Crowdsourcing Perceptions of Fair Predictors for Machine Learning

Crowdsourcing Perceptions of Fair Predictors for Machine Learning
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众包对机器学习公平预测的看法

DOI:
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发表时间:
2019
期刊:
Proc. ACM Hum. Comput. Interact.
影响因子:
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通讯作者:
V. Kostakos
V. Kostakos
中科院分区:
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文献类型:
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作者:
Niels van Berkel;Jorge Gonçalves;Danula Hettiachchi;S. Wijenayake;Ryan M. Kelly;V. Kostakos

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在具有社会影响力的过程中,对算法决策的依赖越来越大,这加剧了对无偏见和程序公平的算法的需求。识别公平的预测器是构建公平算法的一个重要步骤,但公平预测器选择中缺乏基础事实使其成为一项具有挑战性的任务。在我们的研究中,我们招募了90名群众工作者来判断是否包含各种预测累犯的因素。我们将参与者分为三种情况,每组的组成各不相同。我们的研究结果表明,参与者能够在预测选择上做出明智的决定。我们发现,当参与者是一个更多样化的群体的一部分时,与多数人投票的一致性更高。所提出的工作流程,它提供了一个可扩展的和实用的方法,以达到不同的观众,使研究人员能够捕捉参与者的公平性的看法在私人,同时允许结构化的参与者讨论。
The increased reliance on algorithmic decision-making in socially impactful processes has intensified the calls for algorithms that are unbiased and procedurally fair. Identifying fair predictors is an essential step in the construction of equitable algorithms, but the lack of ground-truth in fair predictor selection makes this a challenging task. In our study, we recruit 90 crowdworkers to judge the inclusion of various predictors for recidivism. We divide participants across three conditions with varying group composition. Our results show that participants were able to make informed decisions on predictor selection. We find that agreement with the majority vote is higher when participants are part of a more diverse group. The presented workflow, which provides a scalable and practical approach to reach a diverse audience, allows researchers to capture participants' perceptions of fairness in private while simultaneously allowing for structured participant discussion.
DOI: 10.1145/3025453.3025884
发表时间: 2017
期刊: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
影响因子: --
作者:
Lee, Min Kyung;Kim, Ji Tae;Lizarondo, Leah
通讯作者: Lizarondo, Leah
DOI: 10.1609/aaai.v32i1.11512
发表时间: 2017-09
期刊: ArXiv
影响因子: --
作者:
Ritesh Noothigattu;Snehalkumar `Neil' Gaikwad;E. Awad;Sohan Dsouza;Iyad Rahwan;Pradeep Ravikumar;Ariel D. Procaccia
通讯作者: Ritesh Noothigattu;Snehalkumar `Neil' Gaikwad;E. Awad;Sohan Dsouza;Iyad Rahwan;Pradeep Ravikumar;Ariel D. Procaccia