crowston

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2020
Dalgali, A., & Crowston, K.. (2020). Algorithmic Journalism and Its Impacts on Work. In Computation + Journalism Symposium. Presented at the Computation + Journalism Symposium . Retrieved de https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_26.pdf
PDF icon CJ_2020_paper_26.pdf (1.24 MB)
Dalgali, A., & Crowston, K.. (2020). Factors Influencing Approval of Wikipedia Bots. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.018
PDF icon HICSS_WikipediaPaper_3.9.new kc (2).pdf (473.63 KB)
Harandi, M., Crowston, K., Jackson, C., & Østerlund, C.. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719
PDF icon Social_Construction_of_ML_in_GS_HICCS2020.pdf (124.3 KB)
Crowston, K., & Bolici, F.. (2020). Impacts of Machine Learning on Work Design. Syracuse, NY: Syracuse University School of Information Studies.
PDF icon Impact of machine learning on work.pdf (604.31 KB)
Crowston, K. (2020). Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers. In Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual. Presented at the Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual, Virtual workshop.
PDF icon Everyday_automation camera ready.pdf (421.84 KB)
2019
Crowston, K., & Bolici, F.. (2019). Impacts of machine learning on work. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.719
PDF icon Impacts_of_machine_learning_on_work__revision_.pdf (300.76 KB)
2017
Crowston, K., Østerlund, C., & Lee, T. Kyoung. (2017). Blending machine and human learning processes. In Hawai'i International Conference on System Sciences. https://doi.org/10.24251/HICSS.2017.009
PDF icon training v3 to share.pdf (245.57 KB)
Zevin, M., Coughlin, S., Bahaadini, S., Besler, E., Rohani, N., Allen, S., et al.. (2017). Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science. Classical And Quantum Gravity, 34, 064003. https://doi.org/10.1088/1361-6382/aa5cea