Item Type |
Conference or Workshop Item
(Paper)
|
Abstract |
Innovation requires organizations to tap into the knowledge and creativity of teams. However, teams are confronted with massive amounts of data and information, necessitating a broad set of knowledge, methodologies, and approaches to solve problems and innovate. Consequently, team composition has become a critical challenge. Recent advances in artificial intelligence (AI) may assist in addressing this challenge. As AI is permeating both business and private sectors, organizational teams may be augmented with AI team members. However, given the nascent nature of this phenomenon, little is known about the specific roles and requirements for such AI teammates. Within an interview study we discover common challenges in teams and identify recurring capability gaps of participants and behaviors that negatively impact the team's collective performance. Based on our findings, we propose requirements for AI-based teammates to address these gaps and support beneficial collaboration between humans and AI in teams. |
Authors |
Elshan, Edona; Siemon, Dominik; de Vreede, Triparna; de Vreede, Gert-Jan; Oeste-Reiß, Sarah & Ebel, Philipp |
Research Team |
IWI6 |
Journal or Publication Title |
Hawaii International Conference on System Sciences (HICSS) |
Language |
English |
Keywords |
AI-based teammate, human-AI collaboration, requirements, collaboration, creative workshops |
Subjects |
information management |
HSG Classification |
contribution to scientific community |
Date |
4 January 2022 |
Number of Pages |
10 |
Event Title |
Hawaii International Conference on System Sciences (HICSS) |
Event Location |
Hawaii, USA |
Event Dates |
04-07 Jan 2022 |
ISBN |
978-0-9981331-5-7 |
Publisher DOI |
https://doi.org/10.24251/HICSS.2022.020 |
Official URL |
http://hdl.handle.net/10125/79350 |
Depositing User |
Anonymous Anonymous
|
Date Deposited |
06 May 2022 11:56 |
Last Modified |
18 Aug 2022 07:43 |
URI: |
https://www.alexandria.unisg.ch/publications/266223 |