@inproceedings{alonso-alemany-etal-2023-bias,
title = "Bias assessment for experts in discrimination, not in computer science",
author = "Alonso Alemany, Laura and
Benotti, Luciana and
Maina, Hern{\'a}n and
Gonzalez, Luc{\'\i}a and
Mart{\'\i}nez, Lautaro and
Busaniche, Beatriz and
Halvorsen, Alexia and
Rojo, Amanda and
Rajngewerc, Mariela",
editor = "Dev, Sunipa and
Prabhakaran, Vinodkumar and
Adelani, David and
Hovy, Dirk and
Benotti, Luciana",
booktitle = "Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP)",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.c3nlp-1.10",
doi = "10.18653/v1/2023.c3nlp-1.10",
pages = "91--106",
abstract = "Approaches to bias assessment usually require such technical skills that, by design, they leave discrimination experts out. In this paper we present EDIA, a tool that facilitates that experts in discrimination explore social biases in word embeddings and masked language models. Experts can then characterize those biases so that their presence can be assessed more systematically, and actions can be planned to address them. They can work interactively to assess the effects of different characterizations of bias in a given word embedding or language model, which helps to specify informal intuitions in concrete resources for systematic testing.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="alonso-alemany-etal-2023-bias">
<titleInfo>
<title>Bias assessment for experts in discrimination, not in computer science</title>
</titleInfo>
<name type="personal">
<namePart type="given">Laura</namePart>
<namePart type="family">Alonso Alemany</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Luciana</namePart>
<namePart type="family">Benotti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hernán</namePart>
<namePart type="family">Maina</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lucía</namePart>
<namePart type="family">Gonzalez</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lautaro</namePart>
<namePart type="family">Martínez</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Beatriz</namePart>
<namePart type="family">Busaniche</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alexia</namePart>
<namePart type="family">Halvorsen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Amanda</namePart>
<namePart type="family">Rojo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mariela</namePart>
<namePart type="family">Rajngewerc</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2023-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Sunipa</namePart>
<namePart type="family">Dev</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vinodkumar</namePart>
<namePart type="family">Prabhakaran</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">David</namePart>
<namePart type="family">Adelani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dirk</namePart>
<namePart type="family">Hovy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Luciana</namePart>
<namePart type="family">Benotti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Dubrovnik, Croatia</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Approaches to bias assessment usually require such technical skills that, by design, they leave discrimination experts out. In this paper we present EDIA, a tool that facilitates that experts in discrimination explore social biases in word embeddings and masked language models. Experts can then characterize those biases so that their presence can be assessed more systematically, and actions can be planned to address them. They can work interactively to assess the effects of different characterizations of bias in a given word embedding or language model, which helps to specify informal intuitions in concrete resources for systematic testing.</abstract>
<identifier type="citekey">alonso-alemany-etal-2023-bias</identifier>
<identifier type="doi">10.18653/v1/2023.c3nlp-1.10</identifier>
<location>
<url>https://aclanthology.org/2023.c3nlp-1.10</url>
</location>
<part>
<date>2023-05</date>
<extent unit="page">
<start>91</start>
<end>106</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Bias assessment for experts in discrimination, not in computer science
%A Alonso Alemany, Laura
%A Benotti, Luciana
%A Maina, Hernán
%A Gonzalez, Lucía
%A Martínez, Lautaro
%A Busaniche, Beatriz
%A Halvorsen, Alexia
%A Rojo, Amanda
%A Rajngewerc, Mariela
%Y Dev, Sunipa
%Y Prabhakaran, Vinodkumar
%Y Adelani, David
%Y Hovy, Dirk
%Y Benotti, Luciana
%S Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP)
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F alonso-alemany-etal-2023-bias
%X Approaches to bias assessment usually require such technical skills that, by design, they leave discrimination experts out. In this paper we present EDIA, a tool that facilitates that experts in discrimination explore social biases in word embeddings and masked language models. Experts can then characterize those biases so that their presence can be assessed more systematically, and actions can be planned to address them. They can work interactively to assess the effects of different characterizations of bias in a given word embedding or language model, which helps to specify informal intuitions in concrete resources for systematic testing.
%R 10.18653/v1/2023.c3nlp-1.10
%U https://aclanthology.org/2023.c3nlp-1.10
%U https://doi.org/10.18653/v1/2023.c3nlp-1.10
%P 91-106
Markdown (Informal)
[Bias assessment for experts in discrimination, not in computer science](https://aclanthology.org/2023.c3nlp-1.10) (Alonso Alemany et al., C3NLP 2023)
ACL
- Laura Alonso Alemany, Luciana Benotti, Hernán Maina, Lucía Gonzalez, Lautaro Martínez, Beatriz Busaniche, Alexia Halvorsen, Amanda Rojo, and Mariela Rajngewerc. 2023. Bias assessment for experts in discrimination, not in computer science. In Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP), pages 91–106, Dubrovnik, Croatia. Association for Computational Linguistics.