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arXiv · 2305.16700

Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making

Timothée Schmude·Laura Koesten·Torsten Möller·Sebastian Tschiatschek
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Abstract

We argue that explanations for "algorithmic decision-making" (ADM) systems can profit by adopting practices that are already used in the learning sciences. We shortly introduce the importance of explaining ADM systems, give a brief overview of approaches drawing from other disciplines to improve explanations, and present the results of our qualitative task-based study incorporating the "six facets of understanding" framework. We close with questions guiding the discussion of how future studies can leverage an interdisciplinary approach.

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Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek. 2023-05-26. Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making. https://arxiv.org/abs/2305.16700

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