Integration of Large Language Models and Digital Twins in the Public Sector
| dc.contributor.author | Sultanow, Eldar | |
| dc.contributor.author | Chircu, Alina | |
| dc.contributor.author | Czarnecki , Christian | |
| dc.contributor.author | Seßler, Matthias | |
| dc.contributor.author | Grum, Marcus | |
| dc.date.accessioned | 2024-12-26T21:10:57Z | |
| dc.date.available | 2024-12-26T21:10:57Z | |
| dc.date.issued | 2025-01-07 | |
| dc.description.abstract | The potential of large language models (LLMs) for generative artificial intelligence that underpin chatbots like ChatGPT, Gemini, or Neuroflash to improve both personal and organizational work processes is enormous. In this paper, we discuss how LLMs could be integrated with another emerging digital technology concept, digital twins, to optimize and automate processes in the public sector. This integration can allow for accurate and detailed modeling of complex systems and interactions within society, and enhance decision-making, policy development and strategic planning through simulation and automation. | |
| dc.format.extent | 10 | |
| dc.identifier.doi | 10.24251/HICSS.2025.844 | |
| dc.identifier.isbn | 978-0-9981331-8-8 | |
| dc.identifier.other | 2a6b920c-74e6-439f-972d-eaf37c11477e | |
| dc.identifier.uri | https://hdl.handle.net/10125/109695 | |
| dc.relation.ispartof | Proceedings of the 58th Hawaii International Conference on System Sciences | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Building Software in a World of Digital Twins | |
| dc.subject | artificial intelligence, digital transformation, digital twin, llm, public sector | |
| dc.title | Integration of Large Language Models and Digital Twins in the Public Sector | |
| dc.type | Conference Paper | |
| dc.type.dcmi | Text | |
| prism.startingpage | 7058 |
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