Gender Bias in Word Embeddings

Author:

Caliskan Aylin1,Ajay Pimparkar Parth2,Charlesworth Tessa3,Wolfe Robert1,Banaji Mahzarin R.3

Affiliation:

1. University of Washington, Seattle, WA, USA

2. Birla Institute of Technology and Science, Pilani, India

3. Harvard University, Cambridge, MA, USA

Publisher

ACM

Reference57 articles.

1. The Grey Hoodie Project: Big Tobacco, Big Tech, and the Threat on Academic Integrity

2. Alan Akbik , Duncan Blythe , and Roland Vollgraf . 2018 . Contextual String Embeddings for Sequence Labeling. In COLING 2018, 27th International Conference on Computational Linguistics. 1638--1649 . Alan Akbik, Duncan Blythe, and Roland Vollgraf. 2018. Contextual String Embeddings for Sequence Labeling. In COLING 2018, 27th International Conference on Computational Linguistics. 1638--1649.

3. Implicit gender stereotyping in judgments of fame.

4. Christine Basta , Marta R Costa-Jussà , and Noe Casas . 2019. Evaluating the underlying gender bias in contextualized word embeddings. arXiv preprint arXiv:1904.08783 ( 2019 ). Christine Basta, Marta R Costa-Jussà, and Noe Casas. 2019. Evaluating the underlying gender bias in contextualized word embeddings. arXiv preprint arXiv:1904.08783 (2019).

5. Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science

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