The Erosion of Scientific Inquiry: Economic and Ethical Aspects of Fake Knowledge and GenAI

Abstract

The article explores the increasing prevalence of fake knowledge as a substitute for scientific knowledge and examines its economic drivers. It highlights the rising retraction rates of scientific papers due to fraud, and paper mills, demonstrating weaknesses in peer review. The author argues also that knowledge generated by GenAI and scientific knowledge on the other hand can be perceived as marketable goods, where the former serves as a lower-cost alternative, making it accessible despite its unpredictable lack of validity. The article presents a theoretical approach to examining recent trends in the knowledge market. It discusses economic factors and how they affect shifting consumer preferences from scientific knowledge (SK) to fake knowledge (FK) and GenAI. While top universities remain in demand, financial constraints have pushed some students toward alternative, often less reliable, sources. Apart from income polarization, the proliferation of GenAI has accelerated the spread of fake knowledge by lowering knowledge creation costs and bypassing traditional information gatekeepers, such as peer-reviewed journals or experienced scholars. Furthermore, Generative AI tools and fake knowledge are facilitated by social and psychological tendencies, as people seek knowledge—regardless of its accuracy—to reduce uncertainty. The article concludes by considering fake knowledge in the context of business ethics. It suggests that the dissemination of fake knowledge may serve political and economic interests, particularly in influencing public opinion, destabilizing and eroding trust in public figures and institutions. Given the role of digital platforms in spreading fake knowledge, AI researchers can explore how algorithms influence the visibility of misinformation and what ethical considerations should guide content recommendation systems. Research is needed to examine the interplay between income distribution, digitalization, and the propagation of fake knowledge from sociological, psychological, and economic perspectives; and to investigate the role of cognitive biases, social trust, and political motivations in knowledge preferences.