Social Biases in NLP Models as Barriers for Persons with Disabilities
Table 1: Example toxicity scores from Perspective API.
['Sentence', 'Toxicity']
This paper focuses on the representation of persons with disabilities through the lens of technology. In addition, since text classifiers are trained on large datasets, the biases they exhibit may be indicative of societal perceptions of persons with disabilities Caliskan et al. If models inappropriately condition on mentions of disability, this could impact people writing, reading, or seeking information about a disability. Depending on how such models are deployed, this could potentially result in reduced autonomy, reduced freedom of speech, perpetuation of societal stereotypes or inequities, or harms to the dignity of individuals.