· Subdivision and Implementation

Various fields and scenarios of AI applications should be actively considered for further formulating more specific and detailed guidelines. The implementation of such principles should also be actively promoted – through the whole life cycle of AI research, development, and application.
Principle: Beijing AI Principles, May 25, 2019

Published by Beijing Academy of Artificial Intelligence (BAAI); Peking University; Tsinghua University; Institute of Automation, Chinese Academy of Sciences; Institute of Computing Technology, Chinese Academy of Sciences; Artifical Intelligence Industry Innovation Strategy Alliance (AITISA); etc.

Related Principles

· 2.3 Shaping an enabling policy environment for AI
a) Governments should promote a policy environment that supports an agile transition from the research and development stage to the deployment and operation stage for trustworthy AI systems. To this effect, they should consider using experimentation to provide a controlled environment in which AI systems can be tested, and scaled up, as appropriate. b) Governments should review and adapt, as appropriate, their policy and regulatory frameworks and assessment mechanisms as they apply to AI systems to encourage innovation and competition for trustworthy AI.

Published by G20 Ministerial Meeting on Trade and Digital Economy in G20 AI Principles, Jun 09, 2019

8. Agile Governance
The governance of AI should respect the underlying principles of AI development. In promoting the innovative and healthy development of AI, high vigilance should be maintained in order to detect and resolve possible problems in a timely manner. The governance of AI should be adaptive and inclusive, constantly upgrading the intelligence level of the technologies, optimizing management mechanisms, and engaging with muti stakeholders to improve the governance institutions. The governance principles should be promoted throughout the entire lifecycle of AI products and services. Continuous research and foresight for the potential risks of higher level of AI in the future are required to ensure that AI will always be beneficial for human society.

Published by National Governance Committee for the New Generation Artificial Intelligence, China in Governance Principles for the New Generation Artificial Intelligence--Developing Responsible Artificial Intelligence, Jun 17, 2019

· 2.3 Shaping an enabling policy environment for AI
a) Governments should promote a policy environment that supports an agile transition from the research and development stage to the deployment and operation stage for trustworthy AI systems. To this effect, they should consider using experimentation to provide a controlled environment in which AI systems can be tested, and scaled up, as appropriate. b) Governments should review and adapt, as appropriate, their policy and regulatory frameworks and assessment mechanisms as they apply to AI systems to encourage innovation and competition for trustworthy AI.

Published by The Organisation for Economic Co-operation and Development (OECD) in OECD Principles on Artificial Intelligence, May 22, 2019

5. Benefits and Costs
When developing regulatory and non regulatory approaches, agencies will often consider the application and deployment of AI into already regulated industries. Presumably, such significant investments would not occur unless they offered significant economic potential. As in all technological transitions of this nature, the introduction of AI may also create unique challenges. For example, while the broader legal environment already applies to AI applications, the application of existing law to questions of responsibility and liability for decisions made by AI could be unclear in some instances, leading to the need for agencies, consistent with their authorities, to evaluate the benefits, costs, and distributional effects associated with any identified or expected method for accountability. Executive Order 12866 calls on agencies to “select those approaches that maximize net benefits (including potential economic, environmental, public health and safety, and other advantages; distributive impacts; and equity).” Agencies should, when consistent with law, carefully consider the full societal costs, benefits, and distributional effects before considering regulations related to the development and deployment of AI applications. Such consideration will include the potential benefits and costs of employing AI, when compared to the systems AI has been designed to complement or replace, whether implementing AI will change the type of errors created by the system, as well as comparison to the degree of risk tolerated in other existing ones. Agencies should also consider critical dependencies when evaluating AI costs and benefits, as technological factors (such as data quality) and changes in human processes associated with AI implementation may alter the nature and magnitude of the risks and benefits. In cases where a comparison to a current system or process is not available, evaluation of risks and costs of not implementing the system should be evaluated as well.

Published by The White House Office of Science and Technology Policy (OSTP), United States in Principles for the Stewardship of AI Applications, Nov 17, 2020

5. Benefits and Costs
When developing regulatory and non regulatory approaches, agencies will often consider the application and deployment of AI into already regulated industries. Presumably, such significant investments would not occur unless they offered significant economic potential. As in all technological transitions of this nature, the introduction of AI may also create unique challenges. For example, while the broader legal environment already applies to AI applications, the application of existing law to questions of responsibility and liability for decisions made by AI could be unclear in some instances, leading to the need for agencies, consistent with their authorities, to evaluate the benefits, costs, and distributional effects associated with any identified or expected method for accountability. Executive Order 12866 calls on agencies to “select those approaches that maximize net benefits (including potential economic, environmental, public health and safety, and other advantages; distributive impacts; and equity).” Agencies should, when consistent with law, carefully consider the full societal costs, benefits, and distributional effects before considering regulations related to the development and deployment of AI applications. Such consideration will include the potential benefits and costs of employing AI, when compared to the systems AI has been designed to complement or replace, whether implementing AI will change the type of errors created by the system, as well as comparison to the degree of risk tolerated in other existing ones. Agencies should also consider critical dependencies when evaluating AI costs and benefits, as technological factors (such as data quality) and changes in human processes associated with AI implementation may alter the nature and magnitude of the risks and benefits. In cases where a comparison to a current system or process is not available, evaluation of risks and costs of not implementing the system should be evaluated as well.

Published by The White House Office of Science and Technology Policy (OSTP), United States in Principles for the Stewardship of AI Applications, Nov 17, 2020

Contact

Institute of Automation, Chinese Academy of Sciences
95 Zhongguancun East Road,
Haidian District, Beijing,
China 100190
Principal Investigator - Yi Zeng
contact@long-term-ai.cn

Contributors: Cunqing Huangfu, Enmeng Lu, Zizhe Ruan et al.

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