Probabilistic Scoring Lists for Interpretable Machine Learning - Hanselle, Jonas Manuel; Fürnkranz, Johannes; Hüllermeier, Eyke (26th International Conference on Discovery Science)

Towards Interpretability in Audio and Visual Affective Machine Learning: A Review - Johnson, David; Hakobyan, Olya; Drimalla, Hanna
Machine learning is frequently used in affective computing, but presents challenges due the opacity of state-of-the-art machine learning methods. Because of the impact affective machine learning systems may have on an individual's life, it is important that models be made transparent to detect and mitigate biased decision making. In this regard, affective machine learning could benefit from the recent advancements in explainable artificial intelligence (XAI) research. We perform a structured literature review to examine the use of interpretability in the context of affective machine learning. We focus on studies using audio, visual, or audiovisual data for model training and identified 29 research articles. Our findings show an emergence of the use of interpretability methods in the last five years. However, their use is currently limited regarding the range of methods used, the depth of evaluations, and the consideration of use-cases. We outline the main gaps in the research and provide recommendations for researchers that aim to implement interpretable methods for affective machine learning.

EEG Correlates of Distractions and Hesitations in Human–Robot Interaction: A LabLinking Pilot Study - Richter, Birte; Putze, Felix; Ivucic, Gabriel; Brandt, Mara; Schütze, Christian; Reisenhofer, Rafael; Wrede, Britta; Schultz, Tanja (Multimodal Technologies and Interaction)
In this paper, we investigate the effect of distractions and hesitations as a scaffolding strategy. Recent research points to the potential beneficial effects of a speaker’s hesitations on the listeners’ comprehension of utterances, although results from studies on this issue indicate that humans do not make strategic use of them. The role of hesitations and their communicative function in human-human interaction is a much-discussed topic in current research. To better understand the underlying cognitive processes, we developed a human–robot interaction (HRI) setup that allows the measurement of the electroencephalogram (EEG) signals of a human participant while interacting with a robot. We thereby address the research question of whether we find effects on single-trial EEG based on the distraction and the corresponding robot’s hesitation scaffolding strategy. To carry out the experiments, we leverage our LabLinking method, which enables interdisciplinary joint research between remote labs. This study could not have been conducted without LabLinking, as the two involved labs needed to combine their individual expertise and equipment to achieve the goal together. The results of our study indicate that the EEG correlates in the distracted condition are different from the baseline condition without distractions. Furthermore, we could differentiate the EEG correlates of distraction with and without a hesitation scaffolding strategy. This proof-of-concept study shows that LabLinking makes it possible to conduct collaborative HRI studies in remote laboratories and lays the first foundation for more in-depth research into robotic scaffolding strategies.
Keywords: Computer Networks and Communications; Computer Science Applications; Human-Computer Interaction; Neuroscience (miscellaneous)

SNAPE: A Sequential Non-Stationary Decision Process Model for Adaptive Explanation Generation - Robrecht, Amelie; Kopp, Stefan (Proceedings of the 15th International Conference on Agents and Artificial Intelligence)

Technical Transparency for Robot Navigation Through AR Visualizations - Dyck, Leonie; Beierling, Helen; Helmert, Robin; Vollmer, Anna-Lisa (Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction)

Does Explainability Require Transparency? - Esposito, Elena (Sociologica)
Dealing with opaque algorithms, the frequent overlap between transparency and explainability produces seemingly unsolvable dilemmas, as the much-discussed trade-off between model performance and model transparency. Referring to Niklas Luhmann's notion of communication, the paper argues that explainability does not necessarily require transparency and proposes an alternative approach. Explanations as communicative processes do not imply any disclosure of thoughts or neural processes, but only reformulations that provide the partners with additional elements and enable them to understand (from their perspective) what has been done and why. Recent computational approaches aiming at post-hoc explainability reproduce what happens in communication, producing explanations of the working of algorithms that can be different from the processes of the algorithms.
Keywords: Explainable AI; Transparency; Explanation; Communication; Sociological systems theory

Explaining Machines: Social Management of Incomprehensible Algorithms. Introduction - Esposito, Elena (Sociologica)
This short introduction presents the symposium ‘Explaining Machines’. It locates the debate about Explainable AI in the history of the reflection about AI and outlines the issues discussed in the contributions.
Keywords: Explainable AI; Inexplicability; Transparency; Explanation; Opacity; Contestability

Norms and Rituals of Conflict Settlement in Foreign Affairs in the High Middle Ages - Kamp, Hermann (Le Mediaeval Journal)

Edirom/WeGA-ODD: WeGA ODD files release 4.7.0 - Stadler, Peter; Anna Maria, Neubert; Schreiter, Solveig; Obert, Salome; Ried, Dennis

Der Wirtschaft auch in der Krise das Atmen erlauben, Pandemie und Ökonomie – Interview mit Steuerexpertin Caren Sureth-Sloane - Unterstell, Rembert (forschung - Das Magazin der Deutschen Forschungsgemeinschaft)

Gesundheitsmanagement: Gesunde Mitarbeiter - gesunder Betrieb? - Meier, Heiko; Sennefelder, Lisa (markt&wirtschaft)

Sportliche Angebote zur Förderung von Vertrauen in öffentlichen Verwaltungen - Sennefelder, Lisa

Pushing the Limits of Computational Combinatorial Constructions (Dagstuhl Seminar 23161) - Moura, Lucia; Nakic, Anamari; Östergård, Patric; Wassermann, Alfred; Weiß, Charlene
This report documents the program and the outcomes of Dagstuhl Seminar 23161 "Pushing the Limits of Computational Combinatorial Constructions". In this Dagstuhl Seminar, we focused on computational methods for challenging problems in combinatorial construction. This includes algorithms for construction of combinatorial objects with prescribed symmetry, for isomorph-free exhaustive generation, and for combinatorial search. Examples of specific algorithmic techniques are tactical decomposition, the Kramer-Mesner method, algebraic methods, graph isomorphism software, isomorph-free generation, clique-finding methods, heuristic search, SAT solvers, and combinatorial optimization. There was an emphasis on problems involving graphs, designs and codes, also including topics in related fields such as finite geometry, graph decomposition, Hadamard matrices, Latin squares, and q-analogs of designs and codes.
Keywords: automorphism groups; combinatorial algorithms; finite geometries; subspace designs

Geschichte heilen: Urbane Interventionen und ihre Deutung durch den päpstlichen Hofarchitekten Domenico Fontana (1543–1607) - Voß, Fabian (Antike und Abendland)

»Play it again, Sam« – Levels of Complexity in Encoding Performance Personnel - Bohl, Benjamin W.; Ried, Dennis (Music Encoding Conference Proceedings 2022)

Ludwig Baumann - Ried, Dennis (Blick in die Geschichte. Karlsruher stadthistorische Beiträge)

HenDi-ODD v2.0.0 - Ried, Dennis; Capelle, Irmlind; Minetti, Elena

HenDi-WebApp v1.0.0 - Ried, Dennis

HenDi-ODD v1.0.0 - Ried, Dennis; Capelle, Irmlind; Minetti, Elena

HenDi-WebApp v2.0.0 - Ried, Dennis