Augmenting Organizational Decision-Making with Deep Learning Algorithms: Principles, Promises, and Challenges
It addresses the problem of improving decision-making processes in organizations for managers and employees, but it appears to be a conceptual or review-based analysis rather than an incremental technical advancement.
The paper examines how deep learning algorithms can enhance organizational decision-making by assisting employees with information processing and potentially shifting them towards more creative tasks, though it does not present specific experimental results or concrete numbers.
The current expansion of theory and research on artificial intelligence in management and organization studies has revitalized the theory and research on decision-making in organizations. In particular, recent advances in deep learning (DL) algorithms promise benefits for decision-making within organizations, such as assisting employees with information processing, thereby augment their analytical capabilities and perhaps help their transition to more creative work.