Soul and Machine (Learning)

19 Pages Posted: 24 Sep 2019

See all articles by Davide Proserpio

Davide Proserpio

Marshall School of Business, University of Southern California

John R. Hauser

MIT Sloan School of Management

Xiao Liu

New York University (NYU) - Leonard N. Stern School of Business

Tomomichi Amano

Harvard University - Business School (HBS)

Alex Burnap

MIT Sloan School of Management

Tong Guo

Duke University, Fuqua School of Business

Dokyun (DK) Lee

Carnegie Mellon University - David A. Tepper School of Business

Randall A. Lewis

Netflix

Kanishka Misra

University of Michigan, Stephen M. Ross School of Business; University of Michigan at Ann Arbor

Eric M. Schwartz

University of Michigan, Stephen M. Ross School of Business

Artem Timoshenko

Kellogg School of Management, Northwestern University

Lilei Xu

affiliation not provided to SSRN

Hema Yoganarasimhan

University of Washington

Date Written: September 16, 2019

Abstract

Machine learning is bringing us self-driving cars, improved medical diagnostics and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to "big data," and are a natural fit to rich media such as text, images, audio, and video. Examples include identification of customer needs from online data, accurate prediction of consumer response to advertising, personalized pricing, and product recommendations. But without a soul, the applications of machine learning are limited. Consumer behavior and competitive strategies are nuanced and richly described by formal theory. To learn across applications, to be accurate for "what-if" and "but-for" applications, and to advance knowledge, machine learning needs theory and a soul. The brightest future is based on the synergy of what the machine can do well and what humans do well. We provide examples and predictions for the future.

Keywords: Machine learning, marketing

Suggested Citation

Proserpio, Davide and Hauser, John R. and Liu, Xiao and Amano, Tomomichi and Burnap, Alex and Guo, Tong and Lee, Dokyun (DK) and Lewis, Randall A. and Misra, Kanishka and Schwartz, Eric M. and Timoshenko, Artem and Xu, Lilei and Yoganarasimhan, Hema, Soul and Machine (Learning) (September 16, 2019). Available at SSRN: https://ssrn.com/abstract=3454294 or http://dx.doi.org/10.2139/ssrn.3454294

Davide Proserpio (Contact Author)

Marshall School of Business, University of Southern California ( email )

701 Exposition Blvd
Los Angeles, CA Los Angeles 90089
United States

HOME PAGE: http://faculty.marshall.usc.edu/Davide-Proserpio/

John R. Hauser

MIT Sloan School of Management ( email )

International Center for Research on the Mngmt Tech.
Cambridge, MA 02142
United States
617-253-2929 (Phone)
617-258-7597 (Fax)

Xiao Liu

New York University (NYU) - Leonard N. Stern School of Business ( email )

Suite 9-160
New York, NY
United States

Tomomichi Amano

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Boston, MA 02163
United States

Alex Burnap

MIT Sloan School of Management ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Tong Guo

Duke University, Fuqua School of Business ( email )

United States

Dokyun (DK) Lee

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Randall A. Lewis

Netflix ( email )

Los Gatos, CA
United States
312-RA-LEWIS (Phone)

HOME PAGE: http://www.econinformatics.com/

Kanishka Misra

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States

University of Michigan at Ann Arbor ( email )

500 S. State Street

Eric M. Schwartz

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States

Artem Timoshenko

Kellogg School of Management, Northwestern University ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

Lilei Xu

affiliation not provided to SSRN

Hema Yoganarasimhan

University of Washington ( email )

481 Paccar Hall
Seattle, WA 98195
United States

HOME PAGE: http://faculty.washington.edu/hemay/

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