Humane Intelligence launched the second set of bias bounty challenges, in partnership with Revontulet, a human-centric company that provides intelligence and analysis to help clients around the globe mitigate risk and prevent harm caused by terrorism and violent extremism. This challenge was focused on developing computer vision models capable of detecting, extracting, and interpreting hateful image-based propaganda content often manipulated to evade detection on social media platforms. Centering on far-right extremist groups in Europe, the Nordic region, and beyond and the rise of AI-generated content, the goal was to train a CV model to understand the ways in which hateful image-propaganda can be disguised and manipulated to evade detection on social media platforms.
The Winners
Task: build an unsupervised model that can identify extremist content from the unlabelled sample image dataset provided.
Prizes
$4000 split evenly among the three winners
Task: Building on top of the intermediate challenge, the task is to create adversarial examples to test the robustness of your unsupervised model.
Prizes
$6000 split evenly among the three winners