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Using Generative AI Tools in Academic Work

This guide is aimed at students who wish to know how generative AI tools may be used to help with academic work. It currently covers using AI to help with literature searching and summarising. It also covers how to use AI ethically and responsibly.

What is generative AI?

Generative AI tools are programs that can generate new content like text, images, audio, and video. They do this in an automated way based on given inputs and parameters.

There are many different kinds of AI tool with multiple uses: 

Generate human-like text and conduct conversational dialogs (e.g. ChatGPT, Copilot, Claude and Gemini)

​​​​​​​ Assist researchers by finding and summarising research papers (e.g. Elicit, Semantic Scholar etc.)

​​​​​​​ Create images from text descriptions (e.g. DALL-E and Stable Diffusion )

 Generate human-like voices and convert text into natural speech (e.g. Jasper and Whisper)

 Generate new music compositions and songs based on different genres, instruments, etc. (e.g. MuseNet and Amper Music)

​​​​​​​ Deepfakes (algorithms that can swap faces in images and video or generate fabricated video/audio that resembles real people)

Advantages of using AI in academic work

  • AI tools can generate novel, high-quality content fast. This means they can help with generating new ideas and approaches, such as generating textual mind maps, plans, definitions, and explanations.
  • They can create personalised recommendations and content and can generate content specific to your task.
  • They can assist with processing and interpreting information. They can both produce information based on your prompts and support your interpretation of information by generating summaries and critiques.
  • They can automate tasks that require creativity. For example, tools such as DALL-E can generate images very quickly that would be likely to take a human a much longer time to create with a graphics editor.


Next Steps

Your next step is to learn how AI tools can help with literature searching.Next page arrow

  1. Using AI tools to support your work
  2. Literature searching with AI
  3. critical analysis with AI
  4. Using AI ethically and responsibly
  5. Suggested resources

Disadvantages of using AI in academic work

  • Results can be nonsensical or inappropriate. AI models can confidently present incorrect or false information as factual (also know as hallucinations).
  • Potential bias in training data. The presence of unfair or unrepresentative information in the dataset used to train an AI model can result in unfair outcomes when using the AI tool.
  • May not be up to date. AI tools may not have access to real-time information and may have been last updated quite a long time ago.
  • Ethical issues. Many ethical issues have been raised about the potential for AI tools to reproduce the biases in their training data, to be exploited to spread misinformation or disinformation, to be used to create deceptive content that threatens privacy, to endanger intellectual property rights, to displace jobs in industries that rely on content generation.
  • Environmental costs. Generative AI systems consume a substantial amount of energy, require large amount of water to cool their processors and generate electricity, and lead to significant carbon emissions.