· Control risks

The application of AI should adhere to strict and prudent principles, strive to control and minimize the potential risks to children. Considering that the influence of AI on children's psychology, physiology, and behaviors is still to be studied, and children's own thinking and behaviors are highly uncertain, AI technology and products for children should conform to higher standards and requirements in terms of maturity, robustness, reliability, controllability, safety and security, etc.
Principle: Artificial Intelligence for Children: Beijing Principles, Sep 14, 2020

Published by Beijing Academy of Artificial Intelligence (BAAI), Peking University, Tsinghua University and the Chinese Academy of Sciences, together with enterprises that focus on AI development.

Related Principles

· (4) Security
Positive utilization of AI means that many social systems will be automated, and the safety of the systems will be improved. On the other hand, within the scope of today's technologies, it is impossible for AI to respond appropriately to rare events or deliberate attacks. Therefore, there is a new security risk for the use of AI. Society should always be aware of the balance of benefits and risks, and should work to improve social safety and sustainability as a whole. Society must promote broad and deep research and development in AI (from immediate measures to deep understanding), such as the proper evaluation of risks in the utilization of AI and research to reduce risks. Society must also pay attention to risk management, including cybersecurity awareness. Society should always pay attention to sustainability in the use of AI. Society should not, in particular, be uniquely dependent on single AI or a few specified AI.

Published by Cabinet Office, Government of Japan in Social Principles of Human-centric AI, Dec 27, 2018

· 1.4. Robustness, security and safety
a) AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety risk. b) To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outcomes and responses to inquiry, appropriate to the context and consistent with the state of art. c) AI actors should, based on their roles, the context, and their ability to act, apply a systematic risk management approach to each phase of the AI system lifecycle on a continuous basis to address risks related to AI systems, including privacy, digital security, safety and bias.

Published by G20 Ministerial Meeting on Trade and Digital Economy in G20 AI Principles, Jun 09, 2019

· 1.4. Robustness, security and safety

a) AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety risk. b) To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outcomes and responses to inquiry, appropriate to the context and consistent with the state of art. c) AI actors should, based on their roles, the context, and their ability to act, apply a systematic risk management approach to each phase of the AI system lifecycle on a continuous basis to address risks related to AI systems, including privacy, digital security, safety and bias.

Published by The Organisation for Economic Co-operation and Development (OECD) in OECD Principles on Artificial Intelligence, May 22, 2019

· 2. RESPONSIBILITY MUST BE FULLY ACKNOWLEDGED WHEN CREATING AND USING AI
2.1. Risk based approach. The degree of attention paid to ethical AI issues and the nature of the relevant actions of AI Actors should be proportional to the assessment of the level of risk posed by specific AI technologies and systems for the interests of individuals and society. Risk level assessment shall take into account both known and possible risks, whereby the probability level of threats, as well as their possible scale in the short and long term shall be considered. Making decisions in the field of AI use that significantly affect society and the state should be accompanied by a scientifically verified, interdisciplinary forecast of socio economic consequences and risks and examination of possible changes in the paradigm of value and cultural development of the society. Development and use of an AI systems risk assessment methodology are encouraged in pursuance of this Code. 2.2. Responsible attitude. AI Actors should responsibly treat: • issues related to the influence of AI systems on society and citizens at every stage of the AI systems’ life cycle, i.a. on privacy, ethical, safe and responsible use of personal data; • the nature, degree and extent of damage that may result from the use of AI technologies and systems; • the selection and use of hardware and software utilized in different life cycles of AI systems. At the same time, the responsibility of AI Actors should correspond with the nature, degree and extent of damage that may occur as a result of the use of AI technologies and systems. The role in the life cycle of the AI system, as well as the degree of possible and real influence of a particular AI Actor on causing damage and its extent, should also be taken into account. 2.3. Precautions. When the activities of AI Actors can lead to morally unacceptable consequences for individuals and society, which can be reasonably predicted by the relevant AI Actor, the latter, should take measures to prohibit or limit the occurrence of such consequences. AI Actors shall use the provisions of this Code, including the mechanisms specified in Section 2, to assess the moral unacceptability of such consequences and discuss possible preventive measures. 2.4. No harm. AI Actors should not allow the use of AI technologies for the purpose of causing harm to human life and or health, the property of citizens and legal entities and the environment. Any use, including the design, development, testing, integration or operation of an AI system capable of purposefully causing harm to the environment, human life and or health, the property of citizens and legal entities, is prohibited. 2.5. Identification of AI in communication with a human. AI Actors are encouraged to ensure that users are duly informed of their interactions with AI systems when it affects human rights and critical areas of people’s lives and to ensure that such interaction can be terminated at the request of the user. 2.6. Data security. AI Actors must comply with the national legislation in the field of personal data and secrets protected by law when using AI systems; ensure the security and protection of personal data processed by AI systems or by AI Actors in order to develop and improve the AI systems; develop and integrate innovative methods to counter unauthorized access to personal data by third parties and use high quality and representative datasets obtained without breaking the law from reliable sources. 2.7. Information security. AI Actors should ensure the maximum possible protection from unauthorized interference of third parties in the operation of AI systems; integrate adequate information security technologies, i.a. use internal mechanisms designed to protect the AI system from unauthorized interventions and inform users and developers about such interventions; as well as promote the informing of users about the rules of information security during the use of AI systems. 2.8. Voluntary certification and Code compliance. AI Actors may implement voluntary certification systems to assess the compliance of developed AI technologies with the standards established by the national legislation and this Code. AI Actors may create voluntary certification and labeling systems for AI systems to indicate that these systems have passed voluntary certification procedures and confirm quality standards. 2.9. Control of the recursive self improvement of AI systems. AI Actors are encouraged to cooperate in identifying and verifying information about ways and forms of design of so called universal ("general") AI systems and prevention of possible threats they carry. The issues concerning the use of "general" AI technologies should be under the control of the state.

Published by AI Alliance Russia in AI Ethics Code (revised version), Oct 21, 2022 (unconfirmed)

Principle 5 – Reliability & Safety
The reliability and safety principle ensures that the AI system adheres to the set specifications and that the AI system behaves exactly as its designers intended and anticipated. Reliability is a measure of consistency and provides confidence in how robust a system is. It is a measure of dependability with which it operationally conforms to its intended functionality and the outcomes it produces. On the other hand, safety is a measure of how the AI system does not pose a risk of harm or danger to society and individuals. As an illustration, AI systems such as autonomous vehicles can pose a risk to people’s lives if living organisms are not properly recognized, certain scenarios are not trained for or if the system malfunctions. A reliable working system should be safe by not posing a danger to society and should have built in mechanisms to prevent harm. The risk mitigation framework is closely related to this principle. Potential risks and unintended harms should be minimized in this aspect. The predictive model should be monitored and controlled in a periodic and continuous manner to check if its operations and functionality are aligned with the designed structure and frameworks in place. The AI system should be technically sound, robust, and developed to prevent malicious usage to exploit its data and outcomes to harm entities, individuals or communities. A continuous implementation continuous development approach is essential to ensure reliability.

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

Contact

Institute of Automation, Chinese Academy of Sciences
95 Zhongguancun East Road,
Haidian District, Beijing,
China 100190
Principal Investigator - Yi Zeng
contact@long-term-ai.cn

Contributors: Cunqing Huangfu, Enmeng Lu, Zizhe Ruan et al.

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