|Prof. Dr. Armin Heinzl
|6 ECTS (MMM), 4 ECTS (WI)
|Seminar paper (70%), presentation (20%), discussion (10%)
|See course information below
|Information for Students
|Registration: Please see information below!
Digital technologies and the ever-growing amounts of data are radically reshaping our daily lives as well as the economy. Embedded at the very core of the products, operations, and strategies of many organizations, digital technologies are rapidly transforming existing businesses throughout all industries. New market offerings, business processes, as well as business models are emerging around the use of these digital technologies, yielding digital innovation1. The pervasive nature of digital technology is fundamentally transforming our understanding of information systems (IS), especially regarding their development, coordination, use, and the way we interact with them. At our chair, we offer a wide range of research topics in IS, focusing on new digital technologies such as artificial intelligence (AI) and machine learning (ML). In our research, we take human-computer interaction, system design, value creation or organizational perspectives.
In our seminar, we will examine the design of digital technologies as well as their impact on individuals and organizations. In doing so, we link the offered topics to our ongoing research, which has been and is currently being published at leading international outlets.
1. Nambisan, S., Lyytinen, K. & Yoo, Y. Handbook of Digital Innovation. 2–12 (2020) doi:10.4337/9781788119986.00008.
Interested in learning more about digital innovation? Feel free to have a look at our master course IS 607 (https://www.bwl.uni-mannheim.de/en/heinzl/teaching/digital-innovation/) and/
In this seminar, you will acquire the ability to identify, classify, and evaluate existing research. You will learn how to develop your own research agenda as well as to present and discuss it with the participants of the seminar. You will be taught different techniques of scientific work and writing so that you will be prepared in the best possible way for the conception and writing of your Master's thesis. We offer five different topic areas, which hopefully raise your interest.
You may register via our online registration tool (accessible inside the university network or via VPN). During the registration period, you can select the seminar in the registration form (under ‘Application Details’ à ‘Purpose’)
Registration period: see schedule
Please select a topic and give reasons for your choice, i.e., what are you particularly interested in and what do you want to learn. Please also provide two alternative topics.
We will not consider applications via e-mail or with incomplete data in the registration tool.
Students are asked to write a short letter of motivation (maximum 1 page) to choose a topic and briefly justify your choice. This letter of motivation will be considered as the key reference for seminar entry, in addition to the CV and the transcript of records.
|Emotion Regulation, Wellbeing, Mobile health technologies
|The ability to regulate emotions for situational adaptations is critical for individuals' wellbeing. Emotion Regulation (ER) includes strategies by which individuals influence which emotions they have, when they have them, and how they perceive their experiential, behavioral, and psychological impact. It is assumed that mobile health technologies (mHealth) offer potential to support individuals' development of effective ER strategies. However, it remains unclear whether and how ER occurs during mHealth use to manifest this potential. For this seminar thesis, students are expected to conduct a structured literature review to examine how ER strategies can be taught and supported by mobile health applications. Good starting points are: • Slovak, P., Antle, A., Theofanopoulou, N., et al. (2023) Designing for Emotion Regulation Interventions: An Agenda for HCI Theory and Research. ACM Transactions on Computer-Human Interaction 30(1): 1–51. • Eisenstadt, M., Liverpool, S., Infanti, E., et al. (2021) Mobile Apps That Promote Emotion Regulation, Positive Mental Health, and Well-being in the General Population: Systematic Review and Meta-analysis. JMIR Mental Health 8(11).
|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 dehumanization 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 dehumanization within the domains of IS and HCI. Which theories have been applied? What technologies have been researched? What is the role of AI? 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 dehumanization in IS and HCI and identify potential research gaps.
|Dr. Anna-Maria Seeger
|Human beauty or attractiveness is a dominant characteristic of physical appearance and humans have a drive for beauty. Humans also have a tendency to enhance their self-presentation, thus they engage in beahviours to optimise their apperance. This also includes enhancements of their appearance in virtual realms, such as improving their beauty with filters or photoshop on social media. With the surge of computational power and generative AI, the methods to enhance the virtual images of humans have been rapidly evolving. For instance, some social media applications now provider pre-configured facial filters that can be applied to the front view of the face in real time. To understand the possibilities and potential developments of virtual beautification in the future, it is necessary to understand past efforts of automation of virtual beauty enhancements. In this seminar paper the student is expected to conduct a structured literature review, to identify the algorithms and methods that have been developed in in previous studies to enhance human beauty. Moreover, the aim of this seminar thesis is to provide an overview of the ways the developed algorithms have been evaluated, where and how they can be applied (e.g. only front face, including profile face view; full-body; static images, live video, 3D etc.).
As digital technology advances, so does the complexity of manipulating visual content, giving rise to the phenomenon of deepfakes. Deepfakes involve the use of artificial intelligence to create hyper-realistic videos or images, often featuring manipulated facial expressions, speech patterns, and even body movements. This seminar paper invites students from to explore the landscape of deepfakes. By conducting a comprehensive literature review, students will delve into the algorithms and methodologies employed in previous studies on deepfake creation. Additionally, the thesis should aim to provide insights into the evaluation metrics applied to these algorithms especially concerning their perceived realism, their potential applications (e.g., social media, political discourse), and/
|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 the team likeness of an AI team member. This seminar paper aims to contribute to a better understanding of what qualifies an AI system as a team member by synthesizing the current state of research on AI teaming capabilities through four research questions: 1. What characteristics should an AI team member possess? 2. How do these characteristics differ from those of human team members? 3. How does the current literature approach the definition of characteristics for an AI team member? 4. Are there already inventories available to measure the teaming capabilities of an AI system? literature examples: Wynne, K. T., & Lyons, J. B. (2018). An integrative model of autonomous agent teammate-likeness. Theoretical Issues in Ergonomics Science, 19(3), 353–374. https://doi.org/10.1080/1463922X.2016.1260181 Siemon, D. (2022). Elaborating Team Roles for Artificial Intelligence-based Teammates in Human-AI Collaboration. Group Decision and Negotiation, 31(5), 871–912. https://doi.org/10.1007/s10726-022-09792-z
|Generative AI, fashion design, computational creativity
|Recently, generative AI technologies have captured significant attention. Innovations such as Dalle and ChatGPT, among others, have demonstrated their remarkable creative capabilities. The seminar thesis explores the intersection of fashion design and generative AI. Through this seminar thesis, students will delve into the theoretical foundations, practical applications, and ethical implications of using generative AI in fashion design. They will critically analyze existing research, industry case studies, and emerging trends to develop a well-rounded perspective on the subject. The goal is to capture the current state of research on generative AI and fashion design as well as prospective frontiers.
|The Potential of AI in Enhancing Psychosocial Care for Cancer Patients
|This seminar paper explores how artificial intelligence (AI) within mobile health (mHealth) can address the complexities of psychiatric disorders prevalent in cancer patients. Behavioral and cognitive interventions via mHealth apps demonstrate a reduction in the severity of depression, highlighting the potential of digital health technologies to alleviate mental health challenges (Eisenstadt et al., 2021). AI (e.g., in the form of chatbots) is emerging as a promising tool to provide personalized psychosocial support, which can promote well-being and prevent such conditions independent of traditional therapy sessions. Therefore, a seminar paper could explore how AI can effectively detect latent conditions such as anxiety, grief, stress, and depression in oncological care, highlight the screenings and classifications that AI can provide based on different types of data in mHealth, and demonstrate its potential for more effective and personalized support throughout the patient journey, e.g., through longitudinal monitoring and timely triggers. Eisenstadt, M., Liverpool, S., Infanti, E., Ciuvat, R. M., & Carlsson, C. (2021). Mobile Apps That Promote Emotion Regulation, Positive Mental Health, and Well-being in the General Population: Systematic Review and Meta-analysis. JMIR Mental Health, 8(11), e31170. https://doi.org/10.2196/31170
|Luis Oberste / Mechthild Pieper
|Unlocking Potential: The Role of Open Data in Advancing Healthcare AI
|In recent years, the field of healthcare AI has increasingly leveraged the potential of open data. Open data, characterized by its accessibility and permission for widespread use, has a profound impact on the advancement of AI in healthcare. Open data in the healthcare context refers to freely available data on diseases, treatments, patient outcomes, and healthcare resources. This data can be found in various sources including discussion forums, personal blogs, public research results, and much more. This seminar thesis focuses on the critical exploration of open data utilization in healthcare AI. By examining existing literature, this thesis aims to dissect how open data contributes to the development of AI-driven solutions in healthcare, from diagnostic algorithms to patient care management systems. Emphasis will be placed on understanding the challenges, ethical considerations, and the transformative potential of open data in this sector. Ultimately, this thesis endeavors to construct a comprehensive picture of how open data is reshaping healthcare AI, paving the way for more informed, efficient, and personalized medical care.
|Platform ecosystems, governance, innovation, industrial platforms
|The emergence of digital platforms has strongly influenced various markets, fostering transaction efficiency and innovation. The success of the platform business model is unprecedented: many of the most valuable firms, including Apple, Google or Microsoft are platform companies. Platform business models are increasingly omnipresent in markets that target end-customers (i.e., Business-to-Consumer markets). As such, digital platforms act as facilitator of innovation, providing a stable technological core that third parties can build upon for the development of complementary products and services (e.g., a mobile operating system), or as facilitator of transaction, intermediating interaction between different market sides (e.g., a marketplace). In the industrial sector, the benefits of digital platforms and their role in facilitating digitalization are repeatedly emphasized. The high potential of platform business models in the industrial sector notwithstanding, their adoption remains limited and existing offerings struggle with numerous challenges. In this seminar project, students are expected to review extant platform literature and elaborate on unique features of and challenges posed by digital industrial platforms.
|Dr. André Halckenhäußer
|AI Economy, AI Democratization
|The advent of generative AI (GenAI), exemplified by the rapid developments of ChatGPT over the past year, has marked a pivotal moment in the democratization of AI. This accessibility of novel AI capabilities again forces organizations, regardless of industry or technical expertise, to think about how AI can change their business, industry, and competitive environment. As such, the surge in demand for AI capabilities has led to the emergence of a complex landscape of actors, interactions, and resources. Despite the increasing availability of value-promising AI services, organizations remain hesitant to adopt AI solutions. This seminar thesis aims to address this hesitation and delve into how organizations can successfully navigate the evolving AI economy. Through a systematic literature review, we aim to provide valuable insights into the current state of research related to AI ecosystems and propose avenues for future exploration.
|01.01. – 12.02.2024 (23:59)
|– Register via online registration tool – Include your CV, transcript of records, and your letter of motivation
Notification of acceptance/
|Deadline for drop out
|19.02.2024, 13:00 am – 13:45 am Room: A 301 B 6, 23–25, Bauteil A
|– Participate in the introductory kick-off session – Contact and meet your advisor
|Submit first draft to your advisor – Detailed outline – List of literature
|Submit second draft to your advisor – Table of contents – Introduction: fully formulated – Methodology: fully formulated – Results: structured draft – Discussion: structured draft
|Seminar paper submission
|– Send your seminar work until 12:00 (noon) in PDF-format to Timo Himmelsbach (email@example.com) and add the chair’s secretary mail address (firstname.lastname@example.org) on CC. – Submit two printouts to the secretary as soon as possible after the submission deadline. – Send a digital version of the seminar paper (in PDF format) via e-mail to your advisor
|Slide deck submission
|– Optional: Request feedback on presentation in advance from your supervisor – Send your presentation in PDF format via e-mail to Timo Himmelsbach
|Thursday, 16.05.2024 and Friday, 17.05.2024 (1:00PM– 05:30PM) Room: ExpLAB
|– Attend and actively participate in the discussion on the seminar day – Present and discuss your seminar paper in the joint workshop – Discuss and provide feedback for at least one of the other students’ seminar papers
To access the literature you have to be in the VPN of the University of Mannheim.