· 2) Diversity and Fairness:

Artificial intelligence should provide non discriminatory services to various groups of people in accordance with the principles of fairness, equity and inclusion. We aim to initiate from the disciplined approach of system engineering, and to construct the AI system with diverse data and unbiased algorithms, thus improving the fairness of user experience.
Principle: Chinese Young Scientists’ Declaration on the Governance and Innovation of Artificial Intelligence, Aug 29, 2019

Published by Youth Work Committee of Shanghai Computer Society

Related Principles

V. Diversity, non discrimination and fairness

Data sets used by AI systems (both for training and operation) may suffer from the inclusion of inadvertent historic bias, incompleteness and bad governance models. The continuation of such biases could lead to (in)direct discrimination. Harm can also result from the intentional exploitation of (consumer) biases or by engaging in unfair competition. Moreover, the way in which AI systems are developed (e.g. the way in which the programming code of an algorithm is written) may also suffer from bias. Such concerns should be tackled from the beginning of the system’ development. Establishing diverse design teams and setting up mechanisms ensuring participation, in particular of citizens, in AI development can also help to address these concerns. It is advisable to consult stakeholders who may directly or indirectly be affected by the system throughout its life cycle. AI systems should consider the whole range of human abilities, skills and requirements, and ensure accessibility through a universal design approach to strive to achieve equal access for persons with disabilities.

Published by European Commission in Key requirements for trustworthy AI, Apr 8, 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

3. Artificial intelligence systems transparency and intelligibility should be improved, with the objective of effective implementation, in particular by:

a. investing in public and private scientific research on explainable artificial intelligence, b. promoting transparency, intelligibility and reachability, for instance through the development of innovative ways of communication, taking into account the different levels of transparency and information required for each relevant audience, c. making organizations’ practices more transparent, notably by promoting algorithmic transparency and the auditability of systems, while ensuring meaningfulness of the information provided, and d. guaranteeing the right to informational self determination, notably by ensuring that individuals are always informed appropriately when they are interacting directly with an artificial intelligence system or when they provide personal data to be processed by such systems, e. providing adequate information on the purpose and effects of artificial intelligence systems in order to verify continuous alignment with expectation of individuals and to enable overall human control on such systems.

Published by 40th International Conference of Data Protection and Privacy Commissioners (ICDPPC) in Declaration On Ethics And Data Protection In Artifical Intelligence, Oct 23, 2018

· Fairness and non discrimination

28. AI actors should promote social justice and safeguard fairness and non discrimination of any kind in compliance with international law. This implies an inclusive approach to ensuring that the benefits of AI technologies are available and accessible to all, taking into consideration the specific needs of different age groups, cultural systems, different language groups, persons with disabilities, girls and women, and disadvantaged, marginalized and vulnerable people or people in vulnerable situations. Member States should work to promote inclusive access for all, including local communities, to AI systems with locally relevant content and services, and with respect for multilingualism and cultural diversity. Member States should work to tackle digital divides and ensure inclusive access to and participation in the development of AI. At the national level, Member States should promote equity between rural and urban areas, and among all persons 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, in terms of access to and participation in the AI system life cycle. At the international level, the most technologically advanced countries have a responsibility of solidarity with the least advanced to ensure that the benefits of AI technologies are shared such that access to and participation in the AI system life cycle for the latter contributes to a fairer world order with regard to information, communication, culture, education, research and socio economic and political stability. 29. AI actors should make all reasonable efforts to minimize and avoid reinforcing or perpetuating discriminatory or biased applications and outcomes throughout the life cycle of the AI system to ensure fairness of such systems. Effective remedy should be available against discrimination and biased algorithmic determination. 30. Furthermore, digital and knowledge divides within and between countries need to be addressed throughout an AI system life cycle, including in terms of access and quality of access to technology and data, in accordance with relevant national, regional and international legal frameworks, as well as in terms of connectivity, knowledge and skills and meaningful participation of the affected communities, such that every person is treated equitably.

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