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

· 2.4 Cybersecurity and Privacy

Just like technologies that have come before it, AI depends on strong cybersecurity and privacy provisions. We encourage governments to use strong, globally accepted and deployed cryptography and other security standards that enable trust and interoperability. We also promote voluntary information sharing on cyberattacks or hacks to better enable consumer protection. The tech sector incorporates strong security features into our products and services to advance trust, including using published algorithms as our default cryptography approach as they have the greatest trust among global stakeholders, and limiting access to encryption keys. Data and cybersecurity are integral to the success of AI. We believe for AI to flourish, users must trust that their personal and sensitive data is protected and handled appropriately. AI systems should use tools, including anonymized data, de identification, or aggregation to protect personally identifiable information whenever possible.

Principle: AI Policy Principles, Oct 24, 2017

Published by Information Technology Industry Council (ITI)

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)

5. We are secure.

Data security is a prime quality of Deutsche Telekom. In order to maintain this asset, we ensure that our security measures are up to date while having a full overview of how customer related data is used and who has access to which kind of data. We never process privacy relevant data without legal permission. This policy applies to our AI systems just as much as it does to all of our activities. Additionally, we limit the usage to appropriate use cases and thoroughly secure our systems to obstruct external access and ensure data privacy.

Published by Deutsche Telekom in Deutsche Telekom’s guidelines for artificial intelligence, May 11, 2018

· 2.3 Promoting Innovation and the Security of the Internet

We strongly support the protection of the foundation of AI, including source code, proprietary algorithms, and other intellectual property. To this end, we believe governments should avoid requiring companies to transfer or provide access to technology, source code, algorithms, or encryption keys as conditions for doing business. We support the use of all available tools, including trade agreements, to achieve these ends.

Published by Information Technology Industry Council (ITI) in AI Policy Principles, Oct 24, 2017

• Rethink Privacy

Privacy approaches like The Fair Information Practice Principles and Privacy by Design have withstood the test of time and the evolution of new technology. But with innovation, we have had to “rethink” how we apply these models to new technology. [Recommendations] • Adopt Robust Privacy Laws: Based on the OECD Fair Information Practice Principles. • Implement Privacy by Design: Follow Intel’s Rethinking Privacy approach to implement Privacy by Design into AI product and project development. • Keep data secure: Policies should help enable cutting edge AI technology with robust cyber and physical security to mitigate risks of attacks and promote trust from society. • It takes data for AI to protect data: Governments should adopt policies to reduce barriers to the sharing of data for cybersecurity purposes.

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

· Right to Privacy, and Data Protection

32. Privacy, a right essential to the protection of human dignity, human autonomy and human agency, must be respected, protected and promoted throughout the life cycle of AI systems. It is important that data for AI systems be collected, used, shared, archived and deleted in ways that are consistent with international law and in line with the values and principles set forth in this Recommendation, while respecting relevant national, regional and international legal frameworks. 33. Adequate data protection frameworks and governance mechanisms should be established in a multi stakeholder approach at the national or international level, protected by judicial systems, and ensured throughout the life cycle of AI systems. Data protection frameworks and any related mechanisms should take reference from international data protection principles and standards concerning the collection, use and disclosure of personal data and exercise of their rights by data subjects while ensuring a legitimate aim and a valid legal basis for the processing of personal data, including informed consent. 34. Algorithmic systems require adequate privacy impact assessments, which also include societal and ethical considerations of their use and an innovative use of the privacy by design approach. AI actors need to ensure that they are accountable for the design and implementation of AI systems in such a way as to ensure that personal information is protected throughout the life cycle of the AI system.

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