Info for Students

Artificial Intelligence (AI) is the work of computers to mimic, replicate and create the complex responses and behaviours of humans. Using machine learning, AI can produce human-like text, images and information, and it can respond to specific queries. 

The availability of a variety of AI platforms is rapidly changing. ChatGPT, Google Bard, CoPilot and Notion are some of the currently popular tools being used, but as the technology grows there will be increased competition amongst and change within sector-leading platforms. The platforms that produce text are more accurately known as Large Language Models (LLM), but 'AI' is more commonly used to describe these tools. 

For University-level study and research, AI and its many uses pose a challenge to how we prove our learning for assessment in a way that has integrity and merit. 

The key element of AI is its ability to mimic human-like responses to queries, questions and interrogations. The responses are, however, only replications of human-like output. AI does not have the ability to critique, evaluate or prioritise information.

More significantly, AI does not have the ability to fact-check; as a result, AI can often produce results that are factually incorrect. You should never rely on AI to produce accurate, truthful, critical or reflective information, results of analysis.   

This page is presented as a way of ensuring you engage with AI in an ethical, transparent manner. This guidance does not prohibit the use of AI in your research and writing process; instead, it outlines how the University of Glasgow believes you can make use of the strengths of AI while maintaining good academic practice, rigour and integrity in your submitted work. 

The University of Glasgow’s position on the inappropriate use of AI in research and writing is clear. University policy is that all students are marked and assessed 'in recognition of a student's personal achievement. All work submitted by students for assessment is accepted on the understanding that it is the student's own effort'.

Work that is therefore not your own effort – in other words, work submitted that is the result of the work of AI – does not meet this crucial requirement for our assessments.

The University Regulations on plagiarism define it as: 

'the submission or presentation of work, in any form, which is not one's own, without acknowledgement of the sources' (Plagiarism Statement - see section 32.2)

As with all pieces of assessment submitted, then, we expect that your work is a reflection of your own effort. We discuss below some of the ways in which AI can be of benefit to the research and writing process, but it is your responsibility to ensure that the work submitted is a true reflection of your effort. 

That is to say, all your submitted work must be of your own creation, your own critical evaluation process, and your own experience. We expect your submitted work to clearly and transparently acknowledge any sources – including AI – that have helped you reach your conclusion or that have added to the work in any way.  

The fundamental rule with AI and academic integrity is this: 

If you make use of AI at any point in your research or writing process, no matter at what stage, you must acknowledge the use of that source/platform as you would any other piece of evidence/material in your submission.  

We strongly recommend, however, that you treat AI with caution: AI tools do not know the meaning of what they produce, cannot be critical and evaluative, and are prone to biases, inaccuracies and mistakes. 

If we use any form of AI, it must be with the understanding that it does not understand what things mean. This is an important first step in engaging with AI in a successful way.  

The difference between our intelligence and AI is, to put it simply: we understand meanings, contexts, what things say and do, and the connections between different pieces of information. AI cannot do this. 

AI platforms can, however, help us with some of the steps of our work process. So, what can AI do? 

• AI can provide a quick summary of information. 
  • AI can provide details on large volumes of information in a quick time period, but there are dangers involved here around inaccuracies and made-up information. 
  • If using AI in this way, think of it as the first step. The second step is to check for accuracy, critique the outputs, and ensure you never rely simply on the original outputs. 
• AI can identify key points in texts 
  • AI can produce output of key points in text by scanning the language therein. This can be a useful starting point with reading. 
  • If using AI in this way, again think of it as a first step. AI does not understand what the text means, and it cannot therefore critique or evaluate any of its outputs. It uses language models to predict outputs based on the highest probability of the next word. So, when identifying key points in texts, AI uses this probability method to display key points based on the words used in the text. As with abstracts for academic journal articles, be aware that a short summary loses much of the nuance, subtlety, counterpoint and critique within a whole piece of reading, so make sure to also read fully to confirm (or otherwise) what the brief summary gave you for your starting point.
• AI can help you refine your wording 
  • Think of AI here as a kind-of conversation partner: you can ask it to rework some writing to enhance clarity. You can ask it to refine the output to make the text more simplistic, more complex, longer, shorter, and so on.
  • Do not enter entire essays or paragraphs; use the method to help improve the language of words, phrases or individual sentences. You must ask the tool to offer you an explanation of why it has made the suggestions that it has so that you can use this advice to learn how to improve your own writing the first time around in the future. AI tools commonly use more adjectives or adverbs than would be suitable for an academic essay, even if your prompt asks specifically for a response in an academic tone, so make sure that you are happy with any suggestions before adapting them into your own piece of work. Again: do not create entire paragraphs from individually AI-constructed sentences; the work must be your own.
  • Importantly, however, you must remember that AI uses predictions of the most likely next word based on what has been found in the material used to train whichever tool you are using. This is all it is doing: it simulates human responses, and it does not have the true intelligence capacity to understand why things might be right, might be wrong, might be stronger, or might be weaker.

Separately from AI, there are plenty of other digital tools that can help with your academic work. These resources and tools do not mimic human language in the way AI does, but they are powerful and useful tools. EndNote, for example, helps you catalogue your references and resources, while software like ResearchRabbit, Google Scholar, etc., can help with searching for resources.  

Use of these digital tools is a part of modern-day study. If you have questions about using digital tools for study or research, you can speak with SLD by making a one-to-one appointment.

Current AI tools are limited in the capacity to create meaning that is true, accurate, critical and responsive. You must judge any outputs from AI tools with scepticism, suspicion and a critical eye. 

Key problems with AI include: 

• AI gets things wrong.
  • AI will produce incorrect (and sometimes nonsensical) outputs.
  • AI does not know right/correct from wrong, and will present all outputs as if they are equally valid and true.
• AI is biased.
  • AI tools reflect, prioritise and enhance biases and stereotypes.  
  • AI is not rational and does not understand the complexities around the information available on the internet. It therefore cannot judge inaccurate, offensive statements.
• AI makes things up. 
  • Called 'hallucinations', some AI tools will make up false references to texts that do not exist. While these references often look to be real, a quick search will reveal that the supposed reference or data does not exist.
  • This is because AI tools are simply predicting the most likely next word each time – think of it like asking your phone to write a sentence based on clicking the next autocorrect word each time.
• AI tools cannot access all the necessary data and information.
  • AI tools cannot access anything behind a paywall. For your academic work, the University Library subscribes to a massive collection of academic texts. AI cannot access these paid resources, and so it does not have the ability to reproduce any information from those texts.
  • Many AI tools also do not have access to the current state of the internet, and therefore will not be trained on the most recent information.