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

8. Establish Global Governance Mechanisms

UNI recommends the establishment of multi stakeholder Decent Work and Ethical AI governance bodies on global and regional levels. The bodies should include AI designers, manufacturers, owners, developers, researchers, employers, lawyers, CSOs and trade unions. Whistleblowing mechanisms and monitoring procedures to ensure the transition to, and implementation of, ethical AI must be established. The bodies should be granted the competence to recommend compliance processes and procedures.

Principle: Top 10 Principles For Ethical Artificial Intelligence, Dec 11, 2017

Published by UNI Global Union

Related Principles

· Emergency Preparedness Agreements and Institutions

States should agree on technical and institutional measures required to prepare for advanced AI systems, regardless of their development timescale. To facilitate these agreements, we need an international body to bring together AI safety authorities, fostering dialogue and collaboration in the development and auditing of AI safety regulations across different jurisdictions. This body would ensure states adopt and implement a minimal set of effective safety preparedness measures, including model registration, disclosure, and tripwires. Over time, this body could also set standards for and commit to using verification methods to enforce domestic implementations of the Safety Assurance Framework. These methods can be mutually enforced through incentives and penalty mechanisms, such as conditioning access to markets on compliance with global standards. Experts and safety authorities should establish incident reporting and contingency plans, and regularly update the list of verified practices to reflect current scientific understanding. This body will be a critical initial coordination mechanism. In the long run, however, states will need to go further to ensure truly global governance of risks from advanced AI.

Published by IDAIS (International Dialogues on AI Safety) in IDAIS-Venice, Sept 5, 2024

• Require Accountability for Ethical Design and Implementation

The social implications of computing have grown and will continue to expand as more people have access to implementations of AI. Public policy should work to identify and mitigate discrimination caused by the use of AI and encourage designing in protections against these harms. [Recommendations] • Standing for “Accountable Artificial Intelligence”: Governments, industry and academia should apply the Information Accountability Foundation’s principles to AI. Organizations implementing AI solutions should be able to demonstrate to regulators that they have the right processes, policies and resources in place to meet those principles. • Transparent decisions: Governments should determine which AI implementations require algorithm explainability to mitigate discrimination and harm to individuals.

Published by Intel in AI public policy principles, Oct 18, 2017

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

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

· Multi stakeholder and adaptive governance and collaboration

46. International law and national sovereignty must be respected in the use of data. That means that States, complying with international law, can regulate the data generated within or passing through their territories, and take measures towards effective regulation of data, including data protection, based on respect for the right to privacy in accordance with international law and other human rights norms and standards. 47. Participation of different stakeholders throughout the AI system life cycle is necessary for inclusive approaches to AI governance, enabling the benefits to be shared by all, and to contribute to sustainable development. Stakeholders include but are not limited to governments, intergovernmental organizations, the technical community, civil society, researchers and academia, media, education, policy makers, private sector companies, human rights institutions and equality bodies, anti discrimination monitoring bodies, and groups for youth and children. The adoption of open standards and interoperability to facilitate collaboration should be in place. Measures should be adopted to take into account shifts in technologies, the emergence of new groups of stakeholders, and to allow for meaningful participation by marginalized groups, communities and individuals and, where relevant, in the case of Indigenous Peoples, respect for the self governance of their data.

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