The workload in the healthcare sector is increasing, requiring the need for innovative solutions. One such solution is for AI to assist in clinical decision-making by extracting information from patient’s records. To ensure healthcare professionals stay in the lead, the reasoning of the AI should be …

The rapid advancement of Generative AI (GenAI), particularly large language models (LLMs), has significantly reshaped how individuals and organizations engage in decision-making. From customer service and education to strategic planning and design, these technologies are no longer limited to providing …

This paper investigates the role of conversational AI in improving the quality of decision-making across different stages of the process. Drawing on an experimental study involving 113 students in Dutch higher education, participants engaged in a simulated business challenge using three approaches: no …

This research explores how integrating gamification with AI-powered menu systems can influence consumer behavior toward more sustainable food choices in urban restaurants. Through a mixed-method experiment using two website prototypes, findings reveal that personalized AI suggestions and sustainability …

Trust in AI is crucial for effective and responsible use in high-stakes sectors like healthcare and finance. One of the most commonly used techniques to mitigate mistrust in AI and even increase trust is the use of Explainable AI models, which enables human understanding of certain decisions made by …

The integration of big data and artificial intelligence into modern systems has profoundly influenced societal structures causing significant ethical challenges. This paper investigates the role of professional oaths in mitigating these threats by focusing on Dutch data professionals. Through a two-phase …

This guide was developed for designers and developers of AI systems, with the goal of ensuring that these systems are sufficiently explainable. Sufficient here means that it meets the legal re quirements from AI Act and GDPR and that users can use the system properly. Explainability of decisions is …

This article explores the decision-making processes in the ongoing development of an AI-supported youth mental health app. Document analysis reveals decisions taken during the grant proposal and funding phase and reflects upon reasons why AI is incorporated in innovative youth mental health care. An …

Artificial intelligence (AI) is transforming language access services in healthcare, making interpretation and translation faster and more scalable than ever before. Given that there are approximately 281 million international migrants as of 2024 [1], leveraging AI technology for mitigating language …

One aspect of a responsible application of Artificial Intelligence (AI) is ensuring that the operation and outputs of an AI system are understandable for non-technical users, who need to consider its recommendations in their decision making. The importance of explainable AI (XAI) is widely acknowledged; …