ArticleScientific reports2024
Bias of AI-generated content: an examination of news produced by large language models.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- Artificial intelligence in contact sports research: Promise and peril for predicting and preventing brain injury.Experimental physiology · 2026Article
- Culturally-Aware Prompting in conversational AI: supporting perceived communicative effectiveness in cross-cultural teams in Australia.Scientific reports · 2026Article
- Measuring stereotype and deviation biases in large language models.Scientific reports · 2026Article
- AI literacy and school tier moderate educators' ethical coping mechanisms through sedative and reverse Matthew effects.Scientific reports · 2026Article
- Biased AI writing assistants shift users' attitudes on societal issues.Science advances · 2026Article
- LLMs Can Fuel Extremist Attitudes Using Universal Moral Framings.Annals of the New York Academy of Sciences · 2026Article
- Evaluating AI-Generated Geriatric Case Studies for Interprofessional Education: Systematic Analysis Across 5 Platforms.JMIR medical education · 2026Article
- Intersectional biases in narratives produced by open-ended prompting of generative language models.Nature communications · 2026Article
- AI and social science: Automatic classification tools for big data analysis in sociological research.PloS one · 2026Article
- A systematic pipeline for diagnosing and reducing gender-stereotype bias in Japanese PLMs for sentiment analysis.Frontiers in artificial intelligence · 2026Article
- Using Artificial Intelligence for Scholarly Writing.The American journal of nursing · 2025Article
- Unequal Scientific Recognition in the Age of LLMs.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2025Article
- Impact of YouTube User-Generated Content on News Dissemination and Youth Information Reception.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Participatory Design Approach in the Use of Scenario Analysis for Futureproofing Medical Education: Case Study.Journal of medical Internet research · 2025Article
- Large Language Models' Clinical Decision-Making on When to Perform a Kidney Biopsy: Comparative Study.Journal of medical Internet research · 2025Article
- Challenges of Implementing LLMs in Clinical Practice: Perspectives.Journal of clinical medicine · 2025Article
- Improving large language models accuracy for aortic stenosis treatment via Heart Team simulation: a prompt design analysis.European heart journal. Digital health · 2025Article
- Facial Analysis for Plastic Surgery in the Era of Artificial Intelligence: A Comparative Evaluation of Multimodal Large Language Models.Journal of clinical medicine · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) have the potential to transform our lives and work through the content they generate, known as AI-Generated Content (AIGC). To harness this transformation, we need to understand the limitations of LLMs. Here, we investigate the bias of AIGC produced by seven representative LLMs, including ChatGPT and LLaMA. We collect news articles from The New York Times and Reuters, both known for their dedication to provide unbiased news. We then apply each examined LLM to generate news content with headlines of these news articles as prompts, and evaluate the gender and racial biases of the AIGC produced by the LLM by comparing the AIGC and the original news articles. We further analyze the gender bias of each LLM under biased prompts by adding gender-biased messages to prompts constructed from these news headlines. Our study reveals that the AIGC produced by each examined LLM demonstrates substantial gender and racial biases. Moreover, the AIGC generated by each LLM exhibits notable discrimination against females and individuals of the Black race. Among the LLMs, the AIGC generated by ChatGPT demonstrates the lowest level of bias, and ChatGPT is the sole model capable of declining content generation when provided with biased prompts.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.