by J.S. Love, TU Delft
I recently had the good fortune to join the vibrant Digital Humanities (DH) community at the University of Reading and share some recent work I and my colleagues, Heng Gu and Jeroen Vandommele, have been doing with chatbots in cultural heritage venues. Our conversational agent, dubbed CuratorBot, is one manifestation of the possibilities afforded by new large language models (LLMs). It inhabits a space alongside experiments with chatbots in other domains and shares their capacities for good, ill and shades in-between. Since the release of ChatGPT I have regularly seen conversational agents of various kinds in the news. Our colleagues at MIT present members of the public with avatars of their future selves, contemplative mirrors which encourage them to reflect on personal choices.[1] We also see more ambiguous but very human attempts to revive deceased friends and family.[2] It’s easy to get lost and draw quick conclusions as these experiments flare up and die out, so we’ve been trying to use our prototype as a dialogue piece, an anchor for envisioning how – or whether – this technology can be productively used in our more familiar world of libraries and museums. We’re still learning, but a picture is slowly emerging for what constitutes good utility of this technology when it encounters our cultural heritage.
At present many of us harbour a wish that chatbot interfaces will help resolve information retrieval and let us more naturally parse the digital world (or perhaps explode it?[3]). There is some collective, unspoken promise that LLMs will eventually have the capacity to infer intention from questions we ask of them and then convey that intent on our behalf to negotiate the vast world of…something: contemporary news, collections of books, the internet. This doesn’t work yet, and it’s not entirely certain it ever will, at least not with the LLM-based approach that we currently use.[4] They are built to mimic human speech but have no intentionality behind them toward truth or otherwise.[5] The future fictions of chat-based interfaces in my own head – the Star Trek computer or Douglas Adams’ ‘Deep Thought’ – remain in the realm of the Unreal. But lest we go too far down a technological or philosophical rabbit hole: generative text tools built atop LLMs can produce pretty convincing imitations of what people have said or might say. Surely there are uses for this already, ones which are simultaneously beneficial and not harmful?[6]
For me some of the most promising uses of LLMs right now involve some element of creativity. I work in a design faculty, and my students tinker with prompts to make strange new connections, brainstorm, ideate.[7] Barry Enderwick was doing the same thing in his Friday ChatGPT sessions of ‘Sandwiches of History’ on Youtube.[8] Here chatting with a machine is a means not an end, stimuli more than answers. My colleagues who run the Connected Creativity Design Lab[9] are in much better stead to evaluate the creative process behind this (or refute me outright), but from even with my imperfect understanding, generative text systems look pretty feasible for activities where dialogue and sharing are important, where idea quantity (a particular merit of computed automation) is beneficial and the fictional or unreal are welcome.
We DH practitioners – (art) historians, philologists, archaeologists and many others – are in the business of constantly changing perspective. We investigate old things in new ways. Generative text tools can open up ways of exploring or even draw out new ways of seeing. Some people are ahead of the curve in utilizing generative text for this type of use, as I discovered when hearing Kieran O’Halloran’s presentation on pedagogical uses for ChatGPT in short story interpretation.[10] A part of our scholarly process – and I’m not sure how closely this is related to creativity – is exploration or discovering,[11] getting to know a new area or line of thought. When we branch out into an unknown area, we expect to get lost and spend a fair bit of time confirming, denying and otherwise charting new information. Generative LLM tools tentatively appear rather useful for superficial exploration, where we already force ourselves to validate items we flag as possibly important against more reliable sources. Maybe we should treat ChatGPT as Wikipedia’s gabby younger sibling, one which still needs to incorporate how to curate and represent sources for its claims.
For now we can keep generative text as one arrow in our search quiver. It’s a sharp tool we can teach others to use with care for specific purposes. And if all goes well, we will have the choice to cast it away for a more suitable replacement when it comes.
[1] https://www.theguardian.com/technology/article/2024/jun/05/ai-researchers-build-future-self-chatbot-to-inspire-wise-life-choices
[2] Cf. https://www.theguardian.com/technology/2023/jul/18/ai-chatbots-grief-chatgpt and https://www.theguardian.com/technology/2024/apr/04/chinese-mourners-turn-to-ai-to-remember-and-revive-loved-ones
[3] Cf. Matthew Kirschenbaum’s concern about LLM’s capacity to hinder through the creation of junk: https://www.theatlantic.com/technology/archive/2023/03/ai-chatgpt-writing-language-models/673318/
[4] Hints of LLM limitations and risks were already flagged up by the now famous ‘Stochastic Parrots’ paper (Bender, Emily M., et al. “On the dangers of stochastic parrots: Can language models be too big?🦜.” Proceedings of the 2021 ACM conference on fairness, accountability, and transparency. 2021.)
[5] Cf. Hicks, Michael Townsen, Humphries, James and Slater, Joe. “ChatGPT is bullshit.” Ethics and Information Technology 26.2 (2024): 38.
[6] Here I refer to two of the five ‘principles for AI & Society’ – beneficence and non-malificence – expressed by Thomas Padilla following Floridi & Cowls. Padilla, Thomas. ‘Responsible Operations: Data Science, Machine Learning, and AI in Libraries’. OCLC Research Position Paper, 26 August 2020.
[7] On creativity and ideation cf. Runco, Mark A. 2010. “Divergent thinking, creativity, and ideation.” In The Cambridge Handbook of Creativity, 413-446.
[8] https://www.youtube.com/@SandwichesofHistory
[9] https://delftdesignlabs.org/connected-creativity-lab/
[10] O’Halloran, Kieran. “Digital assemblages with AI for creative interpretation of short stories.” Digital Scholarship in the Humanities (2024)
[11] Cf. John Unsworth’s notion of ‘Scholarly Primitives’ https://people.brandeis.edu/~unsworth/Kings.5-00/primitives.html and his update to these in 2020: https://www.youtube.com/watch?v=XyruWlLDvlc&pp=ygUddW5zd29ydGggc2Nob2xhcmx5IHByaW1pdGl2ZXM%3D.