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Authors: Ciprian Paduraru 1 ; Rares Cristea 2 and Alin Stefanescu 1 ; 3

Affiliations: 1 Department of Computer Science, University of Bucharest, Romania ; 2 Research Institute of the University of Bucharest, Romania ; 3 Institute for Logic and Data Science, Romania

Keyword(s): AI, Classification, Behaviors, Profiling.

Abstract: Creating employee questionnaires, surveys or evaluation forms for people to understand various aspects such as motivation, improvement opportunities, satisfaction, or even potential cybersecurity risks is a common practice within organizations. These surveys are usually not tailored to the individual and have a set of predetermined questions and answers. The objective of this paper is to design AI agents that are flexible and adaptable in choosing the survey content for each individual according to their personality. The developed framework is open source, generic and can be adapted to many use cases. For the evaluation, we present a real-world use case of detecting potentially inappropriate behavior in the workplace. The results obtained are promising and suggest that the decision algorithms for content selection approaches and personalized surveys via AI agents are similar to a real human resource manager in our use case.

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Paper citation in several formats:
Paduraru, C.; Cristea, R. and Stefanescu, A. (2024). Adaptive Questionnaire Design Using AI Agents for People Profiling. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 633-640. DOI: 10.5220/0012379600003636

@conference{icaart24,
author={Ciprian Paduraru. and Rares Cristea. and Alin Stefanescu.},
title={Adaptive Questionnaire Design Using AI Agents for People Profiling},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={633-640},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012379600003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Adaptive Questionnaire Design Using AI Agents for People Profiling
SN - 978-989-758-680-4
IS - 2184-433X
AU - Paduraru, C.
AU - Cristea, R.
AU - Stefanescu, A.
PY - 2024
SP - 633
EP - 640
DO - 10.5220/0012379600003636
PB - SciTePress

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