1. Artificial intelligence should be developed for the common good and benefit of humanity.

The UK must seek to actively shape AI's development and utilisation, or risk passively acquiescing to its many likely consequences. A shared ethical AI framework is needed to give clarity as to how AI can best be used to benefit individuals and society. By establishing these principles, the UK can lead by example in the international community. We recommend that the Government convene a global summit of governments, academia and industry to establish international norms for the design, development, regulation and deployment of artificial intelligence. The prejudices of the past must not be unwittingly built into automated systems, and such systems must be carefully designed from the beginning, with input from as diverse a group of people as possible.
Principle: AI Code, Apr 16, 2018

Published by House of Lords, Select Committee on Artificial Intelligence

Related Principles

· (1) Human centric

Utilization of AI should not infringe upon fundamental human rights that are guaranteed by the Constitution and international norms. AI should be developed and utilized and implemented in society to expand the abilities of people and to pursue the diverse concepts of happiness of diverse people. In the AI utilized society, it is desirable that we implement appropriate mechanisms of literacy education and promotion of proper uses, so as not to over depend on AI or not to ill manipulate human decisions by exploiting AI. AI can expand human abilities and creativity not only by replacing part of human task but also by assisting human as an advanced instrument. When using AI, people must judge and decide for themselves how to use AI. Appropriate stakeholders involved in the development, provision, and utilization of AI should be responsible for the result of AI utilization, depending on the nature of the issue. In order to avoid creating digital divide and allow all people to reap the benefit of AI regardless of their digital expertise, each stakeholder should take into consideration to user friendliness of the system in the process of AI deployment.

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

V. Diversity, non discrimination and fairness

Data sets used by AI systems (both for training and operation) may suffer from the inclusion of inadvertent historic bias, incompleteness and bad governance models. The continuation of such biases could lead to (in)direct discrimination. Harm can also result from the intentional exploitation of (consumer) biases or by engaging in unfair competition. Moreover, the way in which AI systems are developed (e.g. the way in which the programming code of an algorithm is written) may also suffer from bias. Such concerns should be tackled from the beginning of the system’ development. Establishing diverse design teams and setting up mechanisms ensuring participation, in particular of citizens, in AI development can also help to address these concerns. It is advisable to consult stakeholders who may directly or indirectly be affected by the system throughout its life cycle. AI systems should consider the whole range of human abilities, skills and requirements, and ensure accessibility through a universal design approach to strive to achieve equal access for persons with disabilities.

Published by European Commission in Key requirements for trustworthy AI, Apr 8, 2019

· 1. THE MAIN PRIORITY OF THE DEVELOPMENT OF AI TECHNOLOGIES IS PROTECTING THE INTERESTS AND RIGHTS OF HUMAN BEINGS COLLECTIVELY AND AS INDIVIDUALS

1.1. Human centered and humanistic approach. In the development of AI technologies, the rights and freedoms of the individual should be given the greatest value. AI technologies developed by AI Actors should promote or not hinder the realization of humans’ capabilities to achieve harmony in social, economic and spiritual spheres, as well as in the highest self fulfillment of human beings. They should take into account key values such as the preservation and development of human cognitive abilities and creative potential; the preservation of moral, spiritual and cultural values; the promotion of cultural and linguistic diversity and identity; and the preservation of traditions and the foundations of nations, peoples and ethnic and social groups. A human centered and humanistic approach is the basic ethical principle and central criterion for assessing the ethical behavior of AI Actors, which are listed in the section 2 of this Code. 1.2. Respect for human autonomy and freedom of will. AI Actors should take all necessary measures to preserve the autonomy and free will of a human‘s decision making ability, the right to choose, and, in general, the intellectual abilities of a human as an intrinsic value and a system forming factor of modern civilization. AI Actors should, during AIS creation, assess the possible negative consequences for the development of human cognitive abilities and prevent the development of AIS that purposefully cause such consequences. 1.3. Compliance with the law. AI Actors must know and comply with the provisions of the legislation of the Russian Federation in all areas of their activities and at all stages of the creation, development and use of AI technologies, including in matters of the legal responsibility of AI Actors. 1.4. Non discrimination. To ensure fairness and non discrimination, AI Actors should take measures to verify that the algorithms, datasets and processing methods for machine learning that are used to group and or classify data concerning individuals or groups do not intentionally discriminate. AI Actors are encouraged to create and apply methods and software solutions that identify and prevent discrimination based on race, nationality, gender, political views, religious beliefs, age, social and economic status, or information about private life. (At the same time, cannot be considered as discrimination rules, which are explicitly declared by an AI Actor for functioning or the application of AIS for the different groups of users, with such factors taken into account for segmentation) 1.5. Assessment of risks and humanitarian impact. AI Actors are encouraged to assess the potential risks of using an AIS, including the social consequences for individuals, society and the state, as well as the humanitarian impact of the AIS on human rights and freedoms at different stages, including during the formation and use of datasets. AI Actors should also carry out long term monitoring of the manifestations of such risks and take into account the complexity of the behavior of AIS during risk assessment, including the relationship and the interdependence of processes in the AIS’s life cycle. For critical applications of the AIS, in special cases, it is encouraged that a risk assessment be conducted through the involvement of a neutral third party or authorized official body when to do so would not harm the performance and information security of the AIS and would ensure the protection of the intellectual property and trade secrets of the developer.

Published by AI Alliance Russia in Artificial Intelligence Code of Ethics, Oct 26, 2021

· Transparency and explainability

The transparency and explainability of AI systems are often essential preconditions to ensure the respect, protection and promotion of human rights, fundamental freedoms and ethical principles. Transparency is necessary for relevant national and international liability regimes to work effectively. A lack of transparency could also undermine the possibility of effectively challenging decisions based on outcomes produced by AI systems and may thereby infringe the right to a fair trial and effective remedy, and limits the areas in which these systems can be legally used. While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security. People should be fully informed when a decision is informed by or is made on the basis of AI algorithms, including when it affects their safety or human rights, and in those circumstances should have the opportunity to request explanatory information from the relevant AI actor or public sector institutions. In addition, individuals should be able to access the reasons for a decision affecting their rights and freedoms, and have the option of making submissions to a designated staff member of the private sector company or public sector institution able to review and correct the decision. AI actors should inform users when a product or service is provided directly or with the assistance of AI systems in a proper and timely manner. From a socio technical lens, greater transparency contributes to more peaceful, just, democratic and inclusive societies. It allows for public scrutiny that can decrease corruption and discrimination, and can also help detect and prevent negative impacts on human rights. Transparency aims at providing appropriate information to the respective addressees to enable their understanding and foster trust. Specific to the AI system, transparency can enable people to understand how each stage of an AI system is put in place, appropriate to the context and sensitivity of the AI system. It may also include insight into factors that affect a specific prediction or decision, and whether or not appropriate assurances (such as safety or fairness measures) are in place. In cases of serious threats of adverse human rights impacts, transparency may also require the sharing of code or datasets. Explainability refers to making intelligible and providing insight into the outcome of AI systems. The explainability of AI systems also refers to the understandability of the input, output and the functioning of each algorithmic building block and how it contributes to the outcome of the systems. Thus, explainability is closely related to transparency, as outcomes and ub processes leading to outcomes should aim to be understandable and traceable, appropriate to the context. AI actors should commit to ensuring that the algorithms developed are explainable. In the case of AI applications that impact the end user in a way that is not temporary, easily reversible or otherwise low risk, it should be ensured that the meaningful explanation is provided with any decision that resulted in the action taken in order for the outcome to be considered transparent. Transparency and explainability relate closely to adequate responsibility and accountability measures, as well as to the trustworthiness of AI systems.

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO) in Draft Text of The Recommendation on the Ethics of Artificial Intelligence, Nov 24, 2021

4 Foster responsibility and accountability

Humans require clear, transparent specification of the tasks that systems can perform and the conditions under which they can achieve the desired level of performance; this helps to ensure that health care providers can use an AI technology responsibly. Although AI technologies perform specific tasks, it is the responsibility of human stakeholders to ensure that they can perform those tasks and that they are used under appropriate conditions. Responsibility can be assured by application of “human warranty”, which implies evaluation by patients and clinicians in the development and deployment of AI technologies. In human warranty, regulatory principles are applied upstream and downstream of the algorithm by establishing points of human supervision. The critical points of supervision are identified by discussions among professionals, patients and designers. The goal is to ensure that the algorithm remains on a machine learning development path that is medically effective, can be interrogated and is ethically responsible; it involves active partnership with patients and the public, such as meaningful public consultation and debate (101). Ultimately, such work should be validated by regulatory agencies or other supervisory authorities. When something does go wrong in application of an AI technology, there should be accountability. Appropriate mechanisms should be adopted to ensure questioning by and redress for individuals and groups adversely affected by algorithmically informed decisions. This should include access to prompt, effective remedies and redress from governments and companies that deploy AI technologies for health care. Redress should include compensation, rehabilitation, restitution, sanctions where necessary and a guarantee of non repetition. The use of AI technologies in medicine requires attribution of responsibility within complex systems in which responsibility is distributed among numerous agents. When medical decisions by AI technologies harm individuals, responsibility and accountability processes should clearly identify the relative roles of manufacturers and clinical users in the harm. This is an evolving challenge and remains unsettled in the laws of most countries. Institutions have not only legal liability but also a duty to assume responsibility for decisions made by the algorithms they use, even if it is not feasible to explain in detail how the algorithms produce their results. To avoid diffusion of responsibility, in which “everybody’s problem becomes nobody’s responsibility”, a faultless responsibility model (“collective responsibility”), in which all the agents involved in the development and deployment of an AI technology are held responsible, can encourage all actors to act with integrity and minimize harm. In such a model, the actual intentions of each agent (or actor) or their ability to control an outcome are not considered.

Published by World Health Organization (WHO) in Key ethical principles for use of artificial intelligence for health, Jun 28, 2021