Papers
. (In Press). Taming artificial intelligence: A theory of control–accountability alignment among AI developers and users. Academy Of Management Review. https://doi.org/10.5465/amr.2023.0117
. (2025). The task matters: The effect of perceived similarity to AI on intention to use in different task types. In Hawai'i International Conference on System Science.
AI_similarity.pdf (774.81 KB). (2024). Artificial Intelligence and the Future of Citizen Science. Citizen Science: Theory And Practice, 9(1), 32. https://doi.org/10.5334/cstp.812
. (2024). Deskilling and upskilling with generative AI systems. In Working paper.
GAI_and_skills.pdf (281.94 KB). (2024). Editorial: Sharing work with AI: introduction to the special issue on the futures of work in the age of intelligent machines. Information Technology & People, 37(7), 2353 - 2356. https://doi.org/10.1108/ITP-12-2024-994
. (2024). Folksonomies in crowdsourcing platforms: Three tensions associated with the development of shared language in distributed groups. In The European Conference on Computer-Supported Cooperative Work (ECSCW). https://doi.org/10.48340/ecscw2024_n06
ECSCW2024_Folksonomy_Crowdsourcing__Final_.pdf (1.59 MB). (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
frames to share.pdf (391.17 KB). (2024). Gravity Spy: Lessons Learned and a Path Forward. European Physical Journal Plus, 139, Article 100. https://doi.org/10.1140/epjp/s13360-023-04795-4
. (2024). Implications for hybrid newswork from the activities of local US television journalists during COVID. Journalism Practice. https://doi.org/10.1080/17512786.2024.2344643
Implications for hybrid newswork from the activities of local US television journalists during COVID to share.pdf (323.75 KB). (2024). Making sense of AI systems development. Ieee Transactions On Software Engineering, 50(1), 123–140. https://doi.org/10.1109/TSE.2023.3338857
sensemaking_tse_to_share.pdf (619.73 KB). (2024). Mutual learning in human-AI interaction. In Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference. Presented at the Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference, Honolulu, HI.
TREW_Workshop_Paper_2024.pdf (392.26 KB). (2024). ReelFramer: Human-AI Co-Creation for News-to-Video Translation. In CHI '24: CHI Conference on Human Factors in Computing SystemsProceedings of the CHI Conference on Human Factors in Computing Systems (1 - 20). https://doi.org/10.1145/3613904.3642868
. (2024). Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy. Citizen Science: Theory And Practice, 9(1), 42. https://doi.org/10.5334/cstp.738
. (2023). AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3544548.3580907
. (2023). Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications. Classical And Quantum Gravity, 40(6). https://doi.org/10.1088/1361-6382/acb633
. (2023). A decade of surveys on attitudes to data sharing highlights three factors for achieving open science. Retrieved de LSE Impact of Social Science website: https://blogs.lse.ac.uk/impactofsocialsciences/2023/08/22/a-decade-of-surveys-on-attitudes-to-data-sharing-highlights-three-factors-for-achieving-open-science/
. (2023). Design principles for background knowledge to enhance learning in citizen science. In Information for a Better World: Normality, Virtuality, Physicality, Inclusivity: 18th International Conference, iConference (pp. 563–580). https://doi.org/10.1007/978-3-031-28032-0_43
Design_Background_iConf.pdf (3.78 MB). (2023). Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards. Humanities And Social Sciences Communications, 10(1). https://doi.org/10.1057/s41599-023-01831-7
. (2023). Surveys Provide Insight Into Three Factors That Encourage Open Data and Science. Retrieved de Social Science Space website: https://www.socialsciencespace.com/2023/09/surveys-provide-insight-into-three-factors-that-encourage-open-data-and-science/
. (2022). Artificial intelligence in information systems: State of the art and research roadmap. Communications Of The Association For Information Systems (Cais), 50. https://doi.org/10.17705/1CAIS.05017
Artificial Intelligence in Information Systems State of the Art.pdf (1 MB). (2022). Communicating with the masses from isolation: What happened when local television journalists worked from home. In Hawai'i International Conference on System Sciences. Presented at the Hawai'i International Conference on System Sciences, Virtual due to COVID. https://doi.org/10.24251/HICSS.2022.858
Journalists work from home_HICSS Version_Final Submission_Unlinked.pdf (221.34 KB). (2022). Interdisciplinary collaboration from diverse science teams can produce significant outcomes. Plos One, 17(11). https://doi.org/10.1371/journal.pone.0278043
Interdisciplinary collaboration from diverse science teams can produce significant outcomes.pdf (904.84 KB). (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
icis_archetypes_rev1_v20_zora.pdf (433.37 KB). (2021). Assessment, Usability, and Sociocultural Impacts of DataONE: A Global Research Data Cyberinfrastructure Initiative. International Journal Of Digital Curation, 16(1). https://doi.org/10.2218/ijdc.v16i1.678