The principle "AI Ethics Principles" has mentioned the topic "discrimination" in the following places:

    Principle 1 – Fairness

    Bias may occur due to data, representation or algorithms and could lead to discrimination against the historically disadvantaged groups.

    Principle 1 – Fairness

    When designing, selecting, and developing AI systems, it is essential to ensure just, fair, non biased, non discriminatory and objective standards that are inclusive, diverse, and representative of all or targeted segments of society.

    · Plan and Design:

    The fairness principle requires taking necessary actions to eliminate bias, discrimination or stigmatization of individuals, communities, or groups in the design, data, development, deployment and use of AI systems.

    · Plan and Design:

    Bias may occur due to data, representation or algorithms and could lead to discrimination against the historically disadvantaged groups.

    · Plan and Design:

    When designing, selecting, and developing AI systems, it is essential to ensure just, fair,non biased, non discriminatory and objective standards that are inclusive, diverse, andrepresentative of all or targeted segments of society.

    · Plan and Design:

    During this phase, it is important to implement a fairness awaredesign that takes appropriate precautions across the AI system algorithm, processes, andmechanisms to prevent biases from having a discriminatory effect or lead to skewed andunwanted results or outcomes.

    · Prepare Input Data:

    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.