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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

Taming artificial intelligence: A theory of control–accountability alignment among AI developers and users , Gudela Grote; Sharon Parker; Kevin Crowston
Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy , Carsten Østerlund; Kevin Crowston; Corey B. Jackson; Yunan Wu; Alexander O. Smith; Aggelos K. Katsaggelos
Deskilling and upskilling with generative AI systems , Kevin Crowston; Francesco Bolici
The task matters: The effect of perceived similarity to AI on intention to use in different task types , Qingyu Liang; Kevin Crowston; Sangseok You
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

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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An executive’s guide to machine learning

Publication Type:

Journal Article

Authors:

Dorian Pyle; Cristina San Jose

Source:

McKinsey Quarterly (2015)

URL:

https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/an-executives-guide-to-machine-learning