sections/bias.md

Due to the gender bias in data, gender identification by an image captioning model suffers. Also, the gender-activity bias, owing to the word-by-word prediction, influences other words in the caption prediction, resulting in the well-known problem of label bias.

One of the reasons why we chose Conceptual 12M over COCO captioning dataset for training our Multi-lingual Image Captioning model was that in former all named entities of type Person were substituted by a special token <PERSON>. Because of this, the gendered terms in our captions became quite infrequent. We'll present a few captions from our model to analyse how our model performed on different images on which different pre-trained image captioning model usually gives gender prediction biases