Papers
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. (2019). Inferring work task automatability from AI expert evidence (). In the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society - AIES '19 (485 - 491). https://doi.org/10.1145/330661810.1145/3306618.3314247
. (2019). Machine learning for clinical psychology and clinical neuroscience. In researchgate.net. Retrieved de https://www.researchgate.net/publication/331000572_Machine_Learning_for_Clinical_Psychology_and_Clinical_Neuroscience
. (2019). 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). Nurses' Views on the Potential Use of Robots in the Pediatric Unit. Journal Of Pediatric Nursing, 47, e58 - e64. https://doi.org/10.1016/j.pedn.2019.04.027
. (2019). Scaling up analogical innovation with crowds and AI. Proceedings Of The National Academy Of Sciences, 116(6), 1870-1877. https://doi.org/10.1073/pnas.1807185116
. (2019). Towards an AI economy that works for all. In Keystone Research Center Future of Work Project sponsored by The Heinz Endowments. Retrieved de https://www.keystoneresearch.org/sites/default/files/FOW_TowardAIEconomyForAllFinalEdit.pdf
. (2019). Will artificial intelligence take over human resources recruitment and selection?. Network Intelligence Studies, VII(13). Retrieved de https://ideas.repec.org/a/cmj/networ/y2019i13p21-30.html
. (2018). Accounting for the neglected dimensions of AI progress. Data-Efficient Ml. Retrieved de https://arxiv.org/abs/1806.00610
. (2018). Accounting for the neglected dimensions of AI progress. Data-Efficient Ml. Retrieved de https://arxiv.org/abs/1806.00610
. (2018). Advances in the development of a cognitive user interface. Matec Web Of Conferences, 161, 01003. https://doi.org/10.1051/matecconf/201816101003
. (2018). AI Could Provide Moment-by-Moment Nursing for a Hospital’s Sickest Patients. Retrieved de spectrum.ieee.org website: https://globaltechnologies.ca/ai-could-provide-moment-by-moment-nursing-for-a-hospitals-sickest-patients/
. (2018). Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review. Journal Of Affective Disorders, 241, 519-532. https://doi.org/10.1016/j.jad.2018.08.073
. (2018). Artificial intelligence: Implications for social inflation and insurance. Risk Management And Insurance Review, 21(3), 373 - 387. https://doi.org/10.1111/rmir.12111
. (2018). Artificial Intelligence in Service. Journal Of Service Research, 21(2), 155 - 172. https://doi.org/10.1177/1094670517752459
. (2018). Artificial intelligence, machine learning and the evolution of healthcare A bright future or cause for concern?. British Journal Of Radiology, 7(7), 223-225.
. (2018). Artificial intelligence, machine learning and the evolution of healthcare. Bone & Joint Research, 7(3), 223 - 225. https://doi.org/10.1302/2046-3758.73.BJR-2017-0147.R1
. (2018). Autonomous vehicles employment impact study. In Australia & New Zealand Driverless Vehicle Initiate. Retrieved de https://advi.org.au/wp-content/uploads/2018/09/Autonomous-Vehicles-Employment-Impact-Survey-COR050918-5.pdf
. (2018). Boundary spanning at the science–policy interface: the practitioners’ perspectives. Sustainability Science, 13(4), 1175 - 1183. https://doi.org/10.1007/s11625-018-0550-9
. (2018). Can artificial intelligence make work more human?. Strategic Hr Review, 17(5), 263 - 264. https://doi.org/10.1108/SHR-10-2018-146
. (2018). Comment on “Should we fear the robot revolution? (The correct answer is yes)” by Andrew Berg, Ed Buffie, and Felipe Zanna. Journal Of Monetary Economics, 97, 149 - 152. https://doi.org/10.1016/j.jmoneco.2018.05.012
. (2018). Computational power and the social impact of artificial intelligence. Ssrn Electronic Journal. https://doi.org/10.2139/ssrn.3147971