Guidelines on using generative artificial intelligence for research at HEC Montreal
1. Preamble
1.1. These research-specific guidelines are in addition to the Guidelines on using Generative Artificial Intelligence (GenAI) at HEC Montréal.
1.2. They are intended for anyone who conducts or supports research activities at any stage of a research project, be it formulating the research question, planning and conducting the research, collecting data, analysing the research or properly managing research funds.
1.3. They apply to researchers employed by HEC Montréal as well as to students who have been admitted to one of the School’s programs.
1.4. Accordingly, the term “researcher” used in these Guidelines refers to HEC Montréal’s students as well as the professors, full-time lecturers , and researchers it employs1.
1.5 Anyone doing research or supervising a student doing research is asked to follow these guidelines.
2. Principle of transparency
2.1. General principal
All researchers must inform themselves and comply with the rules of good conduct and transparency for using GenAI tools. These rules can be issued by HEC Montréal, publishing houses, granting agencies, or other institutions concerned with the products of research. Respect for transparency contributes to scientific credibility, accountability, and academic integrity.
2.2.1. Specific application for students conducting research in their study program
2.2.1. Transparency with the supervisory committee
Before beginning their research, students must discuss and come to an agreement with their supervisor(s) on how they will use GenAI tools. A new agreement must be reached if there are any changes to the initially agreed-upon use of GenAI.
2.2.2. Transparency with readers
In all deliverables resulting from research (e.g., dissertations, comprehensive exams, theses, supervised projects), in addition to the applicable rules for quotes and citing sources, there must be a clear statement distinguishing the student’s personal contributions from those drawn from GenAI tools, where applicable.
3. Principle of responsibility
3.1. General principal
Whoever identifies themself as the author is ultimately responsible for the deliverable. The use of GenAI does not limit this responsibility in any way. This person is entirely accountable for any errors, omissions, or inappropriate use of GenAI.
3.2. Areas of responsibility
3.2.1. Content quality
GenAI tools can produce imprecise content or inconsistent quality. The person using GenAI is responsible for checking, validating, and guaranteeing that the data and analyses in the deliverable are high quality and relevant.
3.2.2. Intellectual property and protection of personal information
GenAI tools can reuse the data entered in queries to train their models, which entails risk that could lead to:
- Unauthorized reuse of elements protected by intellectual property rights
- Involuntary disclosure of personal information.
Anyone using GenAI must, therefore:
- Refrain from entering sensitive, personal, or copyrighted information without explicit guarantees that the information will remain confidential and not be reused.
- Check the security and privacy settings offered by the tool to ensure they are appropriate for the intended use.
- Be aware of and comply with the legal, regulatory, and institutional provisions applicable to intellectual property and data protection.
3.2.3. Required training and skills
Researchers who plan to use GenAI in their research, or who plan to supervise students wishing to use these tools, are responsible for acquiring the basic skills required to use such tools appropriately.
1 For consistency, the description of the scope is based on that of the “Policy for the Responsible Conduct of Research”.