Abstract
The widespread adoption of AI in marketing and consumer use has raised concerns about data privacy and the risk of AI-driven data breaches. As a result, many consumers are reluctant to disclose personal information, which is crucial for the efficient operation of AI systems. While AI continues to evolve, there is a lack of research addressing the crucial areas of ethics, privacy, and corporate digital responsibility. This chapter examines the growing prevalence of artificial intelligence (AI) in consumer experience and its ethical considerations.
TopIntroduction
Artificial Intelligence (AI) and related technologies are receiving widespread attention due to their potential to produce positive outcomes in various sectors and industries. The proliferation of artificial intelligence (AI) in the marketplace is leading to the widespread availability of AI-powered products and services. However, consumers hold conflicting opinions about these technologies as they are accompanied by different ethical challenges during their development and implementation (Du and Xie, 2020).
As consumers interact with various AI technologies throughout their day, such as Amazon's Alexa, Apple's picture collages, and Spotify's music playlists, the prevalence of AI in their lives is expanding. This shift towards AI-driven experiences also influences the organizational culture of marketers, who increasingly operate in environments shaped by computer science. However, the objectives of software developers, focused on technical issues, may not always align naturally with the goals of marketers, who attempt to create meaningful experiences for consumers. Computer scientists view algorithms as “neutral tools,” emphasizing efficiency and accuracy (Green & Viljoen, 2020) and focusing on technical excellence, which may not always align with the goals of marketers who attempt to create meaningful consumer experiences. This perspective, however, may overlook the social and individual complexities of the contexts in which AI is deployed (Puntoni et al., 2020). While AI can potentially enhance consumers' lives in many significant ways, a failure to incorporate behavioral insights into technological advancements may challenge the overall consumer experience with AI.
Even though AI is experiencing exponential growth in adoption by marketers and customers (Mariani et al., 2021), it is surprising that AI‐related ethics, fairness, privacy, and corporate digital responsibility did not seem to get the research attention they deserved. Consumers are placing greater value on their data due to the growing awareness of the risks associated with AI-driven data breaches. As data privacy regulations gain more attention, privacy concerns are becoming increasingly important (Goldberg et al., 2019). These concerns are likely to lead to consumer hesitance in sharing their data with companies (Stourm et al., 2020). Consequently, this unwillingness may hinder the development and effectiveness of automated analyses that rely on data for learning and operation (Goldfarb & Tucker, 2011). Therefore, it is crucial for marketers aiming to employ AI-powered automated technologies to prioritize strategies that encourage users' willingness to share their data.
Alongside privacy issues, the formidable capabilities of AI (Bornet et al., 2021) lead to significant ethical challenges (Belk, 2020; Breidbach & Maglio, 2020). These challenges pertain to the use of customer data in AI for automated decision-making, which can often lead to biased and unjust outcomes for consumers (known as algorithmic bias). Furthermore, on a broader scale, AI raises concerns in terms of a decrease in autonomy, dignity, and social isolation, among others (Belk, 2020). Expanding on the limited existing research on AI's moral implications and the growing field of AI ethics, this chapter analyzes the ethical dimensions of AI at product, consumer, and societal levels. It highlights ethical issues, such as AI (algorithmic) biases, the need for ethical design, safeguarding consumer privacy and well-being.
Key Terms in this Chapter
AI Ethics: AI ethics refers to the set of principles and rules that guide the responsible and fair use of artificial intelligence (AI) technologies. It involves making sure that AI systems are designed, implemented, and used in ways that consider moral values, fairness, transparency, and the well-being of individuals and society. The goal of AI ethics is to ensure that AI benefits humanity without causing harm, discrimination, or ethical dilemmas. It addresses questions about how AI systems should be developed, deployed, and interact with people in a manner that aligns with ethical standards and societal values.
Moral Mediation Theory: The moral mediation theory suggests that our moral judgments and behaviors are influenced by the media we consume. It proposes that exposure to different forms of media, such as news, movies, or social media, can shape our views on what is morally acceptable or unacceptable. Essentially, the theory highlights the idea that the information and values presented in the media play a role in shaping our understanding of morality and influencing our ethical decisions and actions in everyday life.
Algorithmic Bias: Algorithmic bias refers to the unfair or discriminatory outcomes that can arise from the use of computer algorithms. These algorithms are designed to make decisions or predictions, but they can unintentionally favor certain groups or individuals while disadvantaging others. Bias may emerge due to the data used to train the algorithm, reflecting existing societal prejudices. For example, if historical data contains biases, the algorithm might perpetuate those biases, leading to unequal treatment. Addressing algorithmic bias is crucial for ensuring fairness and equity in automated decision-making systems.
Corporate Digital Responsibility: Corporate Digital Responsibility (CDR) refers to a company's commitment and actions to use digital technologies in a responsible and ethical manner. It involves making sure that a company's use of digital tools and technologies considers the well-being of its customers, employees, and the broader community. CDR includes practices such as protecting user privacy, ensuring cybersecurity, and using digital platforms in ways that benefit society. It's about companies taking responsibility for the impact of their digital actions, fostering a positive digital culture, and staying mindful of ethical considerations in the ever-evolving digital landscape.