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

· Article 5: Secure safe and controllable.

Ensure that AI systems operate securely safely, reliably, and controllably throughout their lifecycle. Evaluate system security safety and potential risks, and continuously improve system maturity, robustness, and anti tampering capabilities. Ensure that the system can be supervised and promptly taken over by humans to avoid the negative effects of loss of system control.

Principle: Joint Pledge on Artificial Intelligence Industry Self-Discipline (Draft for Comment), May 31, 2019

Published by Artificial Intelligence Industry Alliance (AIIA), China

Related Principles

II. Technical robustness and safety

Trustworthy AI requires algorithms to be secure, reliable and robust enough to deal with errors or inconsistencies during all life cycle phases of the AI system, and to adequately cope with erroneous outcomes. AI systems need to be reliable, secure enough to be resilient against both overt attacks and more subtle attempts to manipulate data or algorithms themselves, and they must ensure a fall back plan in case of problems. Their decisions must be accurate, or at least correctly reflect their level of accuracy, and their outcomes should be reproducible. In addition, AI systems should integrate safety and security by design mechanisms to ensure that they are verifiably safe at every step, taking at heart the physical and mental safety of all concerned. This includes the minimisation and where possible the reversibility of unintended consequences or errors in the system’s operation. Processes to clarify and assess potential risks associated with the use of AI systems, across various application areas, should be put in place.

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

Principle 2 – Privacy & Security

The privacy and security principle represents overarching values that require AI systems; throughout the AI System Lifecycle; to be built in a safe way that respects the privacy of the data collected as well as upholds the highest levels of data security processes and procedures to keep the data confidential preventing data and system breaches which could lead to reputational, psychological, financial, professional, or other types of harm. AI systems should be designed with mechanisms and controls that provide the possibility to govern and monitor their outcomes and progress throughout their lifecycle to ensure continuous monitoring within the privacy and security principles and protocols set in place.

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

· 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

· Deploy and Monitor:

1 Monitoring the robustness of the AI system should be adopted and undertaken in a periodic and continuous manner to measure and assess any risks related to the technicalities of the AI system (an inward perspective) as well as the magnitude of the risk posed by the system and its capabilities (an outward perspective). 2 The model must also be monitored in a periodic and continuous manner to verify whether its operations and functions are compatible with the designed structure and frameworks. The AI system must also be safe to prevent destructive use to exploit its data and results to harm entities, individuals, or groups. It is necessary to continuously work on implementation and development to ensure system reliability.

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

Safety and security

Safety and security risks should be identified, addressed and mitigated throughout the AI system lifecycle to prevent where possible, and or limit, any potential or actual harm to humans, the environment and ecosystems. Safe and secure AI systems should be enabled through robust frameworks.

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