Thursday 27 February 2025
The paper introduces a dataset of industrial guidelines and policy statements for generative artificial intelligence (AI) and large language models (LLMs). These models are revolutionizing industries worldwide, offering innovative tools for content creation, process optimization, and decision-making. However, their rapid adoption has also raised concerns about ethical and safe use, transparency, and the establishment of robust frameworks for AI governance.
The dataset, called IGGA, contains 160 industry guidelines and policy statements from reputable companies across six continents. These guidelines cover a broad range of topics, including data privacy, security, and fairness. The dataset is designed to serve as a valuable resource for natural language processing tasks commonly applied in requirements engineering, such as model synthesis, abstraction identification, and document structure assessment.
The authors’ methodology ensures a thorough examination of reputable companies across various industries. They selected companies that represent diverse global institutions and captured perspectives from 14 industry sectors, including technology, finance, and both public and private institutions. This comprehensive approach provides a broad spectrum of insights into the integration of GAIs and LLMs in industry.
The paper highlights the importance of structured frameworks for AI governance. While many organizations are leveraging GAIs to enhance productivity and innovation, there is a gap in the development of comprehensive guidelines to manage their deployment responsibly. The dataset aims to fill this gap by providing a valuable resource for companies to develop and implement AI policies.
One of the significant challenges in developing AI policies is ensuring transparency and fairness. GAIs can generate content that is difficult to distinguish from human-written text, raising concerns about accountability and responsibility. IGGA addresses this challenge by providing guidelines on data privacy, security, and fairness, which can help companies ensure transparency and accountability in their use of GAIs.
The dataset also highlights the need for continuous innovation in AI governance. As GAIs continue to evolve, companies must adapt their policies to ensure responsible deployment. IGGA serves as a valuable resource for companies to stay ahead of the curve, providing insights into best practices for AI governance and policy development.
In summary, the paper introduces a comprehensive dataset of industrial guidelines and policy statements for generative AI and large language models. The dataset provides valuable insights into the integration of GAIs in industry and highlights the importance of structured frameworks for AI governance. By providing guidelines on transparency, fairness, and accountability, IGGA aims to support companies in their efforts to develop responsible AI policies.
Cite this article: “Industrial Guidelines for Responsible Deployment of Generative Artificial Intelligence and Large Language Models”, The Science Archive, 2025.
Ai Governance, Generative Ai, Large Language Models, Industrial Guidelines, Policy Statements, Data Privacy, Security, Fairness, Accountability, Transparency, Responsible Deployment
