The principle "Draft Text of The Recommendation on the Ethics of Artificial Intelligence" has mentioned the topic "transparency" in the following places:

    · Transparency and explainability

    · transparency and explainability

    · Transparency and explainability

    · Transparency and explainability

    · Transparency and explainability

    The transparency and explainability of AI systems are often essential preconditions to ensure the respect, protection and promotion of human rights, fundamental freedoms and ethical principles.

    · Transparency and explainability

    The transparency and explainability of AI systems are often essential preconditions to ensure the respect, protection and promotion of human rights, fundamental freedoms and ethical principles.

    · Transparency and explainability

    transparency is necessary for relevant national and international liability regimes to work effectively.

    · Transparency and explainability

    A lack of transparency could also undermine the possibility of effectively challenging decisions based on outcomes produced by AI systems and may thereby infringe the right to a fair trial and effective remedy, and limits the areas in which these systems can be legally used.

    · Transparency and explainability

    While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security.

    · Transparency and explainability

    While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security.

    · Transparency and explainability

    While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security.

    · Transparency and explainability

    While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security.

    · Transparency and explainability

    While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security.

    · Transparency and explainability

    While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security.

    · Transparency and explainability

    From a socio technical lens, greater transparency contributes to more peaceful, just, democratic and inclusive societies.

    · Transparency and explainability

    transparency aims at providing appropriate information to the respective addressees to enable their understanding and foster trust.

    · Transparency and explainability

    Specific to the AI system, transparency can enable people to understand how each stage of an AI system is put in place, appropriate to the context and sensitivity of the AI system.

    · Transparency and explainability

    In cases of serious threats of adverse human rights impacts, transparency may also require the sharing of code or datasets.

    · Transparency and explainability

    explainability refers to making intelligible and providing insight into the outcome of AI systems.

    · Transparency and explainability

    Explainability refers to making intelligible and providing insight into the outcome of AI systems.

    · Transparency and explainability

    The explainability of AI systems also refers to the understandability of the input, output and the functioning of each algorithmic building block and how it contributes to the outcome of the systems.

    · 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.

    · 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.

    · 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.

    · Transparency and explainability

    AI actors should commit to ensuring that the algorithms developed are explainable.

    · Transparency and explainability

    In the case of AI applications that impact the end user in a way that is not temporary, easily reversible or otherwise low risk, it should be ensured that the meaningful explanation is provided with any decision that resulted in the action taken in order for the outcome to be considered transparent.

    · Transparency and explainability

    transparency and explainability relate closely to adequate responsibility and accountability measures, as well as to the trustworthiness of AI systems.

    · Transparency and explainability

    Transparency and explainability relate closely to adequate responsibility and accountability measures, as well as to the trustworthiness of AI systems.

    · Responsibility and accountability

    Appropriate oversight, impact assessment, audit and due diligence mechanisms, including whistle blowers’ protection, should be developed to ensure accountability for AI systems and their impact throughout their life cycle.

    · 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.

    · 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.