Generative AI (GenAI) has gained significant momentum across various work and life settings in the last years transitioning from data-focused, discriminative AI tasks to more complex and creative endeavors. Due to this change, new paradigms in Human-GenAI collaboration and human-centered design has led information systems (IS) to increasingly evolve from passive tools into autonomous entities capable of learning, adapting content, interacting, and acting independently. More collaborative forms of work are emerging, where Human-GenAI collaboration facilitates new modes of co-creating value with a profound impact on individuals, organizations and their daily operations. This shift in agency from humans to agentic IS artefacts forms the foundation for the next generation of IS artifacts.
While it is still challenging to precisely gauge the influence of GenAI on our global society, its impact is already evident at organizational, technological, and behavioral levels. Alongside its transformative benefits, there are also potential drawbacks, including privacy, trust, and risk concerns and unintended negative consequences. Therefore, it is crucial to engage in research that evaluates the potential and impact of the evolving nature of GenAI and to design socio-technical solutions that harness these technologies for the benefit of individuals, organizations, and society.
In this context, the track offers a forum for researchers across all streams within Information Systems to explore the field of Generative AI. We particularly welcome contributions at the individual, organizational, and societal levels, focusing on the design and impact of generative AI, including new design methodologies, conceptual frameworks, tools, and studies on the behavioral implications of this paradigm. This track encourages authors to critically examine the complexities and unintended consequences of GenAI, including its influence on workforce skills, well-being, and judgment in human-GenAI collaborations, offering fresh insights that build on existing research, theories, and methodologies.
Topics of interest include, but are not limited to:
- Human-GenAI-Collaboration for the future of work and society
- Human-oriented design and application of GenAI
- GenAI Upskilling for the workforce of tomorrow
- Human-GenAI decision-making
- Privacy, Trust, and Risk in Generative AI
- Design Research and Methods for Generative AI
- Generative AI as a driver of creativity and challenge to information integrity
- Role of judgment in human-GenAI decision-making.
- Critical perspectives on Human vs. GenAi content creation
- Role of GenAI in enhancing creativity and innovation
- GenAI for well-being
- Impact of GenAI on Organizations (e.g., communication and content creation)
- GenAI-driven work augmentation
Track chairs
AEs
- Sabrine Mallek, ICN Business School
- Paula Bräuer, Christian-Albrechts-Universität zu Kiel
- Mario Schaarschmidt, Universität Duisburg-Essen
- Hendrik Wache, ICN Business School
- Edona Elshan, VU Amsterdam
- Laura Watkowski, Universität Bayreuth
- Mahei Li, Universität St. Gallen
- Mario Nadj, Universität Duisburg-Essen
- Pauline Weritz, University of Twente
- Philipp Pecher, Universität Göttingen
- Christian Meske, Ruhr-Universität Bochum