New Voices RGU Student Series 2026 – Emily Wareing
Category: RGU Student Series 2026
In the 2026 New Voices Student Series, the CILIPS Students & New Professionals Community will be sharing the views of Robert Gordon University students from the MSc in Information and Library Studies.
With special thanks to Dr Konstantina Martzoukou, Teaching Excellence Fellow and Associate Professor, for organising these thought-provoking contributions.
Emily Wareing is pursuing an MSc in Library and Information Studies at RGU while working as a Library Adviser at Canterbury Christ Church University. She hopes to infuse her professional practice with her academic insight in this ever-changing field. She is passionate about book borrowing, book buying, and – as often as time allows – book reading, and she is a very great lover of libraries.
I’m not a robot – keeping it REAL with AI
I’m not a robot. A statement we’ve seen and ticked a thousand times on CAPTCHAs across the internet, and one that has become increasingly relevant to our academic and professional lives. In this new age of GenAI, how do we, as information professionals, guide our users to make the most of AI tools without losing that which makes our work human? How do we ensure their work is not, at its heart, authored by a robot? Well, be it ChatGPT, Copilot, Claude or any other programme they choose to use, we can start by reminding our users to keep it REAL.
Roleplay – does the AI know its audience? Are you a professional looking for research papers, or a layman looking for a simple explanation? It is important to introduce your own skill level to the AI in the initial prompt, to tell it what level of expertise is required to answer the question and how deep to dive into the topic. If you tell the AI that you are an academic, the AI will look for academic answers. This can either be stated outright or suggested using specialist terminology and contextualisation, to help the AI to establish what its audience requires (Sun & Yuan, 2025).
Existence – when asking AI for help with your research, particularly for resource lists, your first question should always be: “Does this work exist?”. It is known to information professionals that current iterations of AI are prone to hallucinations – or hallucitations – but are students aware of this habit? Thankfully, AI can be persuaded towards honesty. Once the list has been generated, a question of “Are all of these real?” will prompt the AI to declare which of its suggestions are authentic and which were generated upon patterns of phrasing. It does not do to trust an AI blindly – always verify your answers.
Attribution – is your work properly attributed? Have you acknowledged any AI assistance? AI has undoubtedly sown distrust in academic integrity, capable of producing work that seems just diverse enough to be legitimate and casting paranoia into the hearts of essay markers everywhere. Fears of “high-tech plagiarism” and “overreliance on technological aid” run rampant (Amigud & Pell, 2025). Was this AI generated, or was this a false positive? That’s why it is essential to add attributing AI use to your regular referencing routine. Cite Them Right is an excellent recommendation for guidance on how to cite AI use which covers all referencing styles.
Legitimacy – are your sources from reputable publications? AI can deliver sources from across the web, but not every article is created equal. Unlike traditional methods of information seeking using databases and catalogues, the articles produced do not come pre-vetted by the information professionals collating said collections. You can ask AI for peer-reviewed articles from reputable publications, but it is always best to verify the publishers yourself. Another concern is the tendency towards reflecting cultural biases that is prevalent in AI. AI is trained on “large datasets that may contain deep biases” and is prone to positive reinforcement of perceived user perspectives (Zhang, Ismail & Zakaria, 2025). Critical analysis is essential to identify these biases and ensure that an answer is valid, and not merely what AI thinks its user wants to hear.
Students are already eagerly using AI “informally and creatively”, but many of them are doing so without professional guidance (Allen & Poynter, 2025). According to CILIP’s ethical framework, librarians and information professionals – as keepers of knowledge – have a duty to disperse that knowledge among our users through the development of information and literacy skills in a way that promotes transparency, critical analysis and responsible use of AI tools. We need to be trained guides in this brave new world of AI and help our users to employ these tools to create something well-researched and entirely their own (and not the robot’s).
If you would like to explore more of this new chapter in information seeking, this Padlet has been collated with a few helpful resources to get you started.
References
Allen, R.J., Poynter, J. (2025). ‘Listening First: A University Campus-Based Participatory Survey of Generative AI Literacy Needs’. In: J.Allen, R., Nakonechnyi, A. (eds) Using and Understanding AI in Higher Education. Palgrave Macmillan, Cham. https://doi-org.ezproxy.rgu.ac.uk/10.1007/978-3-031-99754-9_5 (Accessed: 26/11/2025).
Amigud, A., & Pell, D. J. (2025) ‘Responsible and Ethical Use of AI in Education: Are We Forcing a Square Peg into a Round Hole?’, World, 6(2), 81. https://doi.org/10.3390/world6020081 (Accessed: 25/11/2025).
Artlist (2025) CAPTCHA verification [Digital art]. Created for Emily Wareing, 29 November.
Artlist (2025) Librarian assisting student on laptop [Digital art]. Created for Emily Wareing, 29 November.
Artlist (2025) Student browsing JISC catalogue online [Digital art]. Created for Emily Wareing, 29 November.
Palgrave Macmillan (2025) Cite Them Right. Available at: https://www.citethemrightonline.com/home (Accessed: 29 November 2025).
Sun, Z., Yuan, R. (2025). ‘Using AI for Literature Review’. In: Zhou, X., Al-Samarraie, H. (eds) Institutional guide to using AI for research. Advances in Artificial Intelligence in Education, vol 2. Springer, Cham. https://doi-org.ezproxy.rgu.ac.uk/10.1007/978-3-031-94809-1_4 (Accessed: 26/11/2025).
Zhang, Q., Mohammad Ismail, M.I.R. & Zakaria, A.R.B. (2025) ‘Enhancing intercultural competence in technical higher education through AI-driven frameworks’, Scientific Reports, 15, 22019. https://doi.org/10.1038/s41598-025-03303-1 (Accessed: 25/11/2025).