Language discrepancies in the performance of generative artificial intelligence models: an examination of infectious disease queries in English and Arabic
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) models perform better in English than Arabic for infectious disease queries, highlighting a disparity that could affect Arabic speakers' access to accurate health information. Addressing this gap is crucial for equitable AI in healthcare.
Area Of Science
- Medical Informatics
- Artificial Intelligence in Healthcare
- Natural Language Processing
Background
- Equitable access to accurate health information across languages is essential.
- Artificial intelligence (AI) models require cross-lingual assessment for global applicability.
- This study focuses on comparing AI model performance for infectious disease queries in English and Arabic.
Purpose Of The Study
- To compare the efficiency of AI models (ChatGPT-3.5, ChatGPT-4, Bing, Bard) in English versus Arabic for infectious disease information.
- To evaluate AI-generated health content for accuracy, completeness, and relevance across languages.
- To identify potential disparities in AI performance that could impact health equity.
Main Methods
- Utilized the METRICS checklist for AI study design and reporting.
- Tested four AI models (ChatGPT-3.5, ChatGPT-4, Bing, Bard) with 15 infectious disease queries (HIV/AIDS, tuberculosis, malaria, COVID-19, influenza).
- Assessed AI-generated content using the validated CLEAR tool by two bilingual experts.
Main Results
- AI models demonstrated superior performance in English compared to Arabic for infectious disease queries.
- Bard, Bing, ChatGPT-4, and ChatGPT-3.5 showed decreasing performance in English (P=.012).
- English responses were rated "excellent" versus "above-average" for Arabic (P=.002), with significant differences in completeness, accuracy, appropriateness, and relevance.
Conclusions
- A notable disparity exists in AI model performance between English and Arabic for infectious disease queries.
- This language-based performance gap may compromise the quality of AI-delivered health information for Arabic speakers.
- AI developers should address these disparities to ensure equitable health outcomes globally.
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