Publication
Improving Conversational User Interfaces for Citizen Complaint Management through enhanced Contextual Feedback
Kai Karren; Michael Schmitz; Stefan Schaffer
In: Proceedings of the 6th ACM Conference on Conversational User Interfaces. International Conference on Conversational User Interfaces (CUI-2024), Luxembourg, Luxembourg, CUI '24, ISBN 9798400705113, Association for Computing Machinery, 2024.
Abstract
As cities transform, disrupting citizens’ lives, their participation in urban development is often undervalued despite its importance. Citizen complaint systems exist but are often limited in fostering meaningful dialogue with municipalities. Meanwhile, smart cities aim to improve living standards, efficiency, and sustainability by integrating digital twins with physical infrastructures, potentially enhancing transparency and enriching communication between cities and their inhabitants with real-time data. Complementing these developments, technologies realizing Conversational User Interfaces (CUIs) are becoming more capable in providing a conversational and feedback-oriented approach such as complaint management processes. The improvement of CUIs for citizen complaint management through enhanced contextual feedback is explored in this work. The term contextual feedback has been developed and defined as all information (for example, background, conditions, explanations, timelines, and the existence of similar complaints) related to a complaint and or the underlying problem that could potentially be relevant for the user. The solution proposed in this paper gathers data from users about their issues via a CUI, which subsequently queries various data sources to obtain relevant contextual information. Following this, a Large Language Model processes the collected data to produce the corresponding feedback. In the study, a static CUI without contextual data as the baseline has been compared to a CUI that includes contextual data, analyzing their impact on pragmatic and hedonic quality, reuse intention, and potential influence on the citizens’ trust in their municipality. The study has been conducted in cooperation with the German municipality of Wadgassen. The good performance of the baseline system shows the general potential of LLMs in the citizen complaint domain even without data sources. The results show that contextual feedback performed better overall, with significant improvements in the pragmatic and hedonic quality, attractiveness, reuse intention, feeling that the complaint is taken seriously, and the citizens’ trust in their municipality.