6 EQUITY PRINCIPLE

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.
Principle: The Montreal Declaration for a Responsible Development of Artificial Intelligence, Dec 4, 2018

Published by University of Montreal

Related Principles

(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

· 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.

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

2 RESPECT FOR AUTONOMY PRINCIPLE
AIS must be developed and used while respecting people’s autonomy, and with the goal of increasing people’s control over their lives and their surroundings. 1) AIS must allow individuals to fulfill their own moral objectives and their conception of a life worth living. 2) AIS must not be developed or used to impose a particular lifestyle on individuals, whether directly or indirectly, by implementing oppressive surveillance and evaluation or incentive mechanisms. 3) Public institutions must not use AIS to promote or discredit a particular conception of the good life. 4) It is crucial to empower citizens regarding digital technologies by ensuring access to the relevant forms of knowledge, promoting the learning of fundamental skills (digital and media literacy), and fostering the development of critical thinking. 5) AIS must not be developed to spread untrustworthy information, lies, or propaganda, and should be designed with a view to containing their dissemination. 6) The development of AIS must avoid creating dependencies through attention capturing techniques or the imitation of human characteristics (appearance, voice, etc.) in ways that could cause confusion between AIS and humans.

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

4 SOLIDARITY PRINCIPLE
The development of AIS must be compatible with maintaining the bonds of solidarity among people and generations. 1) AIS must not threaten the preservation of fulfilling moral and emotional human relationships, and should be developed with the goal of fostering these relationships and reducing people’s vulnerability and isolation. 2) AIS must be developed with the goal of collaborating with humans on complex tasks and should foster collaborative work between humans. 3) AIS should not be implemented to replace people in duties that require quality human relationships, but should be developed to facilitate these relationships. 4) Health care systems that use AIS must take into consideration the importance of a patient’s relationships with family and health care staff. 5) AIS development should not encourage cruel behavior toward robots designed to resemble human beings or non human animals in appearance or behavior. 6) AIS should help improve risk management and foster conditions for a society with a more equitable and mutual distribution of individual and collective risks.

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

Contact

Institute of Automation, Chinese Academy of Sciences
95 Zhongguancun East Road,
Haidian District, Beijing,
China 100190
Principal Investigator - Yi Zeng
contact@long-term-ai.cn

Contributors: Cunqing Huangfu, Enmeng Lu, Zizhe Ruan et al.

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Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences
International Research Center for AI Ethics and Governance, Institute of Automation, Chinese Academy of Sciences
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