@conference {9999,
	title = {Project archetypes: A blessing and a curse for AI development},
	booktitle = {International Conference on Information Systems (ICIS)},
	year = {2022},
	address = {Copenhagen, Denmark},
	abstract = {<p>Software projects rely on what we propose to call project archetypes, i.e., pre-existing mental images of how projects work. They guide distribution of responsibilities, planning, or expectations. However, with the technological progress, project archetypes may become outdated, ineffective, or counterproductive by impeding more adequate approaches. Understanding archetypes of software development projects is core to leverage their potential. The development of applications using machine learning and artificial intelligence provides a context in which existing archetypes might outdate and need to be questioned, adapted, or replaced. We analyzed 36 interviews from 21 projects between IBM Watson and client companies and identified four project archetypes members initially used to understand the projects. We then derive a new project archetype, cognitive computing project, from the interviews. It can inform future development projects based on AI-development platforms. Project leaders should pro-actively manage project archetypes while researchers should investigate what guides initial understandings of software projects.</p>},
	url = {https://aisel.aisnet.org/icis2022/is_design/is_design/6 },
	attachments = {https://waim.network/sites/crowston.syr.edu/files/icis_archetypes_rev1_v20_zora.pdf},
	author = {Mateusz Dolata and Kevin Crowston and Gerhard Schwabe}
}
@article {Seeber2020,
	title = {Machines as teammates: A research agenda on AI in team collaboration},
	journal = {Information and Management},
	volume = {57},
	number = {2},
	year = {2020},
	pages = {103174},
	publisher = {Elsevier},
	abstract = {What if artificial intelligence (AI) machines became teammates rather than tools? This paper reports on an international initiative by 65 collaboration scientists to develop a research agenda for exploring the potential risks and benefits of machines as teammates (MaT). They generated 819 research questions. A subteam of 12 converged them to a research agenda comprising three design areas {\textendash} Machine artifact, Collaboration, and Institution {\textendash} and 17 dualities {\textendash} significant effects with the potential for benefit or harm. The MaT research agenda offers a structure and archetypal research questions to organize early thought and research in this new area of study.},
	keywords = {artificial intelligence, Design, Duality, Research agenda, Team collaboration},
	issn = {03787206},
	doi = {10.1016/j.im.2019.103174},
	url = {https://doi.org/10.1016/j.im.2019.103174},
	author = {Seeber, Isabella and Bittner, Eva and Briggs, Robert O and de Vreede, Triparna and de Vreede, Gert Jan and Elkins, Aaron and Maier, Ronald and Merz, Alexander B and Oeste-Rei{\ss}, Sarah and Randrup, Nils and Schwabe, Gerhard and S{\"o}llner, Matthias}
}
@conference {2018,
	title = {Machines as Teammates: A Collaboration Research Agenda},
	booktitle = {Hawaii International Conference on System Sciences},
	year = {2018},
	publisher = {Hawaii International Conference on System Sciences},
	organization = {Hawaii International Conference on System Sciences},
	doi = {10.24251/HICSS.2018.055},
	url = {http://hdl.handle.net/10125/49887},
	attachments = {https://waim.network/sites/crowston.syr.edu/files/SeeberEtAl_2018_MachinesAsTeammates.pdf},
	author = {Seeber, Isabella and Bittner, Eva and Briggs, Robert O. and de Vreede, Gert-Jan and de Vreede, Triparna and Druckenmiller, Doug and Maier, Ronald and Merz, Alexander B. and Oeste-Rei{\ss}, Sarah and Randrup, Nils and Gerhard Schwabe and S{\"o}llner, Matthias}
}
