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

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.

Principle: Governance Principles for the New Generation Artificial Intelligence--Developing Responsible Artificial Intelligence, Jun 17, 2019

Published by National Governance Committee for the New Generation Artificial Intelligence, China

Related Principles

Accountability

Those responsible for the different phases of the AI system lifecycle should be identifiable and accountable for the outcomes of the AI systems, and human oversight of AI systems should be enabled. This principle aims to acknowledge the relevant organisations' and individuals’ responsibility for the outcomes of the AI systems that they design, develop, deploy and operate. The application of legal principles regarding accountability for AI systems is still developing. Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes. This includes both before and after their design, development, deployment and operation. The organisation and individual accountable for the decision should be identifiable as necessary. They must consider the appropriate level of human control or oversight for the particular AI system or use case. AI systems that have a significant impact on an individual's rights should be accountable to external review, this includes providing timely, accurate, and complete information for the purposes of independent oversight bodies.

Published by Department of Industry, Innovation and Science, Australian Government in AI Ethics Principles, Nov 7, 2019

· (4) Security

Positive utilization of AI means that many social systems will be automated, and the safety of the systems will be improved. On the other hand, within the scope of today's technologies, it is impossible for AI to respond appropriately to rare events or deliberate attacks. Therefore, there is a new security risk for the use of AI. Society should always be aware of the balance of benefits and risks, and should work to improve social safety and sustainability as a whole. Society must promote broad and deep research and development in AI (from immediate measures to deep understanding), such as the proper evaluation of risks in the utilization of AI and research to reduce risks. Society must also pay attention to risk management, including cybersecurity awareness. Society should always pay attention to sustainability in the use of AI. Society should not, in particular, be uniquely dependent on single AI or a few specified AI.

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

Chapter 2. The Norms of Management

　　5. Promotion of agile governance. Respect the law of development of AI, fully understand the potential and limitations of AI, continue to optimize the governance mechanisms and methods of AI. Do not divorce from reality, do not rush for quick success and instant benefits in the process of strategic decision making, institution construction, and resource allocation. Promote the healthy and sustainable development of AI in an orderly manner. 　　6. Active practice. Comply with AI related laws, regulations, policies and standards, actively integrate AI ethics into the entire management process, take the lead in becoming practitioners and promoters of AI ethics and governance, summarize and promote AI governance experiences in a timely manner, and actively respond to the society’s concerns on the ethics of AI. 　　7. Exercise and use power correctly. Clarify the responsibilities and power boundaries of AI related management activities, and standardize the conditions and procedures of power operations. Fully respect and protect the privacy, freedom, dignity, safety and other rights of relevant stakeholders and other legal rights and interests, and prohibit improper use of power to infringe the legal rights of natural persons, legal persons and other organizations. 　　8. Strengthen risk preventions. Enhance bottom line thinking and risk awareness, strengthen the research and judgment on the potential risks during the development of AI, carry out systematic risk monitoring and evaluations in a timely manner, establish an effective early warning mechanism for risks, and enhance the ability of manage, control, and disposal of ethical risks of AI. 　　9. Promote inclusivity and openness. Pay full attention to the rights and demands of all stakeholders related to AI, encourage the application of diverse AI technologies to solve practical problems in economic and social development, encourage cross disciplinary, cross domain, cross regional, and cross border exchanges and cooperation, and promote the formation of AI governance frameworks, standards and norms with broad consensus.

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

· 5. INTERESTS OF DEVELOPING AI TECHNOLOGIES ABOVE THE INTERESTS OF COMPETITION

5.1. Correctness of AIS comparisons. To maintain the fair competition and effective cooperation of developers, AI Actors should use the most reliable and comparable information about the capabilities of AISs in relation to a task and ensure the uniformity of the measurement methodologies. 5.2. Development of competencies. AI Actors are encouraged to follow practices adopted by the professional community, to maintain the proper level of professional competence necessary for safe and effective work with AIS and to promote the improvement of the professional competence of workers in the field of AI, including within the framework of programs and educational disciplines on AI ethics. 5.3. Collaboration of developers. AI Actors are encouraged to develop cooperation within the AI Actor community, particularly between developers, including by informing each other of the identification of critical vulnerabilities in order to prevent their wide distribution. They should also make efforts to improve the quality and availability of resources in the field of AIS development, including by increasing the availability of data (including labeled data), ensuring the compatibility of the developed AIS where applicable and creating conditions for the formation of a national school for the development of AI technologies that includes publicly available national repositories of libraries and network models, available national development tools, open national frameworks, etc. They are also encouraged to share information on the best practices in the development of AI technologies and organize and hold conferences, hackathons and public competitions, as well as high school and student Olympiads. They should increase the availability of knowledge and encourage the use of open knowledge databases, creating conditions for attracting investments in the development of AI technologies from Russian private investors, business angels, venture funds and private equity funds while stimulating scientific and educational activities in the field of AI by participating in the projects and activities of leading Russian research centers and educational organizations.

Published by AI Alliance Russia in Artificial Intelligence Code of Ethics, Oct 26, 2021

· Transparency and explainability

37. The transparency and explainability of AI systems are often essential preconditions to ensure the respect, protection and promotion of human rights, fundamental freedoms and ethical principles. Transparency is necessary for relevant national and international liability regimes to work effectively. A lack of transparency could also undermine the possibility of effectively challenging decisions based on outcomes produced by AI systems and may thereby infringe the right to a fair trial and effective remedy, and limits the areas in which these systems can be legally used. 38. While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security. People should be fully informed when a decision is informed by or is made on the basis of AI algorithms, including when it affects their safety or human rights, and in those circumstances should have the opportunity to request explanatory information from the relevant AI actor or public sector institutions. In addition, individuals should be able to access the reasons for a decision affecting their rights and freedoms, and have the option of making submissions to a designated staff member of the private sector company or public sector institution able to review and correct the decision. AI actors should inform users when a product or service is provided directly or with the assistance of AI systems in a proper and timely manner. 39. From a socio technical lens, greater transparency contributes to more peaceful, just, democratic and inclusive societies. It allows for public scrutiny that can decrease corruption and discrimination, and can also help detect and prevent negative impacts on human rights. Transparency aims at providing appropriate information to the respective addressees to enable their understanding and foster trust. Specific to the AI system, transparency can enable people to understand how each stage of an AI system is put in place, appropriate to the context and sensitivity of the AI system. It may also include insight into factors that affect a specific prediction or decision, and whether or not appropriate assurances (such as safety or fairness measures) are in place. In cases of serious threats of adverse human rights impacts, transparency may also require the sharing of code or datasets. 40. Explainability refers to making intelligible and providing insight into the outcome of AI systems. The explainability of AI systems also refers to the understandability of the input, output and the functioning of each algorithmic building block and how it contributes to the outcome of the systems. Thus, explainability is closely related to transparency, as outcomes and ub processes leading to outcomes should aim to be understandable and traceable, appropriate to the context. AI actors should commit to ensuring that the algorithms developed are explainable. In the case of AI applications that impact the end user in a way that is not temporary, easily reversible or otherwise low risk, it should be ensured that the meaningful explanation is provided with any decision that resulted in the action taken in order for the outcome to be considered transparent. 41. Transparency and explainability relate closely to adequate responsibility and accountability measures, as well as to the trustworthiness of AI systems.

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO) in The Recommendation on the Ethics of Artificial Intelligence, Nov 24, 2021