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Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, (77). https://doi.org/10.1186/s13643-018-0740-7
. (2018). . (2017).
Models and people: An alternative view of the emergent properties of computational models. Complexity, 21(6), 202 - 213. https://doi.org/10.1002/cplx.21680
. (2016). Mining programming activity to promote help (pp. 23 - 42; ). In (pp. 23 - 42). https://doi.org/10.1007/978-3-319-20499-4_2
. (2015). Machine learning in Artificial Intelligence: Towards a common understanding ( ). In Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2019.630
. (2019). Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users' expectations. Technological Forecasting And Social Change, 151, 119794. https://doi.org/10.1016/j.techfore.2019.119794
. (2020). Massive technological unemployment without redistribution: A case for cautious optimism. Science And Engineering Ethics, 25(5), 1389 - 1407. https://doi.org/10.1007/s11948-018-0070-0
. (2019). . (2019).
Making sense of AI systems development. Ieee Transactions On Software Engineering, 50(1), 123–140. https://doi.org/10.1109/TSE.2023.3338857
. (2024). sensemaking_tse_to_share.pdf (619.73 KB)Managing talented worker in the era of new psychological contract. Jurnal Aplikasi Manajemen, 16(1), 20 - 26. https://doi.org/10.21776/ub.jam.2018.016.01.03
. (2018). A method to link advances in Artificial Intelligence to occupational abilities. Aea Papers And Proceedings, 108, 54 - 57. https://doi.org/10.1257/pandp.20181021
. (2018). Machine intelligence: Blessing or curse? It depends on us! (pp. 25 - 39; ). In (pp. 25 - 39). https://doi.org/10.1007/978-3-319-90869-4_4
. (2018). Machine Learning for Ecology and Sustainable Natural Resource ManagementMachine Learning and ‘The Cloud’ for Natural Resource Applications: Autonomous Online Robots Driving Sustainable Conservation Management Worldwide? (pp. 353 - 377; ). In (pp. 353 - 377). https://doi.org/10.1007/978-3-319-96978-7_18
. (2018). Machine Learning for Ecology and Sustainable Natural Resource ManagementUse of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook (pp. 27 - 61; ). In (pp. 27 - 61). https://doi.org/10.1007/978-3-319-96978-7_2
. (2018). Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective. In , Machine Learning for Ecology and Sustainable Natural Resource Management (pp. 3 - 26). https://doi.org/10.1007/978-3-319-96978-7_1
. (2018). Machine learning and decision support in critical care. Proceedings Of The Ieee, 104(2), 444 - 466. https://doi.org/10.1109/JPROC.2015.2501978
. (2016). Machine learning-based clinical prediction modeling – A practical guide for clinicians. Artificial Intelligence In Precision Health, 257–278. https://doi.org/10.1016/b978-0-12-817133-2.00011-2
. (2020). Moral reasoning at work automation and ethics (pp. 69 - 77). In (pp. 69 - 77). Retrieved de 10.1007/978-3-030-15191-1_8
. (2019). The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172 - 181. https://doi.org/10.1016/j.tourman.2019.02.006
. (2019). Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health. Bmj Leader, 2(2), 59 - 63. https://doi.org/10.1136/leader-2018-000071
. (2018). Machine learning concepts, concerns and opportunities for a pediatric radiologist. Pediatric Radiology, 49(4), 509 - 516. https://doi.org/10.1007/s00247-018-4277-7
. (2019). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, 7(1). https://doi.org/10.1186/s13643-018-0740-7
. (2018). A machine is cheaper than a human for the same task. Ai & Society. https://doi.org/10.1007/s00146-018-0874-0
. (2019). Managing Machines: The governance of artificial intelligence. In FCA Conference on Governance in Banking. Retrieved de https://www.bankofengland.co.uk/speech/2019/james-proudman-speech-at-fca-conference-on-governance-in-banking-london
. (2019).