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

1. Transparency and Explainability

...• Ensuring traceability by building an audit trail to document the AI system development and decisionmaking process, implementing a black box recorder that captures all input data streams, or storing data appropriately to avoid degradation and alteration....

Published by ASEAN

3. TRANSPARENCY

...The operation and impacts of an AI system should be transparent, traceable, auditable and generally explainable to a degree appropriate to its use and potential risk profile so outcomes can be understood and challenged, particularly where they relate to people....

Published by the Law, Society and Ethics Working Group of the AI Forum，New Zealand

Published by Beijing Academy of Artificial Intelligence (BAAI); Peking University; Tsinghua University; Institute of Automation, Chinese Academy of Sciences; Institute of Computing Technology, Chinese Academy of Sciences; Artifical Intelligence Industry Innovation Strategy Alliance (AITISA); etc.

Be Responsible

...AI models and algorithms related to Biodiversity Conservation should be as transparent, interpretable, and traceable as possible....

Published by International Research Center for AI Ethics and Governance, Instituteof Automation, Chinese Academy of Sciences，World Animal Protection Beijing Representative Office and other 7 entities

Build a strong network and data security barrier.

...Support the Global Data Security Initiative, deepen cooperation between China and Africa in the fields of network and data security, jointly promote the research and application of network security technology and products, and create auditable, supervised, traceable, and trustworthy artificial intelligence technology....

Published by China Africa Internet Development and Cooperation Forum

3. Traceable.

...traceable....

Published by Defense Innovation Board (DIB), Department of Defense (DoD), United States

IV. Transparency

...The traceability of AI systems should be ensured; it is important to log and document both the decisions made by the systems, as well as the entire process (including a description of data gathering and labelling, and a description of the algorithm used) that yielded the decisions....

Published by European Commission

· 2. Data Governance

...In large enough data sets these will be diluted since correct actions usually overrun the errors, yet a trace of thereof remains in the data....

Published by The European Commission’s High-Level Expert Group on Artificial Intelligence

1. Principle 1 — Human Rights

...Governance frameworks, including standards and regulatory bodies, should be established to oversee processes assuring that the use of A IS does not infringe upon human rights, freedoms, dignity, and privacy, and of traceability to contribute to the building of public trust in A IS....

Published by The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems

5. Safety and Controllability

...The transparency, interpretability, reliability, and controllability of AI systems should be improved continuously to make the systems more traceable, trustworthy, and easier to audit and monitor....

Published by National Governance Committee for the New Generation Artificial Intelligence, China

Chapter 3. The Norms of Research and Development

...In the phases of algorithm design, implementation, and application, etc., improve transparency, interpretability, understandability, reliability, and controllability, enhance the resilience, adaptability, and the ability of anti interference of AI systems, and gradually realize verifiable, auditable, supervisable, traceable, predictable and trustworthy AI....

Published by National Governance Committee for the New Generation Artificial Intelligence, China

Ensure fairness

...We subscribe to the principles laid out in the Department of Defense’s AI ethical principles: that AI technologies should be responsible, equitable, traceable, reliable, and governable....

Published by Rebelliondefense

6. Transparent regulation

...The development of artificial intelligence should avoid the security risks caused by the technology black box, and it is necessary to ensure the unity of target functions and technologies through the establishment of reviewable, traceable, reputable regulatory mechanisms....

Published by Shanghai Advisory Committee of Experts on Artificial Intelligence Industry Security

Principle 6 – Transparency & Explainability

...The degree to which the system is traceable, auditable, transparent, and explainable is dependent on the context and purpose of the AI system and the severity of the outcomes that may result from the technology....

Published by SDAIA

· Plan and Design:

...Decisions should be traceable....

Published by SDAIA

· Plan and Design:

...1 The data sets and the processes that yield the AI system’s decision should be documented to the best possible standard to allow for traceability and an increase in transparency....

Published by SDAIA

· Build and Validate:

...3 If the AI system is built by a third party, AI system owners should make sure that an AI Ethics due diligence is carried out and all the documentation are accessible and traceable before procurement or sign off....

Published by SDAIA

· 1) Accountability:

...Artificial intelligence should be auditable and traceable....

Published by Youth Work Committee of Shanghai Computer Society

2. AI shall be transparent.

...Transparency is the ability to trace cause and effect in the decision making pathways of algorithms and, in hybrid intelligence systems, of their operators....

Published by The Future Society, Science, Law and Society (SLS) Initiative

Second, the principle of security.

...AI algorithms must be traceable and transparent and there should be no algorithm discrimination;...

Published by Center for International Strategy and Security, Tsinghua University (Tsinghua CISS)

· Transparency and explainability

...Thus, explainability is closely related to transparency, as outcomes and ub processes leading to outcomes should aim to be understandable and traceable, appropriate to the context....

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO)

· Responsibility and accountability

...Both technical and institutional designs should ensure auditability and traceability of (the working of) AI systems in particular to address any conflicts with human rights norms and standards and threats to environmental and ecosystem well being....

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO)

3. Traceable

...traceable...

Published by Department of Defense (DoD), United States

1. Transparency and Explainability

...• Ensuring traceability by building an audit trail to document the AI system development and decisionmaking process, implementing a black box recorder that captures all input data streams, or storing data appropriately to avoid degradation and alteration....

3. TRANSPARENCY

...The operation and impacts of an AI system should be transparent, traceable, auditable and generally explainable to a degree appropriate to its use and potential risk profile so outcomes can be understood and challenged, particularly where they relate to people....

· Be Ethical

...This may include, but not limited to: making the system as fair as possible, reducing possible discrimination and biases, improving its transparency, explainability and predictability, and making the system more traceable, auditable and accountable....

Be Responsible

...AI models and algorithms related to Biodiversity Conservation should be as transparent, interpretable, and traceable as possible....

Build a strong network and data security barrier.

3. Traceable.

...traceable....

IV. Transparency

...The traceability of AI systems should be ensured; it is important to log and document both the decisions made by the systems, as well as the entire process (including a description of data gathering and labelling, and a description of the algorithm used) that yielded the decisions....

· 2. Data Governance

...In large enough data sets these will be diluted since correct actions usually overrun the errors, yet a trace of thereof remains in the data....

1. Principle 1 — Human Rights

...Governance frameworks, including standards and regulatory bodies, should be established to oversee processes assuring that the use of A IS does not infringe upon human rights, freedoms, dignity, and privacy, and of traceability to contribute to the building of public trust in A IS....

5. Safety and Controllability

...The transparency, interpretability, reliability, and controllability of AI systems should be improved continuously to make the systems more traceable, trustworthy, and easier to audit and monitor....

Chapter 3. The Norms of Research and Development

Ensure fairness

...We subscribe to the principles laid out in the Department of Defense’s AI ethical principles: that AI technologies should be responsible, equitable, traceable, reliable, and governable....

6. Transparent regulation

...The development of artificial intelligence should avoid the security risks caused by the technology black box, and it is necessary to ensure the unity of target functions and technologies through the establishment of reviewable, traceable, reputable regulatory mechanisms....

Principle 6 – Transparency & Explainability

...The degree to which the system is traceable, auditable, transparent, and explainable is dependent on the context and purpose of the AI system and the severity of the outcomes that may result from the technology....

· Plan and Design:

...Decisions should be traceable....

· Plan and Design:

...1 The data sets and the processes that yield the AI system’s decision should be documented to the best possible standard to allow for traceability and an increase in transparency....

· Build and Validate:

...3 If the AI system is built by a third party, AI system owners should make sure that an AI Ethics due diligence is carried out and all the documentation are accessible and traceable before procurement or sign off....

· 1) Accountability:

...Artificial intelligence should be auditable and traceable....

2. AI shall be transparent.

...Transparency is the ability to trace cause and effect in the decision making pathways of algorithms and, in hybrid intelligence systems, of their operators....

Second, the principle of security.

...AI algorithms must be traceable and transparent and there should be no algorithm discrimination;...

· Transparency and explainability

...Thus, explainability is closely related to transparency, as outcomes and ub processes leading to outcomes should aim to be understandable and traceable, appropriate to the context....

· Responsibility and accountability

...Both technical and institutional designs should ensure auditability and traceability of (the working of) AI systems in particular to address any conflicts with human rights norms and standards and threats to environmental and ecosystem well being....

3. Traceable

...traceable...

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