7.5 Research Ethics

Regardless of the tools you use to find information to support your ideas, the strength of your reporting on your research findings will always lie with the quality and kind of support included, be it raw or analyzed data or qualitative information (see Chapter 7.3), and how you treat that information. In all cases, the ways in which you collect, analyze, and use data must be ethical and consistent with professional standards of safety, privacy, validity, and overall integrity. Lapses in any of these areas can not only lead to poor quality reports in an academic context (poor grades and academic dishonesty penalties), but in the workplace, these lapses can also lead to lawsuits, loss of job, and even criminal charges.  For this reason, making use of a research approach that is characterized by integrity and the pursuit of facts will help you to reveal information that can be used to support your ideas and create strongly argued points. Whether you are using LLMs and other AI tools in your research process or traditional methods, following these principles will go far in bolstering your own professional credibility:

• Ethical use: Researchers are obligated to make ethical use of all research materials, including those generated by LLMs and other AI tools. Ethical use involves ensuring accuracy, avoiding bias, promoting inclusivity, as well as citing and declaring sources. In addition, when humans are subjects of the research, practices that do no harm are required (more on this below).
• Accuracy: Since LLM output is known to often lack accuracy and to contain hallucinations, you must review all output that you use to ensure its accuracy. You also have an obligation to make accurate use of any research information by ensuring that the information represents the intent of the original author(s) when using secondary sources. When using data you generate yourself, you also have an obligation to ensure the integrity of the information.
• Corroboration: Corroboration is especially necessary when using LLM output. When LLMs make claims that are unsupported by accurate citations, researchers must verify them by analyzing reports where original research is published. In traditional research, corroboration of facts is necessary when a study is limited or if it raises questions.
• Declaration of AI Use and Citation: All research sources used in your reporting must be cited using standard methods like the APA, IEEE, or MLA style. When traditional citation methods are not applicable, such as in cases of LLM-human co-creation, researchers must declare their use of genAI applications, including model, mode, date, methods, and prompts.
• Diversity and Inclusion: Some factors become more nuanced given contextual, population, health, and economic considerations. Accounting for the needs and interests of various groups in your research practice will lead to a more inclusive approach to gathering information and analysis of findings.
• Privacy: When gathering, storing, and using data, you must abide by the Canadian federal and provincial privacy laws. Please refer to the Personal Information Protection and Electronic Documents Act (PIPEDA)  and Ontario’s Freedom of Information and Protection of Privacy Act (FIPPA) for more information.
• Transparency: Be transparent in your research methods. Most reporting documents include a Methods section where research methods are described. If you have made use of AI technologies, you must include that in the description of methods. Be specific as to which tools, formulas, databases, etc. you have employed. Keep in your records research documentation along with drafts, prompts, and outputs in case they are requested.
• Validity and reliability: Validity and reliability are qualities that your research information must have for it to support your ideas and withstand scrutiny. Validity refers to the “consistency and stability” of the research results, while reliability refers to the “accuracy with which a research measures what it intends to measure” (Salomao, 2023).

When Humans are Subjects of Your Research

Oftentimes, primary research will involve human subjects such as in stakeholder consultations including focus groups, interviews, surveys (see Chapter 7.4), psychological studies, and others. If you are collecting data from human participants, you are engaging in “human research” and you must be aware of and follow strict ethical guidelines of your academic institution or the company you represent.

In Canada, any post-secondary educational institution that receives funding from one of the three federal granting bodies must ensure that all research involving humans conducted at that institution complies with the Tri-Council Policy Statement (2018). As an example of institutional ethics requirements, you may want to consult Seneca’s Ethical Conduct for Research Involving Human Subjects Policy (2007). In addition, organizations more broadly in Canada must abide by the standards set out by the Human Research Standards Council and the Digital Governance Standards. These rules and standards are in place to protect people and communities from potential risk or harm from research and to ensure ethical conduct including the protection of privacy. Human research in Canada should align with principles expressed in the Belmont Report and summarized as follows by Last, Lemire, & Hagstrom-Schmidt, 2022):

. . .human subjects research is guided by three core principles outlined in the Belmont Report: respect for persons, beneficence, and justice (The Belmont Report, 1979). The first principle, respect for persons, means that researchers must respect the autonomy of research participants and provide protections against coercion, particularly for vulnerable populations. The second principle, beneficence, means that researchers have an obligation to enact the following rules: “(1) do not harm and (2) maximize possible benefits and minimize possible harms” (The Belmont Report, 1979). The third principle, justice, means that research participation should be distributed, rather than concentrated heavily on one population.

To ensure that researchers proceed with research involving humans using ethical methods, they must follow an approval process before conducting certain kinds of limited research (such as surveys, interviews, or other kinds of human-involved research). The approval process most often involves presenting their research plan before a Research Ethics Board (REB). REBs follow guidelines and procedures set out by organizations like the Human Research Standards Council and the Digital Governance Council and other regulatory and accreditation bodies. The REB will review the project plan and make recommendations to ensure that humans are treated ethically and that the proposed research is otherwise sound. Check with your organization’s REB prior to beginning a human-involved research project to ensure alignment with its policies.

Avoiding Research Ethics Violations

As a researcher, you are obligated to be aware of the many ways in which your research can fail due to ethical lapses or outright violations. When a considerable amount of time and effort goes into completing research, you would want to ensure that it is collected, treated, stored, and shared in ways that abide by the ethical standards.  Here in Figure 7.5.1 are many of the ethical lapses and violations that must be avoided:

The following is a brief explanation of these various lapses and intentional actions that can lead to questions surrounding ethical conduct in research:

No informed consent for data collection: Informed consent involves obtaining the consent of human participants prior to collecting information from them. The process involves researchers informing participants about the research goals and how the information will be used and protected. For example, when planning for a focus group or survey, you must inform the participants and respondents of the research goals, what information about them is being gathered, how it will be used and protected, and whether participation is voluntary or not. Consent can be explicit (as when participants check a box or apply their signature to agree to the process) or implicit as for surveys that include a statement that “completion of these survey questions imply consent.”  PIPEDA clearly explains how all organizations and institutions must by the law to protect people’s information.

No permissions obtained for data/information usage: Part of the informed consent process is to also request permission to make use of the data. When making that request, you must be transparent about how the data is going to be used so that participants in your research make an informed consent. According to the PIPEDA, researchers who make use of data in ways that are other than what is specified in the informed consent are violating the law.

Simultaneous and duplicate submissions (Uzon, 2013): A simultaneous or duplicate submission occurs when an author submits a research paper for consideration to two or more publications at the same time. They do this to save time in the process of peer review and to get their work published sooner than later. Such a practice is discouraged by journal publishers and can result in the immediate retraction of your paper if it is found to be published in two journals simultaneously.

Salami slicing: “The term Salami Slicing is used often within academia to refer to the needless separation of a single research study, attached dataset, and argument that should form a single publication, into two or several separate publications for submission in different journals” (Adams, 2022). Authors do this to increase the number of publications in which their work appears and to satisfy pressures to publish which is common in academic settings. Through this process they are also able to increase the odds of being published and obtain simultaneous feedback on various parts of their work.

Copyright infringement: Whether you are working with data or other types of information, publications, art and literary works, etc., if someone else created it then it belongs to them and is protected by copyright laws. It is a copyright infringement to make use of other people’s work in your research and reporting without giving them credit through in text mentions, citation, and documentation (Arnold & Levin, 2021).

LLMs problematize the citation practice, so when a source is unspecified or unclear, you should cite the LLM model when making use of a small amount of output. When making use of a large amount of output, you should be extensively revising and adding content to the output to effectively make it your own. You would then declare use of the LLM instead of citing. More on this topic in Unit 8.

Image manipulation: When using images created by others, it is important to avoid manipulating the images to either distort or misrepresent the information. However, manipulating images to improve clarity is an acceptable practice (Elsevir, 2024). Images must be used fairly in that their original meaning or intent is not altered when you make use of them.

Data fabrication and falsification (Elsevir, 2024): Data fabrication involves making up or creating data or other information to prove your hypothesis or point and support your arguments. Data falsification, on the other hand, involves manipulating existing data, information, as well as research-related procedures, measures, equipment, and materials to gain evidence that aligns with your perspective or argument. It includes ignoring data that obviously disproves or contradicts your ideas and that involves skewing or applying bias to the research. Both fabrication and falsification can have significant impact on research integrity and affect professional practices that have safety, health, financial, political, social, and moral implications. When these actions are determined to be intentional, therefore, they are also considered to be fraudulent activities.

Plagiarism: Plagiarism involves the deliberate use of someone else’s work and passing it off as your own (Arnold & Levin, 2021). Your college writing subjects, COM101 and COM111, spent considerable time and effort to give you an understanding of how and why to avoid academic integrity offences, as well as the consequences of doing so. The practices also extend into the workplace, so it is incumbent upon you to cite and document all information you use that belongs to someone else including when it is created by an LLM. If you would like to review information on plagiarism and other forms of cheating, consult Seneca Polytechnic’s Policy on Academic Integrity and Seneca’s Student Resources on Academic Integrity. Unit 8 of this text offers extensive information on how to avoid plagiarism issues and make ethical use of the work belonging to others.

(Plagiarism and You, 2020)

Authorship issues (CRT, 2025; The Royal Society, n.d.): Research is reported using various vehicles: conference presentations, professional meetings, and publications. These vehicles are evidence of the expertise, professionalization, and credibility of researchers. Research, when shared, can lead to employment, further research opportunities, funding, conference presentations, invited lectures, and other benefits. So, when researchers publish their work, they want their authorship to be fairly represented by being included in the by-line of their publications. However, the process may not be so simple arising to disputes and other misrepresentations. The Royal Society (n.d.) describes the issues as follows:

• Authorship disputes: Authorship disputes arise when two or more researchers who are involved in a range of research activities, including data analysis, investigation, and the like, are in disagreement about their contributions and the type of credit they should receive. CRT (CrediT) (2025) and The Royal Society (n.d.) recommend that contributions to the research be identified and assigned at the outset of a research project and that authorship, including designating the primary author, also be included in the discussions.
• Ghost authorship: Ghost authorship occurs when the name of someone who participated in the research and who would normally be considered an author is not included in the author list.
• Guest authorship: Guest authorship consists of the practice of including in the author list the name of an established and well-respected researcher or expert in the subject in the hopes that this name will boost the credibility of the research and increase the likelihood of publication.
• Gift authorship: Gift authorship consists of the practice of including the name of someone who did not contribute to the research but is included “perhaps to reward a collaborator, return a favor, or for some other personal or financial gain” (The Royal Society, n.d.).

Conflicts of interest: Conflicts of interest occur when researchers or their affiliates stand to gain advantage from the research outcomes (H2020, 2022). Any actual or perceived conflict of interest must be declared; otherwise, the research may be considered suspect and undergo scrutiny for potential conflict of interest violations and potential fraud. Publications routinely ask for declarations of conflicts of interest as a matter of transparency. If any potential for such conflict exists, it’s best to declare it to maintain your credibility.

Non-disclosure of safety procedures: When safety procedures must be followed to complete the research with reduced risk to the researchers and participants, those procedures must be shared with them. It is how they can protect their own safety. A lack of disclosure of those safety procedures and other important information constitutes a withholding of critical information and is considered unethical.

If you approach your research with good intentions and a proactive mindset that is determined to do the right thing all the way through, you should have positive outcomes. Following the principles for ethical research and avoiding the ethical violations that will call your work into question will enable you to focus on the work at hand rather than on often time-consuming scrutiny.

References

Adams, N. N. (2022). Salami Slicing: clarifying common misconceptions for social science early-career researchers | SN Social Sciences (2)

Arnold, M., and Levin, S. (2021). Plagiarism vs Copyright Infringement | Copyright Alliance

CRT. (2025).  CRediT – Contributor Role Taxonomy

Digital Governance Council. (2024). Digital Governance Council –

Elsevir. (2024). Research Fraud: Falsification and Fabrication of Data

Enago Academy. (2021). Research and publication ethics [Infographic]. Research ethics and misconduct: What researchers need to know.  https://www.enago.com/academy/principles-of-ethical-research/

Government of Canada. (2018/2020, February 19, modified). Tri-Council Policy Statement: Ethical conduct for research involving humans. Panel on Research Ethics.  https://ethics.gc.ca/eng/tcps2-eptc2_2018_introduction.html

H2020. (2022). H2020 INTEGRITY – Conflict of interest in research: what is it and why it matters?

Human Research Standards Council. (n.d.) Home – HRSO

Mollick, E. (2024, October 20). Thinking Like an AI – by Ethan Mollick – One Useful Thing Substack.

National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (1979, 18 April). The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects Research, U.S. Department of Health, Education, and Welfare https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html ↵

Office of the Privacy Commissioner of Canada. (n.d.) The Personal Information Protection and Electronic Documents Act (PIPEDA) – Office of the Privacy Commissioner of Canada

Seneca College. (2007, October 31). Ethical Conduct for Research Involving Human Subjects Policy. https://www.senecacollege.ca/about/policies/ethical-conduct-for-research-involving-human-subjects-policy.html