6 papers
From Skill Extraction to Multistakeholder Recommendation: A Two-Stage Framework for Bias Governance in Skills-Based Job Matching
Andrea Forster, Gregor Autischer, Dominik Kowald +1
AI-based labor-market systems or platforms can affect access to job opportunities prior to organizational candidate rankings or hiring decisions. Such applications warrant caution,…
Self-Certification of High-Risk AI Systems: The Example of AI-based Facial Emotion Recognition
Gregor Autischer, Kerstin Waxnegger, Dominik Kowald
The European Union's Artificial Intelligence Act establishes comprehensive requirements for high-risk AI systems, yet the harmonized standards necessary for demonstrating complianc…
Practical Application and Limitations of AI Certification Catalogues in the Light of the AI Act
Gregor Autischer, Kerstin Waxnegger, Dominik Kowald
In this work-in-progress, we investigate the certification of AI systems, focusing on the practical application and limitations of existing certification catalogues in the light of…
Establishing and Evaluating Trustworthy AI: Overview and Research Challenges
Dominik Kowald, Sebastian Scher, Viktoria Pammer-Schindler +13
Artificial intelligence (AI) technologies (re-)shape modern life, driving innovation in a wide range of sectors. However, some AI systems have yielded unexpected or undesirable out…
AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments
Tomislav Duricic, Peter Müllner, Nicole Weidinger +3
Many industrial sectors rely on well-trained employees that are able to operate complex machinery. In this work, we demonstrate an AI-powered immersive assistance system that suppo…
Transparency, Privacy, and Fairness in Recommender Systems
Dominik Kowald
Recommender systems have become a pervasive part of our daily online experience, and are one of the most widely used applications of artificial intelligence and machine learning. T…