Artificial Intelligence and Marketing: Pitfalls and Opportunities

被引:125
|
作者
De Bruyn, Arnaud [1 ]
Viswanathan, Vijay [2 ]
Beh, Yean Shan [3 ,4 ]
Brock, Jurgen Kai-Uwe [5 ]
von Wangenheim, Florian [6 ]
机构
[1] ESSEC Business Sch, Ave Bernard Hirsch, F-95000 Cergy, France
[2] Northwestern Univ, Evanston, IL USA
[3] Univ Auckland, Auckland, New Zealand
[4] Xiamen Univ Malaysia, Sepang, Malaysia
[5] Fujitsu Global, Tokyo, Japan
[6] Swiss Fed Inst Technol, Dept Management Technol & Econ, Zurich, Switzerland
关键词
BRAVE-NEW-WORLD; NEURAL-NETWORKS; KNOWLEDGE; SALES; DISCRIMINATION; IMPROVEMENT; ANALYTICS; DISPLAY; SERVICE;
D O I
10.1016/j.intmar.2020.04.007
中图分类号
F [经济];
学科分类号
02 ;
摘要
This article discusses the pitfalls and opportunities of AI in marketing through the lenses of knowledge creation and knowledge transfer. First, we discuss the notion of "higher-order learning" that distinguishes AI applications from traditional modeling approaches, and while focusing on recent advances in deep neural networks, we cover its underlying methodologies (multilayer perceptron, convolutional, and recurrent neural networks) and learning paradigms (supervised, unsupervised, and reinforcement learning). Second, we discuss the technological pitfalls and dangers marketing managers need to be aware of when implementing AI in their organizations, including the concepts of badly defined objective functions, unsafe or unrealistic learning environments, biased AI, explainable AI, and controllable AI. Third, AI will have a deep impact on predictive tasks that can be automated and require little explainability, we predict that AI will fall short of its promises in many marketing domains if we do not solve the challenges of tacit knowledge transfer between AI models and marketing organizations. (c) 2020 Direct Marketing Educational Foundation, Inc. dba Marketing EDGE. All rights reserved.
引用
收藏
页码:91 / 105
页数:15
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