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

· Empower the development of energy systems

AI should contribute to the development of the energy system. AI can be used to optimize energy systems and promote green energy development. For example, AI can be used to optimize the overall design and deployment of energy systems, and improve energy efficiency. AI can also contribute to research, development and use of green energy technologies such as wind power, photovoltaics, nuclear fusion, geothermal energy, biogas, and electric fuel. Through the development of smart grid control and related technologies, AI can be used to improve the stability and reliability of the power systems.

Principle: Principles on AI for Climate Action, April 26, 2022

Published by International Research Center for AI Ethics and Governance, Instituteof Automation, Chinese Academy of Sciences and other 10 entities

Related Principles

· Energy conservation

The development and use of AI should reduce its own energy consumption as much as possible while meeting specific needs. AI applications with high energy consumption should follow the necessary principles and alternative solutions with relatively low energy consumption should be actively explored. For example, simplifying the AI model within the acceptable range of loss, optimizing the model training method, and co design of software and hardware to achieve the expected level of intelligence with low energy consumption. The potential approach includes but is not limited to smart and low energy consumption. Considering the type and application characteristics of electric power comprehensively, and planning for rational use, where appropriate, green power are encouraged to be used, and efforts on reducing the cost of power storage should be continuously made. It is encouraged to train AI models and algorithms and deploy AI applications in areas where electric power is relatively cheap, and adopt solutions that consume less energy for server cooling as much as possible.

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

· 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.

· Contribute to reducing greenhouse gas emissions

AI can be used to contribute to reduce greenhouse gas emissions through process optimization and monitoring technology, and help develop new materials and new processes that release less greenhouse gases. AI can be used to optimize breeds and agricultural production methods to reduce methane and nitrogen oxides in animal husbandry and agriculture. AI can be used for automatic garbage classification to recycle and obtain fuel, feed, steel and other materials, industrial raw materials, etc. in the garbage for reuse.

· Promote greenhouse gas absorption and carbon storage

AI can be used to monitor, predict the greenhouse gas production from the ecosystems, and contribute to the intervention process. AI can be used to promote the development of greenhouse gas recycling technologies, and to protect ecosystems such as forests, peatlands, and oceans that can absorb and store carbon.

• Foster Innovation and Open Development

To better understand the impact of AI and explore the broad diversity of AI implementations, public policy should encourage investment in AI R&D. Governments should support the controlled testing of AI systems to help industry, academia, and other stakeholders improve the technology. [Recommendations] • Fuel AI innovation: Public policy should promote investment, make available funds for R&D, and address barriers to AI development and adoption. • Address global societal challenges: AI powered flagship initiatives should be funded to find solutions to the world’s greatest challenges such as curing cancer, ensuring food security, controlling climate change, and achieving inclusive economic growth. • Allow for experimentation: Governments should create the conditions necessary for the controlled testing and experimentation of AI in the real world, such as designating self driving test sites in cities. • Prepare a workforce for AI: Governments should create incentives for students to pursue courses of study that will allow them to create the next generation of AI. • Lead by example: Governments should lead the way on demonstrating the applications of AI in its interactions with citizens and invest sufficiently in infrastructure to support and deliver AI based services. • Partnering for AI: Governments should partner with industry, academia, and other stakeholders for the promotion of AI and debate ways to maximize its benefits for the economy.

Published by Intel in AI public policy principles, Oct 18, 2017