Who's new

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

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
Mutual learning in human-AI interaction , Carsten Østerlund; Kevin Crowston; Casey B. Jackson; Marlene Takou-Ayaoh; Yunan Wu; Aggelos K. Katsaggelos
Technological Frames: Interpretations about the Futures of Work and Intelligent Machines on Social Media , Ayşe Öcal; Kevin Crowston
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

Recently added resources

Connected and Autonomous Vehicles in Society: An Agenda for Social and Policy Research , Report , MSU Workshop on Autonomous Vehicles in Society
HCOMP Workshop Report: Work in the Age of Intelligent Machines , Report , Jeffrey V. Nickerson, Matthew Lease
PDW: Work in the Age of Intelligent Machines: Towards Disciplinary Convergence , Report , Kevin Crowston, Mary-Beth Watson-Manheim, Ingrid Erickson, Jeffrey V. Nickerson

Pages

You are here

Papers

Search

Show only items where

Author

Type

Term

Year

Keyword

Export 11 results:

Filters: First Letter Of Last Name is T [Clear All Filters]

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

D

Cruz-Roa, A., Gilmore, H., Basavanhally, A., Feldman, M., Ganesan, S., Shih, N. N. C., et al.. (2017). A deep learning approach for quantifying tumor extent. Scientific Reports, 7(1). https://doi.org/10.1038/srep46450

Møller, N. L. Holten, Bjørn, P., Villumsen, J. Christoffe, Hancock, T. C. Hansen, Aritake, T., & Tani, S.. (2017). Data tracking in search of workflows (C. P. Lee, Poltrock, S., Barkhuus, L., Borges, M., & Kellogg, W., Trans.). In the 2017 ACM ConferenceProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17 (2153 - 2165). https://doi.org/10.1145/2998181.2998296

C

Wogu, I. Ayodele, Misra, S., Assibong, P., Adewumi, A., Damasevicius, R., & Maskeliunas, R.. (2018). A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force (Vol. 10963, pp. 217 - 232; O. Gervasi, Murgante, B., Misra, S., Stankova, E., Torre, C. M., Rocha, A. Maria A. C., et al., Eds.). In (Vol. 10963, pp. 217 - 232). https://doi.org/10.1007/978-3-319-95171-3_18

Wogu, I. Ayodele, Misra, S., Assibong, P., Adewumi, A., Damasevicius, R., & Maskeliunas, R.. (2018). A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force (Vol. 10963, pp. 217 - 232; O. Gervasi, Murgante, B., Misra, S., Stankova, E., Torre, C. M., Rocha, A. Maria A. C., et al., Eds.). In (Vol. 10963, pp. 217 - 232). https://doi.org/10.1007/978-3-319-95171-3_18

Wogu, I. Ayodele, Misra, S., Assibong, P., Adewumi, A., Damasevicius, R., & Maskeliunas, R.. (2018). A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force (Vol. 10963, pp. 217 - 232; O. Gervasi, Murgante, B., Misra, S., Stankova, E., Torre, C. M., Rocha, A. Maria A. C., et al., Eds.). In (Vol. 10963, pp. 217 - 232). https://doi.org/10.1007/978-3-319-95171-3_18

Brinker, T. J., Hekler, A., Enk, A., Klode, J., Hauschild, A., Berking, C., et al.. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005

Brinker, T. J., Hekler, A., Enk, A., Klode, J., Hauschild, A., Berking, C., et al.. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005

Brinker, T. J., Hekler, A., Enk, A., Klode, J., Hauschild, A., Berking, C., et al.. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005

Poon, S. S., Thomas, R. C., Aragon, C., & Lee, B.. (2008). Context-linked virtual assistants for distributed teams: an astrophysics case study. In Proceedings of the ACM Conference on Computer Supported Cooperative Work (361–370).

Poon, S. S., Thomas, R. C., Aragon, C. R., & Lee, B.. (2008). Context-linked virtual assistants for distributed teams (B. Begole & McDonald, D. W., Trans.). In the ACM 2008 conferenceProceedings of the ACM 2008 conference on Computer supported cooperative work - CSCW '08 (361). https://doi.org/10.1145/1460563.1460623

B

Roco, M. C., Bainbridge, W. S., Tonn, B., & Whitesides, G.. (2013). Beyond convergence of Nano-Bio-Info-Cognitive technologies. In WTEC Study on Convergence of Knowledge, Technology, and Society. Retrieved de http://www.wtec.org/NBIC2/Docs/FinalReport/Pdf-secured/NBIC2-FinalReport-WEB.pdf

A

Tyers, R., & Zhou, Y.. (2018). Automation, taxes and transfers with international rivalry. In Centre for Applied Macroeconomic Analysis. Retrieved de https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2018-09/44_2018_tyers_zhou.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

Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlstrom, P., et al.. (2017). Artificial Intelligence: The next digital frontier. Mckinsey Global Institute. Retrieved de https://www.mckinsey.com/~/media/McKinsey/Industries/Advanced%20Electronics/Our%20Insights/How%20artificial%20intelligence%20can%20deliver%20real%20value%20to%20companies/MGI-Artificial-Intelligence-Discussion-paper.ashx

Musib, M., Wang, F., Tarselli, M. A., Yoho, R., Yu, K. - H., Andrés, R. Medina, et al.. (2017). Artificial intelligence in research. Science, 357(6346), 28 - 30. https://doi.org/10.1126/science.357.6346.28

Hager, G. D., Drobnis, A., Fang, F., Ghani, R., Greenwald, A., Lyons, T., et al.. (2017). Artificial Intelligence For Social Good. Retrieved de https://cra.org/ccc/wp-content/uploads/sites/2/2016/04/AI-for-Social-Good-Workshop-Report.pdf

Danysz, K., Cicirello, S., Mingle, E., Assuncao, B., Tetarenko, N., Mockute, R., et al.. (2019). Artificial Intelligence and the Future of the Drug Safety Professional. Drug Safety, 42(4), 491 - 497. https://doi.org/10.1007/s40264-018-0746-z

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

Todolí-Signes, A.. (2019). Algorithms, artificial intelligence and automated decisions concerning workers and the risks of discrimination: the necessary collective governance of data protection. Transfer: European Review Of Labour And Research, 25(4), 465 - 481. https://doi.org/10.1177/1024258919876416

Pages