Human asymmetries in AI art: Syntax and writing direction effects on agent position in AI-generated images
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F25%3A10513559" target="_blank" >RIV/00216208:11210/25:10513559 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=zULpz7A1le" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=zULpz7A1le</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pone.0326729" target="_blank" >10.1371/journal.pone.0326729</a>
Alternative languages
Result language
angličtina
Original language name
Human asymmetries in AI art: Syntax and writing direction effects on agent position in AI-generated images
Original language description
The present study investigates positional patterns in visual representations generated by two artificial intelligence (AI) models in response to textual prompts describing interactions between two animate entities. The primary objective is to assess whether the syntactic structure of a given sentence influences the spatial positioning of the agent (i.e., the entity performing the action) within the generated image. The study follows research showing that in art produced by humans, positioning of agents on the picture depends on reading-writing direction: entities mentioned first are positioned on the left side by people from cultures with left-to-right writing script disproportionately more often than on the right side. We prompted FLUX and DALL & sdot;E 3 with 20 English sentences, 10 passive and 10 active ones, and generated 4,000 pictures in total. In active sentences, FLUX positioned the agent to the left side of the picture significantly more often than to the right side.In passive sentences, both models positioned the agent to the right significantly more often than to the left. In general, DALL & sdot;E 3 placed agents to the right more often than FLUX. The models partially copied the tendencies of humans in active sentences conditions, however, in passive sentences conditions, the models had a much stronger tendency to place agents to the right than did humans.Our study demonstrates that these AI models, primarily influenced by English language patterns, may be replicating and even amplifying Western (English-specific) spatial biases, potentially diminishing the diversity of visual representation influenced by other languages and cultures. This has consequences for the visual landscape around us: AI pictorial art is overflowing our visual space and the information that we have imprinted into pictures as intrinsically human is changing.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
60203 - Linguistics
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
PLoS One
ISSN
1932-6203
e-ISSN
1932-6203
Volume of the periodical
20
Issue of the periodical within the volume
11
Country of publishing house
US - UNITED STATES
Number of pages
19
Pages from-to
e0326729
UT code for WoS article
001617540500008
EID of the result in the Scopus database
2-s2.0-105022222468