Abstract
Artificial intelligence (AI) has dramatically changed the way organizations communicate, understand, and interact with their potential consumers. In the context of this trend, the ethical considerations of advertising when applying AI should be the core question for marketers. This paper discusses six dominant algorithmic purchase decision pathways that align with ethical philosophies for online customers when buying a product/goods. The six ethical positions include: ethical egoism, deontology (i.e., rule-based), relativist, utilitarianism, virtue ethics, and ethics of care (i.e., stakeholders’ perspective). Furthermore, this paper launches an “intelligent advertising” AI theme by examining its present and future as well as identifying the key phases of intelligent advertising. Several research questions are offered to guide future research on intelligent advertising to benefit ethical AI decision-making. Finally, several areas that can be widely applied to ethical intelligent advertising are suggested for future research.
Highlights
Artificial intelligence (AI) has transcended across numerous fields in our lives (Kaplan & Haenlein, 2019, 2020; Russell & Norvig, 2020)
The research explored the stimulus of AI and its related subsets of machine learning, deep learning, and neural networks on advertising
This paper provided a basis to apply ethical considerations for intelligent advertising in customers’ algorithmic purchase decision pathways. This technique may assist marketers and advertisers in comprehending and reaching suitable ethical concerns for customers. This process is useful since biased human judgments can influence AI-based systems in two distinct manners
Summary
Artificial intelligence (AI) has transcended across numerous fields in our lives (Kaplan & Haenlein, 2019, 2020; Russell & Norvig, 2020). This procedure may assist marketers and advertisers in understanding and reaching the appropriate ethical considerations for a particular class of customers at the appropriate time This approach combines the TPM (Rodgers, 2006, 2010) and AI technologies to build the neural network for intelligent advertising based on the consumer’s purchase decision algorithms. The TPM might support businesses in understanding, forecasting, and modifying online consumer purchase decisions through the six different algorithmic pathways This model, which assists people in understanding useful knowledge, offers an in-depth analysis of the various stages affecting decisions so that it allows marketers and organizations to study information and efficient process in several stages before making a decision choice. The advertisers can adjust their advertising plan or message to get in touch with their potential customers more successfully
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