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AI used to make 'fetishised' images of disabled women
British charities highlight the exploitation and deception of AI-generated sexualized images of disabled women, with some videos reaching millions of views on social media platforms.
- British charities and disability advocates have condemned an "alarming trend" of using artificial intelligence to generate sexualized images of women with Down syndrome, vitiligo, and albinism, noting many images lack AI-generated labels.
- Higgsfield, a platform for generating virtual models, offers creators options to add scars, burns, and albinism to avatars. Emanuel Maiberg of 404 Media noted that "outrageous, novel or weird" content drives higher engagement.
- Kamran Mallick, CEO of Disability Rights UK, called the images "exploitation" recalling "historical freak shows of people being wheeled out for the amusement of others." Dr. Aisha Sobey, a University of Cambridge researcher, added the images show "very fetishised bodies" and "very sexual content."
- The Vitiligo Society warned that portraying AI-generated individuals as authentic community members constitutes "misinformation," while the British Down's Syndrome Association called the trend "potentially offensive and hurtful" to those with Down syndrome.
- Real influencers Kayla Ludlow and Mio criticized the AI models for lacking personality and authenticity. Ludlow, who has 857,000 followers on TikTok, said the content "especially with the AI model content, that just seems like it's a fetish.
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These manufactured content include trisomy 21, vitiligo or albinism. Influents affected by this latter condition report being subject to "fetching".
·Paris, France
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Daily Journal+31 Reposted by 31 other sources
AI used to make 'fetishised' images of disabled women
British charities and disability advocates have slammed a trend for using AI to generate "fetishised" images of women with disabilities and genetic conditions including Down syndrome, vitiligo and albinism.
·Cherokee County, United States
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Total News Sources39
Leaning Left5Leaning Right8Center9Last UpdatedBias Distribution41% Center
Bias Distribution
- 41% of the sources are Center
41% Center
L 23%
C 41%
R 36%
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