Papers
Export 11 results:
Filters: First Letter Of Last Name is M [Clear All Filters]
The economics of artificial intelligence: Implications for the future of work. In International Labour Office. Retrieved de https://www.ilo.org/wcmsp5/groups/public/---dgreports/---cabinet/documents/publication/wcms_647306.pdf
. (2018). Ethics of using Artificial Intelligence to augment drafting legal documents. Texas A&M Journal Of Property Law, 4(5). Retrieved de https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1080&context=journal-of-property-law
. (2018). The evolving role of ICT in the economy. In The London School of Economics and Political Science. Retrieved de http://www.lse.ac.uk/business-and-consultancy/consulting/consulting-reports/the-evolving-role-of-ict-in-the-economy
. (2018). . (2018).
Fedex follows Amazon into the robotic future. The New York Times. Retrieved de https://www.nytimes.com/2018/03/18/technology/fedex-robots.html
. (2018). foo.castr: visualising the future AI workforce. Big Data Analytics, 3(1). https://doi.org/10.1186/s41044-018-0034-z
. (2018). Google Researchers Are Learning How Machines Learn. Retrieved de The NewYork Times website: https://www.nytimes.com/2018/03/06/technology/google-artificial-intelligence.html
. (2018). High tech, low growth: Robots and the future of work abstract. Historical Materialism, 26(4), 3 - 34. https://doi.org/10.1163/1569206X-00001745
. (2018). How do machine learning, robotic process automation, and blockchains affect the human factor in business process management?. Communications Of The Association For Information Systems, 297 - 320. https://doi.org/10.17705/1CAIS.04319
. (2018). Human capital management and future of work; job creation and unemployment: a literature review. Oalib, 05(09), 1 - 17. https://doi.org/10.4236/oalib.1104859
. (2018). Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science ( ). In Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.00010.24251/HICSS.2018.359
. (2018). Industrial employment and income inequality: Evidence from panel data. Structural Change And Economic Dynamics, 45, 84 - 93. https://doi.org/10.1016/j.strueco.2018.02.006
. (2018). Is IT changing the world? Conceptions of causality for information systems theorizing. Mis Quarterly, 42(4), 1255-1280. Retrieved de https://dl.acm.org/citation.cfm?id=3370119.3370131
. (2018). Lecture Notes in Computer ScienceArtificial General IntelligenceTowards a Sociological Conception of Artificial Intelligence (Vol. 10999, pp. 130 - 139; ). In (Vol. 10999, pp. 130 - 139). https://doi.org/10.1007/978-3-319-97676-1
. (2018). Lecture Notes in Computer ScienceDesign, User Experience, and Usability: Theory and PracticeComparing Human Against Computer Generated Designs: New Possibilities for Design Activity Within Agile Projects (Vol. 10918, pp. 693 - 710; ). In (Vol. 10918, pp. 693 - 710). https://doi.org/10.1007/978-3-319-91797-9_48
. (2018). A literature Analysis of Research on Artificial Intelligence in Management Information System (MIS). In Americas Conference on Information Systems.
. (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 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 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 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 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). Machines as Teammates: A Collaboration Research Agenda. In Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.055
. (2018). SeeberEtAl_2018_MachinesAsTeammates.pdf (949.98 KB)Machines as Teammates: A Collaboration Research Agenda. In Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.055
. (2018). SeeberEtAl_2018_MachinesAsTeammates.pdf (949.98 KB)