1 citations · 1 across the 2 of their papers we have counts for
5 papers
Explainable AI for the EU Right to Explanation: A Systematic Review of the Law-XAI Translation Gap
Benjamin Fresz, Elena Dubovitskaya, Marco F. Huber
When algorithms make or influence consequential decisions---about loan eligibility, hiring, or healthcare---EU law grants affected individuals a Right to Explanation. Yet whether (…
The Contribution of XAI for the Safe Development and Certification of AI: An Expert-Based Analysis
Benjamin Fresz, Vincent Philipp Göbels, Safa Omri +5
Developing 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 c…
Efficiently Transforming Neural Networks into Decision Trees: A Path to Ground Truth Explanations with RENTT
Helena Monke, Benjamin Fresz, Marco Bernreuther +2
Although neural networks are a powerful tool, their widespread use is hindered by the opacity of their decisions and their black-box nature, which result in a lack of trustworthine…
From Confusion to Clarity: ProtoScore -- A Framework for Evaluating Prototype-Based XAI
Helena Monke, Benjamin Sae-Chew, Benjamin Fresz +1
The complexity and opacity of neural networks (NNs) pose significant challenges, particularly in high-stakes fields such as healthcare, finance, and law, where understanding decisi…
How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law
Benjamin Fresz, Elena Dubovitskaya, Danilo Brajovic +2
This paper investigates the relationship between law and eXplainable Artificial Intelligence (XAI). While there is much discussion about the AI Act, for which the trilogue of the E…