6 papers
Going PLACES: Participatory Localized Red Teaming for Text-to-Image Safety in the Global South
Charvi Rastogi, Mukul Bhutani, Minsuk Kahng +13
Despite the global deployment of text-to-image (T2I) models, their safety frameworks are largely calibrated to a Western-centric default, creating significant vulnerabilities for t…
A Unified Framework to Quantify Cultural Intelligence of AI
Sunipa Dev, Vinodkumar Prabhakaran, Rutledge Chin Feman +16
As generative AI technologies are increasingly being launched across the globe, assessing their competence to operate in different cultural contexts is exigently becoming a priorit…
SAFARI: A Community-Engaged Approach and Dataset of Stereotype Resources in the Sub-Saharan African Context
Aishwarya Verma, Laud Ammah, Olivia Nercy Ndlovu Lucas +3
Stereotype repositories are critical to assess generative AI model safety, but currently lack adequate global coverage. It is imperative to prioritize targeted expansion, strategic…
Cultural Compass: A Framework for Organizing Societal Norms to Detect Violations in Human-AI Conversations
Myra Cheng, Vinodkumar Prabhakaran, Alice Oh +5
Generative AI models ought to be useful and safe across cross-cultural contexts. One critical step toward this goal is understanding how AI models adhere to sociocultural norms. Wh…
Scaling Cultural Resources for Improving Generative Models
Hayk Stepanyan, Aishwarya Verma, Andrew Zaldivar +5
Generative models are known to have reduced performance in different global cultural contexts and languages. While continual data updates have been commonly conducted to improve ov…
Amplify Initiative: Building A Localized Data Platform for Globalized AI
Qazi Mamunur Rashid, Erin van Liemt, Tiffany Shih +19
Current AI models often fail to account for local context and language, given the predominance of English and Western internet content in their training data. This hinders the glob…