Creating a Controlled Dataset of Environmental Assessment Texts for Generative AI Models: The Danish EA Hub

Relevance and roles of artificial intelligence (AI) within impact assessment (IA) depends on the quality of the data input to the AI model. This paper explores the development of a specialized dataset of environmental assessment (EA) texts for use in generative AI models. By establishing a controlled dataset, we aim to ensure that AI models draw from relevant, high-quality sources, avoiding the pitfalls of using potentially irrelevant or inaccurate online data. Key considerations include quality control, content selection, copyright, ownership, structure, classification, and maintaining up-to-date information. Using the Danish EA Hub as a case study, we outline the steps and considerations involved in creating such a dataset. Finally, we discuss the potential of using this controlled dataset to enhance the capabilities of generative AI in the field of environmental assessment. The results are of significant relevance to actors engaged in the process of or intending to develop AI solutions within IA.

Publication Details

Journal
VBN Forskningsportal (Aalborg Universitet)
Published
2024-10-26
Primary Topic
Environmental and Social Impact Assessments
Type
article
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article

Creating a Controlled Dataset of Environmental Assessment Texts for Generative AI Models: The Danish EA Hub

VBN Forskningsportal (Aalborg Universitet)
Environmental and Social Impact Assessments
article

Creating a Controlled Dataset of Environmental Assessment Texts for Generative AI Models: The Danish EA Hub

article en

Abstract

Relevance and roles of artificial intelligence (AI) within impact assessment (IA) depends on the quality of the data input to the AI model. This paper explores the development of a specialized dataset of environmental assessment (EA) texts for use in generative AI models. By establishing a controlled dataset, we aim to ensure that AI models draw from relevant, high-quality sources, avoiding the pitfalls of using potentially irrelevant or inaccurate online data. Key considerations include quality control, content selection, copyright, ownership, structure, classification, and maintaining up-to-date information. Using the Danish EA Hub as a case study, we outline the steps and considerations involved in creating such a dataset. Finally, we discuss the potential of using this controlled dataset to enhance the capabilities of generative AI in the field of environmental assessment. The results are of significant relevance to actors engaged in the process of or intending to develop AI solutions within IA.

VBN Forskningsportal (Aalborg Universitet)
Life in Land
Openalex Percentile: Top 31%
Environmental and Social Impact Assessments
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