Conferentie bijdrage

The shift from linear to circular business models is critical for sustainability in the construction and manufacturing sectors in the Netherlands. However, many companies face significant challenges in making this transition, including financial constraints, cultural resistance, and regulatory hurdles, …

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 …

Het is inmiddels breed geaccepteerd dat beslissingen die door AI-systemen worden genomen, uitlegbaar moeten zijn aan hun gebruikers. Toch blijft het in de praktijk vaak onduidelijk hoe die uitlegbaarheid concreet vorm moet krijgen. Vooral voor niet-technische gebruikers, zoals scha-debeoordelaars bij …

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, …

Deze handreiking is ontwikkeld voor designers en ontwikkelaars van AI-systemen, met als doel om te zorgen dat deze systemen voldoende uitlegbaar zijn. Voldoende betekent hier dat het vol doet aan de wettelijke eisen vanuit AI Act en AVG en dat gebruikers het systeem goed kunnen gebruiken. In deze handreiking …

⚡ ???????????????????????????????????????????? ???????????????????????????????????????????????? Onze collega’s Carolien Kattenbelt en Ronald van Buuren verzorgden gisteren de aftrap van de Masterclass Netcongestie bij Connectr op Industriepark Kleefse Waard (IPKW). Terugkijkend geven deelnemers aan dat …

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 …

Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there’s been growing recognition that explainability is inherently human-centric, tied to how people perceive explanations. Despite this, there is no consensus in the research …

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; …