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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

Balta, D., Kuhn, P., Sellami, M., Kulus, D., Lieven, C., & Krcmar, H.. (2019). How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany (I. Lindgren, Janssen, M., Lee, H., Polini, A., Bolívar, M. Pedro Rodr, Scholl, H. Jochen, & Tambouris, E., Eds.). In Electronic Government (pp. 233-247). https://doi.org/10.1007/978-3-030-27325-5

Balta, D., Kuhn, P., Sellami, M., Kulus, D., Lieven, C., & Krcmar, H.. (2019). How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany (I. Lindgren, Janssen, M., Lee, H., Polini, A., Bolívar, M. Pedro Rodr, Scholl, H. Jochen, & Tambouris, E., Eds.). In Electronic Government (pp. 233-247). https://doi.org/10.1007/978-3-030-27325-5

Balta, D., Kuhn, P., Sellami, M., Kulus, D., Lieven, C., & Krcmar, H.. (2019). How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany (I. Lindgren, Janssen, M., Lee, H., Polini, A., Bolívar, M. Pedro Rodr, Scholl, H. Jochen, & Tambouris, E., Eds.). In Electronic Government (pp. 233-247). https://doi.org/10.1007/978-3-030-27325-5

Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. Marco. (2019). Hybrid Intelligence. Business & Information Systems Engineering, 61(5), 637 - 643. https://doi.org/10.1007/s12599-019-00595-2

Reis, J., Santo, P. Espírito, Lisbon, P., & Melão, N.. (2019). Impacts of Artificial Intelligence on Public Administration: A Systematic Literature Review. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). Presented at the 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). Retrieved de https://ieeexplore.ieee.org/document/8760778

Moore, M. M., Slonimsky, E., Long, A. D., Sze, R. W., & Iyer, R. S.. (2019). Machine learning concepts, concerns and opportunities for a pediatric radiologist. Pediatric Radiology, 49(4), 509 - 516. https://doi.org/10.1007/s00247-018-4277-7

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

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

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

Raghavan, M., Barocas, S., & Levy, J. KleinbergK.. (2019). Mitigating bias in algorithmic employment screening: Evaluating claims and practices. Retrieved de https://www.researchgate.net/publication/333971698_Mitigating_Bias_in_Algorithmic_Employment_Screening_Evaluating_Claims_and_Practices

Li, J. (Justin), Bonn, M. A., & Ye, B. Haobin. (2019). The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172 - 181. https://doi.org/10.1016/j.tourman.2019.02.006

Chiou, E. K., Lee, J. D., & Su, T.. (2019). Negotiated and reciprocal exchange structures in human-agent cooperation. Computers In Human Behavior, 90, 288 - 297. https://doi.org/10.1016/j.chb.2018.08.012

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

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

Correia, A., Jameel, S., Paredes, H., Fonseca, B., & Schneider, D.. (2019). Steps toward a scaffolding design framework (pp. 149 - 161; V. - J. Khan, Papangelis, K., Lykourentzou, I., & Markopoulos, P., Eds.). In (pp. 149 - 161). https://doi.org/10.1007/978-3-030-12334-5_5

Pendleton-Jullian, A., & Lempert, R.. (2019). Technology and Work Worth Doing (Not Jobs) Post-AlphaGo: A World-Building Workshop on the Future of Artificial Intelligence. https://doi.org/10.7249/CF398

Landgrebe, J. (2019). There is no general AI: Why Turing machines cannot pass the Turing test. Retrieved de https://arxiv.org/abs/1906.05833

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

Androutsopoulou, A., Karacapilidis, N., Loukis, E., & Charalabidis, Y.. (2019). Transforming the communication between citizens and government through AI-guided chatbots. Government Information Quarterly, 36(2), 358 - 367. https://doi.org/10.1016/j.giq.2018.10.001

Langlotz, C. P. (2019). Will Artificial Intelligence Replace Radiologists?. Radiology: Artificial Intelligence, 1(3), e190058. https://doi.org/10.1148/ryai.2019190058

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

2020

Cebreros, A., Heffner-Rodríguez, A., Livas, R., & Puggioni, D.. (2020). Automation Technologies and Employment at Risk : The Case of Mexico. Banco de México.

Johnson, R. D., Stone, D. L., & Lukaszewski, K. M.. (2020). The benefits of eHRM and AI for talent acquisition. Journal Of Tourism Futures. https://doi.org/10.1108/JTF-02-2020-0013

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