IGGA: A Dataset of Industrial Guidelines and Policy Statements for Generative AIs

• URL: http://arxiv.org/abs/2501.00959v2
• Date: Fri, 03 Jan 2025 19:17:56 GMT
• Title: IGGA: A Dataset of Industrial Guidelines and Policy Statements for Generative AIs
• Authors: Junfeng Jiao, Saleh Afroogh, Kevin Chen, David Atkinson, Amit Dhurandhar,
• Abstract summary: This paper introduces IGGA, a dataset of 160 industry guidelines and policy statements for the use of Generative AIs (GAIs) and Large Language Models (LLMs) in industry and workplace settings. The dataset contains 104,565 words and serves as a valuable resource for natural language processing tasks commonly applied in requirements engineering.
• Score: 8.420666056013685
• License:
• Abstract: This paper introduces IGGA, a dataset of 160 industry guidelines and policy statements for the use of Generative AIs (GAIs) and Large Language Models (LLMs) in industry and workplace settings, collected from official company websites, and trustworthy news sources. The dataset contains 104,565 words and serves as a valuable resource for natural language processing tasks commonly applied in requirements engineering, such as model synthesis, abstraction identification, and document structure assessment. Additionally, IGGA can be further annotated to function as a benchmark for various tasks, including ambiguity detection, requirements categorization, and the identification of equivalent requirements. Our methodologically rigorous approach ensured a thorough examination, with a selection of reputable and influential companies that represent a diverse range of global institutions across six continents. The dataset captures perspectives from fourteen industry sectors, including technology, finance, and both public and private institutions, offering a broad spectrum of insights into the integration of GAIs and LLMs in industry.

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