知识管理
业务
伦理决策
心理学
工程伦理学
社会心理学
计算机科学
工程类
作者
Mojtaba Rezaei,Marco Pironti,Roberto Quaglia
出处
期刊:Management Decision
[Emerald (MCB UP)]
日期:2024-04-25
标识
DOI:10.1108/md-10-2023-2023
摘要
Purpose This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations. Design/methodology/approach The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes. Findings The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process. Originality/value This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.
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