There are multiple challenges relating to the explainability of algorithmic decision-making
(ADM) systems, such as that there is not a clear consensus on what a ‘good’ explanation is and what sort of explanation fit the different types of ADM-systems. Therefore, in this research, the Delphi-method was used to study which explanation would fit the different types of ADM-systems best. This was done in the Dutch property & casualty insurance industry. This report will show that often the data that is used to reach a decision should be included in the explanation because of the privacy perspective. Also, for most ADM-systems in this study, can be said that the general idea behind the algorithm and/or data should be included in the explanation. The main conclusion, however, is that there is not a one-size-fits-all explanation for ADM-systems and that it depends on the type of ADM-system, for what it is used and in which social context.
- algorithmic decision-making