
While all genAI tools can provide 'information', some can also function as a search engine/tool:
Some tools provide sources directly, while others can provide summaries to asked questions with linked sources, or lists of sources. Because of their internet connectivity and search capability, these tools are less likely to 'hallucinate' sources. With that said, it's still important to consider which of the sources provided will be suitable for your needs, as you may also be presented with general web material and grey literature in addition to articles, chapters and papers (depending on the tool used). Some recent research has suggested that the results from some tools may not be great for accuracy or understanding.
Using AI in academic research means strongly committing to transparency and accountability to keep your scholarly work legitimate (and eventually, as funded researchers, to comply with grant and publishers’ requirements). So, while generative AI can be a game-changer, it’s crucial to use it wisely and follow ethical guidelines to ensure your research is reliable and credible.
The University of Sydney has a number of useful pages in their AI module if you'd like to learn more:
It's important to check each citation that is provided in outputs from genAI tools, due to the potential 'hallucination' problem. If you have citations taken from answers generated by genAI tools and can't find them, try searching directly for the journal titles cited to source the articles - it's possible they don't exist.
Still can't locate something that seems important, or just stuck? You can book in to speak with one of our librarians for help - there are online and in-person options for both students and researchers.
'Connector' AI function by the use of functionality known as 'citation chaining' to find cited, similar, or related articles. This is most helpful when you have found an article that is highly relevant to your needs, and you're searching for connected publications. These AI tools usually work via entering the details of an article, and can often provide visual maps that allow you to engage with other publications via their connect to the article you entered the details for.
Examples include:
While there are many options to enter the details of an article to start the search for connections, best practice is to enter the title or DOI of an article. This relies on materials that are openly available on the web and removes the need to upload files. Wherever possible, uploading files to AI tools should be avoided due to copyright considerations.
There are important considerations around uploading files to genAI tools.
As noted above for files, data security/privacy is a big concern for genAI systems. To ensure that any information you provide in an input does not become part of the AI tool's training data, you should check what is being shared, and whether you can opt out.
The JISC National Centre for AI (UK) has a great summary to help with navigating the terms and conditions of genAI tools across text, image, audio and video generation, plus others, that makes it easier to see what is being shared and whether you can opt out. It's also important to check after any updates/upgrades to the platform that you are still not sahring your information more broadly, otherwise it could become part of a later output and used by someone else.
Note that the University's enterprise access to Copilot includes data security that is highly visible when you log in, top right of screen.
To be safe, it's always best to limit any personal or potentially sensitive information shared with a genAI tool, so being careful when creating CVs and personal or oral histories. Consideration should also be given to uploading interview transcripts and similar materials.
HDR students may have additional considerations from working in research spaces. HDR students and their supervisors should read the guidance for Generative Artificial Intelligence and Higher Degrees by Research (PDF). See also our page on AI for Research.
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