The dark side of artificial intelligence in retail innovation

Mahmoud, A. B. and Tehseen, Shehnaz * and Fuxman, L. (2020) The dark side of artificial intelligence in retail innovation. In: Retail Futures: The Good, the Bad and the Ugly of the digital transformation. Emerald, pp. 165-180. ISBN 978-1-83867-664-3

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Official URL: http://doi.org/10.1108/978-1-83867-663-620201019

Abstract

Many academic scholars argue that the goal of using artificial intelligence (hereafter, AI) in business has been to serve humans in performing their jobs. Nevertheless, some scholars refute such arguments and warn against potential threats of AI to humankind in the future. AI or machine intelligence comprises three main aspects, i.e., learning, reasoning and self-correction, which aggregate to conjure up the artificial mind. In retailing, the employment of AI is progressively becoming a major theme of innovation and retailers are rapidly increasing the use of machine intelligence to efficiently simulate human intelligence and become more competitive through cutting costs and improving customer journeys. However, such benefits can be catastrophic in the long run. As a result of this, this chapter represents an attempt to produce a synthesis of current research on the use of AI in retailing and identify the possible benefits or ramifications on the ‘human’ pillars of the retail process (i.e., the employers, employees and customers). Finally, this chapter aims to reflect on relevant literature to conclude future research and industrial implications.

Item Type: Book Section
Uncontrolled Keywords: Artificial intelligence; AI-based retail innovation; machine learning; neural networks; retail innovation; business ethics
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: Others > Non Sunway Academics
Sunway University > Sunway University Business School > Dept. Management
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 01 Apr 2021 06:47
Last Modified: 01 Apr 2021 06:47
URI: http://eprints.sunway.edu.my/id/eprint/1703

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