Generative AI is a tool that can help us in our daily lives, at work or in our studies. As with any other tool, ethical, evaluative and appropriate use is the key point.
- Integrity
- Can AI be used in an assigmnet or a project? If so, what for? And how should it be reported?
- Mis- and disinformation
-
Misinformation is incomplete or incorrect information, is given inadvertently and is not intended to mislead.
-
Disinformation is the deliberate distribution of false information, which can be motivated by, among other things, political and social influence, financial gain and malicious intent.
- Information literacy
- AI tools do not necessarily report the original sources they use, nor do they necessarily use sources that meet the requirements of scientific writing. In some cases, these sources have proven to be non-existent or inaccurate. If you use a tool that produces some elements of your work, the person reviewing the work needs to know what parts are yours and what is from elsewhere.
- AI-powered search tools may seem to make scientific research easy and fast. However, from the student's perspective, this can mean that the student is not learning important skills, such as the basic skills of scientific research like information retrieval, critical evaluation and problem solving.
- Protection of privacy
- To use generative AI applications you usually have to create an account, which allows for data collection. This is a privacy issue. AI tools may require you to provide a phone number or other personal information. Users should be careful about what information they share when creating an account on the web.
- Please read the program's privacy policy and terms of use carefully. Remember that when you use the tools, your conversations are typically stored by the tool and used for that tool's purposes.
- Authors' copyrights
- In some cases, AI tools can use online material without the permission of the authors. Respecting copyright is a part of academic good scientific practice, which is why it is very important to be critical of the use of such tools in academic work.
- Environmental issues
-
The environmental challenges of AI and digitalization include increasing energy consumption. Developing and maintaining language models also require significant amounts of water, which is used, among other things, to cool data center servers. Consider when the use of AI is necessary.
Discuss with your course teacher or seminar tutor well in advance whether (and which) AI applications are allowed for information searching for your work.