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Agentic Relationship Dynamics in Human-AI Collaboration: A study of interactions with GPT-based agentic IS artifacts

Svensson, Björn LU and Keller, Christina LU (2024) 57th Hawaii International Conference on System Sciences p.7292-7301
Abstract
Generative Artificial Intelligence (AI) having become increasingly embedded into work in both academia and industry has put a magnifying glass on Human-AI collaboration. With this paper, we seek to answer calls for research on the interactions between human and AI agents and their outcomes. We adopt the IS Delegation Framework (Baird & Maruping, 2021) to look at dynamics in relationships between human agents and Generative Pre-trained Transformer-based agentic IS artifacts and how these dynamics manifest. By conducting and analyzing data from semi-structured interviews, we were able to identify five salient agentic relationship dynamics affecting common understanding, willingness to delegate, cognitive load in human agents, confidence,... (More)
Generative Artificial Intelligence (AI) having become increasingly embedded into work in both academia and industry has put a magnifying glass on Human-AI collaboration. With this paper, we seek to answer calls for research on the interactions between human and AI agents and their outcomes. We adopt the IS Delegation Framework (Baird & Maruping, 2021) to look at dynamics in relationships between human agents and Generative Pre-trained Transformer-based agentic IS artifacts and how these dynamics manifest. By conducting and analyzing data from semi-structured interviews, we were able to identify five salient agentic relationship dynamics affecting common understanding, willingness to delegate, cognitive load in human agents, confidence, and human agents' abilities to break GPT-based agentic IS artifacts' "thought loops". With this, we aim to provide nuanced insight into GPT-based agentic IS artifacts and agentic relationship dynamics involving cognitive tasks. (Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
generative artificial intelligence, generative AI, IS delegation, agentic IS artifacts
host publication
Proceedings of the 57th Hawaii International Conference on System Sciences
pages
10 pages
publisher
University of Hawaii at Manoa
conference name
57th Hawaii International Conference on System Sciences
conference location
Honolulu, United States
conference dates
2024-01-03 - 2024-01-06
ISBN
978-0-9981331-7-1
language
English
LU publication?
yes
id
95345918-a7cc-4f3a-abc0-251a2c142a08
alternative location
https://hdl.handle.net/10125/107261
date added to LUP
2024-01-13 22:06:38
date last changed
2024-01-15 09:21:59
@inproceedings{95345918-a7cc-4f3a-abc0-251a2c142a08,
  abstract     = {{Generative Artificial Intelligence (AI) having become increasingly embedded into work in both academia and industry has put a magnifying glass on Human-AI collaboration. With this paper, we seek to answer calls for research on the interactions between human and AI agents and their outcomes. We adopt the IS Delegation Framework (Baird & Maruping, 2021) to look at dynamics in relationships between human agents and Generative Pre-trained Transformer-based agentic IS artifacts and how these dynamics manifest. By conducting and analyzing data from semi-structured interviews, we were able to identify five salient agentic relationship dynamics affecting common understanding, willingness to delegate, cognitive load in human agents, confidence, and human agents' abilities to break GPT-based agentic IS artifacts' "thought loops". With this, we aim to provide nuanced insight into GPT-based agentic IS artifacts and agentic relationship dynamics involving cognitive tasks.}},
  author       = {{Svensson, Björn and Keller, Christina}},
  booktitle    = {{Proceedings of the 57th Hawaii International Conference on System Sciences}},
  isbn         = {{978-0-9981331-7-1}},
  keywords     = {{generative artificial intelligence; generative AI; IS delegation; agentic IS artifacts}},
  language     = {{eng}},
  month        = {{01}},
  pages        = {{7292--7301}},
  publisher    = {{University of Hawaii at Manoa}},
  title        = {{Agentic Relationship Dynamics in Human-AI Collaboration: A study of interactions with GPT-based agentic IS artifacts}},
  url          = {{https://hdl.handle.net/10125/107261}},
  year         = {{2024}},
}