificial Intelligence (AI) and the behavioral awareness of the entire society, to actively guide the responsible AI research, development, and application activities, and to promote healthy development of AI.

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

Chapter 3. The Norms of Research and Development

  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