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Artificial Intelligence Tools and Bias in Journalism-related Content Generation: Comparison Between Chat GPT-3.5, GPT-4 and Bing

Autores

CASTILLO CAMPOS, MAR, VARONA ARAMBURU, DAVID, BECERRA ALONSO, DAVID

Publicación externa

No

Medio

Tripodos

Alcance

Article

Naturaleza

Científica

Cuartil JCR

Cuartil SJR

Fecha de publicacion

01/01/2024

ISI

001335097200005

Scopus Id

2-s2.0-85199539431

Abstract

This study explores the biases present in artificial intelligence (AI) tools, focusing on GPT-3.5, GPT-4, and Bing. The performance of the tools has been compared with a group of experts in linguistics, and journalists specialized in breaking news and international affairs. It reveals that GPT-3.5, widely accessible and free, exhibits a higher tendency rate in its word generation, suggesting an intrinsic bias within the tool itself rather than in the input data. Comparatively, GPT-4 and Bing demonstrate differing patterns in term generation and subjectivity, with GPT-4 aligning more closely with expert opinions and producing fewer opinative words. The research highlights the extensive use of generative AI in media and among the general populace, emphasizing the need for careful reliance on AI-generated content. The findings stress the risks of misinformation and biased reporting inherent in unexamined AI outputs. The challenge for journalists and information professionals is to ensure accuracy and ethical judgment in content creation to maintain the quality and diversity of content in journalistic practices. © 2024 Blanquerna School of Communication and International Relations. All rights reserved.

Palabras clave

chat GPT; computational communication; media bias; natural language; NLP

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