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

4. Fairness:

AI should be designed to minimize bias and promote inclusive representation.

Principle: Everyday Ethics for Artificial Intelligence: Five Areas of Ethical Focus, Sep 6, 2018

Published by IBM

Related Principles

Fairness and non discrimination.

AI actors should promote fairness and non discrimination, diversity and inclusion, ensure social justice, safeguard equity and combat all forms of discrimination, in accordance with international law. AI actors should make all reasonable efforts to minimise and avoid reinforcing or perpetuating discriminatory or biased applications and outcomes throughout the lifecycle of AI systems, in order to ensure the fairness of such systems.

Published by OFFICE OF THE CHIEF OF MINISTERS UNDERSECRETARY OF INFORMATION TECHNOLOGIES in Recommendations for reliable artificial intelligence, Jnue 2, 2023

(b) Inclusiveness:

AI should be inclusive, aiming to avoid bias and allowing for diversity and avoiding a new digital divide.

Published by The Extended Working Group on Ethics of Artificial Intelligence (AI) of the World Commission on the Ethics of Scientific Knowledge and Technology (COMEST), UNESCO in Suggested generic principles for the development, implementation and use of AI, Mar 21, 2019

4 Fairness and Non discrimination

Organisations that develop, deploy or use AI systems and any national laws that regulate such use shall ensure the non discrimination of AI outcomes, and shall promote appropriate and effective measures to safeguard fairness in AI use.

Published by International Technology Law Association (ITechLaw) in The Eight Principles of Responsible AI, May 23, 2019

Principle 1 – Fairness

The fairness principle requires taking necessary actions to eliminate bias, discriminationor stigmatization of individuals, communities, or groups in the design, data, development, deployment and use of AI systems. Bias may occur due to data, representation or algorithms and could lead to discrimination against the historically disadvantaged groups. When designing, selecting, and developing AI systems, it is essential to ensure just, fair, non biased, non discriminatory and objective standards that are inclusive, diverse, and representative of all or targeted segments of society. The functionality of an AI system should not be limited to a specific group based on gender, race, religion, disability, age, or sexual orientation. In addition, the potential risks, overall benefits, and purpose of utilizing sensitive personal data should be well motivated and defined or articulated by the AI System Owner. To ensure consistent AI systems that are based on fairness and inclusiveness, AI systems should be trained on data that are cleansed from bias and is representative of affected minority groups. Al algorithms should be built and developed in a manner that makes their composition free from bias and correlation fallacy.

Published by SDAIA in AI Ethics Principles, Sept 14, 2022

· ③ Respect for Diversity

Throughout every stage of AI development and utilization, the diversity and representativeness of the AI users should be ensured, and bias and discrimination based on personal characteristics, such as gender, age, disability, region, race, religion, and nationality, should be minimized. Commercialized AI systems should be generally applicable to all individuals. The socially disadvantaged and vulnerable should be guaranteed access to AI technologies and services. Efforts should be made to ensure equal distribution of AI benefits to all people rather than to certain groups.

Published by The Ministry of Science and ICT (MSIT) and the Korea Information Society Development Institute (KISDI) in National AI Ethical Guidelines, Dec 23, 2020