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

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.

Principle: Shanghai Initiative for the Safe Development of Artificial Intelligence, Aug 30, 2019

Published by Shanghai Advisory Committee of Experts on Artificial Intelligence Industry Security

Related Principles

· Article 8: Clarify responsibilities.

Make clear the rights and obligations at each stage in artificial intelligence research and development (R&D), design, manufacturing, operation, and services, etc., to be able to determine the responsible party promptly when harm occurs. Advocate for relevant enterprises and organizations to innovate in insurance mechanisms under the existing legal framework, to distribute the social risks brought about by development of the artificial intelligence industry.

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

· 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

Ethical Considerations in Deployment and Design

Principle: AI system designers and builders need to apply a user centric approach to the technology. They need to consider their collective responsibility in building AI systems that will not pose security risks to the Internet and Internet users. Recommendations: Adopt ethical standards: Adherence to the principles and standards of ethical considerations in the design of artificial intelligence, should guide researchers and industry going forward. Promote ethical considerations in innovation policies: Innovation policies should require adherence to ethical standards as a pre requisite for things like funding.

Published by Internet Society, "Artificial Intelligence and Machine Learning: Policy Paper" in Guiding Principles and Recommendations, Apr 18, 2017

8. Open cooperation

The development of artificial intelligence requires the concerted efforts of all countries and all parties, and we should actively establish norms and standards for the safe development of artificial intelligence at the international level, so as to avoid the security risks caused by incompatibility between technology and policies.

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

Plan and Design:

1 This step is crucial to design or procure an AI System in an accountable and responsible manner. The ethical responsibility and liability for the outcomes of the AI system should be attributable to stakeholders who are responsible for certain actions in the AI System Lifecycle. It is essential to set a robust governance structure that defines the authorization and responsibility areas of the internal and external stakeholders without leaving any areas of uncertainty to achieve this principle. The design approach of the AI system should respect human rights, and fundamental freedoms as well as the national laws and cultural values of the kingdom. 2 Organizations can put in place additional instruments such as impact assessments, risk mitigation frameworks, audit and due diligence mechanisms, redress, and disaster recovery plans. 3 It is essential to build and design a human controlled AI system where decisions on the processes and functionality of the technology are monitored and executed, and are susceptible to intervention from authorized users. Human governance and oversight establish the necessary control and levels of autonomy through set mechanisms.

Published by SDAIA in AI Ethics Principles, Sept 14, 2022