@inproceedings{
jiang2023empowering,
title={Empowering Domain Experts to Detect Social Bias in Generative {AI} with User-Friendly Interfaces},
author={Roy Jiang and Rafal Kocielnik and Adhithya Prakash Saravanan and Pengrui Han and R. Michael Alvarez and Anima Anandkumar},
booktitle={XAI in Action: Past, Present, and Future Applications},
year={2023},
url={https://openreview.net/forum?id=GL7RDOru1k}
}
Generative AI models have become vastly popular and drive advances in all aspects of the modern economy. Detecting and quantifying the implicit social biases that they inherit in training, such as racial and gendered biases, is a critical first step in avoiding discriminatory outcomes. However, current methods are difficult to use and inflexible, presenting an obstacle for domain experts such as social scientists, ethicists, and gender studies experts. We present two comprehensive open-source bias testing tools (BiasTestGPT for PLMs and BiasTestVQA for VQA models) hosted on HuggingFace to address this challenge. With these tools, we provide intuitive and flexible tools for social bias testing in generative AI models, allowing for unprecedented ease in detecting and quantifying social bias across multiple generative AI models and mediums.
Empowering Domain Experts to Detect Social Bias in Generative AI with User-Friendly Interfaces
Roy Jiang Rafal Kocielnik Adhithya Prakash Saravanan Pengrui Han R. Michael Alvarez Anima Anandkumar