Guest article by Marah Blaurock, finalist of the 2024 SERVSIG Best Dissertation Award.
It is a privilege to be among the finalists for the SERVSIG Best Dissertation Award – I thank the committee for this recognition of my thesis entitled “Artificial Intelligence and Robots in Services: Theory and Management of (Future) Human–Robot Service Interactions.” I was invited to share some reflections on my research and/or experiences as a service scholar. My research focuses mainly on human-AI collaboration. However, against the background of increasing calls for interdisciplinary research from journals and funding institutions, I opted to write a piece on my recent experiences of interdisciplinary collaboration with my human colleagues. I hope the guest article inspires readers to engage in more interdisciplinary scholarly work.
Overcoming Disciplinary Boundaries – Embracing Interdisciplinary Collaboration in AI Education and Beyond
In today’s academic and research landscape, journals and funding institutions are increasingly advocating for interdisciplinary projects, recognizing their potential to generate richer insights and innovative solutions. My recent experiences working in interdisciplinary research and teaching teams, particularly within the field of artificial intelligence (AI), have highlighted both the potential and the challenges of such collaborations.
AI is a transformative technology with implications that span numerous fields, including computer science, business, law, and ethics. Recognizing this, institutions of higher education need to develop study programs that prepare students to tackle AI-related challenges from a multifaceted perspective and foster their interdisciplinary understanding—a crucial 21st-century skill. The project IKID at Stuttgart Media University, which stands for Interdisciplinary AI Exploratory, aims to do just that. As part of the project, the interdisciplinary team develops a teaching program for different study programs across the university to teach AI interdisciplinarily, integrating insights from four distinct disciplines: computer science, business, law, and ethics.
The program consists of a foundation module and integrated AI projects. The foundation module provides students with basic knowledge of the four disciplines. In consecutive integrated AI projects, students apply the knowledge from the foundation module and work in interdisciplinary teams to solve multifaceted AI-related problems or create AI-enabled products or services. These project-based learning approaches foster critical thinking, problem-solving, communication, and collaboration skills, enhancing students’ ability to work across disciplinary boundaries. For example, the “AI Startup Game” has students operate as AI startups, navigating typical business challenges and balancing technical, ethical, and business considerations. In the “AI Voice Cloning Project,” students develop voice cloning applications, addressing technical, ethical, and legal aspects in the process.
Based on preliminary insights of our evaluation study that accompanies the project, I now share some success factors and challenges that might aid scholars who aim to engage in interdisciplinary collaboration in the context of higher education.
Success Factors
1. Study Program – Foundation Module, Real-World Applications, and Teaching Methods: The foundation module successfully ensured that all students, regardless of their initial expertise, have a shared base of knowledge. This levels the playing field and enables effective interdisciplinary collaboration in the subsequent integrated AI projects. Practical, real-world applications of AI that resonate with students’ realities within the integrated AI projects engage students and provide them with insights into how interdisciplinary knowledge can solve complex problems. Creating an environment that encourages collaboration and open discussion is crucial; methods such as role-plays and gamification elements seemed to aid students in their learning.
2. Lecturer Team – Effective Interdisciplinary Communication: One critical success factor is the ability of team members to communicate effectively across disciplines. However, this skill takes time to develop. Accounting for more time in the whole development phase and for discussions in regular team meetings facilitated a better understanding and integration of diverse perspectives in the final study program.
Challenges
1. Disciplinary Silos: Overcoming ingrained habits and methodologies specific to each discipline requires time, flexibility, and a willingness to adopt new approaches. Providing workshops on successful interdisciplinary collaboration for faculty and students alike can create awareness of different methods of work and, thus, support overcoming the negative effects of disciplinary silos.
2. Varying Pace: Rapid development cycles typical of computer science and business sometimes clash with the more deliberative processes of ethics. The fast-paced developments in AI exhilarated these issues as different disciplines had to keep up with the newest technologies and regulations, which demanded resources to keep up in one’s own discipline before thinking of integrating viewpoints of other disciplines. Creating awareness of differences in disciplinary cultures and approaches, as well as being open to spontaneous changes to class materials, alleviated this issue, but it remains ongoing.
3. Administrative and Institutional Barriers: Administrative hurdles to providing a study program to students from different faculties are notable challenges. Addressing these requires institutional support across faculties from the beginning. Ideally, one person from the administration would regularly join the team to provide their perspective on realizing the study program for different faculties.
In sum, by offering interdisciplinary study programs, we can prepare students to better navigate the complexities of business and society and equip them with crucial 21st-century skills. Although interdisciplinary collaboration does come with its challenges, the results are very rewarding and a great learning experience for scholars and students alike. I hope this guest article provides some valuable insights for scholars intending to embark on interdisciplinary teaching endeavors.
Marah Blaurock
Postdoctoral Researcher
Institute of Applied Artificial Intelligence
Stuttgart Media University (Hochschule der Medien, Stuttgart, Germany)
Image: generated by ChatGPT.