The Price of Truth: How Money Affects the Norms of Science
Abstract
The financial and economic aspects of modern science raise many important and difficult questions for research ethics, the philosophy of science, and science policy. How does money affect scientific research? Can financial interests undermine scientific norms, such as objectivity, truthfulness, and honesty? Have scientists become entrepreneurs bent on making money instead of investigators searching for the truth? How does the commercialization of research affect the public’s perception of science? Can scientists prevent money from corrupting the research enterprise? What types of rules, polices, and guidelines should scientists adopt to prevent financial interests from adversely affecting research and the public’s opinion of science? This book examines these and other questions related to the financial and economic aspects of modern science. It investigates and analyzes the relationship between the pursuit of financial gain and the pursuit of knowledge. It considers how greed can affect the conduct of scientists, universities, corporations, and the public’s perception of science. It explores how moral, social, and political values affect public and private funding of research, and how debates about research funding reflect broader, ideological divisions within society. The book also proposes some policies for controlling, regulating, and monitoring financial interests in research and for counteracting money’s corrupting effects on science.
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There is ample evidence that scientists sometimes incorporate various biases into their study designs.
“There is ample evidence that scientists sometimes incorporate various biases into their study designs [44–47].”
From Autonomous artificial intelligence, scientific research, and human values (2026) · cites this paper as [44]
Cites
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Resnik, D. B., & Hosseini, M. (2025) · AI and Ethics · doi:10.1007/s43681-024-00493-8 · Cited by 228 · see citing works
“Despite these shortcomings, the explainable AI approach is a reasonable way of dealing with transparency issues, and we encourage its continued development and application to AI/ML systems.”
Self-citationThe Ethical Challenges of Socially Responsible Science
Resnik, D. B., & Elliott, K. C. (2016) · Accountability in Research · doi:10.1080/08989621.2014.1002608 · Cited by 131 · see citing works
“…may need to address value questions when deciding whether to enter into research contracts with private companies, because companies may seek to impose contractual requirements for research funding that interfere with the free and open exchange of scientific data and information (Resnik, 2007).”
BackgroundInfluentialSelf-citationSovacool, B. K. (2008) · Journal of Bioethical Inquiry · doi:10.1007/s11673-008-9113-6 · Cited by 116 · see citing works
Science, Values, and the New Demarcation Problem
Resnik, D. B., & Elliott, K. C. (2023) · Journal for General Philosophy of Science · doi:10.1007/s10838-022-09633-2 · Cited by 49 · see citing works
Self-citationValue-entanglement and the integrity of scientific research
Resnik, D. B., & Elliott, K. C. (2019) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2018.12.011 · Cited by 49 · see citing works
Self-citationInstitutional Conflicts of Interest in Academic Research
Resnik, D. B. (2019) · Science and Engineering Ethics · doi:10.1007/s11948-015-9702-9 · Cited by 40 · see citing works
Self-citationScience and money: problems and solutions
Resnik, D. B. (2014) · Journal of Microbiology & Biology Education · doi:10.1128/jmbe.v15i2.792 · Cited by 33 · see citing works
Self-citationMessing with Merton: The intersection between Open Science practices and Mertonian values
Hosseini, M., Senabre Hidalgo, E., Horbach, S. P. J. M., Guttinger, S., & Penders, B. (2022) · doi:10.31235/osf.io/9nyh8 · Cited by 30 · see citing works
“Choice-supportive bias” in science: Explanation and mitigation
Kafaee, M., Marhamati, H., & Gharibzadeh, S. (2021) · Accountability in Research · doi:10.1080/08989621.2021.1872377 · Cited by 12 · see citing works
Autonomous artificial intelligence, scientific research, and human values
Resnik, D. B., Hosseini, M., & Hauswald, R. (2026) · AI and Ethics · doi:10.1007/s43681-025-00908-0 · Cited by 15 · see citing works
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- Authors
- Resnik, D. B.
- Affiliations
- National Institute of Environmental Health Sciences (US)
- Corresponding author
- Resnik, David B.
- ORCID
- Resnik, David B.
- Publisher
- Oxford University PressNew York
- Published
- 2007-01-01
- OpenAlex
- W2501567833
- Cited by
- 160
- References
- 9
- Citations by year
- 2026: 7 · 2025: 7 · 2024: 7 · 2023: 6 · 2022: 9 · 2021: 10 · 2020: 10 · 2019: 7 · 2018: 9 · 2017: 4 · 2016: 1 · 2015: 10 · 2014: 11 · 2013: 11 · 2012: 7
- FWCI
- 13.60
- Type
- book
- Language
- en
- Open access
- closed
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Research, Science, and Academia
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmaceutical industry and healthcare
- Keywords
- research funding, financial conflicts of interest, commercialization of research, research ethics, scientific objectivity, public perception of science, science policy, research regulation, university-industry relations
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