<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="tsvetkov-etal-2018-socially">
    <titleInfo>
        <title>Socially Responsible NLP</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Yulia</namePart>
        <namePart type="family">Tsvetkov</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Vinodkumar</namePart>
        <namePart type="family">Prabhakaran</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Rob</namePart>
        <namePart type="family">Voigt</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Mohit</namePart>
            <namePart type="family">Bansal</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Rebecca</namePart>
            <namePart type="family">Passonneau</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">New Orleans, Louisiana</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>As language technologies have become increasingly prevalent, there is a growing awareness that decisions we make about our data, methods, and tools are often tied up with their impact on people and societies. This tutorial will provide an overview of real-world applications of language technologies and the potential ethical implications associated with them. We will discuss philosophical foundations of ethical research along with state of the art techniques. Through this tutorial, we intend to provide the NLP researcher with an overview of tools to ensure that the data, algorithms, and models that they build are socially responsible. These tools will include a checklist of common pitfalls that one should avoid (e.g., demographic bias in data collection), as well as methods to adequately mitigate these issues (e.g., adjusting sampling rates or de-biasing through regularization). The tutorial is based on a new course on Ethics and NLP developed at Carnegie Mellon University.</abstract>
    <identifier type="citekey">tsvetkov-etal-2018-socially</identifier>
    <identifier type="doi">10.18653/v1/N18-6005</identifier>
    <location>
        <url>https://aclanthology.org/N18-6005</url>
    </location>
    <part>
        <date>2018-06</date>
        <extent unit="page">
            <start>24</start>
            <end>26</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Socially Responsible NLP
%A Tsvetkov, Yulia
%A Prabhakaran, Vinodkumar
%A Voigt, Rob
%Y Bansal, Mohit
%Y Passonneau, Rebecca
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F tsvetkov-etal-2018-socially
%X As language technologies have become increasingly prevalent, there is a growing awareness that decisions we make about our data, methods, and tools are often tied up with their impact on people and societies. This tutorial will provide an overview of real-world applications of language technologies and the potential ethical implications associated with them. We will discuss philosophical foundations of ethical research along with state of the art techniques. Through this tutorial, we intend to provide the NLP researcher with an overview of tools to ensure that the data, algorithms, and models that they build are socially responsible. These tools will include a checklist of common pitfalls that one should avoid (e.g., demographic bias in data collection), as well as methods to adequately mitigate these issues (e.g., adjusting sampling rates or de-biasing through regularization). The tutorial is based on a new course on Ethics and NLP developed at Carnegie Mellon University.
%R 10.18653/v1/N18-6005
%U https://aclanthology.org/N18-6005
%U https://doi.org/10.18653/v1/N18-6005
%P 24-26

Markdown (Informal)

[Socially Responsible NLP](https://aclanthology.org/N18-6005) (Tsvetkov et al., NAACL 2018)

• Socially Responsible NLP (Tsvetkov et al., NAACL 2018)

ACL

• Yulia Tsvetkov, Vinodkumar Prabhakaran, and Rob Voigt. 2018. Socially Responsible NLP. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts, pages 24–26, New Orleans, Louisiana. Association for Computational Linguistics.