AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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2025
Michael, R.; Kutza, J. -O.; Werth, P.; Liebe, J. -D.; Schöning, J.
Simulating Vulnerability: An Examination of Ethical, Legal and Social Aspects in the Context of Training Child Protection Workers Proceedings Article
In: Cheong, M.; Herkert, J.; Zhu, Q.; Love, H. A. (Ed.): Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331532284 (ISBN).
Abstract | Links | BibTeX | Tags: and social aspect), Artificial intelligence, artificial intelligence (AI), Case files, Child Protection, Child protections, Ethical, Ethical aspects, Information Management, Language Model, Large language model, large language model (LLM), Laws and legislation, Legal, Personnel training, Social aspect (ethical, Social aspects, Social Aspects (ELSA), Virtual Reality, Virtual Reality (VR) Training, Virtual reality training, Workers'
@inproceedings{michael_simulating_2025,
title = {Simulating Vulnerability: An Examination of Ethical, Legal and Social Aspects in the Context of Training Child Protection Workers},
author = {R. Michael and J. -O. Kutza and P. Werth and J. -D. Liebe and J. Schöning},
editor = {M. Cheong and J. Herkert and Q. Zhu and H. A. Love},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105014522871&doi=10.1109%2FETHICS65148.2025.11098302&partnerID=40&md5=c5cba2cca188ceb263701952c2f386ea},
doi = {10.1109/ETHICS65148.2025.11098302},
isbn = {9798331532284 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The success of artificial intelligence (AI), particularly large language models (LLMs), has led to innovative applications and numerous attempts to find a use for this tool in different fields. One of these fields is in the work fielded by child protection offices. The AId4Children project investigates the use of AI-generated virtual reality (VR) training environments for child protection workers. This VR training application simulates home visits and is generated on synthetically constructed cases of child abuse and neglect that are based on real case files. Using real case files for AI-based generation of VR training raises several ethical, legal, and social aspects (ELSA) and questions. One question Q1) is how to acquire and create an open data set on child endangerment case files. A second question Q2) is how to represent the vulnerable characters in VR respectfully. A third question Q3) is if the use of AI, incl. LLM within the context of child abuse and neglect is acceptable at all. This paper will discuss and provide the first answers to the considerations on ELSA raised by the explorative concept development of this VR training application. © 2025 Elsevier B.V., All rights reserved.},
keywords = {and social aspect), Artificial intelligence, artificial intelligence (AI), Case files, Child Protection, Child protections, Ethical, Ethical aspects, Information Management, Language Model, Large language model, large language model (LLM), Laws and legislation, Legal, Personnel training, Social aspect (ethical, Social aspects, Social Aspects (ELSA), Virtual Reality, Virtual Reality (VR) Training, Virtual reality training, Workers'},
pubstate = {published},
tppubtype = {inproceedings}
}
Sabir, A.; Hussain, R.; Pedro, A.; Park, C.
Personalized construction safety training system using conversational AI in virtual reality Journal Article
In: Automation in Construction, vol. 175, 2025, ISSN: 09265805 (ISSN), (Publisher: Elsevier B.V.).
Abstract | Links | BibTeX | Tags: Construction safety, Construction safety training, Conversational AI, Digital elevation model, Helmet mounted displays, Language Model, Large language model, large language models, Personalized safety training, Personnel training, Safety training, Training Systems, Virtual environments, Virtual Reality, Workers'
@article{sabir_personalized_2025,
title = {Personalized construction safety training system using conversational AI in virtual reality},
author = {A. Sabir and R. Hussain and A. Pedro and C. Park},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002741042&doi=10.1016%2Fj.autcon.2025.106207&partnerID=40&md5=b071b04c835e74758e168f5c19da8271},
doi = {10.1016/j.autcon.2025.106207},
issn = {09265805 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Automation in Construction},
volume = {175},
abstract = {Training workers in safety protocols is crucial for mitigating job site hazards, yet traditional methods often fall short. This paper explores integrating virtual reality (VR) and large language models (LLMs) into iSafeTrainer, an AI-powered safety training system. The system allows trainees to engage with trade-specific content tailored to their expertise level in a third-person perspective in a non-immersive desktop virtual environment, eliminating the need for head-mounted displays. An experimental study evaluated the system through qualitative, survey-based assessments, focusing on user satisfaction, experience, engagement, guidance, and confidence. Results showed high satisfaction rates (>85 %) among novice users, with improved safety knowledge. Expert users suggested advanced scenarios, highlighting the system's potential for expansion. The modular architecture supports customization across various construction settings, ensuring adaptability for future improvements. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Elsevier B.V.},
keywords = {Construction safety, Construction safety training, Conversational AI, Digital elevation model, Helmet mounted displays, Language Model, Large language model, large language models, Personalized safety training, Personnel training, Safety training, Training Systems, Virtual environments, Virtual Reality, Workers'},
pubstate = {published},
tppubtype = {article}
}