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

Data Agency

A IS developers should respect each individual’s ability to maintain appropriate control over their personal data and identifying information.

Principle: Ethical Aspects of Autonomous and Intelligent Systems, Jun 24, 2019

Published by IEEE

Related Principles

2. Privacy Principles Privacy by Design

o We have implemented an enterprise wide Privacy by Design approach that incorporates privacy and data security into our ML and associated data processing systems. Our ML models seek to minimize access to identifiable information to ensure we are using only the personal data we need to generate insights. ADP is committed to providing individuals with a reasonable opportunity to examine their own personal data and to update it if it is incorrect.

Published by ADP in ADP: Ethics in Artificial Intelligence, 2018 (unconfirmed)

· (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

· 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

• Liberate Data Responsibly

AI is powered by access to data. Machine learning algorithms improve by analyzing more data over time; data access is imperative to achieve more enhanced AI model development and training. Removing barriers to the access of data will help machine learning and deep learning reach their full potential. [Recommendations] • Keep data moving: Governments should eliminate unwarranted data localization mandates and enable secure international data transfers through international agreements and legal tools. • Open public data: While protecting privacy, governments should make useful datasets publicly available when appropriate and provide guidance to startups and small and medium businesses for its reuse. • Support the creation of reliable data sets to test algorithms: Governments should explore non regulatory methods to encourage the development of testing data sets. • Federate access to data: Governments should partner with industry to promote AI tools to access encrypted data for analysis, while not requiring transfer of the data. (Note: Instead of centralizing data from several institutions, federated access to data allows each institution to keep control of their data while enabling joint data analytics across all institutions.)

Published by Intel in AI public policy principles, Oct 18, 2017

3 PROTECTION OF PRIVACY AND INTIMACY PRINCIPLE

Privacy and intimacy must be protected from AIS intrusion and data acquisition and archiving systems (DAAS). 1) Personal spaces in which people are not subjected to surveillance or digital evaluation must be protected from the intrusion of AIS and data acquisition and archiving systems (DAAS). 2) The intimacy of thoughts and emotions must be strictly protected from AIS and DAAS uses capable of causing harm, especially uses that impose moral judgments on people or their lifestyle choices. 3) People must always have the right to digital disconnection in their private lives, and AIS should explicitly offer the option to disconnect at regular intervals, without encouraging people to stay connected. 4) People must have extensive control over information regarding their preferences. AIS must not create individual preference proﬁles to inﬂuence the behavior of the individuals without their free and informed consent. 5) DAAS must guarantee data conﬁdentiality and personal proﬁle anonymity. 6) Every person must be able to exercise extensive control over their personal data, especially when it comes to its collection, use, and dissemination. Access to AIS and digital services by individuals must not be made conditional on their abandoning control or ownership of their personal data. 7) Individuals should be free to donate their personal data to research organizations in order to contribute to the advancement of knowledge. 8) The integrity of one’s personal identity must be guaranteed. AIS must not be used to imitate or alter a person’s appearance, voice, or other individual characteristics in order to damage one’s reputation or manipulate other people.

Published by University of Montreal in The Montreal Declaration for a Responsible Development of Artificial Intelligence, Dec 4, 2018