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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

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
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

Recently added resources

WAIM Doctoral Research Fellowship CFP , Presentation , Kevin Crowston, Ingrid Erickson, Jeffrey Nickerson
Using Work System Theory, Facets of Work, and Dimensions of Smartness to Characterize Applications and Impacts of AI , Report , Steven Alter
Converging Design: AI, Jobs, Job Design and Organizations , Presentation , Discussion Group

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T

Theresa, E., Alessandro, B., Michelle, B., Eriksson, T., Bigi, A., Bonera, M., et al.. (2020). Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation. The Tqm Journal, ahead-of-p. https://doi.org/10.1108/TQM-12-2019-0303

Castro, D., & McLaughlin, M.. (2019). Ten ways the precautionary principle undermines progress in artificial intelligence. In Information Technology & Innovation Foundation. Retrieved de https://itif.org/publications/2019/02/04/ten-ways-precautionary-principle-undermines-progress-artificial-intelligence

R

Petersen, A. C. M., Christensen, L. Rune, & Hildebrandt, T. T.. (2020). The Role of Discretion in the Age of Automation. Computer Supported Cooperative Work: Cscw: An International Journal, 29, 303–333. https://doi.org/10.1007/s10606-020-09371-3

Vishnevsky, V. P., & Chekina, V. D.. (2018). Robot vs. tax inspector or how the fourth industrial revolution will change the tax system: a review of problems and solutions. Journal Of Tax Reform, 4(1), 6 - 26. https://doi.org/10.15826/jtr.2018.4.1.042

Arduengo, M., & Sentis, L.. (2020). The Robot Economy : Here It Comes. International Journal Of Social Robotics. https://doi.org/10.1007/s12369-020-00686-1

Willcocks, L. (2020). Robo-Apocalypse cancelled? Reframing the automation and future of work debate. In Journal of Information Technology. https://doi.org/10.1177/0268396220925830

P

Malone, T. W., Nickerson, J. V., Laubacher, R. J., Fisher, L. Hesse, de Boer, P., Han, Y., & Ben Towne, W.. (2017). Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (1661–1674). https://doi.org/10.1145/2998181.2998343

Malone, T. W., Nickerson, J. V., Laubacher, R. J., Fisher, L. Hesse, de Boer, P., Han, Y., & Ben Towne, W.. (2017). Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (1661–1674). https://doi.org/10.1145/2998181.2998343

Malone, T. W., Nickerson, J. V., Laubacher, R. J., Fisher, L. Hesse, de Boer, P., Han, Y., & Ben Towne, W.. (2017). Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (1661–1674). https://doi.org/10.1145/2998181.2998343

Malone, T. W., Nickerson, J. V., Laubacher, R. J., Fisher, L. Hesse, de Boer, P., Han, Y., & Ben Towne, W.. (2017). Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (1661–1674). https://doi.org/10.1145/2998181.2998343

Malone, T. W., Nickerson, J. V., Laubacher, R. J., Fisher, L. Hesse, de Boer, P., Han, Y., & Ben Towne, W.. (2017). Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (1661–1674). https://doi.org/10.1145/2998181.2998343

M

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

Kernbach, J. M., & Staartjes, V. E.. (2020). Machine learning-based clinical prediction modeling – A practical guide for clinicians. Artificial Intelligence In Precision Health, 257–278. https://doi.org/10.1016/b978-0-12-817133-2.00011-2

J

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

I

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

Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction. https://doi.org/10.1145/3406499.3415070

Impacts_of_ML_for_HAI_2020.pdf (453.59 KB)

H

Carter, D. (2018). How real is the impact of artificial intelligence? The business information survey 2018. Business Information Review, 35(3), 99 - 115. https://doi.org/10.1177/0266382118790150

Carter, D. (2018). How real is the impact of artificial intelligence? The business information survey 2018. Business Information Review, 35(3), 99 - 115. https://doi.org/10.1177/0266382118790150

F

del Sol, P. Egana, Joyce, C., Del Sol, P. Egaña, & Joyce, C.. (2020). The Future of Work in Developing Economies. Mit Sloan Management Review, 61, 1–3.

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

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

The future of skills employment in 2030. (2017). The future of skills employment in 2030. In Pearson. Retrieved de https://futureskills.pearson.com/research/assets/pdfs/technical-report.pdf

Suran, S., Pattanaik, V., & Draheim, D.. (2020). Frameworks for collective intelligence: A systematic literature review. In ACM Computing Surveys (pp. 1–36). https://doi.org/10.1145/3368986

Suran, S., Pattanaik, V., & Draheim, D.. (2020). Frameworks for collective intelligence: A systematic literature review. In ACM Computing Surveys (pp. 1–36). https://doi.org/10.1145/3368986

Reid-musson, E., Cockayne, D., Frederiksen, L., & Worth, N.. (2020). Feminist economic geography and the future of work. Epa: Economy And Space, 1–12. https://doi.org/10.1177/0308518X20947101

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