611 citations · 654 across the 10 of their papers we have counts for
11 papers
Are explainable AI (XAI) evaluation strategies aligned? Comparing subjective, objective, and mathematical evaluation measures using saliency maps
Felix Kares, Timo Speith, Hanwei Zhang +1
The evaluation of explainable AI (XAI) approaches often relies on three families of methods: subjective measures (e.g., questionnaires on trust or satisfaction), objective measures…
A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI)
Timo Speith, Markus Langer
Within the field of Requirements Engineering (RE), the increasing significance of Explainable Artificial Intelligence (XAI) in aligning AI-supported systems with user needs, societ…
Revisiting the Performance-Explainability Trade-Off in Explainable Artificial Intelligence (XAI)
Barnaby Crook, Maximilian Schlüter, Timo Speith
Within the field of Requirements Engineering (RE), the increasing significance of Explainable Artificial Intelligence (XAI) in aligning AI-supported systems with user needs, societ…
Sources of Opacity in Computer Systems: Towards a Comprehensive Taxonomy
Sara Mann, Barnaby Crook, Lena Kästner +2
Modern computer systems are ubiquitous in contemporary life yet many of them remain opaque. This poses significant challenges in domains where desiderata such as fairness or accoun…
Explainability as a Requirement for Hardware: Introducing Explainable Hardware (XHW)
Timo Speith, Julian Speith, Steffen Becker +3
In today's age of digital technology, ethical concerns regarding computing systems are increasing. While the focus of such concerns currently is on requirements for software, this…
How to Evaluate Explainability? -- A Case for Three Criteria
Timo Speith
The increasing complexity of software systems and the influence of software-supported decisions in our society have sparked the need for software that is safe, reliable, and fair.…