7. Principle of ethics

Developers should respect human dignity and individual autonomy in R&D of AI systems. [Comment] It is encouraged that, when developing AI systems that link with the human brain and body, developers pay particularly due consideration to respecting human dignity and individual autonomy, in light of discussions on bioethics, etc. It is also encouraged that, to the extent possible in light of the characteristics of the technologies to be adopted, developers make efforts to take necessary measures so as not to cause unfair discrimination resulting from prejudice included in the learning data of the AI systems. It is advisable that developers take precautions to ensure that AI systems do not unduly infringe the value of humanity, based on the International Human Rights Law and the International Humanitarian Law.
Principle: AI R&D Principles, Jul 28, 2017

Published by Ministry of Internal Affairs and Communications (MIC), the Government of Japan

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

2. Principle of transparency

Developers should pay attention to the verifiability of inputs outputs of AI systems and the explainability of their judgments. [Comment] AI systems which are supposed to be subject to this principle are such ones that might affect the life, body, freedom, privacy, or property of users or third parties. It is desirable that developers pay attention to the verifiability of the inputs and outputs of AI systems as well as the explainability of the judgment of AI systems within a reasonable scope in light of the characteristics of the technologies to be adopted and their use, so as to obtain the understanding and trust of the society including users of AI systems. [Note] Note that this principle is not intended to ask developers to disclose algorithms, source codes, or learning data. In interpreting this principle, consideration to privacy and trade secrets is also required.

Published by Ministry of Internal Affairs and Communications (MIC), the Government of Japan in AI R&D Principles, Jul 28, 2017

7. Principles of human dignity and individual autonomy

Users should respect human dignity and individual autonomy in the utilization of AI systems or AI services. [Main points to discuss] A) Respect for human dignity and individual autonomy With consideration of social contexts in the utilization of AI, users may be expected to respect human dignity and individual autonomy. B) Attention to the manipulation of human decision making, emotions, etc. by AI Users may be expected to pay attention to the risks of the manipulation of human decision making and emotions by AI and risks of excessive dependence on AI. It is crucial to consider who takes what measures against such risks. C) Reference to the discussion of bioethics, etc. in the case of linking AI systems with the human brain and body When linking AI with the human brain and body, users may be required to particularly take into consideration that human dignity and individual autonomy will not be violated, in light of discussions on bioethics, etc.

Published by Ministry of Internal Affairs and Communications (MIC), the Government of Japan in Draft AI Utilization Principles, Jul 17, 2018

6. Human Centricity and Well being

a. To aim for an equitable distribution of the benefits of data practices and avoid data practices that disproportionately disadvantage vulnerable groups. b. To aim to create the greatest possible benefit from the use of data and advanced modelling techniques. c. Engage in data practices that encourage the practice of virtues that contribute to human flourishing, human dignity and human autonomy. d. To give weight to the considered judgements of people or communities affected by data practices and to be aligned with the values and ethical principles of the people or communities affected. e. To make decisions that should cause no foreseeable harm to the individual, or should at least minimise such harm (in necessary circumstances, when weighed against the greater good). f. To allow users to maintain control over the data being used, the context such data is being used in and the ability to modify that use and context. g. To ensure that the overall well being of the user should be central to the AI system’s functionality.

Published by Personal Data Protection Commission (PDPC), Singapore in A compilation of existing AI ethical principles (Annex A), Jan 21, 2020

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