Discussion of how algorithmic affordances in educational recommender systems can help create responsible AI, but how they also potentially introduce new ethical problems

Presentatie van het onderzoek

The intersection of financial technology (FinTech) and financial inclusion is increasingly recognized in both academic research and policy as a powerful tool for addressing global challenges and supporting sustainable development. Financial inclusion is essential for achieving the United Nations' sustainable …

By 2050, the proportion of the world’s population that is over 60 will nearly double from 12% to 22%, representing nearly 2 billion older people worldwide. In response, the United Nations declared 2021–2030 to be the Decade of Healthy Aging, aiming to improve the lives of older people, their families, …

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 …

It is now widely accepted that decisions made by AI systems must be explainable to their users. However, in practice, it often remains unclear how this explainability should be concretely implemented. This is especially important for nontechnical users, such as claims assessors at insurance companies, …

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 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 …

Emergency responders (ERs) work in dynamic, complex, and unpredictable environments. The integration of increasingly advanced sensor and artificial intelligence technology affects the work processes and decision-making of ERs and leads to new challenges regarding efficient and responsible human-AI cooperation. …