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

Responsibility and accountability.

Appropriate oversight, impact assessment, audit and due diligence mechanisms, including with regard to whistleblower protection, should be developed to ensure accountability for AI systems and their impact throughout their lifecycle.

Principle: Recommendations for reliable artificial intelligence, Jnue 2, 2023

Published by OFFICE OF THE CHIEF OF MINISTERS UNDERSECRETARY OF INFORMATION TECHNOLOGIES

Related Principles

6. Accountability and Integrity

There needs to be human accountability and control in the design, development, and deployment of AI systems. Deployers should be accountable for decisions made by AI systems and for the compliance with applicable laws and respect for AI ethics and principles. AI actors9 should act with integrity throughout the AI system lifecycle when designing, developing, and deploying AI systems. Deployers of AI systems should ensure the proper functioning of AI systems and its compliance with applicable laws, internal AI governance policies and ethical principles. In the event of a malfunction or misuse of the AI system that results in negative outcomes, responsible individuals should act with integrity and implement mitigating actions to prevent similar incidents from happening in the future. To facilitate the allocation of responsibilities, organisations should adopt clear reporting structures for internal governance, setting out clearly the different kinds of roles and responsibilities for those involved in the AI system lifecycle. AI systems should also be designed, developed, and deployed with integrity – any errors or unethical outcomes should at minimum be documented and corrected to prevent harm to users upon deployment

Published by ASEAN in ASEAN Guide on AI Governance and Ethics, 2024

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

VII. Accountability

Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes, both before and after their implementation. Auditability of AI systems is key in this regard, as the assessment of AI systems by internal and external auditors, and the availability of such evaluation reports, strongly contributes to the trustworthiness of the technology. External auditability should especially be ensured in applications affecting fundamental rights, including safety critical applications. Potential negative impacts of AI systems should be identified, assessed, documented and minimised. The use of impact assessments facilitates this process. These assessments should be proportionate to the extent of the risks that the AI systems pose. Trade offs between the requirements – which are often unavoidable – should be addressed in a rational and methodological manner, and should be accounted for. Finally, when unjust adverse impact occurs, accessible mechanisms should be foreseen that ensure adequate redress.

Published by European Commission in Key requirements for trustworthy AI, Apr 8, 2019

Responsibility and accountability

United Nations system organizations should have in place appropriate oversight, impact assessment, audit and due diligence mechanisms, including whistle blowers’ protection, to ensure accountability for the impacts of the use of AI systems throughout their lifecycle. Appropriate governance structures should be established or enhanced which attribute the ethical and legal responsibility and accountability for AIbased decisions to humans or legal entities, at any stage of the AI system’s lifecycle. Harms caused by and or through AI systems should be investigated and appropriate action taken in response. Accountability mechanisms should be communicated broadly throughout the United Nations system in order to build shared knowledge resources and capacities.

Published by United Nations System Chief Executives Board for Coordination in Principles for the Ethical Use of Artificial Intelligence in the United Nations System, Sept 20, 2022

· Responsibility and accountability

42. AI actors and Member States should respect, protect and promote human rights and fundamental freedoms, and should also promote the protection of the environment and ecosystems, assuming their respective ethical and legal responsibility, in accordance with national and international law, in particular Member States’ human rights obligations, and ethical guidance throughout the life cycle of AI systems, including with respect to AI actors within their effective territory and control. The ethical responsibility and liability for the decisions and actions based in any way on an AI system should always ultimately be attributable to AI actors corresponding to their role in the life cycle of the AI system. 43. Appropriate oversight, impact assessment, audit and due diligence mechanisms, including whistle blowers’ protection, should be developed to ensure accountability for AI systems and their impact throughout their life cycle. Both technical and institutional designs should ensure auditability and traceability of (the working of) AI systems in particular to address any conflicts with human rights norms and standards and threats to environmental and ecosystem well being.

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