LET EMPLOYEES TRAIN THEIR OWN CHATBOTS: DESIGN OF GENERATIVE AI-ENABLED DELEGATION SYSTEMS
Journal
European Conference on Information Systems (ECIS)
Type
conference paper
Date Issued
2024-06-17
Author(s)
Research Team
IWI6
Abstract
While chatbots can be implemented with very little effort, scaling and maintaining chatbots remains a challenge. This is crucial in knowledge-intensive customer service like IT support, where domain knowledge must stay current with the evolving IT landscape. Following design science research, we derive design principles for a generative AI (GPT4) enabled textual training data creation and curation system (T²C²) as part of a new class of systems – bot delegation systems. For the design of T²C², chatbot and domain expert viewpoints are integrated. We evaluate two instances of T²C², each with distinct degrees of human-ai delegation where employees act both as creators and curators of training data. The paper’s theoretical contribution is two-fold: (1) we present a novel kernel theory that represents the material characteristics of bot delegation systems by contextualizing the IS delegation framework to the self-determination theory; (2) the design and evaluation of T²C² as the built-and-evaluated artifact.
Language
English
Keywords
Chatbot
Generative AI
Customer Service
IS Delegation
Self-Determination Theory
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher place
Paphos, Cyprus
Start page
01
End page
16
Pages
16
Event Title
European Conference on Information Systems (ECIS)
Event Location
Paphos, Cyprus
Event Date
17.06.2024
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
Name
JML_970.pdf
Size
701.12 KB
Format
Adobe PDF
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