TLDR: A new report by the Center for the Study of Organized Hate (CSOH) reveals the alarming rise of AI-generated imagery being weaponized to spread anti-Muslim hate across social media platforms in India. The study, covering May 2023 to May 2025, analyzed over 1,300 hateful posts, highlighting themes like sexualization of Muslim women, dehumanization, and conspiracy theories. Despite widespread reporting, social media platforms have failed to remove this content, prompting urgent calls for stronger regulations and developer accountability.
A groundbreaking report from the Center for the Study of Organized Hate (CSOH), published on September 29, 2025, exposes the escalating threat of AI-generated imagery in propagating Islamophobia across India’s digital landscape. The study, titled ‘AI-Generated Imagery and the New Frontier of Islamophobia in India,’ details how generative AI tools such as Midjourney, Stable Diffusion, and DALL·E are being weaponized to create and disseminate anti-Muslim visual hate at an unprecedented scale.
The report analyzed a dataset of 1,326 publicly available AI-generated images and videos, retrieved from 297 public accounts across X (formerly Twitter), Facebook, and Instagram between May 2023 and May 2025. While activity was minimal in 2023 and early 2024, a sharp increase was observed from mid-2024 onwards, coinciding with the growing popularity and accessibility of AI tools. The study found that Instagram emerged as the most effective amplifier of this hate, driving 1.8 million interactions across 462 posts. X recorded 772.4 thousand interactions from 509 posts, and Facebook saw 143.2 thousand interactions from 355 posts. The total recorded engagement across the analyzed content reached a staggering 27.3 million interactions.
CSOH researchers identified four dominant themes in the AI-generated hateful content:
1. Sexualization of Muslim Women: This category received the highest engagement, with 6.7 million interactions, underscoring the gendered nature of much Islamophobic propaganda that fuses misogyny with anti-Muslim hate.
2. Exclusionary and Dehumanizing Rhetoric: Images in this category suggested or encouraged violence against Muslims, often using animal imagery (e.g., depicting Muslims as snakes wearing skullcaps) to portray them as deceptive, dangerous, and deserving of elimination.
3. Conspiratorial Narratives: AI-generated imagery widely reinforced conspiracy theories such as ‘Love Jihad,’ ‘Population Jihad,’ and ‘Rail Jihad,’ framing Muslims as a perpetual threat to Hindu society and national security.
4. Aestheticization of Violent Imagery: Stylized and animated AI aesthetics, including Studio Ghibli–style imagery, were used to make violent, hateful content appear palatable and even humorous, broadening its reach among younger audiences.
The report highlights that Hindu nationalist media outlets, including OpIndia, Sudarshan News, and Panchjanya, played a central role in producing and amplifying this synthetic hate, thereby embedding AI-generated Islamophobia into mainstream discourse. A critical finding was the failure of social media platforms to act: out of 187 posts reported for violating community guidelines, none were removed, exposing a significant gap in content moderation and policy enforcement.
This phenomenon is particularly concerning in India, a country with an estimated 900 million internet users and a history of anti-Muslim sentiment increasingly visible across political discourse and digital platforms. Previous CSOH reports have documented the extensive use of social media for hate speech, with 995 out of 1,165 hate speech events recorded in 2024 originating on social media. The report also draws parallels with global trends, noting the rise of ‘slopaganda’—the deliberate use of cheap, abundant, and low-veracity synthetic content to seed hate—in Western Europe and the proliferation of misogynistic deepfakes in Australia.
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In response to these alarming findings, CSOH has issued a series of recommendations for stakeholders, including platforms, civil society organizations, and lawmakers. These include implementing targeted legal provisions for AI-generated content, specifying adjudicatory authorities, ensuring developer safety and transparency, building provenance-first defaults into AI tools, establishing standards for AI use in media, creating open-source research databases, demanding algorithmic transparency and independent audits, fostering cross-platform early warning systems, and introducing ‘friction’ protocols to thwart the spread of viral synthetic hate.
