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  • Search: subject:"fair machine learning"
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Year of publication
Subject
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Artificial intelligence 2 Cash Transfers 2 Fair Machine Learning 2 Künstliche Intelligenz 2 Proxy Means Test 2 Social Protection 2 Targeting 2 Algorithm 1 Algorithmus 1 Armutsbekämpfung 1 Gerechtigkeit 1 Impact assessment 1 Justice 1 Poverty reduction 1 Social policy 1 Social security 1 Social security benefits 1 Soziale Sicherheit 1 Sozialpolitik 1 Theorie 1 Theory 1 Wirkungsanalyse 1 algorithmic bias 1 economics of artificial intelligence 1 equal impact 1 equal treatment 1 fair machine learning 1 Öffentliche Sozialleistungen 1
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Online availability
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Free 2 Undetermined 1
Type of publication
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Book / Working Paper 2 Article 1
Type of publication (narrower categories)
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Working Paper 2 Arbeitspapier 1 Article in journal 1 Aufsatz in Zeitschrift 1 Graue Literatur 1 Non-commercial literature 1
Language
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English 3
Author
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Dietrich, Stephan 2 Gassmann, Franziska 2 Malerba, Daniele 2 Aseri, Manmohan 1 Fu, Runshan 1 Singh, Param Vir 1 Srinivasan, Kannan 1
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Published in...
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Management science : journal of the Institute for Operations Research and the Management Sciences 1 UNU-MERIT Working Papers 1 Working paper series / United Nations University, UNU-MERIT 1
Source
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ECONIS (ZBW) 2 EconStor 1
Showing 1 - 3 of 3
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"Un"fair machine learning algorithms
Fu, Runshan; Aseri, Manmohan; Singh, Param Vir; … - In: Management science : journal of the Institute for … 68 (2022) 6, pp. 4173-4195
Persistent link: https://www.econbiz.de/10013369036
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Predicting social assistance beneficiaries : on the social welfare damage of data biases
Dietrich, Stephan; Malerba, Daniele; Gassmann, Franziska - 2023
Persistent link: https://www.econbiz.de/10014310958
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Predicting social assistance beneficiaries: On the social welfare damage of data biases
Dietrich, Stephan; Malerba, Daniele; Gassmann, Franziska - 2023
Targeting error assessments for social transfers commonly rely on accuracy as a performance metric. This process is typically insensitive to the distributional position of incorrectly classified households. In this paper we develop an extended targeting assessment framework for proxy means tests...
Persistent link: https://www.econbiz.de/10015458104
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