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

4. Protect the right of each person on the privacy of their data (sensitive personal information) and in the same way give ethical use to the information of each individual always with the prior consent of its owner. Each person's consent will be required regarding the use of the generation of new data created from the AI.

Principle: Declaration Of Ethics For The Development And Use Of Artificial Intelligence (unofficial translation), Feb 8, 2019 (unconfirmed)

Published by IA Latam

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

(h) Data protection and privacy

In an age of ubiquitous and massive collection of data through digital communication technologies, the right to protection of personal information and the right to respect for privacy are crucially challenged. Both physical AI robots as part of the Internet of Things, as well as AI softbots that operate via the World Wide Web must comply with data protection regulations and not collect and spread data or be run on sets of data for whose use and dissemination no informed consent has been given. ‘Autonomous’ systems must not interfere with the right to private life which comprises the right to be free from technologies that influence personal development and opinions, the right to establish and develop relationships with other human beings, and the right to be free from surveillance. Also in this regard, exact criteria should be defined and mechanisms established that ensure ethical development and ethically correct application of ‘autonomous’ systems. In light of concerns with regard to the implications of ‘autonomous’ systems on private life and privacy, consideration may be given to the ongoing debate about the introduction of two new rights: the right to meaningful human contact and the right to not be profiled, measured, analysed, coached or nudged.

Published by European Group on Ethics in Science and New Technologies, European Commission in Ethical principles and democratic prerequisites, Mar 9, 2018

· 7. Respect for Privacy

Privacy and data protection must be guaranteed at all stages of the life cycle of the AI system. This includes all data provided by the user, but also all information generated about the user over the course of his or her interactions with the AI system (e.g. outputs that the AI system generated for specific users, how users responded to particular recommendations, etc.). Digital records of human behaviour can reveal highly sensitive data, not only in terms of preferences, but also regarding sexual orientation, age, gender, religious and political views. The person in control of such information could use this to his her advantage. Organisations must be mindful of how data is used and might impact users, and ensure full compliance with the GDPR as well as other applicable regulation dealing with privacy and data protection.

Published by The European Commission’s High-Level Expert Group on Artificial Intelligence in Draft Ethics Guidelines for Trustworthy AI, Dec 18, 2018

· 3. HUMANS ARE ALWAYS RESPONSIBILITY FOR THE CONSEQUENCES OF THE APPLICATION OF AN AIS

3.1. Supervision. AI Actors should provide comprehensive human supervision of any AIS to the extent and manner depending on the purpose of the AIS, including, for example, recording significant human decisions at all stages of the AIS life cycle or making provisions for the registration of the work of the AIS. They should also ensure the transparency of AIS use, including the possibility of cancellation by a person and (or) the prevention of making socially and legally significant decisions and actions by the AIS at any stage in its life cycle, where reasonably applicable. 3.2. Responsibility. AI Actors should not allow the transfer of rights of responsible moral choice to the AIS or delegate responsibility for the consequences of the AIS’s decision making. A person (an individual or legal entity recognized as the subject of responsibility in accordance with the legislation in force of the Russian Federation) must always be responsible for the consequences of the work of the AI Actors are encouraged to take all measures to determine the responsibilities of specific participants in the life cycle of the AIS, taking into account each participant’s role and the specifics of each stage.

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

· Prepare Input Data:

1 Following the best practice of responsible data acquisition, handling, classification, and management must be a priority to ensure that results and outcomes align with the AI system’s set goals and objectives. Effective data quality soundness and procurement begin by ensuring the integrity of the data source and data accuracy in representing all observations to avoid the systematic disadvantaging of under represented or advantaging over represented groups. The quantity and quality of the data sets should be sufficient and accurate to serve the purpose of the system. The sample size of the data collected or procured has a significant impact on the accuracy and fairness of the outputs of a trained model. 2 Sensitive personal data attributes which are defined in the plan and design phase should not be included in the model data not to feed the existing bias on them. Also, the proxies of the sensitive features should be analyzed and not included in the input data. In some cases, this may not be possible due to the accuracy or objective of the AI system. In this case, the justification of the usage of the sensitive personal data attributes or their proxies should be provided. 3 Causality based feature selection should be ensured. Selected features should be verified with business owners and non technical teams. 4 Automated decision support technologies present major risks of bias and unwanted application at the deployment phase, so it is critical to set out mechanisms to prevent harmful and discriminatory results at this phase.

Published by SDAIA in AI Ethics Principles, Sept 14, 2022