This research examines AI models (OpenAI GPT-4 and Google Gemini 1.5 Flash) used to access Italian news across genres, focusing on the quality of information and sources (RQ1) and the models’ ability to provide correct links for users to verify and explore the news (RQ2). A custom GPT based on the Whittaker Grid serves as an experimental tool for evaluating the models’ sources. The debate on generative AI’s role in news reveals new biases from content-blocking by outlets, causing second-level distortions via copyright limits. Findings show robots.txt files widely restrict AI access, impacting reliability, while ChatGPT performances rate higher than Gemini ones.

Bad news: AI-LLMs and digital traces in journalism, the bias of copyright protection

Viviana Condorelli
Primo
;
Fiorenza Beluzzi
Secondo
2025-01-01

Abstract

This research examines AI models (OpenAI GPT-4 and Google Gemini 1.5 Flash) used to access Italian news across genres, focusing on the quality of information and sources (RQ1) and the models’ ability to provide correct links for users to verify and explore the news (RQ2). A custom GPT based on the Whittaker Grid serves as an experimental tool for evaluating the models’ sources. The debate on generative AI’s role in news reveals new biases from content-blocking by outlets, causing second-level distortions via copyright limits. Findings show robots.txt files widely restrict AI access, impacting reliability, while ChatGPT performances rate higher than Gemini ones.
2025
AI-LMM bias, Copyright protection, Media outlets and information quality, AI and journalism, Custom GPT
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/687515
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact