Historically, cheating in universities has been limited to smuggling notes into exams, unauthorized cooperation, plagiarism and using ghost writers. New improvements in natural language processing now allow students to easily generate text, that is both unique and, in many ways, indistinguishable from what a human would create. These texts can then be submitted with little to no risk of getting caught by anti-cheating software.

There are currently a multitude of such text generators online, which vary in ease of use, cost and capabilities. They are capable enough to generate unique text which will evade plagiarism-tools employed by universities. If you combine relatively cheap pricing, ease of use, pressure to perform well in school and low risk of detection. It is not too difficult to imagine that students will use tools like these to cheat.

This thesis mainly focuses on whether humans can differentiate AI-generated essays from human written ones and what countermeasures can be used to hinder its use. By giving teachers at Halmstad University human and AI-generated text; then asking them to guess the source of text presented. The experiment concluded that teachers' ability to differentiate AI-generated text from human written text could not be proven. 

This thesis also surveys the currently available detection methods for AI-generated text and determines that they are not sufficient in their current form. Lastly, this thesis showcases alternative examination methods that could be used instead of essay-style examinations.