Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models

Pranav Narayanan Venkit, Mukund Srinath, Shomir Wilson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We analyze sentiment analysis and toxicity detection models to detect the presence of explicit bias against people with disability (PWD). We employ the bias identification framework of Perturbation Sensitivity Analysis to examine conversations related to PWD on social media platforms, specifically Twitter and Reddit, in order to gain insight into how disability bias is disseminated in real-world social settings. We then create the Bias Identification Test in Sentiment (BITS) corpus to quantify explicit disability bias in any sentiment analysis and toxicity detection models. Our study utilizes BITS to uncover significant biases in four open AIaaS (AI as a Service) sentiment analysis tools, namely TextBlob, VADER, Google Cloud Natural Language API, DistilBERT and two toxicity detection models, namely two versions of Toxic-BERT. Our findings indicate that all of these models exhibit statistically significant explicit bias against PWD.

Original languageEnglish (US)
Title of host publication3rd Workshop on Trustworthy Natural Language Processing, TrustNLP 2023 - Proceedings of the Workshop
EditorsAnaelia Ovalle, Kai-Wei Chang, Kai-Wei Chang, Ninareh Mehrabi, Yada Pruksachatkun, Aram Galystan, Aram Galystan, Jwala Dhamala, Apurv Verma, Trista Cao, Anoop Kumar, Rahul Gupta
PublisherAssociation for Computational Linguistics (ACL)
Pages26-34
Number of pages9
ISBN (Electronic)9781959429869
StatePublished - 2023
Event3rd Workshop on Trustworthy Natural Language Processing, TrustNLP 2023, co-located with ACL 2023 - Toronto, Canada
Duration: Jul 14 2023 → …

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

Conference3rd Workshop on Trustworthy Natural Language Processing, TrustNLP 2023, co-located with ACL 2023
Country/TerritoryCanada
CityToronto
Period7/14/23 → …

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

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