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Explaining learned irrelevance classifications of digital objects

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Abstract

Dare2Del is an assistive system which facilitates intentional forgetting of irrelevant digital objects. For an assistive system to be helpful, the user has to trust the system’s decisions. Explanations are a crucial component in establishing this trust. We will introduce different types of explanations which can vary along different dimensions such as level of detail and modality suitable for different application contexts. We will outline the cognitive companion system Dare2Del which is intended to support users managing digital objects in a working environment. Core of Dare2Del is an interpretable machine learning mechanism which induces decision rules to classify whether a digital objects is irrelevant. In this paper, we focus on irrelevance of files. We formalize the decision making process as logic inference. Finally, we present a method to generate verbal explanations for irrelevance decisions and point out how such explanations can be constructed on different levels of details. Furthermore, we show how verbal explanations can be related to the path context of the file. We conclude with a short discussion of the scope and restrictions of our approach.

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Notes

  1. Chair of Work and Organizational Psychology, Friedrich-Alexander Universität Erlangen-Nürnberg, https://www.work-and-organizational-psychology.phil.fau.eu.

  2. If \(C\theta\) is not ground we may substitute every variable in \(C\theta\) with a unique constant.

  3. In order to realize coloured highlighting we designed the string templates to produce valid HTML strings. These are rendered by the displaying component.

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Correspondence to Michael Siebers.

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This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—SCHM 1239/10-1 within the priority program SPP 1921 Intentional Forgetting.

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Siebers, M., Schmid, U. Please delete that! Why should I?. Künstl Intell 33, 35–44 (2019). https://doi.org/10.1007/s13218-018-0565-5

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