Papers

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Galliers, R. D., Newell, S., Shanks, G., & Topi, H.. (2017). The strategic opportunities and challenges of algorithmic decision-making. The Journal Of Strategic Information Systems, 26(3), 185 - 190. https://doi.org/10.1016/j.jsis.2017.08.002
Kuhn, T. (2015). Science bot: a model for the future computation (A. Gangemi, Leonardi, S., & Panconesi, A., Trans.). In the 24th International ConferenceProceedings of the 24th International Conference on World Wide Web - WWW '15 Companion (1061 - 1062). https://doi.org/10.1145/2740908.2742014
Garcia-Murillo, M., & MacInnes, I.. (2019). AI’s path to the present and the painful transitions along the way. Digital Policy, Regulation And Governance, 21(3), 305 - 321. https://doi.org/10.1108/DPRG-09-2018-0051
Garcia-Murillo, M., MacInnes, I., & Bauer, J. M.. (2018). Techno-unemployment: A framework for assessing the effects of information and communication technologies on work. Telematics And Informatics, 35(7), 1863 - 1876. https://doi.org/10.1016/j.tele.2018.05.013
Metcalfe, J. S., Marathe, A. R., Haynes, B., Paul, V. J., Gremillion, G. M., Drnec, K., et al.. (2017). SPIE ProceedingsBuilding a framework to manage trust in automation. In SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX (10194, 101941U). https://doi.org/10.1117/12.2264245
Lee, H., Kwon, H., Robinson, R. M., Nothwang, W. D., & Marathe, A. R.. (2016). SPIE ProceedingsAn efficient fusion approach for combining human and machine decisions. In SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications VIII (9836, 983621). https://doi.org/10.1117/12.2220788
Gill, K. S. (2018). Looking though the Pygmalion Lens. Ai & Society, 33(4), 459 - 465. https://doi.org/10.1007/s00146-018-0866-0
Gillespie, T. (2017). Algorithmically recognizable: Santorum’s google problem, and google’s santorum problem. Information, Communication & Society, 20(1), 63 - 80. https://doi.org/10.1080/1369118X.2016.1199721
Gladden, M. (2014). Leveraging the cross-cultural capacities of artificial agents as leaders of human virtual teams. In European 10th Conference on Management Leadership and Governance. Presented at the European 10th Conference on Management Leadership and Governance. Retrieved de https://www.researchgate.net/publication/268982256_Leveraging_the_Cross-Cultural_Capacities_of_Artificial_Agents_as_Leaders_of_Human_Virtual_Teams
Goldfarb, A., & Tucker, C.. (2019). Digital Economics. Journal Of Economic Literature, 57(1), 3 - 43. https://doi.org/10.1257/jel.20171452
Gombolay, M., Bair, A., Huang, C., & Shah, J.. (2017). Situational awareness, workload, and workflow preferences. The International Journal Of Robotics Research, 36(5-7), 597 - 617. https://doi.org/10.1177/0278364916688255
Goos, M. (2018). The impact of technological progress on labour markets: policy challenges. Oxford Review Of Economic Policy, 34(3), 362 - 375. https://doi.org/10.1093/oxrep/gry002
Grant, A. M., & Parker, S. K.. (2009). Redesigning work design theories: The rise of relational and proactive perspectives. The Academy Of Management Annals, 3(1), 317 - 375. https://doi.org/10.1080/19416520903047327
Morgeson, F. P., Dierdorff, E. C., & Hmurovic, J. L.. (2010). Understanding the role of occupational and organizational context. Journal Of Organizational Behavior, 31(2-3), 351 - 360. https://doi.org/10.1002/job.642
Oldham, G. R., & J. Hackman, R.. (2010). Not what it was and not what it will be: The future of job design research. Journal Of Organizational Behavior, 31(2-3), 463 - 479. https://doi.org/10.1002/job.v31:2/310.1002/job.678

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