Agentic Relationship Dynamics in Human-AI Collaboration: A study of interactions with GPT-based agentic IS artifacts
(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:
https://lup.lub.lu.se/record/95345918-a7cc-4f3a-abc0-251a2c142a08
- author
- Svensson, Björn LU and Keller, Christina LU
- organization
- publishing date
- 2024-01-03
- 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}}, }