Safe and Ethical AI (SEA) Platform Network · Linking Artificial Intelligence Principles (LAIP)

8. Principle of fairness

AI service providers, business users, and data providers should take into consideration that individuals will not be discriminated unfairly by the judgments of AI systems or AI services. [Main points to discuss] A) Attention to the representativeness of data used for learning or other methods of AI AI service providers, business users, and data providers may be expected to pay attention to the representativeness of data used for learning or other methods of AI and the social bias inherent in the data so that individuals should not be unfairly discriminated against due to their race, religion, gender, etc. as a result of the judgment of AI. In light of the characteristics of the technologies to be used and their usage, in what cases and to what extent is attention expected to be paid to the representativeness of data used for learning or other methods and the social bias inherent in the data? Note: The representativeness of data refers to the fact that data sampled and used do not distort the propensity of the population of data. B) Attention to unfair discrimination by algorithm AI service providers and business users may be expected to pay attention to the possibility that individuals may be unfairly discriminated against due to their race, religion, gender, etc. by the algorithm of AI. C) Human intervention Regarding the judgment made by AI, AI service providers and business users may be expected to make judgments as to whether to use the judgments of AI, how to use it, or other matters, with consideration of social contexts and reasonable expectations of people in the utilization of AI, so that individuals should not be unfairly discriminated against due to their race, religion, gender, etc. In light of the characteristics of the technologies to be used and their usage, in what cases and to what extent is human intervention expected?

Principle: Draft AI Utilization Principles, Jul 17, 2018

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

Related Principles

· (3) Privacy

In society premised on AI, it is possible to estimate each person’s political position, economic situation, hobbies preferences, etc. with high accuracy from data on the data subject’s personal behavior. This means, when utilizing AI, that more careful treatment of personal data is necessary than simply utilizing personal information. To ensure that people are not suffered disadvantages from unexpected sharing or utilization of personal data through the internet for instance, each stakeholder must handle personal data based on the following principles. Companies or government should not infringe individual person’s freedom, dignity and equality in utilization of personal data with AI technologies. AI that uses personal data should have a mechanism that ensures accuracy and legitimacy and enable the person herself himself to be substantially involved in the management of her his privacy data. As a result, when using the AI, people can provide personal data without concerns and effectively benefit from the data they provide. Personal data must be properly protected according to its importance and sensitivity. Personal data varies from those unjust use of which would be likely to greatly affect rights and benefits of individuals (Typically thought and creed, medical history, criminal record, etc.) to those that are semi public in social life. Taking this into consideration, we have to pay enough attention to the balance between the use and protection of personal data based on the common understanding of society and the cultural background.

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

1. Principle of proper utilization

Users should make efforts to utilize AI systems or AI services in a proper scope and manner, under the proper assignment of roles between humans and AI systems, or among users. [Main points to discuss] A) Utilization in the proper scope and manner On the basis of the provision of information and explanation from developers, etc. and with consideration of social contexts and circumstances, users may be expected to use AI in the proper scope and manner. In addition, users may be expected to recognize benefits and risks, understand proper uses, acquire necessary knowledge and skills and so on before using AI, according to the characteristics, usage situations, etc. of AI. Furthermore, users may be expected to check regularly whether they use AI in an appropriate scope and manner. B) Proper balance of benefits and risks of AI AI service providers and business users may be expected to take into consideration proper balance between benefits and risks of AI, including the consideration of the active use of AI for productivity and work efficiency improvements, after appropriately assessing risks of AI. C) Updates of AI software and inspections repairs, etc. of AI Through the process of utilization, users may be expected to make efforts to update AI software and perform inspections, repairs, etc. of AI in order to improve the function of AI and to mitigate risks. D) Human Intervention Regarding the judgment made by AI, in cases where it is necessary and possible (e.g., medical care using AI), humans may be expected to make decisions as to whether to use the judgments of AI, how to use it etc. In those cases, what can be considered as criteria for the necessity of human intervention? In the utilization of AI that operates through actuators, etc., in the case where it is planned to shift to human operation under certain conditions, what kind of matters are expected to be paid attention to? [Points of view as criteria (example)] • The nature of the rights and interests of indirect users, et al., and their intents, affected by the judgments of AI. • The degree of reliability of the judgment of AI (compared with reliability of human judgment). • Allowable time necessary for human judgment • Ability expected to be possessed by users E) Role assignments among users With consideration of the volume of capabilities and knowledge on AI that each user is expected to have and ease of implementing necessary measures, users may be expected to play such roles as seems to be appropriate and also to bear the responsibility. F) Cooperation among stakeholders Users and data providers may be expected to cooperate with stakeholders and to work on preventive or remedial measures (including information sharing, stopping and restoration of AI, elucidation of causes, measures to prevent recurrence, etc.) in accordance with the nature, conditions, etc. of damages caused by accidents, security breaches, privacy infringement, etc. that may occur in the future or have occurred through the use of AI. What is expected reasonable from a users point of view to ensure the above effectiveness?

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

6. Principle of privacy

Users and data providers should take into consideration that the utilization of AI systems or AI services will not infringe on the privacy of users’ or others. [Main points to discuss] A) Respect for the privacy of others With consideration of social contexts and reasonable expectations of people in the utilization of AI, users may be expected to respect the privacy of others in the utilization of AI. In addition, users may be expected to consider measures to be taken against privacy infringement caused by AI in advance. B) Respect for the privacy of others in the collection, analysis, provision, etc. of personal data Users and data providers may be expected to respect the privacy of others in the collection, analysis, provision, etc. of personal data used for learning or other methods of AI. C) Consideration for the privacy, etc. of the subject of profiling which uses AI In the case of profiling by using AI in fields where the judgments of AI might have significant influences on individual rights and interests, such as the fields of personnel evaluation, recruitment, and financing, AI service providers and business users may be expected to pay due consideration to the privacy, etc. of the subject of profiling. D) Attention to the infringement of the privacy of users’ or others Consumer users may be expected to pay attention not to give information that is highly confidential (including information on others as well as information on users’ themselves) to AI carelessly, by excessively empathizing with AI such as pet robots, or by other causes. E) Prevention of personal data leakage AI service providers, business users, and data providers may be expected to take appropriate measures so that personal data should not be provided by the judgments of AI to third parties without consent of the person.

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

9. Principle of transparency

AI service providers and business users should pay attention to the verifiability of inputs outputs of AI systems or AI services and the explainability of their judgments. Note: This principle is not intended to ask for the disclosure of algorithm, source code, or learning data. In interpreting this principle, privacy of individuals and trade secrets of enterprises are also taken into account. [Main points to discuss] A) Recording and preserving the inputs outputs of AI In order to ensure the verifiability of the input and output of AI, AI service providers and business users may be expected to record and preserve the inputs and outputs. In light of the characteristics of the technologies to be used and their usage, in what cases and to what extent are the inputs and outputs expected to be recorded and preserved? For example, in the case of using AI in fields where AI systems might harm the life, body, or property, such as the field of autonomous driving, the inputs and outputs of AI may be expected to be recorded and preserved to the extent whch is necessary for investigating the causes of accidents and preventing the recurrence of such accidents. B) Ensuring explainability AI service providers and business users may be expected to ensure explainability on the judgments of AI. In light of the characteristics of the technologies to be used and their usage, in what cases and to what extent is explainability expected to be ensured? Especially in the case of using AI in fields where the judgments of AI might have significant influences on individual rights and interests, such as the fields of medical care, personnel evaluation and recruitment and financing, explainability on the judgments of AI may be expected to be ensured. (For example, we have to pay attention to the current situation where deep learning has high prediction accuracy, but it is difficult to explain its judgment.)

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

5 Ensure inclusiveness and equity

Inclusiveness requires that AI used in health care is designed to encourage the widest possible appropriate, equitable use and access, irrespective of age, gender, income, ability or other characteristics. Institutions (e.g. companies, regulatory agencies, health systems) should hire employees from diverse backgrounds, cultures and disciplines to develop, monitor and deploy AI. AI technologies should be designed by and evaluated with the active participation of those who are required to use the system or will be affected by it, including providers and patients, and such participants should be sufficiently diverse. Participation can also be improved by adopting open source software or making source codes publicly available. AI technology – like any other technology – should be shared as widely as possible. AI technologies should be available not only in HIC and for use in contexts and for needs that apply to high income settings but they should also be adaptable to the types of devices, telecommunications infrastructure and data transfer capacity in LMIC. AI developers and vendors should also consider the diversity of languages, ability and forms of communication around the world to avoid barriers to use. Industry and governments should strive to ensure that the “digital divide” within and between countries is not widened and ensure equitable access to novel AI technologies. AI technologies should not be biased. Bias is a threat to inclusiveness and equity because it represents a departure, often arbitrary, from equal treatment. For example, a system designed to diagnose cancerous skin lesions that is trained with data on one skin colour may not generate accurate results for patients with a different skin colour, increasing the risk to their health. Unintended biases that may emerge with AI should be avoided or identified and mitigated. AI developers should be aware of the possible biases in their design, implementation and use and the potential harm that biases can cause to individuals and society. These parties also have a duty to address potential bias and avoid introducing or exacerbating health care disparities, including when testing or deploying new AI technologies in vulnerable populations. AI developers should ensure that AI data, and especially training data, do not include sampling bias and are therefore accurate, complete and diverse. If a particular racial or ethnic minority (or other group) is underrepresented in a dataset, oversampling of that group relative to its population size may be necessary to ensure that an AI technology achieves the same quality of results in that population as in better represented groups. AI technologies should minimize inevitable power disparities between providers and patients or between companies that create and deploy AI technologies and those that use or rely on them. Public sector agencies should have control over the data collectedby private health care providers, and their shared responsibilities should be defined and respected. Everyone – patients, health care providers and health care systems – should be able to benefit from an AI technology and not just the technology providers. AI technologies should be accompanied by means to provide patients with knowledge and skills to better understand their health status and to communicate effectively with health care providers. Future health literacy should include an element of information technology literacy. The effects of use of AI technologies must be monitored and evaluated, including disproportionate effects on specific groups of people when they mirror or exacerbate existing forms of bias and discrimination. Special provision should be made to protect the rights and welfare of vulnerable persons, with mechanisms for redress if such bias and discrimination emerges or is alleged.

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