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 …

Citizens regularly search the Web to make informed decisions on daily life questions, like online purchases, but how they reason with the results is unknown. This reasoning involves engaging with data in ways that require statistical literacy, which is crucial for navigating contemporary data. However, …

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 …

Machine learning models use high dimensional feature spaces to map their inputs to the corresponding class labels. However, these features often do not have a one-to-one correspondence with physical concepts understandable by humans, which hinders the ability to provide a meaningful explanation for the …

In today’s digital era, small and medium-sized enterprises (SMEs) are facing more cyber threats as they adopt new technologies. From data breaches to ransomware and phishing attacks, these risks are becoming more frequent and advanced. Unlike large companies, SMEs often don’t have the budget or cybersecurity …

Human capital and social capital are crucial in shaping entrepreneurial decisions, yet their combined effects on entrepreneurship entry remain insufficiently explored. This study uses data from the China Household Tracking Survey (2010–2018) to examine how the coupling of human and social capital influences …

Background In geriatric oncology, family members frequently accompany older patients with cancer to medical consultations and participate in shared decision-making (SDM) processes. While family involvement can enhance decision-making, it also presents challenges for healthcare professionals. Additionally, …

Analyzing historical decision-related data can help support actual operational decision-making processes. Decision mining can be employed for such analysis. This paper proposes the Decision Discovery Framework (DDF) designed to develop, adapt, or select a decision discovery algorithm by outlining specific …

Urban densification is promoted for sustainable urban growth, yet it also generates concerns about negative health impacts on local citizens. Engaging local citizens in the co-design of densification projects is therefore crucial to address their needs and concerns. The use of immersive Virtual Reality …