Natural language processing in impact assessment
A review of applications and concerns
Bibliographic Data
| ID | 21154077 |
|---|---|
| Authors | Shiu Fung Hung (University of Liverpool), Pavitra Kumar (0000-0002-4683-724X, Manchester Metropolitan University), Thomas B Fischer (0000-0003-1436-1221, University of Liverpool, corresponding author) |
| Year | 2026 |
| Volume | 44 |
| Issue | 1 |
| Pages | 68-73 |
| Publication date | 2026-01-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Impact Assessment and Project Appraisal (JOURNAL) |
| Journal identifiers | ISSN: 1461-5517 • E-ISSN: 1471-5465 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/14615517.2026.2620186 |
| OpenAlex | W7125497936 |
| Language | EN |
| References cited | 18 |
The rolling out of Artificial Intelligence (AI) applications is extensively discussed among the impact assessment (IA) community. It is in this context that our letter focuses on natural language processing (NLP) applications. We introduce six categories of NLP applications and examine common concerns over their accuracy, quality, and transparency. We emphasize that it is the users’ responsibility to ensure quality and transparency when applying AI. We also suggest that it is time to elevate the discussion on the preparation for further AI use in IA
Language technology · Natural language · Natural language understanding · Employee Welfare and Language Studies · Environmental and Social Impact Assessments · History and advancements in chemistry
Natural language processing
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A survey on sentiment analysis methods, applications, and challenges
Laying the foundation for generative AI and multi-agent systems in environmental assessment
AI in strategic planning and assessment – a game changer in decision-making or a risk for reproduction of hidden biases
Using an Artificial intelligence chatbot to critically review the scientific literature on the use of Artificial intelligence in Environmental Impact Assessment
Large Language Model-assisted EIA screening
Impact assessment in the age of artificial intelligence
Transparency and the Black Box Problem
| Highly cited | No |
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