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Teach an I-O To Fish: Integrating Data Science Into I-O Graduate Education

Published online by Cambridge University Press:  17 December 2015

Juliet R. Aiken  and
Paul J. Hanges
Juliet R. Aiken*
Affiliation:
Department of Psychology, University of Maryland
Paul J. Hanges
Affiliation:
Department of Psychology, University of Maryland
*
Correspondence concerning this article should be addressed to Juliet R. Aiken, Department of Psychology, University of Maryland, College Park, MD 20742. E-mail: jraiken@umd.edu
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Extract

Big data is becoming a buzzword in today's corporate language and lay discussions. From individually targeting advertising based on previous consumer behavior or Internet searches to debates by Congress concerning National Security Agency (NSA) access to phone metadata, the era of big data has arrived. Thus, the Guzzo, Fink, King, Tonidandel, and Landis (2015) discussion of the challenges (e.g., confidentiality, informed consent) that big data projects present to industrial and organizational (I-O) psychologists is timely. If the hype associated with these techniques is warranted, then our field has a clear imperative to debate the ethics and best practices surrounding use of these techniques. We believe that Guzzo et al. have done our field a service by starting this discussion.

Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 8 , Issue 4 , December 2015 , pp. 539 - 544
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

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