Название: Managing AI Wisely: From Development to Organizational Change in Practice
Автор: Lauren Waardenburg, Marleen Huysman
Издательство: Edward Elgar Publishing
Серия: New Horizons in Business Analytics
Год: 2021
Страниц: 157
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Artificial Intelligence (AI) is being rapidly introduced into the workplace, creating debate around what AI means for our work and organizations. This book gives grounded counterweight to provocative newspaper headlines by using in-depth case studies of eight organizations’ experiences of implementing and using AI, providing readers with a solid understanding of what is actually happening in practice.

Artificial Intelligence (AI) refers to a field in computer science that focuses on developing systems that can accomplish tasks that normally require human intelligence. AI uses, among other things, machine learning (self-learning) algorithms, which can learn based on large amounts of data. As a result, an AI system can independently come up with new suggestions, decisions or predictions. This book is about managing AI systems in practice. As far as we are concerned, the word ‘practice’ should be emphasized, because although there are many (popular) scientific publications about the potential influence of AI systems on work and organizations, little of this work is based on real cases that can provide examples from practice. This is specifically important because existing literature on technology and work suggest that a gap may exist between the development of technology and its actual use in daily work, which might trigger unforeseen consequences. It is time to explore what these consequences are.

In this book, we provide insight into the implementation and use of AI in organizations, without losing sight of the development of the technology. To this end, we conducted research at eight incumbent organizations that have introduced AI systems into their existing work processes. From our analysis of the conversations and observations we conducted, and the written information about the organizations, we have identified four themes that specifically apply to the management of AI systems:

1. Organizing for data. To gather or create data − the central building block of AI − management activities that focus on organizing for data are required.
2. Testing and validating. Since AI systems can automate tasks that were previously undertaken by humans, AI systems can potentially have major consequences for people, organizations and society. Due to the black-boxed nature of AI systems, testing and validating AI systems is becoming increasingly complex.
3. Algorithmic brokering. The black-boxed character also affects the applicability of the AI results.
4. Changes to work. The self-learning aspect of AI also provides new knowledge. That is why AI, unlike prior technologies, is focused on knowledge work.

Offering insight into the unique characteristics of AI in organizations, this book will be essential reading for scholars of business and management, data analytics and information systems, technology and innovation, and computer science. With practical recommendations for managing the challenges of AI, it will also provide business managers with reflections to improve their own AI development and implementation processes.




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