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

· Fairness and justice

AI should be transparent and objective when it contributes to climate action. When it is used to assess, analyze and predict the impact of countries, regions and industries on climate change, their characteristics and development stages should be considered to avoid introducing bias. AI should contribute to the attention and evaluation of potential additional damages suffered by vulnerable groups in climate change, as well as the assessment of the negative impact of new technology revolutions on climate change, so as to avoid exacerbating inequality between countries, regions and social groups due to climate change. AI technologies and systems related to climate change control are encouraged to be opensource and shared. We should actively empower low and middle income countries, and regions with lower development status on AI to accelerate the realization of global climate goals.

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

2. Fairness and Equity

Deployers should have safeguards in place to ensure that algorithmic decisions do not further exacerbate or amplify existing discriminatory or unjust impacts across different demographics and the design, development, and deployment of AI systems should not result in unfair biasness or discrimination. An example of such safeguards would include human interventions and checks on the algorithms and its outputs. Deployers of AI systems should conduct regular testing of such systems to confirm if there is bias and where bias is confirmed, make the necessary adjustments to rectify imbalances to ensure equity. With the rapid developments in the AI space, AI systems are increasingly used to aid decision making. For example, AI systems are currently used to screen resumes in job application processes, predict the credit worthiness of consumers and provide agronomic advice to farmers. If not properly managed, an AI system’s outputs used to make decisions with significant impact on individuals could perpetuate existing discriminatory or unjust impacts to specific demographics. To mitigate discrimination, it is important that the design, development, and deployment of AI systems align with fairness and equity principles. In addition, the datasets used to train the AI systems should be diverse and representative. Appropriate measures should be taken to mitigate potential biases during data collection and pre processing, training, and inference. For example, thetraining and test dataset for an AI system used in the education sector should be adequately representative of the student population by including students of different genders and ethnicities.

Published by ASEAN in ASEAN Guide on AI Governance and Ethics, 2024

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

· Facilitate climate analysis and forecasting

AI can be used to assist in monitoring the causes and states of climate change, and through computational modeling and simulation, it can contribute to the understanding of climate mechanisms and forecast climate change trends, assist avoiding climate risks and crisis, such efforts should especially provided to low and middle income countries for early warning of climate disasters. It can be used to track the sources and impacts of greenhouse gases, to analyze and predict the impact of climate change and climate policies on the economy, politics and people's livelihood.

· Reducing the harm caused by climate change

AI can be used to monitor, simulate, and predict extreme climates to reduce their harm, and can be used to make rational planning for agriculture under global warming and assist in the development of crops adapted to the environment change to reduce the impact on agriculture. AI should assist urban planning so that it can cope with the impact of climate change. AI should assist in optimizing industrial processes, enabling companies to comply with green standards for sustainable development.

(d) Justice, equity, and solidarity

AI should contribute to global justice and equal access to the benefits and advantages that AI, robotics and ‘autonomous’ systems can bring. Discriminatory biases in data sets used to train and run AI systems should be prevented or detected, reported and neutralised at the earliest stage possible. We need a concerted global effort towards equal access to ‘autonomous’ technologies and fair distribution of benefits and equal opportunities across and within societies. This includes the formulating of new models of fair distribution and benefit sharing apt to respond to the economic transformations caused by automation, digitalisation and AI, ensuring accessibility to core AI technologies, and facilitating training in STEM and digital disciplines, particularly with respect to disadvantaged regions and societal groups. Vigilance is required with respect to the downside of the detailed and massive data on individuals that accumulates and that will put pressure on the idea of solidarity, e.g. systems of mutual assistance such as in social insurance and healthcare. These processes may undermine social cohesion and give rise to radical individualism.

Published by European Group on Ethics in Science and New Technologies, European Commission in Ethical principles and democratic prerequisites, Mar 9, 2018