Evidence map›Paper›PMID 39834878›Full record

ArticleFrontiers in artificial intelligence2024

Evaluating the role of generative AI and color patterns in the dissemination of war imagery and disinformation on social media.

Estibaliz García-Huete, Sara Ignacio-Cerrato, David Pacios, José Luis Vázquez-Poletti, María José Pérez-Serrano, Andrea Donofrio, Clemente Cesarano, Nikolaos Schetakis, Alessio Di Iorio

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Estibaliz García-HueteDepartment of Journalism and Global Communication, Faculty of Information Sciences, Universidad Complutense de Madrid, Madrid, Spain.
Sara Ignacio-CerratoOptics Department, Faculty of Optics and Optometry, Universidad Complutense de Madrid, Madrid, Spain.
David PaciosDepartment of Computer Architecture and Automation, Faculty of Informatics, Universidad Complutense de Madrid, Madrid, Spain.
José Luis Vázquez-PolettiDepartment of Computer Architecture and Automation, Faculty of Informatics, Universidad Complutense de Madrid, Madrid, Spain.
María José Pérez-SerranoDepartment of Journalism and Global Communication, Faculty of Information Sciences, Universidad Complutense de Madrid, Madrid, Spain.
Andrea DonofrioDepartment of Journalism and Global Communication, Faculty of Information Sciences, Universidad Complutense de Madrid, Madrid, Spain.
Clemente CesaranoSection of Mathematics, International Telematic University Uninettuno, Rome, Italy.
Nikolaos SchetakisComputational Mechanics and Optimization Laboratory, School of Production Engineering and Management, Technical University of Crete, Chania, Greece.
Alessio Di IorioAlma Sistemi Srl, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explores the evolving role of social media in the spread of misinformation during the Ukraine-Russia conflict, with a focus on how artificial intelligence (AI) contributes to the creation of deceptive war imagery. Specifically, the research examines the relationship between color patterns (LUTs) in war-related visuals and their perceived authenticity, highlighting the economic, political, and social ramifications of such manipulative practices. AI technologies have significantly advanced the production of highly convincing, yet artificial, war imagery, blurring the line between fact and fiction. An experimental project is proposed to train a generative AI model capable of creating war imagery that mimics real-life footage. By analyzing the success of this experiment, the study aims to establish a link between specific color patterns and the likelihood of images being perceived as authentic. This could shed light on the mechanics of visual misinformation and manipulation. Additionally, the research investigates the potential of a serverless AI framework to advance both the generation and detection of fake news, marking a pivotal step in the fight against digital misinformation. Ultimately, the study seeks to contribute to ongoing debates on the ethical implications of AI in information manipulation and to propose strategies to combat these challenges in the digital era.

Indexed as

color patternsdisinformationfake newsgenerative AIinformation manipulationLUTssocial mediawar imagery

Identifiers

PMID39834878
PMCPMC11743509

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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.