{"title":"Responsible algorithmic decision-making","authors":"Christoph F. Breidbach","doi":"10.1016/j.orgdyn.2024.101031","DOIUrl":null,"url":null,"abstract":"<div><p>Algorithmic decision-making - the use of computational methods that enable machines to automatically complete tasks and/or make decisions - is emerging as a critical source of competitive advantage for organizations. However, despite many benefits, there is an inherent dark side associated with it that can manifest issues ranging from a loss of privacy for individuals to societal power imbalance. Managers and policymakers alike need to be able to understand potentially unethical consequences that can arise from algorithmic decision-making before they can fully manifest. This article aims to support this undertaking by identifying, analysing, and explaining the challenges that can arise from algorithmic decision-making, and by contributing a seven-step roadmap to those wanting to responsibly implement and benefit from algorithms today.</p></div>","PeriodicalId":48061,"journal":{"name":"Organizational Dynamics","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0090261624000044/pdfft?md5=9e5e1e15c6d1b43fc32cb009c7943091&pid=1-s2.0-S0090261624000044-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Organizational Dynamics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0090261624000044","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Algorithmic decision-making - the use of computational methods that enable machines to automatically complete tasks and/or make decisions - is emerging as a critical source of competitive advantage for organizations. However, despite many benefits, there is an inherent dark side associated with it that can manifest issues ranging from a loss of privacy for individuals to societal power imbalance. Managers and policymakers alike need to be able to understand potentially unethical consequences that can arise from algorithmic decision-making before they can fully manifest. This article aims to support this undertaking by identifying, analysing, and explaining the challenges that can arise from algorithmic decision-making, and by contributing a seven-step roadmap to those wanting to responsibly implement and benefit from algorithms today.
期刊介绍：
Organizational Dynamics domain is primarily organizational behavior and development and secondarily, HRM and strategic management. The objective is to link leading-edge thought and research with management practice. Organizational Dynamics publishes articles that embody both theoretical and practical content, showing how research findings can help deal more effectively with the dynamics of organizational life.
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