@inproceedings{bhat-etal-2021-people,
title = "How do people interact with biased text prediction models while writing?",
author = "Bhat, Advait and
Agashe, Saaket and
Joshi, Anirudha",
editor = "Blodgett, Su Lin and
Madaio, Michael and
O'Connor, Brendan and
Wallach, Hanna and
Yang, Qian",
booktitle = "Proceedings of the First Workshop on Bridging Human{--}Computer Interaction and Natural Language Processing",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.hcinlp-1.18",
pages = "116--121",
abstract = "Recent studies have shown that a bias in thetext suggestions system can percolate in theuser{'}s writing. In this pilot study, we ask thequestion: How do people interact with text pre-diction models, in an inline next phrase sugges-tion interface and how does introducing senti-ment bias in the text prediction model affecttheir writing? We present a pilot study as afirst step to answer this question.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="bhat-etal-2021-people">
<titleInfo>
<title>How do people interact with biased text prediction models while writing?</title>
</titleInfo>
<name type="personal">
<namePart type="given">Advait</namePart>
<namePart type="family">Bhat</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Saaket</namePart>
<namePart type="family">Agashe</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anirudha</namePart>
<namePart type="family">Joshi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2021-04</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing</title>
</titleInfo>
<name type="personal">
<namePart type="given">Su</namePart>
<namePart type="given">Lin</namePart>
<namePart type="family">Blodgett</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Michael</namePart>
<namePart type="family">Madaio</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Brendan</namePart>
<namePart type="family">O’Connor</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hanna</namePart>
<namePart type="family">Wallach</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Qian</namePart>
<namePart type="family">Yang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Online</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Recent studies have shown that a bias in thetext suggestions system can percolate in theuser’s writing. In this pilot study, we ask thequestion: How do people interact with text pre-diction models, in an inline next phrase sugges-tion interface and how does introducing senti-ment bias in the text prediction model affecttheir writing? We present a pilot study as afirst step to answer this question.</abstract>
<identifier type="citekey">bhat-etal-2021-people</identifier>
<location>
<url>https://aclanthology.org/2021.hcinlp-1.18</url>
</location>
<part>
<date>2021-04</date>
<extent unit="page">
<start>116</start>
<end>121</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T How do people interact with biased text prediction models while writing?
%A Bhat, Advait
%A Agashe, Saaket
%A Joshi, Anirudha
%Y Blodgett, Su Lin
%Y Madaio, Michael
%Y O’Connor, Brendan
%Y Wallach, Hanna
%Y Yang, Qian
%S Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F bhat-etal-2021-people
%X Recent studies have shown that a bias in thetext suggestions system can percolate in theuser’s writing. In this pilot study, we ask thequestion: How do people interact with text pre-diction models, in an inline next phrase sugges-tion interface and how does introducing senti-ment bias in the text prediction model affecttheir writing? We present a pilot study as afirst step to answer this question.
%U https://aclanthology.org/2021.hcinlp-1.18
%P 116-121
Markdown (Informal)
[How do people interact with biased text prediction models while writing?](https://aclanthology.org/2021.hcinlp-1.18) (Bhat et al., HCINLP 2021)
ACL