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Frisst die Transformation ihre Kinder? Kostenimplikationen transformativer Verträge für Open Access Verlage
Full text linkMit der rasanten Ausbreitung des Internets hoffte die Wissenschaft, dass neues Wissen frei verfügbar und schnell verbreitet werden könne. Dennoch veröffentlichen die meisten Forschenden weiterhin in etablierten Zeitschriften, anstatt vollständig auf Open-Access-Alternativen umzusteigen. Dadurch bleibt die Marktmacht großer kommerzieller Verlage bestehen, die Tausende von Zeitschriften hinter Bezahlschranken kontrollieren.
Um diese Portfolios in Open Access umzuwandeln, verhandeln Forschungseinrichtungen weltweit „transformative Verträge“ wie in Deutschland u.a. die „DEAL“-Verträge: Artikel werden vollständig Open Access veröffentlicht, und Universitäten zahlen nur noch für deren Veröffentlichung, nicht mehr jedoch für Subskriptionen/Lesezugänge, die mit den Veröffentlichungsgebühren ebenfalls abgegolten werden.
Ich demonstriere theoretisch, dass Verlage, die über ein großes Portfolio etablierter, subskriptionsbasierter Fachzeitschriften verfügen, diese als Druckmittel nutzen können, um trotz sinkender Publikationszahlen hohe Einnahmen sicherzustellen. Das könnte Wettbewerbern schaden, die ausschließlich Open Access verlegen, und den Wettbewerb behindern. So könnte die dominante Position der großen Verlage weiter gefestigt werden
Finding Commonalities in Dynamical Systems with Gaussian Processes
Full text linkGaussian processes can be utilized in the area of equation discovery to identify differential equations describing the physical processes present in time series data.Furthermore, automatically constructed models can be split into components that facilitate comparisons between time series on a structural level. We consider the potential combination of these two methods and describe how they could be used to detect shared physical properties in multiple recordings of dynamical systems as time series. This approach provides insights into the underlying dynamics of the observed systems, facilitating a deeper understanding of complex processes
Closing the Loop with Concept Regularization
Full text linkConvolutional Neural Networks (CNNs) are widely adopted in industrial settings, but are prone to biases and lack transparency. Explainable Artificial Intelligence (XAI), particularly through concept extraction (CE), allows for global explanations and bias detection, yet fails to offer corrective measures for identified biases. To bridge this gap, we introduce Concept Regularization (CoRe), which uses CE capabilities alongside human feedback to embed a regularization term during retraining. CoRe allows for the adjustments in model sensitivities based on identified biases, aligning model prediction process with expert human assessments. Our evaluations on a modified metal casting dataset demonstrate CoRe's efficacy in bias mitigation, highlighting its potential to refine models in practical applications
Interpretable Machine Learning via Linear Temporal Logic
Full text linkIn recent years, deep neural networks have shown excellent performance, outperforming even human experts in various tasks. However, their inherent complexity and black-box nature often make it hard, if not impossible, to understand the decisions made by these models, hindering their practical application in high-stakes scenarios.
We propose a framework for learning LTL formulas as inherently interpretable machine learning models. These models can be trained both in a supervised and unsupervised setting. Furthermore, they can easily be extended to handle noisy data and to incorporate expert knowledge
Distributive Justice of Resource Allocation Through Artificial Intelligence
Full text linkArtificial intelligence will take over leadership functions such as rewarding employee performance. It will therefore make decisions about employee outcomes and most likely allocate different resources to employees. Resource Theory of Social Exchange distinguishes six resource classes. The theory postulates that the value of some resources depend on the identity of the provider of the resource and on the relationship with the provider. This raises the question of whether certain resources, such as the resource affiliation, have a value when they are allocated by artificial intelligence. This contribution calls for studies that investigate the value of different resources allocated by artificial intelligence in leadership functions
Die Kostenreports der Landesinitiative openaccess.nrw
No full textWährend vor dem Aufkommen von Open Access die Kostenerfassung für die Bereitstellung von Literatur maßgeblich Ausgaben für Subskriptionsverträge mit Verlagen oder Einzelkäufe beinhaltete, ist eine entsprechende Darstellung heute komplexer, da Open-Access-Publikationskosten teils von Forschenden selbst geleistet werden. Mit den vom Wissenschaftsrat empfohlenen Informationsbudgets soll dieses Kosteninformationsdefizit bei Bibliotheken bzw. den Hochschulleitungen geschlossen werden. Jedoch sind die Informationsbudgets erst im Aufbau, weswegen es Ziel der Landesinitiative openaccess.nrw ist die Kostentransparenz mithilfe von Kostenreports für Hochschulen der DH.NRW zu erhöhen. Der Vortrag beinhaltet eine Übersicht der ermittelten Kostendynamik in NRW und an der Universität Bielefeld, sowie eine Einführung in die Methodik der Kostenreports 2024.Da die in dem Vortrag präsentierten Ergebnisse vorläufig sind, wird von einer Veröffentlichung der Folien abgesehen
Question Answering from Healthcare Fora
Full text linkAssessing the quality of life of cancer patients is an important aspect of patient-focused drug development and real-world evidence generation. Specialized quality of life questionnaires exist for this purpose, and different types of cancer, such as breast cancer or lung cancer, can be assessed. However, conducting these surveys is a time-consuming process for both patients and clinical staff. At the same time, many patients discuss their experiences with and symptoms of their specific diseases in online healthcare fora. These forum posts may contain information that could be used to answer quality of life questions. Our objective is to determine whether forum posts can be used to answer quality of life questionnaires and, if so, whether this process can be automated successfully
Improving Trust in AI Through Sustainable and Trustworthy Reporting
Full text linkThis extended abstract outlines STREP, our (S)ustainable and (T)rustworthy (REP)orting framework. It communicates performance indicators of systems that build on artificial intelligence and thus makes them more trustworthy
Study on the Influence of Texture Variation on the Validation Performance of a Synthetically Trained Object Detector
Full text linkIn recent years, the utilization of synthetic data for the training of Deep Learning (DL) approaches has emerged as a valid alternative to the costly process of real data acquisition. Yet, the influence of the sim-to-real gap on the model performance still poses an obstacle to the broader usage of synthetic data. To investigate the major contributing factors, this study focuses on the influence of texture variation as a first step. Examining different strategies for generating synthetic validation sets for the training process of an object detector, the results of this study indicate that the sole influence of textures is insufficient to cause the observable performance gap alone
Concept Extraction for Time Series With ECLAD
Full text linkConcept Extraction (CE) methods are being increasingly used in the image domain for explaining deep learning models, which are not inherently interpretable. However, there have not been transfer studies yet for their usage in the time series domain. The purpose of this work is to explore the use of CE methods in time series. We propose to modify the ECLAD algorithm for this domain by changing the latent space representation used to extract concepts. This method is then tested on an InceptionTime model trained on the Gunpoint dataset. Preliminary results show that we can successfully extract concepts from time series models on datasets with local features and provide conceptual explanations that effectively explain how the model works