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crowston

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F
Öcal, A., & Crowston, K.. (2024). Framing and feelings on social media: The futures of work and intelligent machines. Information, Technology & People. https://doi.org/10.1108/ITP-01-2023-0049
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M
Dolata, M., & Crowston, K.. (2024). Making sense of AI systems development. Ieee Transactions On Software Engineering, 50(1), 123–140. https://doi.org/10.1109/TSE.2023.3338857
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R
Wang, S., Menon, S., Long, T., Henderson, K., Li, D., Crowston, K., et al.. (2024). ReelFramer: Human-AI Co-Creation for News-to-Video Translation. In CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3613904.3642868
P
Dolata, M., Crowston, K., & Schwabe, G.. (2022). Project archetypes: A blessing and a curse for AI development. In International Conference on Information Systems (ICIS). Presented at the International Conference on Information Systems (ICIS), Copenhagen, Denmark. Retrieved de https://aisel.aisnet.org/icis2022/is_design/is_design/6
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F
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
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I
Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction. https://doi.org/10.1145/3406499.3415070
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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.
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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
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B
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
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