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

4. HUMAN OVERSIGHT AND ACCOUNTABILITY

AI stakeholders should retain an appropriate level of human oversight of AI systems and their outputs. Technologies capable of harming individuals or groups should not be deployed until stakeholders have determined appropriate accountability and liability.

Principle: Trustworthy AI in Aotearoa: The AI Principles, Mar 4, 2020

Published by the Law, Society and Ethics Working Group of the AI Forum，New Zealand

Related Principles

Human centred values

Throughout their lifecycle, AI systems should respect human rights, diversity, and the autonomy of individuals. This principle aims to ensure that AI systems are aligned with human values. Machines should serve humans, and not the other way around. AI systems should enable an equitable and democratic society by respecting, protecting and promoting human rights, enabling diversity, respecting human freedom and the autonomy of individuals, and protecting the environment. Human rights risks need to be carefully considered, as AI systems can equally enable and hamper such fundamental rights. It’s permissible to interfere with certain human rights where it’s reasonable, necessary and proportionate. All people interacting with AI systems should be able to keep full and effective control over themselves. AI systems should not undermine the democratic process, and should not undertake actions that threaten individual autonomy, like deception, unfair manipulation, unjustified surveillance, and failing to maintain alignment between a disclosed purpose and true action. AI systems should be designed to augment, complement and empower human cognitive, social and cultural skills. Organisations designing, developing, deploying or operating AI systems should ideally hire staff from diverse backgrounds, cultures and disciplines to ensure a wide range of perspectives, and to minimise the risk of missing important considerations only noticeable by some stakeholders.

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

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

• 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

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

2 Promote human well being, human safety and the public interest

AI technologies should not harm people. They should satisfy regulatory requirements for safety, accuracy and efficacy before deployment, and measures should be in place to ensure quality control and quality improvement. Thus, funders, developers and users have a continuous duty to measure and monitor the performance of AI algorithms to ensure that AI technologies work as designed and to assess whether they have any detrimental impact on individual patients or groups. Preventing harm requires that use of AI technologies does not result in any mental or physical harm. AI technologies that provide a diagnosis or warning that an individual cannot address because of lack of appropriate, accessible or affordable health care should be carefully managed and balanced against any “duty to warn” that might arise from incidental and other findings, and appropriate safeguards should be in place to protect individuals from stigmatization or discrimination due to their health status.

Published by World Health Organization (WHO) in Key ethical principles for use of artificial intelligence for health, Jun 28, 2021