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Date
2020-08Type
- Journal Article
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Abstract
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. © 2020 Direct Marketing Educational Foundation. Show more
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publishedExternal links
Journal / series
Journal of Interactive MarketingVolume
Pages / Article No.
Publisher
ElsevierOrganisational unit
03995 - von Wangenheim, Florian / von Wangenheim, Florian
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Show all metadata
Citations
Cited 60 times in
Web of Science
Cited 85 times in
Scopus
ETH Bibliography
yes
Altmetrics