The principle "Draft Ethics Guidelines for Trustworthy AI" has mentioned the topic "test" in the following places:

    · 2. The Principle of Non maleficence: “Do no Harm”

    Therefore not only should AI be designed with the impact on various vulnerable demographics in mind but the above mentioned demographics should have a place in the design process (rather through testing, validating, or other).

    · 2. Data Governance

    In addition, it must be ensured that the proper division of the data which is being set into training, as well as validation and testing of those sets, is carefully conducted in order to achieve a realistic picture of the performance of the AI system.

    · 2. Data Governance

    It must particularly be ensured that anonymisation of the data is done in a way that enables the division of the data into sets to make sure that a certain data – for instance, images from same persons – do not end up into both the training and test sets, as this would disqualify the latter.

    · 4. Governance of AI Autonomy (Human oversight)

    All other things being equal, the greater degree of autonomy that is given to an AI system, the more extensive testing and stricter governance is required.