Stereotyping and Bias in the Flickr30K Dataset

In: Proceedings of the Workshop on Multimodal Corpora: Computer vision and language processing (MMC-2016), pages 1–4. Workshop held: 24 May 2016, collocated with LREC 2016, Portorož, Slovenia. Proceedings available at: http://www.lrec-conf.org/proceedings/lrec2016/workshops/ LREC2016Workshop-MCC-2016-proceedings.pdf 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.