The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European Languages
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Abstract (arXiv)
The project BIAS: Mitigating Diversity Biases of AI in the Labor Market is a four-year project funded by the European commission and supported by the Swiss State Secretariat for Education, Research and Innovation (SERI). As part of the project, novel bias detection methods to identify societal bias in language models and word embeddings in European languages are developed, with particular attention to linguistic and geographic particularities. This technical report describes the overall architecture and components of the BIAS Detection Framework. The code described in this technical report is available and will be updated and expanded continuously with upcoming results from the BIAS project. The details about the datasets for the different languages are described in corresponding papers at scientific venues.
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References · 11
- 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
- 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
- 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
- 2020CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Modelscited by 703
- 2019On Measuring Social Biases in Sentence Encoderscited by 397
- 2019Mitigating Gender Bias in Natural Language Processing: Literature Reviewcited by 287
- 2019Measuring Bias in Contextualized Word Representationscited by 275
- 2019Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Themcited by 268
- 2020Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biasescited by 167
- 2019Assessing Social and Intersectional Biases in Contextualized Word Representationscited by 134
- 2021Mitigating Language-Dependent Ethnic Bias in BERTcited by 87
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