Ethical Considerations
Ethical considerations in research refer to the principles and standards that ensure the protection of participants, the integrity of data, and the honesty of the research process. They guide how researchers collect, analyse, and report data in a responsible and transparent manner.
On this page:
- Ethical Considerations in the Use of AI
- Core Principles of Ethical Considerations
- When to Address Ethical Considerations
Ethical Considerations in the Use of AI
The increasing use of AI tools such as ChatGPT in academic research introduces new ethical considerations that must be carefully addressed. Most common ethical risks of AI use include plagiarism or unintentional duplication and over-reliance on AI-generated content. Moreover, inclusion of inaccurate or fabricated information and the lack of transparency in the research process is also risks AI use can cause in your work.
When using AI in your dissertation, you should:
- Ensure that AI-generated content is not presented as your own original thinking without modification
- Use AI tools as support tools, not as substitutes for critical analysis
- Verify the accuracy and reliability of any information generated by AI
- Follow your university’s guidelines regarding AI usage and disclosure
- Clearly acknowledge the use of AI tools where required
AI can assist your research (which you should acknowledge), but you remain fully responsible for the accuracy, originality, and integrity of your work
Core Principles of Ethical Consideration
Ethical considerations are one of the most important parts of any research project and must be clearly addressed in your dissertation.
Ethical research in business studies involving primary data collection is based on the following nine core principles:
- No harm to participants – physical, psychological, or emotional
- Informed consent – participants must fully understand the study
- Voluntary participation – no pressure or coercion
- Confidentiality and anonymity – identities must be protected
- Honesty and transparency – no deception or misleading information
- Data integrity – findings must not be manipulated or biased
- Proper referencing – all sources must be acknowledged
- Compliance with regulations – follow institutional and legal requirements
- Responsible use of AI tools – any use of AI (e.g. ChatGPT) must support the research process without replacing the researcher’s own critical thinking. AI-generated content should be reviewed, verified, and used in accordance with university guidelines, with appropriate disclosure where required.
If you research is desk-based and doesn’t involve primary data collection, then only principles 5-9 from above list will apply to your case.
In your dissertation you have to discuss and each of these principles and clearly state that you have adhered to all of them. And this should be true.
Most universities have their own Code of Ethical Practice. It is critically important for you to thoroughly adhere to this code in every aspect of your research and declare your adherence in ethical considerations part of your dissertation.
When to Address Ethical Considerations
Ethical considerations must be addressed in all types of research, but their importance varies depending on the research design.
You should:
- Address full ethical considerations when collecting primary data (e.g. interviews, surveys)
- Focus on data integrity and referencing when using secondary data only
- Pay special attention to ethics when dealing with sensitive topics or vulnerable groups
- Follow university-specific ethical guidelines in all cases
Failure to address ethical considerations properly can undermine the credibility of the entire research
My e-book, How to Write a Dissertation: A Step-by-Step System to Plan, Write and Defend Your Dissertation in the age of AI contains discussions of theory and application of research philosophy. The e-bookalso explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research approach, research design, methods of data collection and data analysis are explained in this e-book in simple words.
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Preparing to Defend Your Methodology?
Understanding research design is one thing. Defending it under examination is another.
If you would like structured guidance on how to justify your methodological choices, respond to challenging viva questions, address limitations confidently, and navigate academic integrity in the AI era, you may find the following resource helpful:
The manual provides a structured system for aligning your research design, strengthening your justifications, and preparing for defense scenarios with clarity and confidence.
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John Dudovskiy
[1] Bryman, A. & Bell, E. (2007) “Business Research Methods”, 2nd edition. Oxford University Press.
[2] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited.