16 citations · 16 across the 2 of their papers we have counts for
5 papers
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…
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…
Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI
Mahima Pushkarna, Andrew Zaldivar, Oddur Kjartansson
As research and industry moves towards large-scale models capable of numerous downstream tasks, the complexity of understanding multi-modal datasets that give nuance to models rapi…
Model Cards for Model Reporting
Margaret Mitchell, Simone Wu, Andrew Zaldivar +6
Trained machine learning models are increasingly used to perform high-impact tasks in areas such as law enforcement, medicine, education, and employment. In order to clarify the in…