@proceedings {9999, title = {Impacts of the Use of Machine Learning on Work Design}, year = {2020}, month = {11/2020}, publisher = {ACM}, address = {Virtual Event, NSW, Australia}, abstract = {

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) to automate information tasks, we draw on a simple framework for identifying the impacts of an automated system on a task that suggests 3 patterns for the use of ML{\textemdash}decision support, blended decision making and complete automation. In this paper, we extend this framework by considering how automation of one task might have implications for interdependent tasks and how automation applies to coordination mechanisms.

}, keywords = {artificial intelligence, automation, Coordination, machine learning, work design}, isbn = {978-1-4503-8054-6/20/11}, doi = {10.1145/3406499.3415070}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/Impacts_of_ML_for_HAI_2020.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @proceedings {9999, title = {Impacts of machine learning on work}, year = {2019}, address = {Wailea, HI}, abstract = {

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) that automate information tasks, we present a simple framework for identifying the impacts of an automated system on a task. From an analysis of popular press articles about ML, we develop 3 patterns for the use of ML--decision support, blended decision making and complete automation--with implications for the kinds of tasks and systems. We further consider how automation of one task might have implications for other interdependent tasks. Our main conclusion is that designers have a range of options for systems and that automation of tasks is not the same as automation of work.

}, keywords = {artificial intelligence, automation, machine learning, work design}, doi = {10.24251/HICSS.2019.719}, url = { http://hdl.handle.net/10125/60031}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/Impacts_of_machine_learning_on_work__revision_.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @proceedings {9999, title = {Stigmergic coordination in Wikipedia}, year = {2018}, abstract = {

We examine a novel approach to coordination, namely stigmergic coordination, that is, coordination mediated by changes to a shared work product. Stigmergy stands in contrast to the two coordination approaches identified in the existing literature on coordination, explicit coordination, based on direct communication through discussion page or user talk pages, and implicit coordination, based on unspoken expectations and shared mental models of the task to be accomplished. We look for evidence of stigmergic coordination in the context of Wikipedia, as one of the most successful experiments in online collaborative knowledge building. Using a novel approach to identifying edits to the same part of a Wikipedia article, we show that a majority of edits to two example articles are not associated with discussion on the article Talk page, suggesting the possibility of stigmergic coordination. However, some amount of discussion does seem to be related to article quality, suggesting the limits to this approach to coordination.

}, keywords = {Coordination, distributed groups, on-line epistemic community, Stigmergy, Wikipedia}, url = {http://www.opensym.org/wp-content/uploads/2018/07/OpenSym2018_paper_34.pdf}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/stigmergic-coordination-wikipedia\%20final.pdf}, author = {Amira Rezgui and Kevin Crowston} } @proceedings {Howison:2008, title = {e{R}esearch workflows for studying free and open source software development}, year = {2008}, note = {Slides from the presentation at the Oxford eResearch Conference of lessons learned in replicating research in eResearch workflows.}, address = {Milan, Italy, 7-10 September}, abstract = {This paper proposes a demonstration of eResearch workflow tools as a model for the research community studying free and open source software and its development. For purposes of background and justification, the paper first introduces eResearch as increasingly practiced in fields such as astrophysics and biology, then contrasts the practice of research on free and open source software. After outlining the suitable public data sources the paper introduces a class of tools known as scientific workflow frameworks, specifically focusing on one---Taverna---and introducing its features. To further explain the tool a complete workflow used for original research on FLOSS is described and the agenda for the live demonstration is outlined. }, keywords = {eResearch, FLOSS, Workflow}, doi = {10.1007/978-0-387-09684-1_39}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/eResearchWorkflows.pdf}, author = {James Howison and Wiggins, Andrea and Kevin Crowston} } @article {Howison:2008a, title = {Towards a data and workflow collaboratory for research on Free and Open Source Software and its development (Poster)}, year = {2008}, address = {Los Angeles, CA}, keywords = {eScience, FLOSS, Workflow}, author = {James Howison and Squire, Megan and Kevin Crowston} }