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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

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2019

Zhang, H., Feinzi, S., Raisbec, L., McCombe, I., Guenol, N., Montalt, J., & Messe, K.. (2019). IBM Talent Management Solutions The role of AI in mitigating bias to enhance diversity and inclusion. Presented at the. Retrieved de https://www.ibm.com/downloads/cas/2DZELQ4O

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

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

Salvucci, M., Rahman, A., Resler, A. J., Udupi, G. M., McNamara, D. A., Kay, E. W., et al.. (2019). A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic. Jco Clinical Cancer Informatics, (3), 1 - 17. https://doi.org/10.1200/CCI.18.00056

Saba, L., Biswas, M., Kuppili, V., Godia, E. Cuadrado, Suri, H. S., Edla, D. Reddy, et al.. (2019). The present and future of deep learning in radiology. European Journal Of Radiology, 114, 14 - 24. https://doi.org/10.1016/j.ejrad.2019.02.038

Saba, L., Biswas, M., Kuppili, V., Godia, E. Cuadrado, Suri, H. S., Edla, D. Reddy, et al.. (2019). The present and future of deep learning in radiology. European Journal Of Radiology, 114, 14 - 24. https://doi.org/10.1016/j.ejrad.2019.02.038

Levine, A. B., Schlosser, C., Grewal, J., Coope, R., Jones, S. J. M., & Yip, S.. (2019). Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis. Trends In Cancer, 5(3), 157 - 169. https://doi.org/10.1016/j.trecan.2019.02.002

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

Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., et al.. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings Of The National Academy Of Sciences, 116, 6531–6539. https://doi.org/10.1073/pnas.1900949116

Greco, C., Polonioli, A., & Tagliabue, J.. (2019). Why small data holds the key to the future of artificial intelligence. In 8th International Conference on Data Science, Technology and ApplicationsProceedings of the 8th International Conference on Data Science, Technology and Applications (340 - 347). https://doi.org/10.5220/0007956203400347

2020

Gentili, A., Compagnucci, F., Gallegati, M., & Valentini, E.. (2020). Are machines stealing our jobs?. Cambridge Journal Of Regions, Economy And Society, 13, 153–173. https://doi.org/10.1093/cjres/rsz025

Gentili, A., Compagnucci, F., Gallegati, M., & Valentini, E.. (2020). Are machines stealing our jobs?. Cambridge Journal Of Regions, Economy And Society, 13, 153–173. https://doi.org/10.1093/cjres/rsz025

Bessen, J., Goos, M., Salomons, A., & van den Berge, W.. (2020). Automation: A Guide for Policymakers. Retrieved de https://www.brookings.edu/research/automation-a-guide-for-policymakers/

Gerber, A., Derckx, P., Döppner, D. A., & Schoder, D.. (2020). Conceptualization of the Human-Machine Symbiosis – A Literature Review. In Proceedings of the 53rd Hawaii International Conference on System Sciences (3, 289–298). https://doi.org/10.24251/hicss.2020.036

Mart'nez-Plumed, F., Tolan, S. 'l, Pesole, A., Hern'ndez-Orallo, J., Fern'ndez-Mac'as, E., & G'mez, E.. (2020). Does AI qualify for the job? A bidirectional model mapping labour and AI intensities. In AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (94–100). https://doi.org/10.1145/3375627.3375831

Hacker, P., Krestel, R., Grundmann, S., & Naumann, F.. (2020). Explainable AI under contract and tort law: legal incentives and technical challenges. Artificial Intelligence And Law. https://doi.org/10.1007/s10506-020-09260-6

H. Harvey, B., & Gowda, V.. (2020). How the FDA regulates AI. Academic Radiology, 27(1), 58 - 61. https://doi.org/10.1016/j.acra.2019.09.017

Grimshaw, D. (2020). International organisations and the future of work: How new technologies and inequality shaped the narratives in 2019. In Journal of Industrial Relations (pp. 477–507). https://doi.org/10.1177/0022185620913129

Brundage, M., Avin, S., Wang, J., Belfield, H., Krueger, G., Hadfield, G., et al.. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213

Brundage, M., Avin, S., Wang, J., Belfield, H., Krueger, G., Hadfield, G., et al.. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. 1–9. Retrieved de http://arxiv.org/abs/2004.07213

Clifton, J., Clifton, J., Glasmeier, A., & Gray, M.. (2020). When machines think for us: The consequences for work and place. Cambridge Journal Of Regions, Economy And Society, 13, 3–23. https://doi.org/10.1093/cjres/rsaa004

Clifton, J., Clifton, J., Glasmeier, A., & Gray, M.. (2020). When machines think for us: The consequences for work and place. Cambridge Journal Of Regions, Economy And Society, 13, 3–23. https://doi.org/10.1093/cjres/rsaa004

In Press

Grote, G., Parker, S., & Crowston, K.. (In Press). Taming artificial intelligence: A theory of control–accountability alignment among AI developers and users. Academy Of Management Review. https://doi.org/10.5465/amr.2023.0117

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