The rapid adoption of Artificial Intelligence (AI) in research brings not only new possibilities, but also emerging risks and ethical challenges. This talk explores questionable practices in AI use including undisclosed reliance on generative AI in academic writing, misuse in peer review or grant applications, and the uncritical acceptance of AI-generated content.

Through real-world examples, we examine where common practices begin to compromise research integrity, data protection, and trust in scientific work.
The focus lies on researchers' individual responsibilities: distinguishing between helpful support and problematic shortcuts, and understanding the ethical boundaries of AI use.

The aim is to support researchers and illustrate the interplay between the FAIR framework and the privacy requirements in RDM, by showing that the two in fact supplement each other.
Thus, researchers can learn how to comply with both frameworks, identify legal issues in their research projects and use various tools and resources for self-education.
The session will also cover journal guidelines on using AI tools such as ChatGPT, and identify common challenges in complying with data policies.