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

· 3. Be built and tested for safety.

We will continue to develop and apply strong safety and security practices to avoid unintended results that create risks of harm. We will design our AI systems to be appropriately cautious, and seek to develop them in accordance with best practices in AI safety research. In appropriate cases, we will test AI technologies in constrained environments and monitor their operation after deployment.

Principle: Artificial Intelligence at Google: Our Principles, Jun 7, 2018

Published by Google

Related Principles

Reliability and safety

Throughout their lifecycle, AI systems should reliably operate in accordance with their intended purpose. This principle aims to ensure that AI systems reliably operate in accordance with their intended purpose throughout their lifecycle. This includes ensuring AI systems are reliable, accurate and reproducible as appropriate. AI systems should not pose unreasonable safety risks, and should adopt safety measures that are proportionate to the magnitude of potential risks. AI systems should be monitored and tested to ensure they continue to meet their intended purpose, and any identified problems should be addressed with ongoing risk management as appropriate. Responsibility should be clearly and appropriately identified, for ensuring that an AI system is robust and safe.

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

6. We set the framework.

Our AI solutions are developed and enhanced on grounds of deep analysis and evaluation. They are transparent, auditable, fair, and fully documented. We consciously initiate the AI’s development for the best possible outcome. The essential paradigm for our AI systems’ impact analysis is “privacy und security by design”. This is accompanied e.g. by risks and chances scenarios or reliable disaster scenarios. We take great care in the initial algorithm of our own AI solutions to prevent so called “Black Boxes” and to make sure that our systems shall not unintentionally harm the users

Published by Deutsche Telekom in Deutsche Telekom’s guidelines for artificial intelligence, May 11, 2018

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

Chapter 4. The Norms of Supply

　　14. Respect market rules. Strictly abide by the various rules and regulations for market access, competition, and trading activities, actively maintain market order, and create a market environment conducive to the development of AI. Data monopoly, platform monopoly, etc. must not be used to disrupt the orderly market competitions, and any means that infringe on the intellectual property rights of other subjects are forbidden. 　　15. Strengthen quality control. Strengthen the quality monitoring and the evaluations on the use of AI products and services, avoid infringements on personal safety, property safety, user privacy, etc. caused by product defects introduced during the design and development phases, and must not operate, sell, or provide products and services that do not meet the quality standards. 　　16. Protect the rights and interests of users. Users should be clearly informed that AI technology is used in products and services. The functions and limitations of AI products and services should be clearly identified, and users’ rights to know and to consent should be ensured. Simple and easy to understand solutions for users to choose to use or quit the AI mode should be provided, and it is forbidden to set obstacles for users to fairly use AI products and services. 　　17. Strengthen emergency protection. Emergency mechanisms and loss compensation plans and measures should be investigated and formulated. AI systems need to be timely monitored, user feedbacks should be responded and processed in a timely manner, systemic failures should be prevented in time, and be ready to assist relevant entities to intervene in the AI systems in accordance with laws and regulations to reduce losses and avoid risks.

Published by National Governance Committee for the New Generation Artificial Intelligence, China in Ethical Norms for the New Generation Artificial Intelligence, Sep 25, 2021

6 Promote artificial intelligence that is responsive and sustainable

Responsiveness requires that designers, developers and users continuously, systematically and transparently examine an AI technology to determine whether it is responding adequately, appropriately and according to communicated expectations and requirements in the context in which it is used. Thus, identification of a health need requires that institutions and governments respond to that need and its context with appropriate technologies with the aim of achieving the public interest in health protection and promotion. When an AI technology is ineffective or engenders dissatisfaction, the duty to be responsive requires an institutional process to resolve the problem, which may include terminating use of the technology. Responsiveness also requires that AI technologies be consistent with wider efforts to promote health systems and environmental and workplace sustainability. AI technologies should be introduced only if they can be fully integrated and sustained in the health care system. Too often, especially in under resourced health systems, new technologies are not used or are not repaired or updated, thereby wasting scare resources that could have been invested in proven interventions. Furthermore, AI systems should be designed to minimize their ecological footprints and increase energy efficiency, so that use of AI is consistent with society’s efforts to reduce the impact of human beings on the earth’s environment, ecosystems and climate. Sustainability also requires governments and companies to address anticipated disruptions to the workplace, including training of health care workers to adapt to use of AI and potential job losses due to the use of automated systems for routine health care functions and administrative tasks.

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