Title
The Power of Algorithms and Big Data: A Marketing Perspective on Consumer Manipulation in Business
First Advisor
George Watson
Date of Award
Spring 3-3-2023
Document Type
Thesis
Degree Name
Bachelor of Arts (B.A.) in Business: Marketing and University Honors
Department
Business
Language
English
Subjects
Artificial Intelligence, Big Data, Data Science, Technology, Predictive Analytics, Consumer Manipulation
DOI
10.15760/honors.1338
Abstract
In marketing, predictive analytics molds big data into tools that can create demographics, target pleasurable neuromodulator chemicals like dopamine, and influence individual and societal behavior patterns. Professionals and scholars alike can use machine-based computation to transform big data into usable knowledge that accurately represents and tracks human behavior. The deception used by marketers to achieve monetary profit can be seen as a direct exploitation of consumers’ trust and privacy. In the past couple of decades this has led to the acceleration of the attention economy and has fueled the age of information. It has pushed countries to not only enforce new laws and regulations, but also race to secure control over data science technologies. Thus, this unchecked greed has created a world in which the power of algorithms and big data is of paramount importance. The future of humanity rides on the success of artificial intelligence algorithms (AI technologies), it is imperative that conversations around this topic become more frequent. The research for this thesis will ultimately lead to a better understanding of how the unregulated dynamic between artificial intelligence programs, big data, corporations, and marketers have had an invasive impact on consumers.
Rights
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Persistent Identifier
https://archives.pdx.edu/ds/psu/40166
Recommended Citation
Reuille-Dupont, Jordan C'rene, "The Power of Algorithms and Big Data: A Marketing Perspective on Consumer Manipulation in Business" (2023). University Honors Theses. Paper 1309.
https://doi.org/10.15760/honors.1338
Included in
Advertising and Promotion Management Commons, Business Analytics Commons, Business and Corporate Communications Commons, Business Intelligence Commons, Business Law, Public Responsibility, and Ethics Commons, Management Information Systems Commons, Marketing Commons, Organizational Behavior and Theory Commons, Other Business Commons