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

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

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 H [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

Brinker, T. J., Hekler, A., Enk, A., Klode, J., Hauschild, A., Berking, C., et al.. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001

Brinker, T. J., Hekler, A., Enk, A., Klode, J., Hauschild, A., Berking, C., et al.. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001

Larsen, K. R., Hovorka, D. S., Dennis, A. R., & West, J. D.. (2018). The discourse approach to boundary identification and corpus construction for theory review articles. Journal Of The Association For Information Systems. Retrieved de https://www.researchgate.net/publication/325215971_Understanding_the_Elephant_The_Discourse_Approach_to_Boundary_Identification_and_Corpus_Construction_for_Theory_Review_Articles

Hershbein, B. (2018). Discussion for JME special issue: APST paper. Journal Of Monetary Economics, 97, 68 - 70. https://doi.org/10.1016/j.jmoneco.2018.05.003

Hutchins, E., & Klausen, T.. (1996). Distributed cognition in an airline cockpit. Cognition And Communication At Workcognition And Communication At Work, 15–34.

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

E

Gemmell, L., Wenham, L., & Hauert, S.. (2019). Educating those most impacted by artificial intelligence (Vol. 11626, pp. 344 - 349; S. Isotani, Millán, E., Ogan, A., Hastings, P., McLaren, B., & Luckin, R., Eds.). In (Vol. 11626, pp. 344 - 349). https://doi.org/10.1007/978-3-030-23207-8_63

Gemmell, L., Wenham, L., & Hauert, S.. (2019). Educating those most impacted by artificial intelligence (Vol. 11626, pp. 344 - 349; S. Isotani, Millán, E., Ogan, A., Hastings, P., McLaren, B., & Luckin, R., Eds.). In (Vol. 11626, pp. 344 - 349). https://doi.org/10.1007/978-3-030-23207-8_63

Reddy, S. (2018). eHealth - Making Health Care SmarterUse of Artificial Intelligence in Healthcare Delivery (T. F. Heston, Ed.). https://doi.org/http://dx.doi.org/10.5772/intechopen.74714

Higgins, T. (2017). Elon Musk Lays Out Worst-Case Scenario for AI Threat. Wall Street Journal. Retrieved de https://www.wsj.com/articles/elon-musk-warns-nations-governors-of-looming-ai-threat-calls-for-regulations-1500154345

Hager, P., & Beckett, D.. (2019). The emergence of complexity. https://doi.org/10.1007/978-3-030-31839-0

Huang, M. Hui, & Rust, R. T.. (2020). Engaged to a Robot? The Role of AI in Service. Journal Of Service Research. https://doi.org/10.1177/1094670520902266

Hri, D. Hricik, Morgan, A. - L. S., & Williams, K. H.. (2018). Ethics of using Artificial Intelligence to augment drafting legal documents. Texas A&M Journal Of Property Law, 4(5). Retrieved de https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1080&context=journal-of-property-law

Natalie, E., & Hveem, C.. (2017). Evaluating the effects of industrial robots on the European labour market. In Employment and wage effects. Retrieved de https://pdfs.semanticscholar.org/4e19/3a0a02315803d799520b094cce36a1888a94.pdf

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

Caleb-Solly, P., Dogramadzi, S., Huijnen, C. A. G. J., & van den Heuvel, H.. (2018). Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptance. The Information Society, 34(3), 153 - 165. https://doi.org/10.1080/01972243.2018.1444255

Harini, B. (2019). An Extensive Review on Recent Emerging Applications of Artificial Intelligence. Asia-Pacific Journal Of Convergent Research Interchange, 5(2), 79 - 88. https://doi.org/10.21742/apjcri10.21742/apjcri.2019.0610.21742/apjcri.2019.06.09

F

Hempel, J. (2015). Facebook launches M, its bold answer to Siri and Cortana. Retrieved de https://www.wired.com/2015/08/facebook-launches-m-new-kind-virtual-assistant/

Hoc, J. - M. (2000). From human – machine interaction to human – machine cooperation. Ergonomics, 43(7), 833 - 843. https://doi.org/10.1080/001401300409044

Madakam, S., Holmukhe, R. M., & Jaiswal, D. Kumar. (2019). The future digital work force: Robotic process automation (RPA). Journal Of Information Systems And Technology Management, 16. https://doi.org/10.4301/S1807-1775201916001

Kittur, A., Nickerson, J. V., Bernstein, M. S., Gerber, E., Shaw, A., Zimmerman, J., et al.. (2013). The future of crowd work. In Proceedings of the 2013 conference on Computer supported cooperative work (1301–1318). ACM.

Lund, S., Manyika, J., Segal, L. Hilton, Dua, A., Hancock, B., Rutherford, S., & Macon, B.. (2019). The future of the work in America. In McKinsey Global Institute. Retrieved de https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-in-america-people-and-places-today-and-tomorrow

Madgavkar, A., Manyika, J., Krishnan, M., Ellingrud, K., Yee, L., Woetzel, J., et al.. (2019). The future of women at work. Retrieved de https://www.mckinsey.com/~/media/mckinsey/featured%20insights/gender%20equality/the%20future%20of%20women%20at%20work%20transitions%20in%20the%20age%20of%20automation/mgi-the-future-of-women-at-work-full-report-june%202019.ashx

Schwartz, J., Hagel, III, J., Wooll, M., & Monahan, K.. (2019). Future of work initiatives promise lots of noise and lots of activity, but to what end?. Mit Slogan Management Review. Retrieved de https://sloanreview.mit.edu/article/reframing-the-future-of-work/

G

Harandi, M., Crowston, K., Jackson, C., & Østerlund, C.. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719

Social_Construction_of_ML_in_GS_HICCS2020.pdf (124.3 KB)

Pages