Publications
With our publications we cover the most diverse research areas that arise in the field of man, task and technology. In addition to traditional Business Information Systems topics such as knowledge management and business process management, you will also find articles on current topics such as blended learning, cloud computing or smart grids. Use this overview to get an impression of the range and possibilities of research in Business Information Systems at the University of Duisburg-Essen.
Type of Publication: Article in Journal
"Hey Siri, Don't Make Me Mad" - Overcomming User Annoyances With Voice Assistants
- Author(s):
- Strauss, Christina; Harr, Michael Dominic; Schütte, Reinhard; Wimmer, Simon
- Title of Journal:
- Proceedings of the European Conference on Information Systems
- Publication Date:
- 2024
- Language:
- English
- Keywords:
- Voice Assistants, Siri, User Annoyances, Large Language Model, Digitalization
- Fulltext:
- “HEY SIRI, DON’T MAKE ME MAD” – OVERCOMING USER ANNOYANCES WITH VOICE ASSISTANTS
- Link to complete version:
- https://aisel.aisnet.org/ecis2024/track19_hci/track19_hci/7/
- Talk associated with this publication:
- European Conference on Information Systems (ECIS)
- Citation:
- Download BibTeX
Abstract
This study examines the effects of integrating a technically advanced and more human-like large language model into a voice assistant to assess, how technical advancements mitigate user annoyances. Therefore, a generative pre-trained transformer was integrated into Siri and made available to 23 interview participants. Preliminary results reveal a decrease in user-reported annoyances, showing that the integration not only improves technical accuracy but also enhances the perceived humanness of interactions. However, subsequent interviews indicated that the distinction between the effects of technical advancements and the infusion of humanness emerged as critical, indicating a complex interplay between these factors. It is therefore planned to differentiate between technical and human improvements in the further development of this article. The results contribute to the discourse on optimizing voice assistants by pinpointing the reduction of user annoyances as a pivotal factor in improving user experience, suggesting pathways for future enhancements in voice assistant platforms.