Safe and Ethical AI (SEA) Platform Network · Linking Artificial Intelligence Principles (LAIP)

· 1) Accountability:

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.

Principle: Chinese Young Scientists’ Declaration on the Governance and Innovation of Artificial Intelligence, Aug 29, 2019

Published by Youth Work Committee of Shanghai Computer Society

Related Principles

· Article 6: Transparent and explainable.

Continuously improve the transparency of artificial intelligence systems. Regarding system decision making processes, data structures, and the intent of system developers and technological implementers: be capable of accurate description, monitoring, and reproduction; and realize explainability, predictability, traceability, and verifiability for algorithmic logic, system decisions, and action outcomes.

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

3. Artificial intelligence systems transparency and intelligibility should be improved, with the objective of effective implementation, in particular by:

a. investing in public and private scientific research on explainable artificial intelligence, b. promoting transparency, intelligibility and reachability, for instance through the development of innovative ways of communication, taking into account the different levels of transparency and information required for each relevant audience, c. making organizations’ practices more transparent, notably by promoting algorithmic transparency and the auditability of systems, while ensuring meaningfulness of the information provided, and d. guaranteeing the right to informational self determination, notably by ensuring that individuals are always informed appropriately when they are interacting directly with an artificial intelligence system or when they provide personal data to be processed by such systems, e. providing adequate information on the purpose and effects of artificial intelligence systems in order to verify continuous alignment with expectation of individuals and to enable overall human control on such systems.

Published by 40th International Conference of Data Protection and Privacy Commissioners (ICDPPC) in Declaration On Ethics And Data Protection In Artifical Intelligence, Oct 23, 2018

3. Clear responsibility

The development of artificial intelligence should establish a complete framework of safety responsibility, and we need to innovate laws, regulations and ethical norms for the application of artificial intelligence, and clarify the mechanism of identification and sharing of safety responsibility of artificial intelligence.

Published by Shanghai Advisory Committee of Experts on Artificial Intelligence Industry Security in Shanghai Initiative for the Safe Development of Artificial Intelligence, Aug 30, 2019

· 1) Robustness:

Artificial intelligence should be safe and reliable. We are dedicated to accentuating technical robustness and security throughout the research process, providing a secure and reliable system to improve the ability to prevent attack and conduct self repair.

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

· 2) Transparency:

Artificial intelligence should be transparent and interpretable. We are committed to conducting open source and interpretative research, reducing research on blind black box algorithm, and enhancing multi layered transparency, thus attesting to the compliance with the proposed framework of ethics.

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