Organizational Learning in the Age of Data [electronic resource] /
by Andrew Banasiewicz.
- 1st ed. 2021.
- XV, 307 p. 67 illus., 9 illus. in color. online resource.
- EAI/Springer Innovations in Communication and Computing, 2522-8609 .
- EAI/Springer Innovations in Communication and Computing, .
Introduction -- Out with the Old In with the New -- Democratization of Organizations -- Organizational Dynamics and Individual Cognition -- Learning with Data: A Brief History -- Learning with Data in the 21st Century -- Managing by the Numbers -- Decision Automation -- In Machine we Trust -- Letting Go – Knowing When and How -- The Future -- Conclusion.
This book discusses the impact of advanced information technologies, such as data processing, machine learning, and artificial intelligence, on organizational decision-making processes and practices. One of the book’s central themes is the interplay between human reasoning and machine logic in the context of organizational functioning, specifically, the fairly common situations in which subjective beliefs are pitted against objective evidence giving rise to conflict rather than enhancing the quality of organizational sensemaking. Aiming to not only raise the awareness of the potential challenges but also to offer solutions, the book delineates and discusses the core impediments to effective human-information technology interactions, and outlines strategies for overcoming those obstacles on the way to enhancing the efficacy of organizational decision-making. Tackles inherently technical aspects of advanced information technologies and cognitive functioning; Discusses what it means to ‘learn’ and ‘know’ in the age of data and advanced information technologies such as big data, data analytics, AI, and machine learning; Provides specific recommendations for how to effectively combine the power of information technology with human creative thinking.
9783030748661
10.1007/978-3-030-74866-1 doi
Telecommunication. Data mining. Business information services. Communications Engineering, Networks. Data Mining and Knowledge Discovery. IT in Business.