The Impact of Generative Artificial Intelligence on Terminological Definitions

Core Concepts

Generative Artificial Intelligence (GenAI) tools like ChatGPT can profoundly transform the creation and consumption of terminological definitions, challenging the very existence of terminological resources as we know them.

Abstract

This article examines the impact of Generative Artificial Intelligence (GenAI) tools, particularly ChatGPT, on terminological definitions and the field of terminology work. Key highlights: GenAI tools can enable AI-assisted terminography, notably post-editing terminography, where the machine produces a definition that the terminologist then corrects or refines. This can streamline the definition-writing process. However, GenAI tools can also fulfill all the terminological needs of a user, including term definitions, which challenges the very existence of terminological definitions and resources as we know them. Unlike terminological definitions, GenAI tools can describe the knowledge activated by a term in a specific context. But their output can contain errors, biases, and reliability issues. Definitions with a prescriptive or standardizing orientation, as well as in-text definitions, are less likely to be replaced by AI. The distinction between human-created and AI-created content will become increasingly blurred. Terminologists will need to embrace AI and develop skills for its efficient integration into their workflow, as AI-assisted terminography is set to become synonymous with terminography itself.

Stats

"Positive radiative forcing tends on average to warm the earth's surface; a negative radiative forcing on average tends to cool the earth's surface." (EIA) "The addition of greenhouse gases traps an increased fraction of the infrared radiation, reradiating it back toward the surface and creating a warming influence (i.e., positive radiative forcing because incoming solar radiation will exceed outgoing infra-red radiation)." (EO-NASA) "Radiative forcing is most commonly measured in units of watts per square meter (W/m2)." (Climate CoLab)

Quotes

"ChatGPT can also assist terminologists in their work. Given this enormous potential, we can wonder, as [17] does for Lexicography, whether ChatGPT will replace terminological resources, terminologists, and the tools used for terminology work." "Still another question is if ChatGPT will replace terminological definitions, the terminologists that write them, and the tools used for definition writing."

Key Insights Distilled From

What Generative Artificial Intelligence Means for Terminological Definitions

by Anto... at arxiv.org 04-01-2024

https://arxiv.org/pdf/2402.16139.pdf

Deeper Inquiries

How might the integration of GenAI into terminology work impact the role and skills required of terminologists in the future?

The integration of Generative Artificial Intelligence (GenAI) into terminology work is poised to revolutionize the role of terminologists and the skills they require. With GenAI tools like ChatGPT becoming increasingly sophisticated, terminologists will need to adapt to a more AI-assisted workflow. While GenAI can streamline the process of crafting definitions and enhance productivity, terminologists will need to develop new skills to effectively utilize these tools. Skills such as post-editing terminography, optimizing prompts for AI-generated definitions, and critically evaluating AI-generated content will become essential. Terminologists will also need to focus on higher-level tasks like verifying information, ensuring accuracy, and maintaining the reliability of terminological resources in the face of AI advancements.

What are the potential ethical and legal concerns around the use of GenAI tools in terminological definition writing, and how can they be addressed?

The use of GenAI tools in terminological definition writing raises several ethical and legal concerns. One major issue is the potential for errors, biases, and inaccuracies in AI-generated content, which can impact the reliability of terminological resources. Additionally, there are concerns about plagiarism, copyright infringement, and the unauthorized use of copyrighted materials by AI models like ChatGPT. To address these concerns, terminologists can implement strict verification processes to ensure the accuracy and integrity of AI-generated definitions. They can also provide clear attribution for AI-generated content and adhere to copyright laws when using external sources. Furthermore, establishing guidelines and best practices for the ethical use of GenAI in terminology work can help mitigate these risks and ensure compliance with legal standards.

In what ways could GenAI be leveraged to enhance the flexibility and contextual relevance of terminological definitions beyond the current state-of-the-art?

GenAI offers exciting possibilities for enhancing the flexibility and contextual relevance of terminological definitions beyond the current state-of-the-art. By leveraging GenAI tools like ChatGPT, terminologists can create definitions tailored to specific contexts, user needs, and thematic perspectives with greater efficiency. GenAI can assist in generating multiple definitions for polysemic terms, incorporating definitional templates, and extracting semantic information from existing definitions. Moreover, GenAI can be used to analyze corpus data, provide real-time feedback on definition quality, and suggest enhancements to improve terminological resources. Overall, the integration of GenAI into terminology work opens up new avenues for creating dynamic, contextually rich, and user-centric definitions that cater to diverse linguistic and domain-specific requirements.