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7 Recommendations

Framework for the Responsible Use of GenAI in Research at Ghent University

Protection of privacy, IP rights and confidential data

Ultimate accountability and critical mindset

Honesty with regard to substantial use

Compliance with legislation

Well-considered use

No sensitive tasks

Lifelong learning

Well-considered use

Do not use AI models flippantly, but only if their use brings significant added value. This does not mean that you cannot experiment responsibly with AI tools in order to learn how to use them more efficiently. Therefore, be aware of the ethical implications, such as the digital divide in AI literacy and access to certain (paid) models, the fact that AI models are often trained on illegally obtained data, and that they have a huge ecological footprint.

Bescherming van privacy, intellectuele eigendomsrechten en vertrouwelijke data

Respect and protect personal, privacy-sensitive, confidential and/or copyright-protected data. Check whether the sources of all generated information and multimedia are correctly displayed and never enter personal, privacy-sensitive, confidential or copyright-protected information into a GenAI tool without binding protection guarantees or explicit and informed consent. See also the research tips:

"GDPR: What should I take into account when developing or using AI?"

"GenAI: Copilot Chat as an AI assistant at Ghent University (choosing data security)"

No sensitive tasks

Do not outsource sensitive tasks to (Gen)AI, such as peer review, the evaluation of project proposals, etc., but maintain autonomy and independence in the assessment. For more information on the use of GenAI in the context of peer reviews and evaluation, consult the following research tip “GenAI: Using (Gen)AI for peer review and evaluations”.

Lifelong learning

GenAI is evolving rapidly, so keep learning and share your knowledge and expertise with others, both within and outside our institution. You can make use of the information and training opportunities offered by our institution; an overview of these can be found on our general webpage.

Ultimate accountability and critical mindset

Take ultimate accountability for the research quality and integrity of your scientific output. Maintain a critical mindset and verify the quality of the output, considering factors such as inaccuracies, hallucinations, bias, plagiarism, copyright or intellectual property rights infringements, and potential breaches of anonymity. In doing so, take into account the strengths, limitations, and constraints of GenAI systems and their operation.

Compliance with legislation

Inform yourself about and comply with national, European and international legislation. Not only the European AI Act (or AI Regulation) is of great importance here, but also other legislation, such as the General Data Protection Regulation (GDPR) and copyright legislation (EU and Belgium). For more information, see “What does the law say?” on the general webpage for GenAI at Ghent University.

Honesty with regard to substantial use

Be honest if you have made substantial use of (Gen)AI for your research and indicate this as you would also do for other employed tools (e.g. in the methodology section) in the manner and to the extent customary according to the accepted standards in your field (and, by extension, those of the journal or research funding institution).