These tips are not a policy on detecting AI writing, and it is important to follow university and programme policy on the use and detection of AI. These tips are less about pattern recognition or catching students, and more about considering what you value in good writing and what kind of writers you want your students to become.
We are also working on a Canvas course with activities to practise spotting AI writing. Send us an email at alp.sgw@vu.nl if you would like to be added to that course when it is ready.
We will explore what current research says about common tendencies of AI-generated writing. But first, some disclaimers:
- Many of these tendencies aren’t inherently bad and are often employed by skilful writers. AI tools have been trained on a large amount of data, and much of it represents good writing. Some of the tendencies are, however, more problematic.
- These tendencies aren’t a means to detect inappropriate AI use and fraud. Human writing can also include these tendencies, and many courses allow AI tools for editing, which, just like text generation, can produce some of these tendencies. Ultimately, it is important to know and follow the university and programme policies on inappropriate AI usage. But recognising AI text tendencies can give you confidence in your judgements about writing and in your ability to comment on the quality of the writing.
- The technology is constantly evolving. Any description of the tendencies of AI writing tools is just a snapshot of the current situation. These tendencies will continue to change. Furthermore, as AI-generated texts become more common, these trends may influence human writing. For example, writers across social media, news, and blogs have noted that AI tools often use the em dash—a long dash that marks a break or adds emphasis. As a result, some writers now use it deliberately, while others avoid it because they worry that their writing will look AI-generated.
- These are simply tendencies. Not all texts produced by AI writing tools have these features, and AI humaniser tools and prompting can remove some of them.
With those disclaimers out of the way, let’s examine what the some of the current research says about the tendencies of AI generated text. We’ll outline the linguistic, structural and content clues that have been identified through statistical linguistic analysis. We’ll also look at clues identified through more qualitative research relying on expert and instructor opinion. Click on the headings below to read about the clues in each area.