New Voices RGU Student Series 2025 – Daine Meekison
Category: RGU Student Series 2025
In the 2025 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.
Today’s blog post author is Daine Meekison. With a background in providing customer services and in English for Speakers of Other Languages (ESOL) education, Daine is interested in exploring how public libraries can assist with the promotion of language and linguistics skills.
From finding ‘needles in haystacks’ to apprehending ‘the butterfly effect’: The evolving role of public library information professionals in the epoch of Generative Artificial Intelligence.
There is little doubt that Generative Artificial Intelligence (GenAI, hereafter) is having a profound effect upon the world of information-seeking and retrieval (IBM, 2024a; McKinsey, 2023). Moreover, with the widespread adoption of GenAI tools (McKinsey, 2024), and their continued development (IBM, 2024a), it looks as though this technology is – like it or lump it – here to stay.
Key question: “Is the GenAI revolution going to affect how I search for information in my public library role?”
Key answer: “You bet.”
Traditional information-seeking involves ‘keyword searching’, where, using specific vocabulary and phraseology, we trawl the data-depths in formulaic fashion attempting to reduce masses of knowledge into bite- (or byte-) sized chunks (Rumsey, 2008). Although this tried-and-tested technique arguably amounts to us fumbling around for ‘a needle in a haystack’, it does nevertheless produce very black-and-white binary results: information is either discovered, or it isn’t, and patron enquiries – for better or worse – normally achieve resolution.
Still, if conventional keyword-searching is monochromous, then information retrieval using GenAI is kaleidoscopic. Hold on to your hats, folks.
While GenAI too relies on lexicon and locution to delineate search parameters (Bozkurt, 2024), this is where its similarity to orthodox information-seeking ends. In place of keyword-searching we find ‘prompt-engineering’; where natural, conversational language is king (ibid). This novel method of elicitation brings with it a myriad of new skill demands; not least that data-divers have purchase on context, syntax, nuance, and – actually – linguistics as a whole (IBM, 2024b).
But there’s more.
Given that “every word in a prompt can influence the outcome” (ibid), the permutational possibilities are literally endless. (Psst! Welcome to the “butterfly effect” (OED, 2024), where minute prompt alterations can lead to MASSIVE changes in what might be retrieved.)
Yikes.
So, what does this mean for public library information professionals?
First, since the GenAI genie has been released from its receptacle (whoops!), we need to ‘bite the bullet’ and attain at least a foundational knowledge of how prompt-engineering works. Why? Well, how can we attest to being a “safe space” (Reid and Mesjar, 2022, p. 315) if we say ‘I don’t know’ to those – i.e. our patrons – seeking refuge from the GenAI informational storm? Prompt-engineering training sessions are therefore an absolute must.
Second, GenAI is, lest we forget, an unwieldy weapon in our arsenal and not (yet) the AI-bomb (McKinsey, 2024). Indeed, rather than supplanting keyword-searching, prompt-engineering is more likely to complement it; proffering alternative, supplementary – even corroboratory – conduits through which information can be un-siloed.
Yes, using prompt-engineering in isolation to find information may appeal to some information-seekers, but the open-endedness of GenAI will frustrate those who want definitive answers – and simplicity. GenAI might well be ‘context-specific’, but so are our patrons, after all.
Third, since “English is often the primary language used to train GenAI” (IBM, 2024b) this inferentially presupposes a proficiency in English that many public library users may not possess. Alarm bells should be ringing because, if GenAI can be wielded only by those who have the firmest of handles on English, then many people will indubitably become informationally disenfranchised.
Whether the solution to this lies in embedding English language classes into our schedules – perhaps by inviting English for Speakers of Other Languages (ESOL) tutors into our branches to demonstrate how to ‘scaffold’ English in a Vygotsky-esque style (Wilson, 2016) – who knows, but we have to be ready to confront this looming information literacy challenge.
Fundamentally, we must acknowledge to ourselves, and emphasise to our patrons, our para-professional role as GenAI prompt-engineers. This disclaimer is not a cop-out – it is needed to highlight the difficulties we all face in harnessing the GenAI steed, namely:
- the abundance of GenAI models (IBM 2024a), but the dearth of one-size-fits-all prompt-engineering techniques (Schulhoff et al, 2024);
- the unceasing creativity (and linguistic flair!) required to craft ever-effective prompts (IBM, 2024b); and, especially,
- the risk of receiving inaccurate information (McKinsey, 2023) due to nascent GenAI’s often “mutually exclusive” (Cambridge Dictionary, 2024) relationship with Verity.
References
Bozkurt, A. (2024) ‘Tell Me Your Prompts and I Will Make Them True: The Alchemy of Prompt Engineering and Generative AI’, Open Praxis, 16(2), pp. 111–118.
Available at: https://doi.org/10.55982/openpraxis.16.2.661
Cambridge Dictionary, (2024) Mutually Exclusive definition. Cambridge Dictionary Online.
Available at: https://dictionary.cambridge.org/dictionary/english/mutually-exclusive
(Accessed: 7 October 2024).
IBM (2024a) What is generative AI?.
Available at: https://www.ibm.com/topics/generative-ai
(Accessed: 7 October 2024).
IBM (2024b) What is prompt engineering?.
Available at: https://www.ibm.com/topics/prompt-engineering
(Accessed: 7 October 2024).
McKinsey (2023) The state of AI in 2023: Generative AI’s breakout year.
Available at: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year
(Accessed: 7 October 2024).
McKinsey (2024) The state of AI in early 2024: GenAI adoption spikes and starts to create value.
Available at: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
(Accessed: 7 October 2024).
OED (2024) Butterfly Effect definition. Oxford English Dictionary Online.
Available at: https://www.oed.com/search/dictionary/?scope=Entries&q=butterfly%20effect
(Accessed: 7 October 2024).
Reid, P. and Mesjar, L. (2022) ‘Bloody amazing really: voices from Scotland’s public libraries in lockdown’, Journal of Documentation, 79(2), pp. 301–319.
Available at: https://doi-org.ezproxy.rgu.ac.uk/10.1108/JD-03-2022-0067
(Accessed: 21 October 2024).
Rumsey, S. (2008) How to find information: a guide for researchers. 4th edn. Maidenhead: McGraw-Hill Education.
Available at: https://ebookcentral.proquest.com/lib/rgu/reader.action?docID=345140
(Accessed: 07 October 2024).
Schulhoff, S. et al (2024) ‘The Prompt Report: A Systematic Survey of Prompting Techniques’, arXiv (Cornell University), 2024(6).
Available at: https://doi.org/10.48550/arXiv.2406.06608
Wilson, K. (2016) ‘Critical reading, critical thinking: Delicate scaffolding in English for Academic Purposes (EAP)’, Thinking Skills and Creativity, 22(2016), pp. 256–265.
Available at: https://doi.org/10.1016/j.tsc.2016.10.002
(Accessed: 07 October 2024).