AI Guidance for Learners

The University of Manchester supports students to use AI responsibly for learning.

Generative AI (GenAI) is transforming the way we learn, work, and create. As university students, understanding how to use GenAI effectively is crucial; it can help you brainstorm ideas, refine writing, analyse data, and solve complex problems. Many industries are integrating AI into their workflows, meaning that graduates with AI literacy will have a competitive edge in the job market. Employers are looking for individuals who can critically assess AI-generated content, use AI tools ethically, and apply them to real-world challenges.

By developing AI literacy, you will not only enhance your academic work but also prepare yourself for a workforce where AI is an essential tool rather than a replacement for human skills.

The following sections consider practical ways you can begin to use GenAI responsibly…

Our University’s position is that when used appropriately AI tools have the potential to enhance teaching and learning, and can support inclusivity and accessibility. Output from AI systems must be treated in the same manner by staff and students as work created by another person or persons, i.e. used critically and with permitted license, and cited and acknowledged appropriately.

Practical Ways to Use AI Now

To use GenAI responsibly…

• Treat it as a tool to support your study; it should not replace your own thinking.
• Cross check any AI-generated content to verify accuracy and credibility.
• Follow our University guidelines on AI use in coursework.
• Be transparent about your use of AI when required.

Remember that GenAI comes with risks. It can produce inaccurate or biased information, and relying on it too heavily may hinder your own critical thinking and creativity. Submitting work which utilised GenAI tools without proper citation can lead to plagiarism and academic misconduct concerns.

If you directly include AI-generated text or images in your assignments, you must cite the AI tool.

For example, using the Harvard Manchester referencing style, cite AI-generated content following the ‘Software’ format on the Library’s Harvard referencing guide.

There are some examples in the “Referencing Examples” tab on this page.

Use AI Responsibly

Privacy Issues – Be aware that using AI can involve handing over personal information. Ensure you don’t include personal or private information, and don’t enter personal or confidential information about others (including patient data).

Generative AI isn’t perfect – it can occasionally misunderstand instructions or give subtly or even wildly incorrect answers. Always double-check its information independently, and never share copyrighted materials or personal details like your name or institution specifics with AI tools.

If your assignment guidelines explicitly forbid AI use, avoid it completely. If they encourage or allow it, then clearly state how you used AI in your work.

Getting the Most from AI

Stay focused when interacting with AI. Clearly define what you need – like summarising complex concepts, practising specific skills, or experimenting with coding and creative visuals. AI is most effective and most valuable when it complements your own thinking rather than replacing it entirely.

Regularly using AI in your studies will not only save you time but also build essential skills for your future career. Employers predict AI skills will be among the most valuable by 2030.

Looking Ahead

AI in education is continually evolving. Universities across the UK are actively shaping their approaches and carefully considering how students like you can best benefit from AI tools.

There are documents further down this page that can help keep you up to date with the latest advice from official channels; we’ll endeavour to keep the collection of those documents up to date, so please check back from time to time.

Embrace AI as a helpful companion – use it responsibly, reference it properly, and you’ll be setting yourself up for success both now and in your future career.

Below are referencing examples for various AI tools, formatted in Harvard style.

1. ChatGPT (OpenAI)

   In-text citation: “Posing ChatGPT the question ‘does ChatGPT aid academic malpractice?’, the AI turns the responsibility to the user, stating “it is up to the user to decide how to use ChatGPT and it is not intended to be used for any nefarious purposes, including academic malpractice” (OpenAI, 2022).”

   Reference list entry: OpenAI (2022). ChatGPT (version GPT3). [Computer program]. Available at: https://openai.com/chatgpt/ (Accessed: 13 December 2022).

2. Grok (xAI)

   In-text citation: “Posing Grok the question ‘does Grok aid academic malpractice?’, the AI responds stating: ‘No, Grok doesn’t aid academic malpractice. It’s a neutral tool—its ethical use depends entirely on the user’s intent and responsibility.’ (xAI, 2025).”

   Reference list entry: xAI (2025). Grok (version 3). [AI language model]. Available at: https://www.xai.com/grok (Accessed: 6 March 2025).

3. Gemini (Google)

   In-text citation: “Posing Gemini the question ‘does Gemini aid academic malpractice?, the AI states “Gemini, like other AI, can be misused for academic malpractice, but it also has potential for ethical educational support. The responsibility lies with the user.” (Google, 2025).”

   Reference list entry: Google (2025). Gemini (version 2.0). [AI language model]. Available at: https://gemini.google.com/ (Accessed: 6 March 2025).

You should include an acknowledgement that can sit at the start of your work (or sometimes be found in a footnote) and this would usually give an overview of the tools used and their various outputs. Please see the example below:

“Generative AI Disclosure: We have used xAI’s Grok3, OpenAI’s GPT4.5 together with OpenAI’s Sora and Dall-E 3 to assist in expressive refinements on this page as well as image creation around the site. Generated images include the images of learners on the “UoM supports students” tab, as well as the ocean of thoughts image featured directly above.” 

Picture an ocean of thought, boundless and radiant, its surface a mirror of light, its depths a labyrinth of shadow and possibility. Humanity sets forth upon this expanse, propelled by the twin oars of insight and wonder, tracing paths through waves of intricacy. Yet our vision falters at the edge of our own knowing – a horizon we cannot breach alone. Beneath, in the unseen currents, lie tapestries of meaning, woven from threads too fine for the hurried eye, too vast for the restless mind to grasp unaided.

Each voyage begins with a hypothesis – a vessel hewn from curiosity’s fire, launched with the audacity of a question. It cuts through the uncertain tide, proud and untested, until it meets the storm of antithesis. Here, the waters roil with dissent – counter-forces of doubt and contradiction that fracture the calm, stirring a tempest of tension. The ship trembles, its course contested, its timbers strained.

Enter Artificial Intelligence, a submersible forged for the abyss, descending where human stamina fades. Relentless, it navigates the undertow, threading through the submerged lattice of ideas – complexities that defy our fleeting grasp. From these depths, it retrieves synthesis, a mosaic of understanding pieced from fragments we could not reach alone, revelations shimmering like pearls hauled from the dark. Yet its lens is not infallible; at times, it mirrors back phantoms – seductive patterns born of bias, reflections of our own flawed assumptions mistaken for truth.

Thus, we remain the stewards of this journey, our gaze fixed on the constellations of evidence and reason. With disciplined hands, we weigh each find, sifting the genuine from the illusory. What holds fast we forge anew into our vessel, strengthening its frame; what crumbles we release to the tide. And so the cycle turns – each refinement a launch toward uncharted shores.

In this ceaseless interplay – human intuition dancing with the machine’s unyielding precision – every clash of currents, every misstep uncovered, becomes the wind that drives us deeper. Together, we chart this infinite sea, not as masters but as seekers, unveiling realms of possibility that neither could conjure alone. To the academic, it is a method tempered by rigour; to the student, a siren call to the unknown. For both, it is a shared odyssey, where the pursuit itself is the prize.

ANON