A critical survey on fairness benefits of explainable AI

L Deck, J Schoeffer, M De-Arteaga, N Kühl - Proceedings of the 2024 …, 2024‏ - dl.acm.org
In this critical survey, we analyze typical claims on the relationship between explainable AI
(XAI) and fairness to disentangle the multidimensional relationship between these two …

Appropriate reliance on AI advice: Conceptualization and the effect of explanations

M Schemmer, N Kuehl, C Benz, A Bartos… - Proceedings of the 28th …, 2023‏ - dl.acm.org
AI advice is becoming increasingly popular, eg, in investment and medical treatment
decisions. As this advice is typically imperfect, decision-makers have to exert discretion as to …

More capable, less benevolent: Trust perceptions of AI systems across societal contexts

E Novozhilova, K Mays, S Paik, JE Katz - Machine Learning and …, 2024‏ - mdpi.com
Modern AI applications have caused broad societal implications across key public domains.
While previous research primarily focuses on individual user perspectives regarding AI …

The impact of imperfect XAI on human-AI decision-making

K Morrison, P Spitzer, V Turri, M Feng, N Kühl… - Proceedings of the …, 2024‏ - dl.acm.org
Explainability techniques are rapidly being developed to improve human-AI decision-
making across various cooperative work settings. Consequently, previous research has …

[HTML][HTML] Leveraging explainable AI for informed building retrofit decisions: Insights from a survey

D Leuthe, J Mirlach, S Wenninger, C Wiethe - Energy and buildings, 2024‏ - Elsevier
Accurate predictions of building energy consumption are essential for reducing the energy
performance gap. While data-driven energy quantification methods based on machine …

Ethics in the Age of Algorithms: Unravelling the Impact of Algorithmic Unfairness on Data Analytics Recommendation Acceptance

M Ghasemaghaei, N Kordzadeh - Information Systems Journal, 2024‏ - Wiley Online Library
Algorithms used in data analytics (DA) tools, particularly in high‐stakes contexts such as
hiring and promotion, may yield unfair recommendations that deviate from merit‐based …

“I Want It That Way”: Enabling Interactive Decision Support Using Large Language Models and Constraint Programming

C Lawless, J Schoeffer, L Le, K Rowan, S Sen… - ACM Transactions on …, 2024‏ - dl.acm.org
A critical factor in the success of many decision support systems is the accurate modeling of
user preferences. Psychology research has demonstrated that users often develop their …

On the interdependence of reliance behavior and accuracy in AI-assisted decision-making

J Schoeffer, J Jakubik, M Voessing… - HHAI 2023 …, 2023‏ - ebooks.iospress.nl
In AI-assisted decision-making, a central promise of putting a human in the loop is that they
should be able to complement the AI system by adhering to its correct and overriding its …

Explaining the unexplainable: The impact of misleading explanations on trust in unreliable predictions for hardly assessable tasks

M Sadeghi, D Pöttgen, P Ebel… - Proceedings of the 32nd …, 2024‏ - dl.acm.org
To increase trust in systems, engineers strive to create explanations that are as accurate as
possible. However, if the system's accuracy is compromised, providing explanations for its …

Overlap Number of Balls Model-Agnostic CounterFactuals (ONB-MACF): A data-morphology-based counterfactual generation method for trustworthy artificial …

JD Pascual-Triana, A Fernández, J Del Ser… - Information Sciences, 2025‏ - Elsevier
Abstract Explainable Artificial Intelligence (XAI) is a pivotal research domain aimed at
clarifying AI systems, particularly those considered “black boxes” due to their complex …