# Toward Human-Centered AI-Assisted Terminology Work

arXiv: https://arxiv.org/abs/2512.18859 · HTML: https://mlsanity.com/paper/2512.18859/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 101 references that are in the map.
- First posted on arXiv 21 Dec 2025.

## Builds on (most cited first, 16 of 16)

- [Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus](https://mlsanity.com/paper/2104.08758/) (2021)
- [Explainability for Large Language Models: A Survey](https://mlsanity.com/paper/2309.01029/) (2023)
- [Do Llamas Work in English? On the Latent Language of Multilingual Transformers](https://mlsanity.com/paper/2402.10588/) (2024)
- [How do Large Language Models Handle Multilingualism?](https://mlsanity.com/paper/2402.18815/) (2024)
- [Cultural Bias and Cultural Alignment of Large Language Models](https://mlsanity.com/paper/2311.14096/) (2023)
- [Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models](https://mlsanity.com/paper/2304.03738/) (2023)
- [Neural Machine Translation: A Review and Survey](https://mlsanity.com/paper/1912.02047/) (2019)
- [Unintended Impacts of LLM Alignment on Global Representation](https://mlsanity.com/paper/2402.15018/) (2024)
- [GEO: Generative Engine Optimization](https://mlsanity.com/paper/2311.09735/) (2023)
- [The Homogenizing Effect of Large Language Models on Human Expression and Thought](https://mlsanity.com/paper/2508.01491/) (2025)
- [Generative AI Literacy: Twelve Defining Competencies](https://mlsanity.com/paper/2412.12107/) (2024)
- [Information-Guided Identification of Training Data Imprint in (Proprietary) Large Language Models](https://mlsanity.com/paper/2503.12072/) (2025)
- [An Interdisciplinary Approach to Human-Centered Machine Translation](https://mlsanity.com/paper/2506.13468/) (2025)
- [Generative AI Literacy: A Comprehensive Framework for Literacy and Responsible Use](https://mlsanity.com/paper/2504.19038/) (2025)
- [What Generative Artificial Intelligence Means for Terminological Definitions](https://mlsanity.com/paper/2402.16139/) (2024)
- [What is Human-Centeredness in Human-Centered AI? Development of Human-Centeredness Framework and AI Practitioners' Perspectives](https://mlsanity.com/paper/2502.03293/) (2025)

## Built on by (most cited first, 1 of 1)

- [Introducing Human-Centeredness in AI-Assisted Lexicography](https://mlsanity.com/paper/2607.11808/) (2026)

## Abstract (arXiv)

Generative AI is likely to transform terminology work by creating new opportunities for automation. At the same time, it raises concerns about the future of terminologists and terminological resources, as efficiency pressures may encourage excessive automation based on the perception that human expertise can be replaced by AI. However, large language models remain unreliable for terminological purposes due to errors, hallucinations, and various forms of bias, making terminologists indispensable for ensuring the accuracy and reliability of terminological data. This paper argues that human-centered AI, an approach that emphasizes that AI's primary goal should be to contribute to human well-being, provides a framework for maximizing the benefits of generative AI while mitigating its risks. It contends that high levels of automation and meaningful human control are compatible and desirable, and that AI should enhance terminologists' capabilities while preserving their agency and decision-making authority. The implications of AI-assisted terminology work are examined through three interrelated dimensions: the augmented terminologist, ethical AI, and human-centered design. In particular, the paper examines how AI integration reshapes the role of the terminologist, affects professional values and working conditions, requires the management of AI-generated bias, and calls for the design of AI tools around the terminologist's needs. The paper concludes that a human-centered orientation is necessary to ensure that AI strengthens, rather than undermines, the essential role of terminology work in supporting specialized communication and the accurate transmission of knowledge across languages and cultures.