Results 31 to 40 of about 846,299 (286)
FNNC: Achieving Fairness through Neural Networks
, 2020 In classification models fairness can be ensured by solving a constrained optimization problem. We focus on fairness constraints like Disparate Impact, Demographic Parity, and Equalized Odds, which are non-decomposable and non-convex.
Gujar, Sujit, Manisha, Padala
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Fairness, Adverse Selection, and Employment Contracts [PDF]
, 2005 This paper considers a firm whose potential employees have private information on both their productivity and the extent of their fairness concerns. Fairness is modelled as inequity aversion, where fair-minded workers suffer if their colleagues get more ...
Siemens, Ferdinand von
core +4 more sources
Mathematics, 2021 Against the backdrop of emerging markets and the transitional society, the large-scale start-up of real estate development projects has brought about rapid economic growth and accelerated urban expansion, followed by extreme disputes between social ...
Zhaoyu Cao +4 more
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Can medical algorithms be fair? Three ethical quandaries and one dilemma
BMJ Health & Care Informatics, 2022 Objective To demonstrate what it takes to reconcile the idea of fairness in medical algorithms and machine learning (ML) with the broader discourse of fairness and health equality in health research.Method The methodological approach used in this paper ...
Kristine Bærøe +3 more
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Metric Learning for Individual Fairness [PDF]
, 2020 There has been much discussion concerning how "fairness" should be measured or enforced in classification. Individual Fairness [Dwork et al., 2012], which requires that similar individuals be treated similarly, is a highly appealing definition as it ...
Ilvento, Christina
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Éducation et socialisation, 2023 La fonction du manager est circonscrite dès son origine dans l’idée de faire faire aux autres. Ainsi le manager est avant tout celui qui doit « prendre en main », c’est-à-dire à la fois motiver, contrôler et encadrer l’activité des membres de son équipe.
Martin, Christine +1 more
openaire +3 more sources
50 Years of Test (Un)fairness: Lessons for Machine Learning
, 2018 Quantitative definitions of what is unfair and what is fair have been introduced in multiple disciplines for well over 50 years, including in education, hiring, and machine learning. We trace how the notion of fairness has been defined within the testing
Buolamwini Joy +11 more
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Preference-Informed Fairness [PDF]
, 2019 We study notions of fairness in decision-making systems when individuals have diverse preferences over the possible outcomes of the decisions. Our starting point is the seminal work of Dwork et al.
Kim, Michael P. +3 more
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Modular oversight methodology: a framework to aid ethical alignment of algorithmic creations
Design ScienceEvaluating the algorithmic behavior of interactive systems is complex and time-consuming. Developers increasingly recognize the importance of accountability for their algorithmic creations’ unanticipated behavior and resulting implications.
Kyriakos Kyriakou, Jahna Otterbacher
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Zhongguo dianli, 2023 Whether we can “properly handle the cross-subsidies of electricity price” is becoming the key problem throttling the progress of new round of power market-oriented deepening reform.
Siqiang LIU +5 more
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