· 1. The Principle of Beneficence: “Do Good”

AI systems should be designed and developed to improve individual and collective wellbeing. AI systems can do so by generating prosperity, value creation and wealth maximization and sustainability. At the same time, beneficent AI systems can contribute to wellbeing by seeking achievement of a fair, inclusive and peaceful society, by helping to increase citizen’s mental autonomy, with equal distribution of economic, social and political opportunity. AI systems can be a force for collective good when deployed towards objectives like: the protection of democratic process and rule of law; the provision of common goods and services at low cost and high quality; data literacy and representativeness; damage mitigation and trust optimization towards users; achievement of the UN Sustainable Development Goals or sustainability understood more broadly, according to the pillars of economic development, social equity, and environmental protection. In other words, AI can be a tool to bring more good into the world and or to help with the world’s greatest challenges.
Principle: Draft Ethics Guidelines for Trustworthy AI, Dec 18, 2018

Published by The European Commission’s High-Level Expert Group on Artificial Intelligence

Related Principles

Human, social and environmental wellbeing

Throughout their lifecycle, AI systems should benefit individuals, society and the environment. This principle aims to clearly indicate from the outset that AI systems should be used for beneficial outcomes for individuals, society and the environment. AI system objectives should be clearly identified and justified. AI systems that help address areas of global concern should be encouraged, like the United Nation’s Sustainable Development Goals. Ideally, AI systems should be used to benefit all human beings, including future generations. AI systems designed for legitimate internal business purposes, like increasing efficiency, can have broader impacts on individual, social and environmental wellbeing. Those impacts, both positive and negative, should be accounted for throughout the AI system's lifecycle, including impacts outside the organisation.

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

(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

· 4. The Principle of Justice: “Be Fair”

For the purposes of these Guidelines, the principle of justice imparts that the development, use, and regulation of AI systems must be fair. Developers and implementers need to ensure that individuals and minority groups maintain freedom from bias, stigmatisation and discrimination. Additionally, the positives and negatives resulting from AI should be evenly distributed, avoiding to place vulnerable demographics in a position of greater vulnerability and striving for equal opportunity in terms of access to education, goods, services and technology amongst human beings, without discrimination. Justice also means that AI systems must provide users with effective redress if harm occurs, or effective remedy if data practices are no longer aligned with human beings’ individual or collective preferences. Lastly, the principle of justice also commands those developing or implementing AI to be held to high standards of accountability. Humans might benefit from procedures enabling the benchmarking of AI performance with (ethical) expectations.

Published by The European Commission’s High-Level Expert Group on Artificial Intelligence in Draft Ethics Guidelines for Trustworthy AI, Dec 18, 2018


The development and use of AIS must contribute to the creation of a just and equitable society. 1) AIS must be designed and trained so as not to create, reinforce, or reproduce discrimination based on — among other things — social, sexual, ethnic, cultural, or religious differences. 2) AIS development must help eliminate relationships of domination between groups and people based on differences of power, wealth, or knowledge. 3) AIS development must produce social and economic benefits for all by reducing social inequalities and vulnerabilities. 4) Industrial AIS development must be compatible with acceptable working conditions at every step of their life cycle, from natural resources extraction to recycling, and including data processing. 5) The digital activity of users of AIS and digital services should be recognized as labor that contributes to the functioning of algorithms and creates value. 6) Access to fundamental resources, knowledge and digital tools must be guaranteed for all. 7) We should support the development of commons algorithms — and of open data needed to train them — and expand their use, as a socially equitable objective.

Published by University of Montreal in The Montreal Declaration for a Responsible Development of Artificial Intelligence, Dec 4, 2018


1.1. Human centered and humanistic approach. Human rights and freedoms and the human as such must be treated as the greatest value in the process of AI technologies development. AI technologies developed by Actors should promote or not hinder the full realization of all human capabilities to achieve harmony in social, economic and spiritual spheres, as well as the highest self fulfillment of human beings. AI Actors should regard core values such as the preservation and development of human cognitive abilities and creative potential; the preservation of moral, spiritual and cultural values; the promotion of cultural and linguistic diversity and identity; and the preservation of traditions and the foundations of nations, peoples, ethnic and social groups. A human centered and humanistic approach is the basic ethical principle and central criterion for assessing the ethical behavior of AI Actors listed in Section 2 of this Code. 1.2. Recognition of autonomy and free will of human. AI Actors should take necessary measures to preserve the autonomy and free will of human in the process of decision making, their right to choose, as well as preserve human intellectual abilities in general as an intrinsic value and a system forming factor of modern civilization. AI Actors should forecast possible negative consequences for the development of human cognitive abilities at the earliest stages of AI systems creation and refrain from the development of AI systems that purposefully cause such consequences. 1.3. Compliance with the law. AI Actors must know and comply with the provisions of the national legislation in all areas of their activities and at all stages of creation, integration and use of AI technologies, i.a. in the sphere of legal responsibility of AI Actors. 1.4. Non discrimination. To ensure fairness and non discrimination, AI Actors should take measures to verify that the algorithms, datasets and processing methods for machine learning that are used to group and or classify data that concern individuals or groups do not entail intentional discrimination. AI Actors are encouraged to create and apply methods and software solutions that identify and prevent discrimination manifestations based on race, nationality, gender, political views, religious beliefs, age, social and economic status, or information about private life (at the same time, the rules of functioning or application of AI systems for different groups of users wherein such factors are taken into account for user segmentation, which are explicitly declared by an AI Actor, cannot be defined as discrimination). 1.5. Assessment of risks and humanitarian impact. AI Actors are encouraged to: • assess the potential risks of the use of an AI system, including social consequences for individuals, society and the state, as well as the humanitarian impact of an AI system on human rights and freedoms at different stages of its life cycle, i.a. during the formation and use of datasets; • monitor the manifestations of such risks in the long term; • take into account the complexity of AI systems’ actions, including interconnection and interdependence of processes in the AI systems’ life cycle, during risk assessment. In special cases concerning critical applications of an AI system it is encouraged that risk assessment be conducted with the involvement of a neutral third party or authorized official body given that it does not harm the performance and information security of the AI system and ensures the protection of the intellectual property and trade secrets of the developer.

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