Systems cause representational harm when they misrepresent a group of people in a negative manner.
[6] For example, the model minority stereotype of Asian Americans as highly intelligent and good at mathematics can be damaging professionally and academically.
[6] For example, when searching for "Black-sounding" names versus "white-sounding" ones, some retrieval systems bolster the false perception of criminality by displaying ads for bail-bonding businesses.
[8] A system may shift the representation of a group to be of lower social status, often resulting in a disregard from society.
[6] Misrecognition, or incorrect recognition, can display in many forms, including, but not limited to, erasing and alienating social groups, and denying people the right to self-identify.
[10] Another prevalent example of representational harm is the possibility of stereotypes being encoded in word embeddings, which are trained using a wide range of text.
[12] This could be interpreted as a misrepresentation of computer programming as a profession that is better performed by men, which would be an example of representational harm.