· 6. Uphold high standards of scientific excellence.

Technological innovation is rooted in the scientific method and a commitment to open inquiry, intellectual rigor, integrity, and collaboration. AI tools have the potential to unlock new realms of scientific research and knowledge in critical domains like biology, chemistry, medicine, and environmental sciences. We aspire to high standards of scientific excellence as we work to progress AI development. We will work with a range of stakeholders to promote thoughtful leadership in this area, drawing on scientifically rigorous and multidisciplinary approaches. And we will responsibly share AI knowledge by publishing educational materials, best practices, and research that enable more people to develop useful AI applications.
Principle: Artificial Intelligence at Google: Our Principles, Jun 7, 2018

Published by Google

Related Principles


Artificial intelligence is an important driving force for a new round of scientific and technological revolution and industrial transformation, which will bring revolutionary changes to people's production methods and lifestyles. Establish a correct view of artificial intelligence development; clarify the basic principles and operational guides for the development and use of artificial intelligence; help to build an inclusive and shared, fair and orderly development environment; and form a sustainable development model that is safe secure, trustworthy, rational, and responsible. As enterprises, universities, research institutes, and industry organizations that research, design, manufacture, operate, and service artificial intelligence; to promote ethics and self discipline in China's artificial intelligence industry; to guide and standardize the behavior of practitioners; we make the following commitments:

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

· (7) Innovation

To realize Society 5.0 and continuous innovation in which people evolve along with AI, it is necessary to account for national, industry academia, and public private borders, race, sex, nationality, age, political and religious beliefs, etc. Beyond these boundaries, through a Global perspective we must promote diversification and cooperation between industry academia public private sectors, through the development of human capabilities and technology. To encourage mutual collaboration and partnership between universities, research institutions and private sectors, and the flexible movement of talent. To implement AI efficiently and securely in society, methods for confirming the quality and reliability of AI and for efficient collection and maintenance of data utilized in AI must be promoted. Additionally, the establishment of AI engineering should also be promoted. This engineering includes methods for the development, testing and operation of AI. To ensure the sound development of AI technology, it is necessary to establish an accessible platform in which data from all fields can be mutually utilized across borders with no monopolies, while ensuring privacy and security. In addition, research and development environments should be created in which computer resources and highspeed networks are shared and utilized, to promote international collaboration and accelerate AI research. To promote implementation of AI technology, governments must promote regulatory reform to reduce impeding factors in AI related fields.

Published by Cabinet Office, Government of Japan in Social Principles of Human-centric AI (Draft), Dec 27, 2018

Rigorous and evidence based

Our technical research has long conformed to the highest academic standards, and we’re committed to maintaining these standards when studying the impact of AI on society. We will conduct intellectually rigorous, evidence based research that explores the opportunities and challenges posed by these technologies. The academic tradition of peer review opens up research to critical feedback and is crucial for this kind of work.

Published by DeepMind in DeepMind Ethics & Society Principles, Oct 3, 2017 (unconfirmed)

· 3.2 Science, Technology, Engineering and Math (STEM) Education

Current and future workers need to be prepared with the necessary education and training to help them succeed. We recognize that delivering training is critical and will require significant investment, not only in STEM education, but also in understanding human behavior via the humanities and social sciences. To ensure employability of the workforce of the future, the public and private sectors should work together to design and deliver work based learning and training systems, and advance approaches that provide students with real work experiences and concrete skills. In conjunction, prioritizing diversity and inclusion in STEM fields, and in the AI community specifically, will be a key part in ensuring AI develops in the most robust way possible.

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