Alexander Dregger, Andreas Oberweis

Description

A chatbot is to be implemented based on the model of artificial personality (Dregger, 2023) using a large language model. Methods such as Personality Infusion (Kovacevic, 2024) can be used here. Users should be able to use sliders, for example, to adjust the personality of a chatbot that they subsequently use. Based on the personality setting, the language of the system should vary in order to create the impression of a customizable artificial personality (Dregger, Seifermann & Oberweis, 2024). The users then have to complete two different tasks and evaluate the personality using the questionnaire for measuring artificial personality (Dregger et al., in press). Here, the effects of the customized artificial personality on the user experience are to be examined in more detail. In this context, the similarity hypothesis can be considered, which assumes that people like to interact with social actors who are similar to them, e.g. in their personality. However, this hypothesis is also criticized and it is necessary to examine whether the expectations of a personality are also influenced by the social role independently of the similarity.

Procedure

• Review of the literature on the design and adaptation of personality in conversational agents
• Development of an approach for the adaptation of artificial personality in conversational agents
• Development of an experiment for measurement, e.g. using an LLM-based chatbot
• Conducting the experiment with users
• Evaluation of the experiment using statistical methods

What you bring with you

• You are studying computer science, business informatics, industrial engineering, economics or a comparable course of study
• You are interested in UX and the design of conversational agents
• You enjoy working independently
• Ideally, you have basic knowledge of literature research
• Ideally, you have basic knowledge in the construction of questionnaires
• Ideally, you have basic knowledge of LLM and chatbot development
• You have a very good command of written and spoken German and English
• You have basic knowledge of statistics and relevant software, e.g. R or SPSS
• You are motivated and committed

What we offer you:

• Motivated and competent support is important to us. For us, this includes taking enough time for you and supporting you with helpful feedback.
• You will gain exciting insights into interdisciplinary research topics.
• You can flexibly organize the implementation (working hours, remote)

Please send your application to dregger@fzi.de with your CV and current transcript of records.

Literature

Dregger, A. More than Big Five? Towards Modeling and Defining Artificial Personality for Conversational Agents. Conversations, Oslo, 2023

Dregger, A. (2025). Artificial Personality: Model and Questionnaire Development (unpublished manuscript).

Dregger, A., Seifermann, M., & Oberweis, A. (2024). Language Cues for Expressing Artificial Personality: A Systematic Literature Review for Conversational Agents. Proceedings of the 6th ACM Conference on Conversational User Interfaces, 1-17. https://doi.org/10.1145/3640794.3665559

Kovacevic, N., Boschung, T., Holz, C. Gross, M., & Wampfler, R. (2024). Chatbots with Attitude: Enhancing Chatbot Interactions through Dynamic Personality Infusion, Proceedings of the 6th ACM Conference on Conversational User Interfaces, 1-16. https://doi.org/10.1145/3640794.3665543

Kathrin Janowski, Hannes Ritschel, and Elisabeth André. 2022. Adaptive Artificial Personalities. In The Handbook on Socially Interactive Agents (1st ed.), Birgit Lugrin, Catherine Pelachaud and David Traum (eds.). ACM, New York, NY, USA, 155-194. https://doi.org/10.1145/3563659.3563666

Jiang, G., Xu, M., Zhu, S.-C., Han, W., Zhang, C., & Zhu, Y. (2023). Evaluating and Inducing Personality in Pre-trained Language Models. https://doi.org/10.48550/ arXiv.2206.07550

Sebastian Schneider and Franz Kummert. 2021. comparing Robot and Human guided Personalization: Adaptive Exercise Robots are Perceived as more Competent and Trustworthy. Int J of Soc Robotics 13, 2 (April 2021), 169-185. https://doi.org/10.1007/s12369-020-00629-w

Völkel, S. T. & Kaya, L. (2021). Examining User Preference for Agreeableness in Chatbots. In CUI 2021 - 3rd Conference on Conversational User Interfaces (pp. 1-6). ACM. https://doi.org/10.1145/3469595.3469633

Völkel, S. T., Schödel, R., Buschek, D., Stachl, C., Winterhalter, V., Bühner, M., & Hussmann, H. (2020). Developing a Personality Model for Speech-based Conversational Agents Using the Psycholexical Approach. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-14. https://doi.org/10.1145/3313831.3376210