Appendix 1: AI in Research Guidelines
AI in Research Guidelines
Accountability and Responsibility
- Accountability rests with the researcher/author/grant applicant and/or research administrator.
- Be aware of and adhere to any applicable policies and guidelines of the funding body and/or institution.
- Obtain necessary permissions if required.
- Human oversight is mandatory, including ensuring the accuracy and appropriateness of AI-generated results to the best of one’s ability.
Research Design and Implementation
- Clearly document AI methodologies, datasets, and algorithms used.
- Implement strategies to identify and mitigate biases in AI systems.
Informed Consent
- Obtain informed consent from participants before collecting or analyzing their data with the assistance of AI tools. Special consideration should be given to security issues relating to data analysis by AI tools.
- Safeguard personal data and ensure compliance with relevant privacy regulations.
Peer Review
- For Fanshawe employees performing peer review as part of their duties to protect the privacy and potential intellectual property of applicants, AI tools may not be used in the review process (e.g. Research & Innovation Fund (RIF), Research Ethics Board (REB), etc.)
Transparency
- If required, disclose the use of AI tools in the application and/or research process.
- This may be a conversation with a manager, project collaborators (co-investigators, industry partners, classmates, etc.)
- This may be formal disclosure (to the funding body, industry partner, publisher, instructor, etc.) in the form of a citation or acknowledgement.
- Disclosure may include citation/reference/footnotes/acknowledgement or inclusion of prompts used.
Data Privacy and Security:
- It is the responsibility of the researcher to ensure compliance with relevant privacy regulations (e.g. institutional, federal, funder).
- To the best of your ability and abiding by current protocols, safeguard the personal data of project participants and industry partners.
- Do not enter confidential, personal, or proprietary data.