{"id":1674,"date":"2024-07-05T10:00:03","date_gmt":"2024-07-05T09:00:03","guid":{"rendered":"https:\/\/research.reading.ac.uk\/digitalhumanities\/?p=1674"},"modified":"2024-07-18T16:27:36","modified_gmt":"2024-07-18T15:27:36","slug":"generative-text-for-by-with-digital-humanists","status":"publish","type":"post","link":"https:\/\/research.reading.ac.uk\/digitalhumanities\/generative-text-for-by-with-digital-humanists\/","title":{"rendered":"Generative Text for\/by\/with Digital Humanists"},"content":{"rendered":"

by J.S. Love, TU Delft<\/p>\n

\"An
CuratorBot Mascot (generated with Midjourney)<\/figcaption><\/figure>\n

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).\u00a0 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]<\/a> We also see more ambiguous but very human attempts to revive deceased friends and family.[2]<\/a> It\u2019s easy to get lost and draw quick conclusions as these experiments flare up and die out, so we\u2019ve been trying to use our prototype as a dialogue piece, an anchor for envisioning how \u2013 or whether \u2013 this technology can be productively used in our more familiar world of libraries and museums. We\u2019re still learning, but a picture is slowly emerging for what constitutes good utility of this technology when it encounters our cultural heritage.<\/p>\n

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]<\/a>). 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\u2019t work yet, and it\u2019s not entirely certain it ever will, at least not with the LLM-based approach that we currently use.[4]<\/a> They are built to mimic human speech but have no intentionality behind them toward truth or otherwise.[5]<\/a> The future fictions of chat-based interfaces in my own head – the Star Trek computer or Douglas Adams\u2019 \u2018Deep Thought\u2019 – 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]<\/a><\/p>\n

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<\/em>.[7]<\/a> Barry Enderwick was doing the same thing in his Friday ChatGPT sessions of \u2018Sandwiches of History\u2019 on Youtube.[8]<\/a> Here chatting with a machine is a means not an end, stimuli more than answers. My colleagues who run the Connected Creativity Design Lab<\/em>[9]<\/a> 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.<\/p>\n

\"A
Wooden Spade (1686) (Rijksmuseum, CC0)<\/figcaption><\/figure>\n

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\u2019Halloran\u2019s presentation on pedagogical uses for ChatGPT in short story interpretation.[10]<\/a> A part of our scholarly process – and I\u2019m not sure how closely this is related to creativity \u2013 is exploration or discovering,[11]<\/a> 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\u2019s gabby younger sibling, one which still needs to incorporate how to curate and represent sources for its claims.<\/p>\n

For now we can keep generative text as one arrow in our search quiver. It\u2019s 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.<\/p>\n

 <\/p>\n

[1]<\/a> https:\/\/www.theguardian.com\/technology\/article\/2024\/jun\/05\/ai-researchers-build-future-self-chatbot-to-inspire-wise-life-choices<\/a><\/p>\n

[2]<\/a> Cf. https:\/\/www.theguardian.com\/technology\/2023\/jul\/18\/ai-chatbots-grief-chatgpt<\/a> and\u00a0 https:\/\/www.theguardian.com\/technology\/2024\/apr\/04\/chinese-mourners-turn-to-ai-to-remember-and-revive-loved-ones<\/a><\/p>\n

[3]<\/a> Cf. Matthew Kirschenbaum\u2019s concern about LLM\u2019s capacity to hinder through the creation of junk: https:\/\/www.theatlantic.com\/technology\/archive\/2023\/03\/ai-chatgpt-writing-language-models\/673318\/<\/a><\/p>\n

[4]<\/a> Hints of LLM limitations and risks were already flagged up by the now famous \u2018Stochastic Parrots\u2019 paper (Bender, Emily M., et al. “On the dangers of stochastic parrots: Can language models be too big?\ud83e\udd9c.” Proceedings of the 2021 ACM conference on fairness, accountability, and transparency<\/em>. 2021.)<\/p>\n

[5]<\/a> Cf. Hicks, Michael Townsen, Humphries, James and Slater, Joe. “ChatGPT is bullshit.” Ethics and Information Technology<\/em> 26.2 (2024): 38.<\/p>\n

[6]<\/a> Here I refer to two of the five \u2018principles for AI & Society\u2019 – beneficence and non-malificence – expressed by Thomas Padilla following Floridi & Cowls. Padilla, Thomas. \u2018Responsible Operations: Data Science, Machine Learning, and AI in Libraries\u2019. OCLC Research Position Paper, 26 August 2020.<\/p>\n

[7]<\/a> On creativity and ideation cf. Runco, Mark A.\u00a0 2010. “Divergent thinking, creativity, and ideation.” In The Cambridge Handbook of Creativity,<\/em> 413-446.<\/p>\n

[8]<\/a> https:\/\/www.youtube.com\/@SandwichesofHistory<\/a><\/p>\n

[9]<\/a> https:\/\/delftdesignlabs.org\/connected-creativity-lab\/<\/a><\/p>\n

[10]<\/a> O’Halloran, Kieran. “Digital assemblages with AI for creative interpretation of short stories.” Digital Scholarship in the Humanities<\/em> (2024)<\/p>\n

[11]<\/a> Cf. John Unsworth\u2019s notion of \u2018Scholarly Primitives\u2019 https:\/\/people.brandeis.edu\/~unsworth\/Kings.5-00\/primitives.html<\/a> and his\u00a0 update to these in 2020: https:\/\/www.youtube.com\/watch?v=XyruWlLDvlc&pp=ygUddW5zd29ydGggc2Nob2xhcmx5IHByaW1pdGl2ZXM%3D<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

by J.S. 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