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

Optimize the safe development, production and compliance of therapeutics and healthcare solutions to deliver Precision Health

Principle: GE Healthcare AI principles, Oct 1, 2018 (unconfirmed)

Published by GE Healthcare

Related Principles

· Promote energy conservation

AI can be used to contribute to energy conservation. For example, it can be used to optimize industrial processes to improve material and energy utilization, optimize logistics to reduce vehicle unloading rates, optimize urban lighting and traffic, optimize the use of air conditioning and lighting in buildings according to people's work and rest time, and intelligent remote work platforms can help reduce unnecessary energy cost.

Published by International Research Center for AI Ethics and Governance, Instituteof Automation, Chinese Academy of Sciences and other 10 entities in Principles on AI for Climate Action, April 26, 2022

· 6. Uphold high standards of scientific excellence.

Technological innovation is rooted in the scientific method and a commitment to open inquiry, intellectual rigor, integrity, and collaboration. AI tools have the potential to unlock new realms of scientific research and knowledge in critical domains like biology, chemistry, medicine, and environmental sciences. We aspire to high standards of scientific excellence as we work to progress AI development. We will work with a range of stakeholders to promote thoughtful leadership in this area, drawing on scientifically rigorous and multidisciplinary approaches. And we will responsibly share AI knowledge by publishing educational materials, best practices, and research that enable more people to develop useful AI applications.

Published by Google in Artificial Intelligence at Google: Our Principles, Jun 7, 2018

· 2.1 Investment in AI Research and Development

We encourage robust support for research and development (R&D) to foster innovation through incentives and funding. As the primary source of funding for long term, high risk research initiatives, we support governments’ investment in research fields specific or highly relevant to AI, including: cyber defense, data analytics, detection of fraudulent transactions or messages, robotics, human augmentation, natural language processing, interfaces, and visualizations.

Published by Information Technology Industry Council (ITI) in AI Policy Principles, Oct 24, 2017

Chapter 3. The Norms of Research and Development

　　10. Strengthen the awareness of self discipline. Strengthen self discipline in activities related to AI research and development, actively integrate AI ethics into every phase of technology research and development, consciously carry out self censorship, strengthen self management, and do not engage in AI research and development that violates ethics and morality. 　　11. Improve data quality. In the phases of data collection, storage, use, processing, transmission, provision, disclosure, etc., strictly abide by data related laws, standards and norms. Improve the completeness, timeliness, consistency, normativeness and accuracy of data. 　　12. Enhance safety, security and transparency. In the phases of algorithm design, implementation, and application, etc., improve transparency, interpretability, understandability, reliability, and controllability, enhance the resilience, adaptability, and the ability of anti interference of AI systems, and gradually realize verifiable, auditable, supervisable, traceable, predictable and trustworthy AI. 　　13. Avoid bias and discrimination. During the process of data collection and algorithm development, strengthen ethics review, fully consider the diversity of demands, avoid potential data and algorithmic bias, and strive to achieve inclusivity, fairness and non discrimination of AI systems.

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

Design for human control, accountability, and intended use

Humans should have ultimate control of our technology, and we strive to prevent unintended use of our products. Our user experience enforces accountability, responsible use, and transparency of consequences. We build protections into our products to detect and avoid unintended system behaviors. We achieve this through modern software engineering and rigorous testing on our entire systems including their constituent data and AI products, in isolation and in concert. Additionally, we rely on ongoing user research to help ensure that our products function as expected and can be appropriately disabled when necessary. Accountability is enforced by providing customers with insight into the provenance of data sources, methodologies, and design processes in easily understood and transparent language. Effective governance — of data, models, and software — is foundational to the ethical and accountable deployment of AI.

Published by Rebelliondefense in AI Ethical Principles, January 2023