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

8. Avoid biases and unfair impacts on people, particularly those related to sensitive characteristics such as race, ethnicity, gender, nationality, income, sexual orientation, ability and political or religious beliefs.

Principle: Declaration Of Ethics For The Development And Use Of Artificial Intelligence (unofficial translation), Feb 8, 2019 (unconfirmed)

Published by IA Latam

Related Principles

· Fairness

The development of AI should treat and serve all children fairly and should not cause discrimination or harm to any child. The research and application of AI shall not make any distinction as to the child's, his or her parent's, legal guardians', or other caregivers' race, color, gender, language, religion, political or other opinions, nationality, or social origin, property, disability, birth or other status, as far as the fundamental rights of the child are concerned.

Published by Beijing Academy of Artificial Intelligence (BAAI), Peking University, Tsinghua University and the Chinese Academy of Sciences, together with enterprises that focus on AI development. in Artificial Intelligence for Children: Beijing Principles, Sep 14, 2020

· 2. Avoid creating or reinforcing unfair bias.

AI algorithms and datasets can reflect, reinforce, or reduce unfair biases. We recognize that distinguishing fair from unfair biases is not always simple, and differs across cultures and societies. We will seek to avoid unjust impacts on people, particularly those related to sensitive characteristics such as race, ethnicity, gender, nationality, income, sexual orientation, ability, and political or religious belief.

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

· 5. Non Discrimination

Discrimination concerns the variability of AI results between individuals or groups of people based on the exploitation of differences in their characteristics that can be considered either intentionally or unintentionally (such as ethnicity, gender, sexual orientation or age), which may negatively impact such individuals or groups. Direct or indirect discrimination through the use of AI can serve to exploit prejudice and marginalise certain groups. Those in control of algorithms may intentionally try to achieve unfair, discriminatory, or biased outcomes in order to exclude certain groups of persons. Intentional harm can, for instance, be achieved by explicit manipulation of the data to exclude certain groups. Harm may also result from exploitation of consumer biases or unfair competition, such as homogenisation of prices by means of collusion or non transparent market. Discrimination in an AI context can occur unintentionally due to, for example, problems with data such as bias, incompleteness and bad governance models. Machine learning algorithms identify patterns or regularities in data, and will therefore also follow the patterns resulting from biased and or incomplete data sets. An incomplete data set may not reflect the target group it is intended to represent. While it might be possible to remove clearly identifiable and unwanted bias when collecting data, data always carries some kind of bias. Therefore, the upstream identification of possible bias, which later can be rectified, is important to build in to the development of AI. Moreover, it is important to acknowledge that AI technology can be employed to identify this inherent bias, and hence to support awareness training on our own inherent bias. Accordingly, it can also assist us in making less biased decisions.

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

3. Justice

[QUESTIONS] How do we ensure that the benefits of AI are available to everyone? Must we fight against the concentration of power and wealth in the hands of a small number of AI companies? What types of discrimination could AI create or exacerbate? Should the development of AI be neutral or should it seek to reduce social and economic inequalities? What types of legal decisions can we delegate to AI? [PRINCIPLES] The development of AI should promote justice and seek to eliminate all types of discrimination, notably those linked to gender, age, mental physical abilities, sexual orientation, ethnic social origins and religious beliefs.

Published by University of Montreal, Forum on the Socially Responsible Development of AI in The Montreal Declaration for a Responsible Development of Artificial Intelligence, Nov 3, 2017

· Ensuring diversity and inclusiveness

19. Respect, protection and promotion of diversity and inclusiveness should be ensured throughout the life cycle of AI systems, consistent with international law, including human rights law. This may be done by promoting active participation of all individuals or groups regardless of race, colour, descent, gender, age, language, religion, political opinion, national origin, ethnic origin, social origin, economic or social condition of birth, or disability and any other grounds. 20. The scope of lifestyle choices, beliefs, opinions, expressions or personal experiences, including the optional use of AI systems and the co design of these architectures should not be restricted during any phase of the life cycle of AI systems. 21. Furthermore, efforts, including international cooperation, should be made to overcome, and never take advantage of, the lack of necessary technological infrastructure, education and skills, as well as legal frameworks, particularly in LMICs, LDCs, LLDCs and SIDS, affecting communities.

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO) in The Recommendation on the Ethics of Artificial Intelligence, Nov 24, 2021