Titlebook: Business Data Ethics; Emerging Models for Dennis Hirsch,Timothy Bartley,Piers Norris Turner Book‘‘‘‘‘‘‘‘ 2024 The Editor(s) (if applicable

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書(shū)目名稱Business Data Ethics影響因子(影響力)




書(shū)目名稱Business Data Ethics影響因子(影響力)學(xué)科排名




書(shū)目名稱Business Data Ethics網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Business Data Ethics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Business Data Ethics被引頻次




書(shū)目名稱Business Data Ethics被引頻次學(xué)科排名




書(shū)目名稱Business Data Ethics年度引用




書(shū)目名稱Business Data Ethics年度引用學(xué)科排名




書(shū)目名稱Business Data Ethics讀者反饋




書(shū)目名稱Business Data Ethics讀者反饋學(xué)科排名

野蠻

2192-855X a third component: data ethics management. This third element consists of the management structures, processes, training and substantive benchmarks that companies use to operationalize their high-level ethical 978-3-031-21490-5978-3-031-21491-2Series ISSN 2192-855X Series E-ISSN 2192-8568

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The Empowerment of Women in Diplomacy, teach or apply consistently. Companies need substantive standards that are more actionable than high-level principles, and more standardized than intuitive judgment calls. They need generalizable . that draw the line between ethical and unethical applications of advanced analytics and AI. How best

陪審團(tuán)每個(gè)人

Conceptualising Youth Quality of Life,e discuss the importance of role clarity (i.e., who is responsible for data ethics) within organizations and its relationship with developing organizational structure to support data ethics management.

groggy

https://doi.org/10.1007/978-3-319-75681-3nd compliance ethical thinking in recognition of the convergence of their own business interests with the demands of trustworthy and responsible decision-making. These efforts raise interesting questions about companies’ moral obligation to pursue the public good and how companies will behave when t

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Introduction, This third component consists of the managementstructures, processes, training and substantive benchmarks that companies use tooperationalize their high-level data and?AI ethics principles and to guide and hold accountabletheir developers. AI ethics management is the connective tissue that makes AI

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Drawing Substantive Lines, teach or apply consistently. Companies need substantive standards that are more actionable than high-level principles, and more standardized than intuitive judgment calls. They need generalizable . that draw the line between ethical and unethical applications of advanced analytics and AI. How best

Jubilation

Management Structures and Functions,e discuss the importance of role clarity (i.e., who is responsible for data ethics) within organizations and its relationship with developing organizational structure to support data ethics management.

FRAX-tool

Data Analytics for the Social Good,nd compliance ethical thinking in recognition of the convergence of their own business interests with the demands of trustworthy and responsible decision-making. These efforts raise interesting questions about companies’ moral obligation to pursue the public good and how companies will behave when t