# Identity interweaving, act boundaries, illusion and reality interweaving: A study of visual narratives of scientists and citizen scientists through AI

## TL;DR

This study explores how AI influences visual storytelling in science, comparing scientists and citizen scientists through three narrative dimensions.

## Contribution

It introduces a new method combining computer vision and quantitative analysis to study AI's impact on scientific visual narratives.

## Key findings

- Both scientists and citizen scientists show a mix of authority and closeness in narrative visuals.
- AI portrays scientists as professionals and citizen scientists as practical actors.
- Scientists' stories include surreal visuals, while citizen scientists focus on everyday themes.

## Abstract

The rise of generative artificial intelligence (AI) is transforming human-computer interaction, reshaping communication methods and altering public perceptions of science. This shift challenges traditional scientific authority, especially as citizen science gains prominence. While research on scientific rhetoric has focused on qualitative analyses in media, little attention has been given to how AI influences visual rhetorical narratives in science. This study employs computer visual analysis and quantitative rhetorical difference analysis to explore the intersection of AI and science through Visual Narrative Theory.It investigates the rhetorical differences between scientists and citizen scientists across three dimensions: narrate, act, and resonate. Findings reveal that both groups embody a mixed rhetoric of authority and proximity in the narrative dimension. In the act dimension, AI depicts scientists in professional roles while showing citizen scientists in practical roles, portraying scientists as “flowers in the greenhouse”. In the resonate dimension, scientists’ narratives often feature surreal elements, while citizen scientists present more everyday narratives.This analysis, utilizing computer vision and quantitative methods, offers a fresh perspective on the image of science in the AI era and suggests strategies for enhancing science communication and building trust in science using generative AI.