Prompt-Driven ChatGPT Carbon Calculator for Dental Practices: Estimation and Tailored Improvement Strategies
Year: 2026
Type: article
Abstract: INTRODUCTION AND AIMS: This study investigates the feasibility of applying ChatGPT, a generative artificial intelligence (AI) language model, to develop a user-friendly carbon footprint calculator tailored for dental practices. Building on a previously developed Excel-based tool, the research aimed to evaluate ChatGPT's capacity to generate accurate emissions estimates and sustainability recommendations using different prompting strategies. METHODS: Three prompting variants were tested. Variant 1 employed an unstructured request to assess general responses. Variant 2 used structured data entry with predefined emission factors. Variant 3 combined structured input with instructions to rely exclusively on outputs from a previously validated sustainability tool. ChatGPT-generated results were compared with the Excel benchmark, focusing on accuracy, contextual relevance and alignment with peer-reviewed guidance. RESULTS: Unstructured prompts (Variant 1) produced general recommendations of limited contextual relevance. Structured prompts improved both accuracy and specificity. Variant 2 generated tailored outputs using emission factors, while Variant 3 provided detailed, evidence-based recommendations consistent with established literature. Across variants, ChatGPT's carbon footprint estimates were largely comparable to the Excel benchmark, with only minor discrepancies in waste-related emissions. CONCLUSION: Structured prompting significantly enhances ChatGPT's performance in generating reliable carbon footprint data and recommendations for dental practices. When supported by transparent emission factors and credible literature, generative AI tools can increase access to environmental data, support sustainability decision-making and facilitate climate action in clinical contexts. However, limitations remain, including risks of inaccurate outputs ('hallucinations') and regional generalisations. Effective use requires prompt literacy and open access to validated emission factor databases to maximise impact and reliability. CLINICAL RELEVANCE: AI-driven calculators such as ChatGPT can help dental teams without carbon accounting expertise to understand and reduce their environmental impacts, supporting the integration of sustainability into routine clinical practice.
Source: International Dental Journal
Authors: Brett Duane, Paul Ashley, James Larkin
Institutions: Trinity College Dublin, University College London
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,550
OpenAlex ID: W7118076004