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

Accountability

Accountability By Design: All AI systems must be designed to facilitate end to end answerability and auditability. This requires both responsible humans in the loop across the entire design and implementation chain and activity monitoring protocols that enable end to end oversight and review.

Principle: The FAST Track Principles, Jun 10, 2019

Published by The Alan Turing Institute

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

· Build and Validate:

1 Privacy and security by design should be implemented while building the AI system. The security mechanisms should include the protection of various architectural dimensions of an AI model from malicious attacks. The structure and modules of the AI system should be protected from unauthorized modification or damage to any of its components. 2 The AI system should be secure to ensure and maintain the integrity of the information it processes. This ensures that the system remains continuously functional and accessible to authorized users. It is crucial that the system safeguards confidential and private information, even under hostile or adversarial conditions. Furthermore, appropriate measures should be in place to ensure that AI systems with automated decision making capabilities uphold the necessary data privacy and security standards. 3 The AI System should be tested to ensure that the combination of available data does not reveal the sensitive data or break the anonymity of the observation. Deploy and Monitor: 1 After the deployment of the AI system, when its outcomes are realized, there must be continuous monitoring to ensure that the AI system is privacy preserving, safe and secure. The privacy impact assessment and risk management assessment should be continuously revisited to ensure that societal and ethical considerations are regularly evaluated. 2 AI System Owners should be accountable for the design and implementation of AI systems in such a way as to ensure that personal information is protected throughout the life cycle of the AI system. The components of the AI system should be updated based on continuous monitoring and privacy impact assessment.

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

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

Second principle: Responsibility

Human responsibility for AI enabled systems must be clearly established, ensuring accountability for their outcomes, with clearly defined means by which human control is exercised throughout their lifecycles. The increased speed, complexity and automation of AI enabled systems may complicate our understanding of pre existing concepts of human control, responsibility and accountability. This may occur through the sorting and filtering of information presented to decision makers, the automation of previously human led processes, or processes by which AI enabled systems learn and evolve after their initial deployment. Nevertheless, as unique moral agents, humans must always be responsible for the ethical use of AI in Defence. Human responsibility for the use of AI enabled systems in Defence must be underpinned by a clear and consistent articulation of the means by which human control is exercised, and the nature and limitations of that control. While the level of human control will vary according to the context and capabilities of each AI enabled system, the ability to exercise human judgement over their outcomes is essential. Irrespective of the use case, Responsibility for each element of an AI enabled system, and an articulation of risk ownership, must be clearly defined from development, through deployment – including redeployment in new contexts – to decommissioning. This includes cases where systems are complex amalgamations of AI and non AI components, from multiple different suppliers. In this way, certain aspects of responsibility may reach beyond the team deploying a particular system, to other functions within the MOD, or beyond, to the third parties which build or integrate AI enabled systems for Defence. Collectively, these articulations of human control, responsibility and risk ownership must enable clear accountability for the outcomes of any AI enabled system in Defence. There must be no deployment or use without clear lines of responsibility and accountability, which should not be accepted by the designated duty holder unless they are satisfied that they can exercise control commensurate with the various risks.

Published by The Ministry of Defence (MOD), United Kingdom in Ethical Principles for AI in Defence, Jun 15, 2022