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

(b) Inclusiveness:

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

Principle: Suggested generic principles for the development, implementation and use of AI, Mar 21, 2019

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

Related Principles

Human centred values

Throughout their lifecycle, AI systems should respect human rights, diversity, and the autonomy of individuals. This principle aims to ensure that AI systems are aligned with human values. Machines should serve humans, and not the other way around. AI systems should enable an equitable and democratic society by respecting, protecting and promoting human rights, enabling diversity, respecting human freedom and the autonomy of individuals, and protecting the environment. Human rights risks need to be carefully considered, as AI systems can equally enable and hamper such fundamental rights. It’s permissible to interfere with certain human rights where it’s reasonable, necessary and proportionate. All people interacting with AI systems should be able to keep full and effective control over themselves. AI systems should not undermine the democratic process, and should not undertake actions that threaten individual autonomy, like deception, unfair manipulation, unjustified surveillance, and failing to maintain alignment between a disclosed purpose and true action. AI systems should be designed to augment, complement and empower human cognitive, social and cultural skills. Organisations designing, developing, deploying or operating AI systems should ideally hire staff from diverse backgrounds, cultures and disciplines to ensure a wide range of perspectives, and to minimise the risk of missing important considerations only noticeable by some stakeholders.

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

4. Fairness:

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

Published by IBM in Everyday Ethics for Artificial Intelligence: Five Areas of Ethical Focus, Sep 6, 2018

7 DIVERSITY INCLUSION PRINCIPLE

The development and use of AIS must be compatible with maintaining social and cultural diversity and must not restrict the scope of lifestyle choices or personal experiences. 1) AIS development and use must not lead to the homogenization of society through the standardization of behaviours and opinions. 2) From the moment algorithms are conceived, AIS development and deployment must take into consideration the multitude of expressions of social and cultural diversity present in the society. 3) AI development environments, whether in research or industry, must be inclusive and reﬂect the diversity of the individuals and groups of the society. 4) AIS must avoid using acquired data to lock individuals into a user proﬁle, ﬁx their personal identity, or conﬁne them to a ﬁltering bubble, which would restrict and conﬁne their possibilities for personal development — especially in ﬁelds such as education, justice, or business. 5) AIS must not be developed or used with the aim of limiting the free expression of ideas or the opportunity to hear diverse opinions, both of which being essential conditions of a democratic society. 6) For each service category, the AIS offering must be diversiﬁed to prevent de facto monopolies from forming and undermining individual freedoms.

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

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