3 Ensure transparency, explainability and intelligibility

Two broad approaches to ensuring intelligibility are improving the transparency and explainability of AI technology.

AI technologies should be explainable to the extent possible and according to the capacity of those to whom the explanation is directed.

Data protection laws already create specific obligations of explainability for automated decision making.

There is a possible trade off between full explainability of an algorithm (at the cost of accuracy) and improved accuracy (at the cost of explainability).

There is a possible trade off between full explainability of an algorithm (at the cost of accuracy) and improved accuracy (at the cost of explainability).

Institutions have not only legal liability but also a duty to assume responsibility for decisions made by the algorithms they use, even if it is not feasible to explain in detail how the algorithms produce their results.