•  
  •  
 

SMU Data Science Review

Abstract

Abstract. This paper aims to present a comparative analysis of a custom-built AI Journalist Assistant and ChatGPT 4.0 for news article generation. The goal is to evaluate the performance of each model based on accuracy, speed, ethical safeguards, and relevance, particularly in the context of journalism. While ChatGPT is widely used for general-purpose content creation, its reliance on older data and potential for plagiarism presents challenges in the fast-paced, high-stakes world of news reporting. To address these issues, we will design and implement an AI Assistant using Retrieval-Augmented Generation (RAG) techniques, focusing on real-time data access, bias reduction, and plagiarism prevention. By comparing both models through established metrics such as BERTScore, precision, recall, and inference time, this paper contributes insights into the role of specialized AI tools in journalistic workflows and highlights the trade-offs between prompt engineering and domain-specific AI development. The findings will guide future advancements in AI-generated news and its ethical implications.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Download

Included in

Data Science Commons

Share

COinS