Approaches to Improve Fairness when Deploying AI-based Algorithms in Hiring – Using a Systematic Literature Review to Guide Future Research - Rieskamp, Jonas; Hofeditz, Lennart; Mirbabaie, Milad; Stieglitz, Stefan (Proceedings of the Annual Hawaii International Conference on System Sciences (HICSS))
Algorithmic fairness in Information Systems (IS) is a concept that aims to mitigate systematic discrimination and bias in automated decision-making. However, previous research argued that different fairness criteria are often incompatible. In hiring, AI is used to assess and rank applicants according to their fit for vacant positions. However, various types of bias also exist for AI-based algorithms (e.g., using biased historical data). To reduce AI’s bias and thereby unfair treatment, we conducted a systematic literature review to identify suitable strategies for the context of hiring. We identified nine fundamental articles in this context and extracted four types of approaches to address unfairness in AI, namely pre-process, in-process, post-process, and feature selection. Based on our findings, we (a) derived a research agenda for future studies and (b) proposed strategies for practitioners who design and develop AIs for hiring purposes.
Keywords: fairness in AI; SLR; hiring; AI implementation; AI-based algorithms

Predicting the Bond Quality of Heavy Copper Wire Bonds using a Friction Model Approach - Althoff, Simon
Ultraschall-Drahtbonden ist eine Standardtechnologie im Bereich der Aufbau- und Verbindungstechnik von Leistungshalbleitermodulen. Um Prozessschritte und damit wertvolle Zeit zu sparen, sollen die Kupferdickdrähte für die Leistungshalbleiter auch für die Kontaktierung von eingespritzten Anschlusssteckern im Modulrahmen verwendet werden. Das Kontaktierungsverfahren mit diesen Drähten auf Steckern in dünnwandigen Kunststoffrahmen führt häufig zu unzureichender Bondqualität. In dieser Arbeit wird das Bonden von Anschlusssteckern experimentell und anhand von Simulationen untersucht, um die Prozessstabilität zu steigern. Zunächst wurden Experimente auf Untergründen mit hoher Steifigkeit durchgeführt, um Störgrößen von Untergrundeigenschaften zu verringern. Die gewonnenen Erkenntnisse erlaubten die Entwicklung eines Simulationsmodells für die Vorhersage der Bondqualität. Dieses basiert auf einer flächenaufgelösten Reibarbeitsbestimmung im Fügebereich unter Berücksichtigung des Ultraschallerweichungseffektes und der hierdurch entstehenden hohen Drahtverformung. Experimente an den Anschlusssteckern im Modulrahmen zeigten eine verringerte Relativverschiebung zwischen Draht und Stecker, was zu einer deutlichen Verringerung der Reibarbeit führt. Außerdem wurden verminderte Schwingamplituden des Bondwerkzeugs nachgewiesen. Dies führt zu einer weiteren Reduktion der Reibarbeit. Beide Effekte wurden mithilfe eines Mehrmassenschwingers modelliert. Die gewonnenen Erkenntnisse und die erstellten Simulationsmodelle ermöglichen die Entwicklung von Klemmvorrichtungen, welche die identifizierten Störgrößen gezielt kompensieren und so ein verlässliches Bonden der Anschlussstecker im gleichen Prozessschritt ermöglichen, in dem auch die Leistungshalbleiter kontaktiert werden.
Keywords: heavy copper bonding; wire bonding; quality prediction; friction model; point-contact-element

Model-based condition monitoring of piezoelectric bending actuators - Bender, Amelie (Sensors and Actuators A: Physical)
With enhancing digitalization, condition monitoring is used in an increasing number of application fields across various industrial sectors. By its application, increased reliability as well as reduced risks and costs can be achieved. Based on different approaches, technical systems are monitored and measured data is analyzed to enable condition-based or predictive maintenance. To this end, machine learning approaches are usually implemented to diagnose the health states or predict the health index of the monitored system. However, these trained models are often black-box models, not intuitively explainable for a human. To overcome this shortcoming, a model-based approach based on physics is developed for piezoelectric bending actuators. Such a model enables a transparent representation of the system. Moreover, the model-based approach is extended by a parameter-estimation to account for sudden changes in behavior e. g. caused by occurring cracks.
Keywords: Condition Monitoring; Model-based approach Diagnostics; Varying conditions; Explainability; Piezoelectric bending actuators

Interview Study on Strategy Options for Platform Operation in B2B Markets - Özcan, Leon; Fichtler, Timm; Kasten, Benjamin; Koldewey, Christian; Dumitrescu, Roman
Keywords: Digital Platform; Platform Strategy; Strategic Management; Platform Life Cycle; Interview Study; Business Model; Business-to-Business; Two-sided Market; Multi-sided Market

AnnoPy. Ein digitales Tool zur Förderung von Textkompetenzen - Rezat, Sara; Scholle, Oliver (Medien im Deutschunterricht)
Im Beitrag wird ein digitales Tool zur fächerübergreifenden Förderung von Textkompetenzen vorgestellt. Zunächst werden die Funktionen des Tools beschrieben und das zugrundeliegende tool-based task Design erläutert. Anhand eines Lehr-Lern-Arrangements zum argumentierenden Schreiben wird exemplarisch gezeigt, wie das Tool im Deutschunterricht eingesetzt werden kann. Anschließend werden erste empirische Befunde aus der am Design-Based-Research orientierten Studie vorgestellt. Abstract (english): AnnoPy – A digital tool for cross-curricular text literacy development In this article we present a digital tool for cross-curricular text literacy development. At first, we describe the basic functions of the tool and the underlying tool-based task design. After that, a teaching arrangement for German lessons is used to show how the tool can be used to foster argumentative writing. Subsequently, first results of the design-based study are presented.
Keywords: Textkompetenz; Digitales Lesen und Schreiben; Kollaborativer Umgang mit Texten; Prozedurenorientierte Schreibdidaktik; Design-based-Research

Umgang mit Evidenzen angehender Lehrkräfte in den Naturwissenschaften - Epistemologie in der Lehrkräfteausbildung - Pollmeier, Pascal
Eine Forderung nach evidenzbasierter Praxis (EBP) im Bildungswesen kann sowohl vor dem Hintergrund der Bedeutung wissenschaftlicher Evidenzen innerhalb gesellschaftlicher Diskurse als auch der Evidenzbasierung in anderen Bereichen formuliert werden. Der Umgang mit und die Bewertung von Evidenzen stellen somit vor dem Hintergrund epistemologischer Überzeugungen relevante Aufgaben für den Chemieunterricht dar. Dabei ist unklar, inwiefern (angehende) Lehrkräfte über Kompetenzen in EBP verfügen. Bestehende Studien weisen auf einen Bedarf der fachdidaktischen Analyse und Förderung von Kompetenzen in EBP bei angehenden Lehrkräften hin.Im Rahmen dieser Dissertation wurde die Domänenspezifität der Kompetenzen in EBP sowie deren Förderung in einem fachdidaktischen Kontext untersucht. Dabei wurde ein weiterer Schwerpunkt auf den Umgang mit anomalen Beobachtungen im Sinne widersprüchlicher Evidenzen gelegt. Innerhalb von drei Teilstudien wurden unterschiedliche methodische Zugänge zur Kompetenz in EBP auf Grundlage epistemologischer Überzeugungen gewählt.Die Ergebnisse weisen auf einen Förderbedarf der Kompetenz in EBP für angehende Lehrkräfte aller Unterrichtsfächer hin. Eine entwickelte Intervention für angehende Chemielehrkräfte weist eine Wirksamkeit zur Förderung von Kompetenzen in EBP auf. Im Rahmen einer Modellierungsstudie kann der Einfluss von Fachwissen sowie Indizien für einen Einfluss epistemologischer Überzeugungen auf den Umgang mit anomalen Beobachtungen gezeigt werden.
Keywords: Epistemologie; Evidenzen; evidence-based practice

Designing digital actor engagement platforms for local high streets: an action design research study - Bartelheimer, Christian; zur Heiden, Philipp; Berendes, Carsten Ingo; Beverungen, Daniel (European Journal of Information Systems)
High streets across Europe continue to lose consumers to online retail, leading to business closures and the decline of city centres, impairing cities’ overall liveability. To counter this vicious cycle, our study presents smartmarket2, the first instantiation of a digital actor engagement platform designed specifically for high streets. smartmarket2 enables hybrid online-offline customer journeys by connecting consumers to stores and other high street service providers. In an action design research (ADR) project, we design, implement and evaluate smartmarket2, involving 150 high street operators and 2,300 citizens in three cycles of building, intervention and evaluation. We derive four design principles that contribute prescriptive knowledge on the design of digital actor engagement platforms. Our results reveal that such a platform is able to increase engagement, but that it is subject to actors’ engagement dispositions.
Keywords: Digital platform; action design research; design principles; actor engagement; engagement platform; location-based advertising

Towards comparable ratings: Exploring bias in German physician reviews - Kersting, Joschka; Maoro, Falk; Geierhos, Michaela (Data & Knowledge Engineering)
In this study, we evaluate the impact of gender-biased data from German-language physician reviews on the fairness of fine-tuned language models. For two different downstream tasks, we use data reported to be gender biased and aggregate it with annotations. First, we propose a new approach to aspect-based sentiment analysis that allows identifying, extracting, and classifying implicit and explicit aspect phrases and their polarity within a single model. The second task we present is grade prediction, where we predict the overall grade of a review on the basis of the review text. For both tasks, we train numerous transformer models and evaluate their performance. The aggregation of sensitive attributes, such as a physician’s gender and migration background, with individual text reviews allows us to measure the performance of the models with respect to these sensitive groups. These group-wise performance measures act as extrinsic bias measures for our downstream tasks. In addition, we translate several gender-specific templates of the intrinsic bias metrics into the German language and evaluate our fine-tuned models. Based on this set of tasks, fine-tuned models, and intrinsic and extrinsic bias measures, we perform correlation analyses between intrinsic and extrinsic bias measures. In terms of sensitive groups and effect sizes, our bias measure results show different directions. Furthermore, correlations between measures of intrinsic and extrinsic bias can be observed in different directions. This leads us to conclude that gender-biased data does not inherently lead to biased models. Other variables, such as template dependency for intrinsic measures and label distribution in the data, must be taken into account as they strongly influence the metric results. Therefore, we suggest that metrics and templates should be chosen according to the given task and the biases to be assessed.
Keywords: Language model fairness; Aspect phrase classification; Grade prediction; Physician reviews

Situational Business Model Developer: A Tool-support for Situation-speciﬁc Business Model Development - Gottschalk, Sebastian; Yigitbas, Enes; Nowosad, Alexander; Engels, Gregor (Proceedings of the 17th International Conference on Wirtschaftsinformatik)
The development of business models is a challenging task that can be supported with software tools. Here, existing approaches and tools do not focus on the company’s situation in which the development takes place (e.g., ﬁnancial resources, product type). To tackle this challenge, we used design science research to develop a situation-speciﬁc business model development approach that contains three stages: First, existing knowledge in terms of tasks to do (e.g., analyze competitive advantage), and decisions to be made (e.g., social media marketing) are stored in repositories. Second, the knowledge is used to compose a development method based on the company’s situation. Third, the development method is enacted to develop a business model. This demonstration paper presents a tool-support called Situational Business Model Developer that supports all stages of our approach. We release the tool under open-source and evaluate it with a case study on developing business models for mobile apps.
Keywords: Business Model Development; Situational Method Engineering; Tool Support

Model-driven Continuous Experimentation on Component-based Software Architectures - Gottschalk, Sebastian; Yigitbas, Enes; Engels, Gregor (Proceedings of the 18th International Conference on Software Architecture Companion)
To build successful software products, developers continuously have to discover what features the users really need. This discovery can be achieved with continuous experimentation, testing different software variants with distinct user groups, and deploying the superior variant for all users. However, existing approaches do not focus on explicit modeling of variants and experiments, which offers advantages such as traceability of decisions and combinability of experiments. Therefore, our vision is the provision of model-driven continuous experimentation, which provides the developer with a framework for structuring the experimentation process. For that, we introduce the overall concept, apply it to the experimentation on component-based software architectures and point out future research questions. In particular, we show the applicability by combining feature models for modeling the software variants, users, and experiments (i.e., model-driven) with MAPE-K for the adaptation (i.e., continuous experimentation) and implementing the concept based on the component-based Angular framework.
Keywords: continuous experimentation; model-driven; component-based software architectures; self-adaptation