Navigating Muslim identity in AI systems.
VISMA analyzes how generative AI models represent diverse Muslim cultures. We investigate algorithmic biases in imagery and recommendation feeds to expose patterns of erasure and stereotyping.
Our groups build digital galleries that contrast synthetic outputs with authentic cultural documentation. We propose actionable guidelines to ensure fair, inclusive, and positive representation in media.
VISMA Team
Research & Curatorial Lab
Authentic Lens
Verified cultural data
Experts in algorithmic justice
Our interdisciplinary team of researchers, archivists, and cultural consultants works to dismantle AI biases and promote authentic representation of Muslim identities.
Dr. Amina Al-Farsi
Algorithmic Bias • Muslim Identity
Analyzes how generative models flatten cultural nuance, focusing on the erasure of diverse Muslim visual traditions in training sets.
Marcus Thorne
Dataset Integrity • Visual Metadata
Specializes in reconstructing authentic documentary archives to serve as counter-narratives to synthetic algorithmic hallucinations.
Layla Ibrahim
Cultural Representation • Oral History
Facilitates workshops with diaspora communities to document authentic visual identities and challenge stereotypical AI outputs.
Prof. Kenji Sato
Global Muslim Art • Iconography
Maps the intersection of traditional Islamic art forms and modern digital media, identifying patterns of regional erasure.
Sarah Jenkins
Ontology Design • Bias Detection
Develops taxonomies for AI prompt rectification, ensuring diverse cultural markers are accurately represented in media feeds.
Omar Hassan
Digital Literacy • Bias Awareness
Leads educational initiatives for youth to critically engage with AI-generated imagery and promote inclusive representation.
Join our research initiative?
We host regular audit sessions and workshops to analyze AI datasets and develop fair representation guidelines.