Artificial Intelligence (AI) and the literature review process: Welcome
This guide shows you how you can use AI tools to help with aspects of the literature review process:
- Abstract and title creation
- Scoping and protocol development
- Searching
- Screening
- Data extraction
- Synthesis
You will learn the terminology behind the technology, find advice about prompt engineering, the art of interacting with AI agents, and a list of the AI tools referenced in this guide.
We also highlight key ethical concerns about the use of AI tools when reviewing the literature (i.e. lawsuits for copyright infringement).
University guidance about using AI
AI tools analyze a large volume of articles, accurately extract and summarise information, provide different perspectives and integrate information from across different disciplines (Blanco-Gonzalez et al., 2023; Huang and Tan, 2023). These are among the potential benefits of using large language models in learning as the QAA identifies in its January 2023 briefing paper.
However, the QAA briefing paper recognizes that if you present the output of generative AI tools as your own work, there is a clear challenge to academic integrity.
The university recognizes that AI tools can be helpful in assisting learning.
You can use an AI tool in the preliminary stages of your assignment process, for instance to brainstorm, as well as planning/researching to identify relevant sources.
There is evidence that models such as ChatGPT are really useful in this respect and there is no need to cite the AI tool.
Most current assignment briefs will only permit very limited use of AI tools.
Follow the guidance on referencing generative AI in the referencing pages.
The subject is in its infancy and it will take many years before some consensus is reached in the academic community on questions such as:
- Which tools work best in supporting the searching process?
- How best to use AI tools?
- Should institutional subscriptions to specific tools be taken out where possible?
However, there is demand from students for guidance on the responsible and effective use of AI (see section 5.2.2 within the student expectations section of Jisc's AI in Tertiary Education, 3rd edn., p. 13). This guide attempts to meet some of that demand. One of the recommendations of HEPI Policy Note 51 (Freeman, 2024) is that institutions should teach students how it can be used appropriately and effectively, such as how to write an effective ‘prompt’, and how to evaluate the quality of content generated by AI. The HEPI/Kortext survey suggests that students who have not used AI tools remain a large group and particular efforts might be made to increase AI literacy among these students as long as this is done alongside the university's existing student guidance on the use of AI tools (see above).
This guide does not cover the use of generative AI in coding, in the production of music or in the creation of artwork. The AI tools that are included are those which are a) freely available, and b) mentioned in the academic literature in the context of searching and reviewing the literature.