University of Illinois at Urbana-Champaign
Me, myself, and AI: The impact of artificial intelligence on marketing and the self
Abstract
dc:descriptionArtificial intelligence (AI) is one of the most prominent and potentially transformative technologies in society today. How this trend will impact individuals, firms, organizations, and society is still unknown, and depends largely on how individual consumers choose to adopt and use AI. This two-essay dissertation focuses on understanding how consumers perceive, adopt, and use artificial intelligent technologies, but also how these technologies can have subsequent effects on the self. My dissertation offers two main contributions. First, I build on psychological research on implicit self-theories and on marketing scholarship about artificial intelligence, to develop a theoretical understanding of the forces that shape consumer perceptions of artificial intelligence and how these perceptions affect their subsequent behavior. Second, I develop practical marketing interventions that can be used to influence patterns of adoption and positively enhance perceptions of artificial intelligence in the marketplace. This dissertation is organized as follows. In Chapter 1, I introduce definitions of artificial intelligence and review important literature in the fields of marketing, management, psychology, and human-computer interaction. I then examine three ways in which consumers react to AI (i.e., distrust, trust, and reliance) based on conceptual and empirical research in this domain. My first goal is to build on current research and empirically test viable, but simple ways to enhance evaluations of AI recommendations. My second goal is to enhance understanding on how AI impacts consumers, specifically their cognitive performance. In my essays, I examine the current literature to tackle two main research questions: 1) How can consumers overcome an aversion to recommendations from AI? and 2) How does the salience of artificial intelligence’s superiority impact our own performance on cognitive tasks? Essay 1, in Chapter 2, takes a different approach compared to prevailing literature. While prior research focuses on changing perceptions of AI to overcome algorithm aversion, I focus on changing perceptions of the purchase experience itself. Essay 1 also develops a practical strategy to overcome algorithm aversion and promote adoption by shifting how an AI-based recommendation is framed. By framing an AI recommendation as an experience, I propose that consumers are more likely to connect with the recommendation. Essay 2, in Chapter 3, I focus on the impact of artificial intelligence on the consumer. More specifically, Essay 2 examines how artificial intelligence can impact consumers’ cognitive performance on tasks such as the GRE, working memory capacity, and financial literacy. I propose that making AI’s capabilities salient (vs. absent) undermines cognitive performance because AI promotes a fixed mindset (vs. growth mindset). Together, these two essays offer an empirically supported conceptual structure for marketing scholars and practitioners to understand artificial intelligence and influence the processes through which consumers perceive and adopt it. Artificial intelligence has the potential to create exponential value for consumers, firms, and society, but also poses many profound challenges and risks. A better understanding of how this transformative technology is perceived and impacts the consumer can potentially help to maximize its potential value and minimize its risks.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Business Administration
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2022
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Danienta, Nadia R
- Contributors dc:contributor
-
- Rindfleisch, Aric
- Shavitt, Sharon
- Mehta, Ravi
- Hoffman, Donna
Subjects
dc:subject × 7Rights
dc:rights- Statement dc:rights
-
- Copyright 2021 Nadia Danienta
- Language dc:language
- en
Identifiers
dc:identifier.*- Handle dc:identifier
- http://hdl.handle.net/2142/113189
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/113189