It Takes a Village: A Distributed Training Model for AI-Based Chatbots.
The introduction of Large Language Models (LLM) to the chatbot landscape has opened intriguing possibilities for academic libraries to offer more responsive and institutionally contextualized support to users, especially outside of regular service hours. While a few academic libraries currently empl...
| Published in: | Information Technology & Libraries Vol. 43; no. 3; pp. 1 - 9 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Published: |
American Library Association
Sep2024
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179871816&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179871816 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 07309295 ITL jtl: Information Technology & Libraries issn: 07309295 maglogo: N pubinfo: dt: Sep2024 vid: 43 iid: 3 pid: 55 pub: American Library Association place: Chicago, Illinois artinfo: ui: 179871816 10.5860/ital.v43i3.17243 179871816 ppf: 1 ppct: 8 formats: fmt: @attributes: type: P tig: atl: It Takes a Village: A Distributed Training Model for AI-Based Chatbots. aug: au: Twomey, Beth Johnson, Annie Estes, Colleen affil: Head for Research and Engagement, University of Delaware sug: subj: Artificial Intelligence, Generative Natural Language Processing Libraries, Academic Library Services Chatbot World Wide Web Information Technology Interprofessional Relations Learning Methods Information Resources Librarians Program Development Workflow ab: The introduction of Large Language Models (LLM) to the chatbot landscape has opened intriguing possibilities for academic libraries to offer more responsive and institutionally contextualized support to users, especially outside of regular service hours. While a few academic libraries currently employ AI-based chatbots on their websites, this service has not yet become the norm and there are no best practices in place for how academic libraries should launch, train, and assess the usefulness of a chatbot. In summer 2023, staff from the University of Delaware's Morris Library information technology (IT) and reference departments came together in a unique partnership to pilot a low-cost AI-powered chatbot called UDStax. The goals of the pilot were to learn more about the campus community's interest in engaging with this tool and to better understand the labor required on the staff side to maintain the bot. After researching six different options, the team selected Chatbase, a subscription-model product based on ChatGPT 3.5 that provides user-friendly training methods for an AI model using website URLs and uploaded source material. Chatbase removed the need to utilize the OpenAI API directly to code processes for submitting information to the AI engine to train the model, cutting down the amount of work for library information technology and making it possible to leverage the expertise of reference librarians and other public-facing staff, including student workers, to distribute the work of developing, refining, and reviewing training materials. This article will discuss the development of prompts, leveraging of existing data sources for training materials, and workflows involved in the pilot. It will argue that, when implementing AI-based tools in the academic library, involving staff from across the organization is essential to ensure buy-in and success. Although chatbots are designed to hide the effort of the people behind them, that labor is substantial and needs to be recognized. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|