Master-Seminar
IS 712 für Master Studierende (MMM und Wirtschaftsinformatik) / IS 918 (MMBR)
Allgemeines
| Durchführender Dozent | Deborah Mateja |
|---|---|
| Prüfer | Prof. Dr. Armin Heinzl |
| Veranstaltungsart | Seminar |
| Leistungspunkte | 6 ECTS (MMM), 4 ECTS (WI ab HWS 2013) |
| Sprache | Englisch |
| Prüfungsform und -umfang | Seminararbeit (70%), Präsentation (20%), Diskussionsbeitrag (10%) |
| Prüfungstermin | Siehe Infos zur Veranstaltung |
| Infos für Studierende | Registrierung: Bitte beachten Sie unten stehende Informationen! |
Infos zur Veranstaltung
New Frontiers in Digital Transformation
Kurzbeschreibung
Digitale Technologien und die ständig wachsende Datenmenge verändern unser tägliches Leben und die Wirtschaft radikal. Digitale Technologien, die in den Kern der Produkte, Abläufe und Strategien vieler Unternehmen eingebettet sind, führen in allen Branchen zu einer raschen Umgestaltung bestehender Unternehmen. Rund um die Nutzung dieser digitalen Technologien entstehen neue Marktangebote, Geschäftsprozesse und Geschäftsmodelle, die zu digitalen Innovationen führen1. Die Allgegenwärtigkeit digitaler Technologien verändert unser Verständnis von Informationssystemen (IS) grundlegend, insbesondere im Hinblick auf ihre Entwicklung, Koordination, Nutzung und die Art und Weise, wie wir mit ihnen interagieren. An unserem Lehrstuhl bieten wir ein breites Spektrum an Forschungsthemen im Bereich der Informationssysteme an, wobei wir uns auf neue digitale Technologien wie künstliche Intelligenz (KI) und maschinelles Lernen (ML) konzentrieren. In unserer Forschung nehmen wir die Perspektiven der Mensch-Computer-Interaktion, des Systemdesigns, der Wertschöpfung oder der Organisation ein.
In unserem Seminar werden wir die Gestaltung digitaler Technologien sowie deren Auswirkungen auf Individuen und Organisationen untersuchen. Dabei verknüpfen wir die angebotenen Themen mit unserer laufenden Forschung, die in führenden internationalen Zeitschriften veröffentlicht wurde und wird.
1. Nambisan, S., Lyytinen, K. & Yoo, Y. Handbook of Digital Innovation. 2–12 (2020) doi:10.4337/9781788119986.00008.
Möchten Sie mehr über digitale Innovation erfahren? Werfen Sie einen Blick auf unseren Masterkurs IS 607 (https://www.bwl.uni-mannheim.de/en/heinzl/teaching/digital-innovation/) und/
oder sehen Sie Nambisan, S., Lyytinen, K. & Yoo, Y. Handbook of Digital Innovation, (2020), doi:10.4337/9781788119986. Ziel des Seminars
In diesem Seminar erwerben Sie die Fähigkeit, vorhandene Forschung zu identifizieren, einzuordnen und zu bewerten. Sie lernen, ein eigenes Forschungsprogramm zu entwickeln sowie dieses zu präsentieren und mit den Seminarteilnehmern zu diskutieren. Sie werden in verschiedenen Techniken des wissenschaftlichen Arbeitens und Schreibens unterrichtet, so dass Sie optimal auf die Konzeption und das Verfassen Ihrer Masterarbeit vorbereitet werden. Wir bieten verschiedene Themenbereiche an, die hoffentlich Ihr Interesse wecken.
HWS 2024
Registrierung
Die Registrierung erfolgt ausschließlich über das Online-Registrierungsportal (erreichbar innerhalb des Uni-Netzwerkes oder über VPN). Während des Registrierungszeitraums können Sie das Seminar im Anmeldeformular auswählen.
Registrierungszeitraum: siehe Termine
Anforderungen:
- Kurzes formloses Motivationsschreiben (maximal 1 Seite):
Bitte wählen Sie ein Thema und begründen Sie Ihre Wahl, z. B. was Sie besonders interessiert und was Sie lernen möchten. Bitte geben Sie auch zwei alternative Themen an.
- Lebenslauf und Studienergebnisse (Notentranskript)
Es werden weder Registrierungen per E-Mail noch unvollständige Formulare im Registrierungstool berücksichtigt.
Themen
Die Studierenden werden gebeten, ein formloses Motivationsschreiben (maximal 1 Seite) zu verfassen, in dem Sie dieThemenauswahl darlegen und kurz begründen.Dieses Motivationsschreiben stellt neben dem Lebenslauf und dem Notentranskript eine wichtige Referenz für die Seminarzulassung dar.
Explainable AI, Counterfactual Reasoning Ensuring transparency and interpretability in artificial intelligence (AI) is crucial as AI systems become increasingly integrated into critical decision-making processes. Explainable AI (XAI) addresses these needs by making AI decisions more understandable to humans. Among XAI techniques, counterfactual explanations are particularly important because they offer clear, actionable insights by illustrating „what if“ scenarios. These scenarios show how altering input variables can change the AI's output, making the decision process more transparent.Counterfactual explanations are essential because they align closely with human cognitive processes. Humans naturally engage in counterfactual thinking, considering alternative realities and their possible outcomes to make sense of events and decisions. This cognitive alignment makes counterfactual explanations intuitive and effective for users trying to understand AI decisions. This seminar will explore the intersection of counterfactual XAI and cognitive psychology, examining recent literature on how these explanations can enhance the interpretability of AI models. It will delve into the methods of generating counterfactual explanations, highlight practical applications, particularly in healthcare, and discuss how counterfactual explanations align with human reasoning. The seminar will also lay out future research directions on improving counterfactual explanations to better align with human cognition, paving the way for enhanced explainability of AI. Florian Rüffer Team-AI Collaboration, AI Team Members Organizations are beginning to incorporate artificial intelligence (AI) as team members to assist humans in handling complex tasks. The literature in the field of human-AI teaming and team-AI collaboration is currently working towards establishing an understanding of the characteristics of AI team members. However, there is no consensus on the characteristics and capabilities that define AI team members and shape the perception of their team-likeness. This seminar paper aims to contribute to a better understanding of what qualifies an AI system as a team member by synthesizing the literature on team-AI collaboration published since 2022. Desiree Zercher Responsible AI; Organizational Outsourcing Relationships Developing AI inhouse raises new organizational and managerial challenges for firms. Often-cited obstacles are the scarcity of AI/ ML talent in the market, volatile regulatory environments, and overall, the high complexity of transforming towards an AI-driven company. In this regard, accessing external, readily available AI services offer firms a quick and easy way to AI. For example, the large cloud service providers such as Amazon, IBM, SAP, Google, and Microsoft have started to offer generic AI services (Lins et al., 2021). Currently, there is a lack of understanding of additional governance requirements for sourcing AI externally. Against this background, this seminar paper will delve into the practices organizations apply to responsibly access third-party AI services, exploring the governance mechanisms of ‘Responsible AI’ inter-firm relationships. As a student, you will gain deep insights on managerial challenges of AI in organizations and the make vs. buy decision and related practices that many firms face today. Tobias Maier Automation of Avatar Creation The creation of 3D avatars using AI is transforming digital marketing and online interactions. With advanced AI methods, we can generate 3D avatars for various applications, from virtual reality to social media. This seminar thesis will explore the current state of algorithms used for automating avatar generation. In this thesis, the student will conduct a structured literature review to identify and analyze existing AI algorithms for 3D avatar creation. The aim is to understand the capabilities, limitations, and contexts in which these algorithms are applied. The research can cover methods for both the generation of new avatars (e.g. rigs, textures). Additionally, the thesis will examine how these algorithms have been evaluated and validated, focusing on their realism, quality, and adaptability, and whether they were compared with manually created avatars. The thesis should provide insights into the effectiveness of AI in producing engaging and realistic virtual characters. Applicants should have a background in computer science or a related field, with an interest in AI and/ or digital marketing. Experience with programming and AI frameworks is advantageous. Rosa Holtzwart, Deborah Mateja Digital Fashion Artefacts The improvements of digital rendering methods have sparked a wave of innovation in the design and development of virtual clothing and accessories. From virtual try-on experiences to personalized digital avatars, these assets offer consumers new ways to engage with fashion in the digital realm. However, as the demand for digital fashion continues to grow, it is crucial to understand the processes and principles underlying its design and development, as well as use and consumption of these digital artefacts. Existing research has highlighted the potential for digital fashion assets to reduce the environmental footprint of traditional fashion production by minimizing the need for physical materials and transportation. Yet, little is known about the specific resources and capabilities required to design digital fashion artefacts effectively. Furthermore, questions remain about the scalability and accessibility of these innovations. This bachelor thesis aims to address this gap by investigating theories and empirical evidence related to the construction and consumption of digital fashion assets. Through a structured literature review, the student will analyse existing research to uncover the processes, principles, and technologies involved in crafting digital fashion artifacts. Simultaneously, the thesis will explore user interactions and utilization patterns, including factors such as engagement, satisfaction, and their influence on real-world fashion consumption behaviors. By synthesizing insights from both realms, the thesis seeks to offer comprehensive understanding for optimising the creation and usage of digital fashion assets, with implications for sustainability, user engagement, and industry advancement. Rosa Holtzwart Dehumanization, Generative AI, HCI This seminar paper adopts Haslam's (2006) dual model of dehumanization as a foundational framework, with the goal of constructing a comprehensive literature synthesis on the dehumanization caused by the use of generative AI within the realms of Information Systems (IS) and Human-Computer Interaction (HCI) research. Haslam's model posits that humanness comprises two dimensions: human uniqueness and human nature. Denying uniquely human attributes to others characterizes them as animal-like, while denying human nature represents them as objects. Psychological research validates these dimensions as distinct facets of humanness. The objective of this seminar paper is to develop a literature review encompassing studies on the dehumanization effects within the domains of IS and HCI. Which theories have been applied? What technologies have been researched? What is the role of generative AI in exacerbating or mitigating dehumanization? The resulting body of literature should be scrutinized through the lens of the dual model of dehumanization. Ultimately, the literature review aims to synthesize existing knowledge on the dehumanization in IS and HCI and identify potential research gaps. Dr. Anna-Maria Seeger Affordance Theory, mHealth Mobile health technologies (mHealth) for supporting individuals' health behavior change are becoming increasingly popular. Despite initial evidence of the various benefits of mHealth, studies repeatedly report mixed results in terms of mHealth effectiveness. It is not uncommon for two similar users having access to the same mHealth app to report different outcomes and satisfaction with using that mHealth app. Affordance Theory, which distinguishes between technology features and the affordances that this technology provides for specific users—i.e., the potential for achieving goals by using the technology—promises to provide an explanation for the varying effectiveness of mHealth for different user groups. This seminar thesis explores how Affordance Theory can be applied to assess mHealth features and functionalities and how using the same app may result in different feature use patterns and varying outcomes for different users. Students are expected to search existing Information Systems literature that applies Affordance Theory to study individuals' use behavior, synthesize the content of these studies, and assess the applicability of Affordance Theory to study, design, and improve mHealth apps. To learn more about Affordance Theory see: Volkoff, O., & Strong, D. M. (2017). Affordance theory and how to use it in IS research. In R. D. Galliers & M.-K. Stein (Eds.), The Routledge Companion to Management Information Systems (1st ed., pp. 232–245). Routledge. https://doi.org/10.4324/9781315619361-18 Majchrzak, A., & Markus, M. L. (2012). TECHNOLOGY AFFORDANCES AND CONSTRAINTS IN MANAGEMENT INFORMATION SYSTEMS (MIS). In Encyclopedia of Management Theory. Sage Publications. https://ssrn.com/abstract=2192196 Mechthild Pieper Nudges; User Behavior; IS Use An increasing number of individuals use information systems (IS) for explaining, shaping, and changing individuals’ intentions, cognitions, and behavior. Developers often nudge use of these technologies by sending messages to users. Concurrently IS are constantly collecting data on users, their environment, and their behavior (e.g. location, weather, use behavior, contextual behavior, and mood). This data could be leveraged to deliver messages that adapt to an individual’s dynamic state and context over time. However, little is known about what content such messages should contain, under what circumstances messages should be sent, and when the best time is to nudge IS use and behavior. This seminar paper will review academic literature that employs nudges to change individual’s behavior. It will focus on what dynamic states or contexts can be captured with technology to improve the receptivity of nudges. The seminar paper will identify what theoretical perspectives are used, identify research gaps, and provide avenues for future research. The results of the literature review will have implications for how to better design messages to nudge use and subsequent behavior. In order to do this, this seminar paper will draw on academic literature related to information systems and behavioral science. Dr. Monica Fallon Human-AI Collaboration The field of AI is evolving rapidly, especially with the recent introduction of large-scaled pretrained AI systems such as ChatGPT. It is not only the underlying technologies that are changing but also the way we interact with such systems. As the field is evolving so rapidly, this seminar thesis targets the synthesis and analysis of the most recent research on human-AI collaboration. In particular, this seminar thesis will investigate high-level, peer-reviewed human-AI collaboration literature that has been published in the research streams of information systems, management, and human-computer interaction since the year 2021. The results of the literature review will have implications for where to target future research on human-AI collaboration. Deborah Mateja Human-AI Collaboration This seminar thesis investigates literature on organization search and showcases how it can be applied to study human-AI collaboration (Raisch & Fomina, 2024). The search process is central to a broad variety of organizational behaviors, including the creation of novel strategies, the pursuit of entrepreneurial activities, and the development of new products. This literature review will synthesize studies that apply the theoretical lens of organizational search in computational modeling from the management and information systems research disciplines and beyond. The goal is to synthesize elements of the search literature that can be transferred to the context of human-AI collaboration and derive respective avenues for future research. Deborah Mateja Explainable AI, Healthcare Explainable Artificial Intelligence (XAI) techniques enable the generation of explanations that allow clinicians to comprehend the underlying factors influencing AI-driven outcomes and help validate the results. While a variety of XAI methods have been developed, there is a lack of understanding of which methods and in which situations can provide clinicians with an adequate understanding of AI outputs. As clinicians will face challenges in deciding when to rely on the advice and when not to, it has been observed that XAI often alters this ability for the worse. Based on a structured review of information systems, computer science, and medical informatics literature, this seminar paper aims to uncover the theoretical discourses around clinicians’ cognitive capabilities to use XAI assistance. The paper could relate the findings from the medical context to the risks that were commonly observed in XAI, including overreliance, diagnostic efficiency, and the ability to detect errors, to name but a few. Luis Oberste Platform ecosystems, platform core, Generative Artificial Intelligence Digital platform business models have evolved into a dominant form of value creation and are the basis of many of the most successful firms. Recent developments regarding Generative Artificial Intelligence have already started to impact digital platform ecosystems. Established platform owners are incorporating Generative AI into their platform cores and potentially change the way how complementors (e.g., developers on iOS) and users interact with and contribute to the ecosystem. For example, in its recent announcement of iOS 18, Apple presented various AI services and features, including a feature to create personalized emojis based on textual inputs. In this seminar project, students are expected to review extant research on platform ecosystems and elaborate on how incorporating Generative AI may influence existing roles like complementors and users. Dr. André Halckenhäußer Kursüberblick und -termine
Event Zeitraum / Deadline Arbeitsergebnisse Registrierungszeitraum 01.08. – 02.09.2024 (23:59) – Registrierung über das Online-Tool – Fügen Sie Ihren Lebenslauf, das Notentranskript und Ihr Motivations¬schreiben an Versand der Bestätigungen 04.09.2024 (mittags) Deadline zum Rücktritt 09.09.2024 (mittags) Kick-Off Meeting 11.09.2024, 15:00 pm – 15:45 pm Room: B6, A103 – Teilnahme an der Kick-Off-Einführungsveranstaltung
– Kontakt und Treffen mit Ihrem Betreuer1. Meilenstein 25.09.2024 Ersten Entwurf bei Ihrem Betreuer einreichen: – Detaillierte Gliederung – Literatur¬verzeichnis 2. Meilenstein 23.10.2024 Zweiten Entwurf bei Ihrem Betreuer einreichen: – Inhaltsverzeichnis – Einführung: vollständig formuliert – Methodik: vollständig formuliert – Ergebnisse: strukturierter Entwurf – Diskussion: strukturierter Entwurf Abgabe der Arbeit 06.11.2024 (mittags) – Senden Sie Ihre Seminararbeit bis 12:00 Uhr im PDF-Format an Deborah Mateja (mateja@uni-mannheim.de) und fügen Sie die Mailadresse des Sekretariats des Lehrstuhls (wifo1@uni-mannheim.de) als CC hinzu. – Reichen Sie zwei Ausdrucke so bald wie möglich nach dem Abgabetermin beim Sekretariat ein. – Senden Sie eine digitale Version der Seminararbeit (im PDF-Format) per E-Mail an Ihren Betreuer Abgabe der Präsentation 26.11.2024 (mittags) – Optional: Bitten Sie Ihren Betreuer vorab um Feedback zur Präsentation – Senden Sie Ihre Präsentation im PDF-Format per E-Mail an Deborah Mateja Präsentation Monday, 25.11.2024 Room: Experience Lab – Besuchen Sie das Seminar und beteiligen Sie sich aktiv an der Diskussion am Seminartag – Präsentieren und diskutieren Sie Ihre Seminararbeit im gemeinsamen Workshop – Diskussion und Feedback für mindestens eine Seminararbeit der anderen Studierenden Literatur
- Webster, J., & Watson, R. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS Quarterly, 26(2), XIII-XXIII.
- Leidner, D. E. (2018). Review and theory symbiosis: An introspective retrospective. Journal of the Association for Information Systems, 19(6), 1.
Für den Zugriff auf die Literatur müssen Sie sich im VPN der Universität Mannheim befinden.
