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

Pranav Narayanan Venkit, Mukund Srinath, Shomir Wilson

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.
Anthology ID:
2023.trustnlp-1.3
Volume:
Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anaelia Ovalle, Kai-Wei Chang, Ninareh Mehrabi, Yada Pruksachatkun, Aram Galystan, Jwala Dhamala, Apurv Verma, Trista Cao, Anoop Kumar, Rahul Gupta
Venue:
TrustNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
26–34
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/2023.trustnlp-1.3/
DOI:
10.18653/v1/2023.trustnlp-1.3
Bibkey:
Cite (ACL):
Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2023. Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models. In Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023), pages 26–34, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models (Narayanan Venkit et al., TrustNLP 2023)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/2023.trustnlp-1.3.pdf
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