· 3.1 Democratizing Access and Creating Equality of Opportunity

While AI systems are creating new ways to generate economic value, if the value favors only certain incumbent entities, there is a risk of exacerbating existing wage, income, and wealth gaps. We support diversification and broadening of access to the resources necessary for AI development and use, such as computing resources, education, and training, including opportunities to participate in the development of these technologies.
Principle: AI Policy Principles, Oct 24, 2017

Published by Information Technology Industry Council (ITI)

Related Principles

· (7) Innovation

To realize Society 5.0 and continuous innovation in which people evolve along with AI, it is necessary to account for national, industry academia, and public private borders, race, sex, nationality, age, political and religious beliefs, etc. Beyond these boundaries, through a Global perspective we must promote diversification and cooperation between industry academia public private sectors, through the development of human capabilities and technology. To encourage mutual collaboration and partnership between universities, research institutions and private sectors, and the flexible movement of talent. To implement AI efficiently and securely in society, methods for confirming the quality and reliability of AI and for efficient collection and maintenance of data utilized in AI must be promoted. Additionally, the establishment of AI engineering should also be promoted. This engineering includes methods for the development, testing and operation of AI. To ensure the sound development of AI technology, it is necessary to establish an accessible platform in which data from all fields can be mutually utilized across borders with no monopolies, while ensuring privacy and security. In addition, research and development environments should be created in which computer resources and highspeed networks are shared and utilized, to promote international collaboration and accelerate AI research. To promote implementation of AI technology, governments must promote regulatory reform to reduce impeding factors in AI related fields.

Published by Cabinet Office, Government of Japan in Social Principles of Human-centric AI (Draft), Dec 27, 2018

(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

• Foster Innovation and Open Development

To better understand the impact of AI and explore the broad diversity of AI implementations, public policy should encourage investment in AI R&D. Governments should support the controlled testing of AI systems to help industry, academia, and other stakeholders improve the technology. [Recommendations] • Fuel AI innovation: Public policy should promote investment, make available funds for R&D, and address barriers to AI development and adoption. • Address global societal challenges: AI powered flagship initiatives should be funded to find solutions to the world’s greatest challenges such as curing cancer, ensuring food security, controlling climate change, and achieving inclusive economic growth. • Allow for experimentation: Governments should create the conditions necessary for the controlled testing and experimentation of AI in the real world, such as designating self driving test sites in cities. • Prepare a workforce for AI: Governments should create incentives for students to pursue courses of study that will allow them to create the next generation of AI. • Lead by example: Governments should lead the way on demonstrating the applications of AI in its interactions with citizens and invest sufficiently in infrastructure to support and deliver AI based services. • Partnering for AI: Governments should partner with industry, academia, and other stakeholders for the promotion of AI and debate ways to maximize its benefits for the economy.

Published by Intel in AI public policy principles, Oct 18, 2017

• Create New Human Employment Opportunities and Protect People’s Welfare

AI will change the way people work. Public policy in support of adding skills to the workforce and promoting employment across different sectors should enhance employment opportunities while also protecting people’s welfare. [Recommendations] • Encouraging Human Employment: Governments should implement programs to mitigate AI’s impact on jobs and devise policies that promote employment. These programs should particularly focus on the effectiveness of incentives in government funded infrastructure projects. • Retraining: Governments should implement policies that support the up skilling and the re skilling of the workforce, particularly in job areas that are less likely to be automated, such as positions focused on person to person interaction and the need for “guided computation” where individuals direct and oversee the operation of the technology.

Published by Intel in AI public policy principles, Oct 18, 2017


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.

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