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cs.HC2024
Better Together? The Role of Explanations in Supporting Novices in Individual and Collective Deliberations about AI
Timothée Schmude, Laura Koesten, Torsten Möller +1
Deploying AI systems in public institutions can have far-reaching consequences for many people, making it a matter of public interest. Providing opportunities for stakeholders to c…
cs.HC2024
Information That Matters: Exploring Information Needs of People Affected by Algorithmic Decisions
Timothée Schmude, Laura Koesten, Torsten Möller +1
Every AI system that makes decisions about people has a group of stakeholders that are personally affected by these decisions. However, explanations of AI systems rarely address th…
cs.HC2023
Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making
Timothée Schmude, Laura Koesten, Torsten Möller +1
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…