Large language models for digital foundational identity

Large language models (LLMs) represent a groundbreaking development in the artificial intelligence (AI) domain, capable of ingesting textual data and generating coherent text outputs Bommasani et al. (2022). These models have ushered in a transformative era in AI, showcasing their effectiveness across an extensive array of applications. Their remarkable success has been observed in diverse sectors such as healthcare, law, and education Kaddour et al. (2023). Nonetheless, the extent of their impact within the digital identity realm remains underexplored. In light of this, this paper delves into potential use cases for LLMs in the digital identity space, drawing inspiration from the insights gleaned from ID4D reports World Bank (2022), highlighting the specific needs and requirements in this domain.

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Publication Details

Journal
IET conference proceedings.
Published
2025-12-01
DOI
https://doi.org/10.1049/icp.2025.1268
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Large language models for digital foundational identity

Alpay Sabuncuoğlu, C.G. Maple
IET conference proceedings.
Artificial Intelligence in Healthcare and Education
article

Large language models for digital foundational identity

Alpay Sabuncuoğlu, C.G. Maple
article en

Abstract

Large language models (LLMs) represent a groundbreaking development in the artificial intelligence (AI) domain, capable of ingesting textual data and generating coherent text outputs Bommasani et al. (2022). These models have ushered in a transformative era in AI, showcasing their effectiveness across an extensive array of applications. Their remarkable success has been observed in diverse sectors such as healthcare, law, and education Kaddour et al. (2023). Nonetheless, the extent of their impact within the digital identity realm remains underexplored. In light of this, this paper delves into potential use cases for LLMs in the digital identity space, drawing inspiration from the insights gleaned from ID4D reports World Bank (2022), highlighting the specific needs and requirements in this domain.

IET conference proceedings.Vol. 2024(39)
University of Warwick (GB), The Alan Turing Institute (GB)
Openalex Percentile: Top 40%
Artificial Intelligence in Healthcare and Education
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