By Evelyn Brister, Erin Shoemaker, Susan M. Wolf and Gillian H. Roehrig.
2. Erin Shoemaker (biography)
3. Susan M. Wolf (biography)
4. Gillian H. Roehrig (biography)
What problems in research ethics arise for research networks that cross disciplines and institutions? How do they differ from the ethical issues affecting individual researchers or society at large? What are the lessons for leaders of large research networks?
Addressing complex, real-world problems requires expertise from multiple disciplines. Large, diverse research teams that address these problems may be organized across multiple universities or other research institutions. The larger scale of this network science creates distinctive ethical responsibilities.
To identify responsibilities that fall on network leaders, it is useful to consider ethical issues at three levels: micro, meso, and macro.
The microlevel primarily focuses on individual investigators and small teams working in a single location. Examples of ethical issues at this level are avoiding research misconduct such as plagiarism, conflicts of interest, and detrimental practices.
The mesolevel primarily focuses on multi-team, cross-disciplinary, and cross-institutional research networks. Ethical issues at this level include managing differences across the network in approaches to ethically sensitive issues such as authorship and data sharing, promoting transparency and collaboration, and ensuring the network capacity to consider societal implications.
The macrolevel primarily focuses on substantively addressing large scale societal impacts. Ethical issues include minimizing risks and maximizing benefits to society, along with ensuring that potentially affected groups are consulted about the research and resulting innovations.
Most work on research ethics has focused on the microlevel of individual researchers and small teams. Consideration has also been given to the macrolevel of the large-scale implications of the research for society. The least consideration has been given to the mesolevel.
Three categories of mesolevel issues
Mesolevel ethical issues can be grouped into three categories:
- Differences at the microlevel that cause mesolevel problems
Differences across research groups, usually at different institutions, can be obstacles to collaboration across networks. For example, conflicts may arise among collaborating groups that have different norms and practices related to authorship, data-sharing, ownership of intellectual property, and commercialization.
- Mesolevel issues facing the network itself
Key issues here include creating a shared vision and mission, establishing consistent best practices, managing data and complying with data privacy requirements, and determining which stakeholders to engage with and how any commercialization opportunities would be handled. Ethical issues can arise as network leaders consider what research policies to adopt, how to structure community partnerships, and how best to support the responsible conduct of research across the network.
- Mesolevel processes needed to build the capacity to address societal issues at the macrolevel
This involves ensuring that the network builds the capacity to anticipate and address societal challenges, including how to secure net societal benefit from the research. Examples include building the capacity to co-develop commercialization options and technologies with key interested parties.
A framework for network-scale research ethics
Initial steps to develop solutions for research ethics in complex networks include:
- Establish network-wide norms to determine authorship, data sharing, and trainee expectations.
- Build an ethos of ethics and integrity to create a culture that handles conflict and supports creativity. This process begins with network leadership.
- Attend to interactions between the network and a variety of organizations and institutions, including affiliated universities, professional organizations, corporations, regulatory agencies, and end-user groups.
- Adopt tools from social psychology, organizational behavior, and the science of team science to conceptualize and address mesolevel problems in research ethics.
Concluding questions
What do you think? Our focus is U.S.-based and, if you are from another country, do our ideas resonate with you? What research norms have you found difficult to harmonize among team members in other research groups, institutions, and disciplines? Can you suggest competencies needed to ensure that a network performs research ethically? What similarities and differences do you see for leaders of large networks and of smaller research groups?
To find out more:
Wolf, S. M., Roehrig, G. H., Pruett, T. L., Uygun, K., Koch, A., McVan, C. C., Brister, E., Callier, S. L., Capron, A. M., Childress, J. F., Isasi, R., Maynard, A. D., Oye, K. A., Thompson, P. B. and Tiersch, R. R. (2026). Filling the Network Gap in Research Ethics: Analyzing Ethical Issues at Scale in Big Team Science. Hastings Center Report, 56, 4: 32-43. (Online – open access) (DOI): https://doi.org/10.1002/hast.70046
Use of Artificial Intelligence (AI) Statement: Artificial intelligence was not used in the development of this i2Insights contribution or the work on which the contribution is based. (For i2Insights policy on artificial intelligence please see https://i2insights.org/contributing-to-i2insights/guidelines-for-authors/#artificial-intelligence.)
Biography: Evelyn Brister PhD is Professor of Philosophy in the School of Public Affairs at Rochester Institute of Technology in Rochester, New York, USA. Her research is in philosophy of science, with a focus on interdisciplinarity and sustainability solutions.
Biography: Erin Shoemaker is a JD candidate at the University of Minnesota Law School in Minneapolis, Minnesota, USA and a Research Assistant at the University of Minnesota’s Consortium on Law and Values in Health, Environment and the Life Sciences. Her interests include law and bioethics, emerging technologies, and the ethical and legal challenges posed by interdisciplinary research and collaboration.
Biography: Susan M. Wolf JD is Regents Professor; McKnight Presidential Professor of Law, Medicine & Public Policy; Faegre Drinker Professor of Law; and Professor of Medicine at the University of Minnesota in Minneapolis, Minnesota, USA. She is a Principal Investigator of the NetEthics project. Her research focuses on ethical, legal, and societal issues in biomedicine and the implications of emerging technologies including genomics, neuroscience, and bioengineering.
Biography: Gillian H. Roehrig PhD is Professor of Curriculum and Instruction in the College of Education and Human Development at the University of Minnesota in Minneapolis, Minnesota, USA. She is a Principal Investigator of the NetEthics project. Her research interests include how teachers translate national and state standards into their classrooms, K-12 STEM integration, culturally-relevant STEM approaches for American Indian youth, chemistry education, and teacher professional learning.
Acknowledgment: Preparation of this i2Insights contribution was supported by National Science Foundation (NSF) award 2220611 for a project on “NetEthics: Building Tools and Training to Advance Responsible Conduct in Complex Research Networks Pioneering Novel Technologies” and NSF award EEC 1941543. All views expressed are those of the authors not the funder.
Ethics and Research Collaboration are a very natural fit. Sort of like Cinderella’s foot and the glass slipper.
Knowing what the collaborative principles are for conducting interdisciplinary and transdisciplinary research are not enough. Researchers must know how to put those principles into action – in other words demonstrating congruence between what is espoused and what is enacted.
In fact, the Responsible Conduct of Collaborative Research is an ethical imperative. To me this means living into a collaboration with others that results in raising all boats, not just some.
Productive conflict, setting clear expectations, holding self and others accountable, creating psychologically safe environments, and intentionally building trust so that differences (all of them among team members) can be surfaced and then used for greater research productivity, stronger team dynamics, and healthy relationships.
Thanks for taking the time to read this post and share your thoughts, Michelle. The ultimate goal, of course, is to produce good science and engineering, and especially research that serves societal goals. This means attending to our closest team members but also to building and maintaining productive, collaborative relationships with researchers at different institutions and creating processes that harmonize norms and expectations across a network. Your expression about “intentionally building trust” is at the heart of network ethics.
Good framework. You might to address acceptable AI use in it. This affects so many things–writing, authorship, accountability, data sharing, data analysis–to name a few.
That’s a great thought, David. The norms on AI are still so open—and changing so quickly—that it is an important area where members of dispersed research networks are likely to have different background assumptions about what constitutes responsible use. That variation in norms could lead to misunderstandings across the network, and as you note, it can affect many different research activities. This problem is complicated by additional factors, such as the variation in institutional policies concerning AI use (university policies, funder policies, journal policies) and the way that some AI platforms obscure data and knowledge sources. One of our goals with this research project has been to identify the gaps in research ethics for large networks, and that is certainly one of them.