The rapid development of generative AI (GenAI) raises new questions in higher education such as: What should be the university policy regarding GenAI? How ought courses be redesigned for fair and resilient assessment? What the added pedagogical and didactical values when involving GenAI in teaching and learning activities? Different universities have rapidly created and presented contradictory standpoints and draft policies, and teachers show different opinions regarding the pros and cons of GenAI. This study has been carried out with a student perspective, where 16 students have been examining their own Master's programme on sustainable information provision. Students have assessed the assessment in their previous courses in the Master's programme. The aim of the study is to investigate how sustainable course activities and assignment are, and to explore how GenAI tools might support and facilitate teaching and learning activities. Moreover, the students were given the task to test detection software on GenAI generated solutions to assignments in chosen Master's courses. Students conducted these tasks as a part of a 7.5 ECTS project course in the same Master's programme as the investigated courses are a part of. For inspiration and for background information on artificial intelligence to the project work students participated in the first Symposium on AI Opportunities and Challenges (SAIOC) in December 2023. Data have been gathered from reports of 3 group projects where 16 students have investigated 5 freely chosen courses in the programme in each group work. Beside from testing GenAI tools in existing activities and assignments students also interviewed the subject matter experts that are responsible for the chosen courses. Results were firstly analysed and presented in group reports, combined with 16 individual reflection essays. Regarding the individual essays students were instructed to bring up ethical perspectives on GenAI in higher education, and also to present and discuss suggestions for how the current course design and assignments better could be redesigned for improved sustainability and fairness. Finally, all the group reports and the individual reflection essays were thematically analysed by the author, who also is the subject matter expert and main teacher for the project course. Findings show that many of the existing assignments in the Master's programme could be partly solved with different GenAI tools. The AI generated solutions showed different levels of quality and correctness for different types of activities and assignments. An ethical concern that many student essays brought up was the relatively poor quality of the tested detection software. A question in one of the essays was if teachers should use detection software with an accuracy rate just above 50% to evaluate student submissions. The recommendations from both the students and the author are to provide clear instructions about when GenAI is allowed and not in course activities, and to redesign the course structure for continuous assessment. With or without GenAI tools, a continuous assessment where the whole study path through a course is assessed, and not only isolated submissions, would strengthen fairness and sustainability. Finally, several students suggest oral examinations as a complement to the existing assessment methods, even if their findings showed that GenAI tools can be used to prepare oral presentations.