3. The existence value of AI is to teach people to learn and make people grow, instead of surpassing humans and replacing people.

Principle: Four principles of AI ethics, May 26, 2018

Published by Robin Li, co-founder and CEO of Baidu

Related Principles

· (2) Diversity & Inclusion

The society in which people with diverse backgrounds, concepts on priorities and mentality can pursue their own idea of happiness, be flexibly included to create new values, is one of the ideals in present world worth challenged to establish. AI is a technology powerful enough for us to reach such an ideal. With appropriate development and deployment of AI, we need to change the framework of society to reach such a goal.

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

· (2) Education

In a society premised on AI, we have to eliminate disparities, divisions, or socially weak people. Therefore, policy makers and managers of the enterprises involved in AI must have an accurate understanding of AI, the knowledge for proper use of AI in society and AI ethics, taking into account the complexity of AI and the possibility that AI can be misused intentionally. The AI user should understand the outline of AI and be educated to utilize it properly because AI is much more complicated than the already developed conventional tools. On the other hand, from the viewpoint of AI’s contributions to society, it is important for the developers of AI to learn about the social sciences, business models, and ethics, including normative awareness of norms and wide range of liberal arts not to mention the basis possibly generated by AI. From the above point of view, it is necessary to establish an educational environment that provides AI literacy according to the following principles, equally to every person. In order to get rid of disparity between people having a good knowledge about AI technology and those being weak in it, opportunities for education such as AI literacy are widely provided in early childhood education and primary and secondary education. The opportunities of learning about AI should be provided for the elderly people as well as workforce generation. Our society needs an education scheme by which anyone should be able to learn AI, mathematics, and data science beyond the boundaries of literature and science. Literacy education provides the following contents: 1) Data used by AI are usually contaminated by bias, 2) AI is easy to generate unwanted bias in its use, and 3) The issues of impartiality, fairness, and privacy protection which are inherent to actual use of AI. In a society in which AI is widely used, the educational environment is expected to change from the current unilateral and uniform teaching style to one that matches the interests and skill level of each individual person. Therefore, the society probably shares the view that the education system will change constantly to the above mentioned education style, regardless of the success experience in the educational system of the past. In education, it is especially important to avoid dropouts. For this, it is desirable to introduce an interactive educational environment which fully utilizes AI technologies and allows students to work together to feel a kind accomplishment. In order to develop such an educational environment, it is desirable that companies and citizens work on their own initiative, not to burden administrations and schools (teachers).

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

8. We foster the cooperative model.

We believe that human and machine intelligence are complementary, with each bringing its own strength to the table. While we believe in a people first approach of human machine collaboration, we recognize, that humans can benefit from the strength of AI to unfold a potential that neither human or machine can unlock on its own. We recognize the widespread fear, that AI enabled machines will outsmart the human intelligence. We as Deutsche Telekom think differently. We know and believe in the human strengths like inspiration, intuition, sense making and empathy. But we also recognize the strengths of AI like data recall, processing speed and analysis. By combining both, AI systems will help humans to make better decisions and accomplish objectives more effective and efficient.

Published by Deutsche Telekom in Deutsche Telekom’s guidelines for artificial intelligence, May 11, 2018

3. Reward AI for ‘showing its workings’

Any AI system learning from bad examples could end up becoming socially inappropriate – we have to remember that most AI today has no cognition of what it is saying. Only broad listening and learning from diverse data sets will solve for this. One of the approaches is to develop a reward mechanism when training AI. Reinforcement learning measures should be built not just based on what AI or robots do to achieve an outcome, but also on how AI and robots align with human values to accomplish that particular result.

Published by Sage in The Ethics of Code: Developing AI for Business with Five Core Principles, Jun 27, 2017

2. Human centric

AI is used to simplify and enhance our customers’ lives. Employees’ issues are recognized and respected. We acknowledge the advantages of a cooperative and complementary model of humanmachine interactions and seek to use this in a sustainable way. Our preference and intention is for AI to extend and complement human abilities rather than lessen or restrict them.

Published by Telia Company AB in Telia Company Guiding Principles on trusted AI ethics, Jan 22, 2019