Published by European Commission in Key requirements for trustworthy AI, Apr 8, 2019

To promote the responsible use of data and ensure its integrity at every stage, industry has a responsibility to understand the parameters and characteristics of the data, to demonstrate the recognition of potentially harmful bias, and to test for potential bias before and throughout the deployment of AI systems. AI systems need to leverage large datasets, and the availability of robust and representative data for building and improving AI and machine learning systems is of utmost importance.

Published by Information Technology Industry Council (ITI) in AI Policy Principles, Oct 24, 2017

Artificial intelligence should be auditable and traceable. We are committed to confirming test standards, deployment processes and specifications, ensuring algorithms verifiable, and gradually improving the accountability and supervision mechanism of artificial intelligence systems.

Published by Youth Work Committee of Shanghai Computer Society in Chinese Young Scientists’ Declaration on the Governance and Innovation of Artificial Intelligence, Aug 29, 2019

Published by United Nations Children's Fund (UNICEF) and the Ministry of in Requirements for child-centred AI, Sep 16, 2020

The department's AI capabilities will be developed and deployed such that relevant personnel possess an appropriate understanding of the technology, development processes and operational methods applicable to AI capabilities, including with transparent and auditable methodologies, data sources and design procedures and documentation.

Published by Department of Defense (DoD), United States in DoD's AI ethical principles, Feb 24, 2020