After confronting the limitations of data collection in exploring my own identity—and later encountering the biases embedded in computer vision models—I created Salaf (Ancestors). It's a dataset of approximately 6,000 colonial archival photographs from which I used an AI segmentation technique (as shown in my first post) to detect and remove the human subjects. This process was a conscious inversion of technology's usual function, highlighting both the erasure of my ancestors' collective memory and AI's reductionist tendencies.
I built what I call an "absent dataset". While Artificial Intelligence is often used to imagine the future, Salaf employs AI to interrogate the past. Salaf serves as a dataset designed to train AI on empty images and resists the reproduction of orientalist narratives, offering a method to disrupt AI's role in amplifying historical distortions.