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Accountable algorithms? The ethical implications of data-driven business models
Journal of Service Management ( IF 7.8 ) Pub Date : 2020-03-09 , DOI: 10.1108/josm-03-2019-0073
Christoph F. Breidbach , Paul Maglio

Purpose The purpose of this study is to identify, analyze and explain the ethical implications that can result from the datafication of service. Design/methodology/approach This study uses a midrange theorizing approach to integrate currently disconnected perspectives on technology-enabled service, data-driven business models, data ethics and business ethics to introduce a novel analytical framework centered on data-driven business models as the general metatheoretical unit of analysis. The authors then contextualize the framework using data-intensive insurance services. Findings The resulting midrange theory offers new insights into how using machine learning, AI and big data sets can lead to unethical implications. Centered around 13 ethical challenges, this work outlines how data-driven business models redefine the value network, alter the roles of individual actors as cocreators of value, lead to the emergence of new data-driven value propositions, as well as novel revenue and cost models. Practical implications Future research based on the framework can help guide practitioners to implement and use advanced analytics more effectively and ethically. Originality/value At a time when future technological developments related to AI, machine learning or other forms of advanced data analytics are unpredictable, this study instigates a critical and timely discourse within the service research community about the ethical implications that can arise from the datafication of service by introducing much-needed theory and terminology.

中文翻译:

负责任的算法?数据驱动的业务模型的伦理意义

目的本研究的目的是识别,分析和解释服务数据化可能产生的道德隐含。设计/方法/方法这项研究使用中端理论方法来整合当前对技术支持服务,数据驱动的业务模型,数据伦理和商业道德的脱节观点,以引入一个以数据驱动的商业模型为中心的新颖分析框架。分析的元理论单位。然后,作者使用数据密集型保险服务将框架环境化。结果产生的中端理论为使用机器学习,人工智能和大数据集如何导致不道德的暗示提供了新的见解。此工作围绕13个道德挑战展开,概述了数据驱动的业务模型如何重新定义价值网络,改变了单个参与者作为价值创造者的角色,导致出现了新的以数据为导向的价值主张,以及新颖的收入和成本模型。实际意义基于该框架的未来研究可以帮助指导从业者更有效,更道德地实施和使用高级分析。独创性/价值在与人工智能,机器学习或其他形式的高级数据分析相关的未来技术发展无法预测的时候,本研究促使服务研究界及时,关键地讨论由数据分配可能产生的伦理影响。通过引入急需的理论和术语来提供服务。实际意义基于该框架的未来研究可以帮助指导从业者更有效,更道德地实施和使用高级分析。独创性/价值在与人工智能,机器学习或其他形式的高级数据分析相关的未来技术发展无法预测的时候,本研究促使服务研究界及时,关键地讨论由数据的传播可能产生的伦理影响。通过引入急需的理论和术语来提供服务。实际意义基于该框架的未来研究可以帮助指导从业者更有效,更道德地实施和使用高级分析。独创性/价值在与人工智能,机器学习或其他形式的高级数据分析相关的未来技术发展无法预测的时候,本研究促使服务研究界及时,关键地讨论由数据分配可能产生的伦理影响。通过引入急需的理论和术语来提供服务。
更新日期:2020-03-09
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