%0 Conference Paper %1 ls_leimeister %A Elshan, Edona %A Siemon, Dominik %A de Vreede, Triparna %A de Vreede, Gert-Jan %A Oeste-Reiß, Sarah %A Ebel, Philipp %B Hawaii International Conference on System Sciences (HICSS) %D 2022 %K AI-based_teammate cepub collaboration creative_workshops human-AI_collaboration itegpub pub_peb pub_soe requirements %R 10.24251/HICSS.2022.020 %T Requirements for AI-based Teammates: A Qualitative Inquiry in the Context of Creative Workshops %U http://pubs.wi-kassel.de/wp-content/uploads/2022/05/JML_871.pdf %X 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.

@inproceedings{ls_leimeister, 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.}, added-at = {2022-05-06T13:37:16.000+0200}, author = {Elshan, Edona and Siemon, Dominik and de Vreede, Triparna and de Vreede, Gert-Jan and Oeste-Reiß, Sarah and Ebel, Philipp}, biburl = {https://www.bibsonomy.org/bibtex/2854091eeb4ca6a9be2923228a6503197/ls_leimeister}, booktitle = {Hawaii International Conference on System Sciences (HICSS)}, doi = {10.24251/HICSS.2022.020}, eventdate = {04.01.2022 - 07.01.2022}, eventtitle = {Hawaii International Conference on System Sciences (HICSS)}, interhash = {332a935b74f15e7a81c6e16bf4bc5e05}, intrahash = {854091eeb4ca6a9be2923228a6503197}, keywords = {AI-based_teammate cepub collaboration creative_workshops human-AI_collaboration itegpub pub_peb pub_soe requirements}, timestamp = {2022-05-06T14:09:30.000+0200}, title = {Requirements for AI-based Teammates: A Qualitative Inquiry in the Context of Creative Workshops}, url = {http://pubs.wi-kassel.de/wp-content/uploads/2022/05/JML_871.pdf}, venue = {Hawaii, USA}, year = 2022 }