[HTML][HTML] Designing explainable AI to improve human-AI team performance: a medical stakeholder-driven sco** review

HV Subramanian, C Canfield, DB Shank - Artificial Intelligence in Medicine, 2024‏ - Elsevier
The rise of complex AI systems in healthcare and other sectors has led to a growing area of
research called Explainable AI (XAI) designed to increase transparency. In this area …

Explain any concept: Segment anything meets concept-based explanation

A Sun, P Ma, Y Yuan, S Wang - Advances in Neural …, 2024‏ - proceedings.neurips.cc
EXplainable AI (XAI) is an essential topic to improve human understanding of deep neural
networks (DNNs) given their black-box internals. For computer vision tasks, mainstream …

Harnessing explainable artificial intelligence for patient-to-clinical-trial matching: A proof-of-concept pilot study using phase I oncology trials

S Ghosh, HM Abushukair, A Ganesan, C Pan… - Plos one, 2024‏ - journals.plos.org
This study aims to develop explainable AI methods for matching patients with phase 1
oncology clinical trials using Natural Language Processing (NLP) techniques to address …

The Contribution of XAI for the Safe Development and Certification of AI: An Expert-Based Analysis

B Fresz, VP Göbels, S Omri, D Brajovic… - ar** and certifying safe-or so-called trustworthy-AI has become an increasingly
salient issue, especially in light of upcoming regulation such as the EU AI Act. In this context …

[HTML][HTML] Comparing expert systems and their explainability through similarity

F Gwinner, C Tomitza, A Winkelmann - Decision Support Systems, 2024‏ - Elsevier
In our work, we propose the use of Representational Similarity Analysis (RSA) for
explainable AI (XAI) approaches to enhance the reliability of XAI-based decision support …

Dynamic Explanation Selection Towards Successful User-Decision Support with Explainable AI

Y Fukuchi, S Yamada - arxiv preprint arxiv:2402.18016, 2024‏ - arxiv.org
This paper addresses the problem of how to select explanations for XAI (Explainable AI)-
based Intelligent Decision Support Systems (IDSSs). IDSSs have shown promise in …

On the Effect of Contextual Information on Human Delegation Behavior in Human-AI collaboration

P Spitzer, J Holstein, P Hemmer, M Vössing… - arxiv preprint arxiv …, 2024‏ - arxiv.org
The constantly increasing capabilities of artificial intelligence (AI) open new possibilities for
human-AI collaboration. One promising approach to leverage existing complementary …

LLM-based collaborative programming: impact on students' computational thinking and self-efficacy

YM Yan, CQ Chen, YB Hu, XD Ye - Humanities and Social Sciences …, 2025‏ - nature.com
At present, collaborative programming is a prevalent approach in programming education,
yet its effectiveness often falls short due to the varying levels of coding skills among team …

Working memory and the need for explainable AI–Scenarios from healthcare, social media and insurance

M Liebherr, E Gößwein, C Kannen, A Babiker… - Heliyon, 2025‏ - cell.com
Explainable AI (XAI) is discussed as an important feature of AI systems that is required for
professional, ethical and commercial reasons. XAI is particularly needed in AI systems that …

Adopting AI teammates in knowledge-intensive crowdsourcing contests: the roles of transparency and explainability

Z Wang, J Wang, C Tian, A Ali, X Yin - Kybernetes, 2024‏ - emerald.com
Purpose As the role of AI on human teams shifts from a tool to a teammate, the
implementation of AI teammates into knowledge-intensive crowdsourcing (KI-C) contest …