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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Artificial intelligence and visual discourse
T2 - a multimodal critical discourse analysis of AI-generated images of “Dementia”
AU - Putland, Emma
AU - Chikodzore-Paterson, Chris
AU - Brookes, Gavin
PY - 2025/4/30
Y1 - 2025/4/30
N2 - This article examines the ideologies reproduced in AI-generated images, focusing in particular on representations of dementia. Utilising Stable Diffusion version 1.4, a text-to-image AI model, we conduct a multimodal critical discourse analysis of 171 images generated from the text prompt “dementia.” Our analysis aims to identify and contextualise the visual discourses within the generated images by comparing these with existing multimodal representations of dementia. As well as observing a general lack of visual diversity (with an over-representation of older, light-skinned individuals), we find that these images tend to depict dementia by recycling existing, prominent visual discourses surrounding the syndrome, including a biomedical focus on the disease, narratives of loss, and dementia as a “living death.” These visual discourses combine with particular semiotic choices that promote emotional distance between viewers and people with dementia. Overall, this study highlights the potential for AI-generated images to reinforce and amplify harmful stereotypes and biases. As well as demonstrating the ideological import of such imagery, and thus the need for these to be critically interrogated by (multimodal) critical discourse analysts, this study underscores the need for ethical consideration in AI design and usage, including developing more diverse and inclusive training datasets.
AB - This article examines the ideologies reproduced in AI-generated images, focusing in particular on representations of dementia. Utilising Stable Diffusion version 1.4, a text-to-image AI model, we conduct a multimodal critical discourse analysis of 171 images generated from the text prompt “dementia.” Our analysis aims to identify and contextualise the visual discourses within the generated images by comparing these with existing multimodal representations of dementia. As well as observing a general lack of visual diversity (with an over-representation of older, light-skinned individuals), we find that these images tend to depict dementia by recycling existing, prominent visual discourses surrounding the syndrome, including a biomedical focus on the disease, narratives of loss, and dementia as a “living death.” These visual discourses combine with particular semiotic choices that promote emotional distance between viewers and people with dementia. Overall, this study highlights the potential for AI-generated images to reinforce and amplify harmful stereotypes and biases. As well as demonstrating the ideological import of such imagery, and thus the need for these to be critically interrogated by (multimodal) critical discourse analysts, this study underscores the need for ethical consideration in AI design and usage, including developing more diverse and inclusive training datasets.
KW - Dementia
KW - AI-generated images
KW - multimodal critical discourse analysis
U2 - 10.1080/10350330.2023.2290555
DO - 10.1080/10350330.2023.2290555
M3 - Journal article
VL - 35
SP - 228
EP - 253
JO - Social Semiotics
JF - Social Semiotics
SN - 1035-0330
IS - 2
ER -