Skip to content
#explainable ai Open access

When AI travels through history: digital narratives, visual credibility, and epistemic injustice on the “Chloe VS History” channel

Sep 2026 · Frontiers in Communication · 0 citations · 14 references

Abstract

The emergence of historical channels mediated by artificial intelligence (AI) on social media platforms constitutes an emerging communicative phenomenon that the academic literature in visual communication has not yet addressed in a systematic way. Chloe VS History, a YouTube and TikTok channel, offers a paradigmatic case of this new digital narrative. Based on three consolidated theoretical frameworks: the grammar of visual design by Kress and van Leeuwen, the gatekeeping theory by Shoemaker and Vos, and the concept of epistemic injustice by Fricker, the convergence construct of visual hyperrealism is proposed to name the simultaneous intersection of three conditions: the production of images of technical fidelity indistinguishable from a real record, a distribution environment without institutional verification mechanisms, and a good part of audiences without critical tools to evaluate that content. It is proposed that this convergence could generate a form of new epistemic risk that none of the three frameworks, in isolation, manages to fully capture, and that would help explain how a historical inaccuracy could be perceived as true without encountering any institutional or cognitive barrier. The central problem is not the use of AI in itself, nor the story as content, nor entertainment as a format, but its specific articulation in an ecosystem where visual credibility operates independently of factual fidelity. Ethical implications are derived for the individual production of historical content with AI and for the role of distribution platforms, and the analytical limits of the case are discussed in order to open an empirical research agenda in this emerging field.

Read PDF

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations
#artificial intelligence Conference Open access Jun 2018

The Key Concepts of Ethics of Artificial Intelligence

It is suggested that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.

Ville Vakkuri, P. Abrahamsson · 39 citations · ⚡2

Related blog posts

Microsoft Research Blog Sep 23, 2026

Offloaded inference for real-world physical AI robotics

Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.