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Devesh Narayanan Stanford University
Bas Becker Vrije Universiteit Amsterdam
Luciana Dadderio Edinburgh University
Jocelyn Cranefield Victoria University of Wellington
Wayne Wang Fundação Getulio Vargas

Recent publications

Technological Frames: Interpretations about the Futures of Work and Intelligent Machines on Social Media , Ayşe Öcal; Kevin Crowston
ReelFramer: Human-AI Co-Creation for News-to-Video Translation , Sitong Wang; Samia Menon; Tao Long; Keren Henderson; Dingzeyu Li; Kevin Crowston; Mark Hansen; Jeffrey V. Nickerson; Lydia B. Chilton
Making sense of AI systems development , Mateusz Dolata; Kevin Crowston
AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models , Savvas Petridis; Nicholas Diakopoulos; Kevin Crowston; Mark Hansen; Keren Henderson; Stan Jastrzebski; Jefrey V. Nickerson; Lydia B. Chilton
Project archetypes: A blessing and a curse for AI development , Mateusz Dolata; Kevin Crowston; Gerhard Schwabe

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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H

Lee, M. H., Yun, J. H., Pyka, A., Won, D. K., Kodama, F., Schiuma, G., et al.. (2018). How to respond to the fourth industrial revolution, or the second information technology revolution? Dynamic new combinations between technology, market, and society through open innovation. Journal Of Open Innovation: Technology, Market, And Complexity, 4(3), 21. https://doi.org/10.3390/joitmc4030021

Lee, M. H., Yun, J. H., Pyka, A., Won, D. K., Kodama, F., Schiuma, G., et al.. (2018). How to respond to the fourth industrial revolution, or the second information technology revolution? Dynamic new combinations between technology, market, and society through open innovation. Journal Of Open Innovation: Technology, Market, And Complexity, 4(3), 21. https://doi.org/10.3390/joitmc4030021

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

Lee, C. - Shing, Wang, M. - Hui, Ko, L. - Wei, Kubota, N., Lin, L. - An, Kitaoka, S., et al.. (2018). Human and smart machine co-learning with brain computer interface. Ieee Smc Magazine, 4. Retrieved de https://arxiv.org/abs/1802.06521

Lee, C. - Shing, Wang, M. - Hui, Ko, L. - Wei, Kubota, N., Lin, L. - An, Kitaoka, S., et al.. (2018). Human and smart machine co-learning with brain computer interface. Ieee Smc Magazine, 4. Retrieved de https://arxiv.org/abs/1802.06521

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

Ebel, P., Söllner, M., Leimeister, J. Marco, Crowston, K., & de Vreede, G. - J.. (2021). Hybrid intelligence in business networks. Electronic Markets. https://doi.org/10.1007/s12525-021-00481-4

Ebel2021_Article_HybridIntelligenceInBusinessNe.pdf (605.72 KB)

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J. Munoz, P., Boger, R., Dexter, S., Low, R., & Li, J.. (2018). Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science (T. Bui, Tran.). In Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.00010.24251/HICSS.2018.359

J. Munoz, P., Boger, R., Dexter, S., Low, R., & Li, J.. (2018). Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science (T. Bui, Tran.). In Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.00010.24251/HICSS.2018.359

Lamberton, C., Brigo, D., & Hoy, D.. (2017). Impact of robotics, RPA and AI on the insurance industry. The Journal Of Financial Perspectives: Insurance. Retrieved de https://www.ey.com/Publication/vwLUAssets/ey-impact-of-robotics-rpa-and-ai-on-the-insurance-industry-challenges-and-opportunities/%24File/ey-impact-of-robotics-rpa-and-ai-on-the-insurance-industry-challenges-and-opportunities.pdf

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

Jung, J. Hwa, & Lim, D. Geon. (2020). Industrial robots, employment growth, and labor cost: A simultaneous equation analysis. Technological Forecasting And Social Change, 159, 120202. https://doi.org/10.1016/j.techfore.2020.120202

Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., & Elhadad, N.. (2015). Intelligible Models for HealthCare (L. Cao, Zhang, C., Joachims, T., Webb, G., Margineantu, D. D., & Williams, G., Trans.). In the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15 (1721 - 1730). https://doi.org/10.1145/278325810.1145/2783258.2788613

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Manyika, J., Lund, S., Chui, M., Woetzel, J., Ko, R., Sanghvi, S., et al.. (2017). Jobs lost, jobs gained: Workforce transactions in a time of automation. In McKinsey Global Institute. Retrieved de https://www.mckinsey.com/~/media/mckinsey/featured%20insights/future%20of%20organizations/what%20the%20future%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/mgi-jobs-lost-jobs-gained-report-december-6-2017.ashx

M

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

Huettmann, F., Craig, E. H., Herrick, K. A., Baltensperger, A. P., Humphries, G., Lieske, D. J., et al.. (2018). Machine Learning for Ecology and Sustainable Natural Resource ManagementUse of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook (pp. 27 - 61; G. Humphries, Magness, D. R., & Huettmann, F., Eds.). In (pp. 27 - 61). https://doi.org/10.1007/978-3-319-96978-7_2

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

Beller, E., Clark, J., Tsafnat, G., Adams, C., Diehl, H., Lund, H., et al.. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, (77). https://doi.org/10.1186/s13643-018-0740-7

Beller, E., Clark, J., Tsafnat, G., Adams, C., Diehl, H., Lund, H., et al.. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, 7(1). https://doi.org/10.1186/s13643-018-0740-7

Capatina, A., Kachour, M., Lichy, J., Micu, A., Micu, A. Eliza, & Codignola, F.. (2020). Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users' expectations. Technological Forecasting And Social Change, 151, 119794. https://doi.org/10.1016/j.techfore.2019.119794

Loh, E. (2018). Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health. Bmj Leader, 2(2), 59 - 63. https://doi.org/10.1136/leader-2018-000071

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