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Dyuti Pandya European Centre for International Political Economy
Devesh Narayanan Stanford University
Bas Becker Vrije Universiteit Amsterdam
Luciana Dadderio Edinburgh University
Jocelyn Cranefield Victoria University of Wellington

Recent publications

The Role of Human Creativity in the Presence of AI Creativity Tools at Work: A Case Study on AI-Driven Content Transformation in Journalism , Sitong Wang; Jocelyn McKinnon-Crowley; Tao Long; Kian Loong Lua; Keren Henderson; Kevin Crowston; Jeffrey V. Nickerson; Mark Hansen; Lydia B. Chilton
Deskilling and upskilling with AI systems , Kevin Crowston; Francesco Bolici
Artificial Intelligence and the Future of Citizen Science , Lucy Fortson; Kevin Crowston; Laure Kloetzer; Marisa Ponti
Editorial: Sharing work with AI: introduction to the special issue on the futures of work in the age of intelligent machines , Kevin Crowston; Ingrid Erickson; Jeffrey Nickerson
Taming artificial intelligence: A theory of control–accountability alignment among AI developers and users , Gudela Grote; Sharon Parker; Kevin Crowston

Recently added resources

Work in The Age Of AI, Robots, and Algorithms , Syllabus , Diane Bailey
Comm493: Analytics and Artificial Intelligence for Business , Syllabus , Tracy Jenkin

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2019

Hines, A. (2019). Getting ready for a post-work future. Foresight And Sti Governance, 13(1), 19 - 30. https://doi.org/10.17323/2500-2597.2019.1.19.30

von Wolff, R. Meyer, Hobert, S., & Schumann, M.. (2019). How May I Help You? – State of the Art and Open Research Questions for Chatbots at the Digital Workplace (T. Bui, Tran.). 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.2019.013

Duckworth, P., Graham, L., & Osborne, M.. (2019). Inferring work task automatability from AI expert evidence (V. Conitzer, Hadfield, G., & Vallor, S., Trans.). 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

Countanche, M. N., & Hallion, L. S.. (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

Kühl, N., Goutier, M., Hirt, R., & Satzger, G.. (2019). Machine learning in Artificial Intelligence: Towards a common understanding (T. Bui, Tran.). 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

Liang, H. - F., Wu, K. - M., Weng, C. - H., & Hsieh, H. - W.. (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

Hagerty, A., & Rubinov, I.. (2019). A Review of the Social Impacts and Ethical Implications of Artificial Intelligence. Retrieved de https://arxiv.org/ftp/arxiv/papers/1907/1907.07892.pdf

Kittur, A., Yu, L., Hope, T., Chan, J., Lifshitz-Assaf, H., Gilon, K., et al.. (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

Herzenberg, S., & Alic, J.. (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

Hmoud, B., & Laszlo, V.. (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

Martine-Plumed, F., Avin, S., Brundage, M., Dafoe, A., hEigeartaigh, S. O., & Hernández-Orallo, J.. (2018). Accounting for the neglected dimensions of AI progress. Data-Efficient Ml. Retrieved de https://arxiv.org/abs/1806.00610

Martine-Plumed, F., Avin, S., Brundage, M., Dafoe, A., hEigeartaigh, S. O., & Hernández-Orallo, J.. (2018). Accounting for the neglected dimensions of AI progress. Data-Efficient Ml. Retrieved de https://arxiv.org/abs/1806.00610

Jokisch, O., & Huber, M.. (2018). Advances in the development of a cognitive user interface. Matec Web Of Conferences, 161, 01003. https://doi.org/10.1051/matecconf/201816101003

Gholami, B., Haddad, W. M., & Bailey, J. M.. (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/

Lee, Y., Ragguett, R. - M., Mansur, R. B., Boutilier, J. J., Rosenblat, J. D., Trevizol, A., et al.. (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

Brynjolfsson, E., Hui, X., & Liu, M.. (2018). Artificial intelligence can transform the economy. Retrieved de https://www.washingtonpost.com/opinions/artificial-intelligence-can-transform-the-economy/2018/09/18/50c9c9c8-bab8-11e8-bdc0-90f81cc58c5d_story.html

Kelley, K. H., Fontanetta, L. M., Heintzman, M., & Pereira, N.. (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

Huang, M. - H., & Rust, R. T.. (2018). Artificial Intelligence in Service. Journal Of Service Research, 21(2), 155 - 172. https://doi.org/10.1177/1094670517752459

Jones, L. D., Golan, D., Hanna, S. A., & Ramachandran, M.. (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.

Jones, L. D., Golan, D., Hanna, S. A., & Ramachandran, M.. (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

Gómez, E., Castillo, C., Charisi, V., Dahl, V., Deco, G., Delipetrev, B., et al.. (2018). As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour. Retrieved de https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf

Gómez, E., Castillo, C., Charisi, V., Dahl, V., Deco, G., Delipetrev, B., et al.. (2018). As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour. Retrieved de https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf

Haratsis, B., Carmichael, T., Coutney, M., & Fong, J.. (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

Bednarek, A. T., Wyborn, C., Cvitanovic, C., Meyer, R., Colvin, R. M., Addison, P. F. E., et al.. (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

He, E. (2018). Can artificial intelligence make work more human?. Strategic Hr Review, 17(5), 263 - 264. https://doi.org/10.1108/SHR-10-2018-146

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