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Generative Artificial Intelligence refers to computer systems that can create new content such as text, images, code, audio, or summaries by learning patterns from large amounts of existing data.
In higher education terms, GenAI:
Does not “know” things in a human sense
Predicts likely outputs based on prompts and context
Can support thinking, drafting, planning, explaining, and revising
Still requires human judgement, disciplinary knowledge, and ethical use
A helpful way to describe it to students and staff is:
GenAI is a powerful assistant that can help you think, draft, and explore ideas—but it doesn’t replace understanding, responsibility, or academic judgement.
The system is trained on large data sets from three primary sources of information:
- Information that is publicly available on the internet
- Information that is licenced from third parties
- Information that users or human trainers provide
University recognises that a variety of Generative AI tools can and are being used. These should be used with caution however, because external platforms generally pose higher risks in terms of data security and are commonly subject to paywalls or subscription models, raising concerns about fairness and accessibility. In addition, the lifespan of apps in the GenAi space is unpredictable given that they are susceptible to market forces and can quickly become outdated and/or retired by their developer.
As part of our current use of Microsoft 365, the University has access to Microsoft Copilot, an AI assistant embedded within everyday applications like Word, PowerPoint, Excel, Outlook and Teams
Operate within the University’s Microsoft environment, providing stronger assurances around data protection and governance
Avoids paywalls and personal subscription costs, supporting fair and equitable access for all students and staff
Integrates directly into everyday academic workflows, reducing the need to upload work to third-party platforms
Limitations
The most rapid evolution in these tools has been natural language conversational interfaces which appear to respond in an intelligent human like way.
The tools however do lack other attributes which we consider human, including morality, critical thought, or common-sense judgement. The tools provide outputs based on patterns contained within training data. These outputs may contain bias, be incomplete, out of date, or in some cases entirely false.
While AI tools may be useful for initial planning of work, and for the generation of ideas, apply caution in their use.
They should enhance, but not replace your work outputs.
Always apply critical judgment when reviewing the content generated by Gen AI tools, and be aware of their limitations:
Some of the current limitations of Large Language Model (LLM) AI tools include:
- The tools do not understand the meaning of the words they produce.
- The tools will often generate arguments that are factually wrong.
- The tools will often generate false references and quotations.
- Content generated is not checked for accuracy.
- The tools can distort the truth and emphasise the strength of an opposing argument.
- The tools may struggle to maintain contextual understanding over extended conversations however, there are current developments in this area.
- The tools may struggle to generate responses based on visual and auditory input.
- Generated content can include harmful bias and reinforce stereotypes. These biases can be reinforced through further human interaction with the model.
- The tools rely heavily on data access to generate responses. This has led to concerns about data privacy
- The models are trained on a data set from a Western English-speaking perspective again reinforcing particular perspectives. Developing skills to prompt AI tools is likely to be a useful digital skill but users should also understand the limitations, remain open, curious, and critical when making judgements about the accuracy of the content generated.
