12 citations · 17 across the 5 of their papers we have counts for
5 papers
Enhancing Diversity of LLM-Generated Educational Tasks
Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla
Large language models (LLMs) have shown the potential for generating educational content at scale, assisting educators in creating practice tasks or synthesizing data for training…
Two Means to an End Goal: Connecting Explainability and Contestability in the Regulation of Public Sector AI
Timothée Schmude, Mireia Yurrita, Kars Alfrink +3
Explainability and its emerging counterpart contestability have become important normative and design principles for trustworthy AI as they enable users and subjects to understand…
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…
Challenging the Human-in-the-loop in Algorithmic Decision-making
Sebastian Tschiatschek, Eugenia Stamboliev, Timothée Schmude +2
We discuss the role of humans in algorithmic decision-making (ADM) for socially relevant problems from a technical and philosophical perspective. In particular, we illustrate tensi…
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…