Stereotyping and Bias in the Flickr30K Dataset
Computation and Language
2016-05-20 v1 Computer Vision and Pattern Recognition
Abstract
An untested assumption behind the crowdsourced descriptions of the images in the Flickr30K dataset (Young et al., 2014) is that they "focus only on the information that can be obtained from the image alone" (Hodosh et al., 2013, p. 859). This paper presents some evidence against this assumption, and provides a list of biases and unwarranted inferences that can be found in the Flickr30K dataset. Finally, it considers methods to find examples of these, and discusses how we should deal with stereotype-driven descriptions in future applications.
Keywords
Cite
@article{arxiv.1605.06083,
title = {Stereotyping and Bias in the Flickr30K Dataset},
author = {Emiel van Miltenburg},
journal= {arXiv preprint arXiv:1605.06083},
year = {2016}
}
Comments
In: Proceedings of the Workshop on Multimodal Corpora (MMC-2016), pages 1-4. Editors: Jens Edlund, Dirk Heylen and Patrizia Paggio