Unveiling the Mind of the Machine

101 Pages Posted: 26 Sep 2023 Last revised: 14 Nov 2023

See all articles by Melanie Clegg

Melanie Clegg

Vienna University of Economics and Business; University of Lucerne

Reto Hofstetter

University of Lucerne - Faculty of Economics and Management

Emanuel de Bellis

Institute of Behavioral Science and Technology, University of St.Gallen

Bernd H. Schmitt

Columbia Business School - International Business

Date Written: September 7, 2023

Abstract

Previous research has shown that consumers respond differently to decisions made by humans versus algorithms. Many tasks, however, are not performed by humans anymore but entirely by algorithms. In fact, consumers increasingly encounter algorithm-controlled products, such as robotic vacuum cleaners or smart refrigerators, which are steered by different types of algorithms. Building on insights from computer science and consumer research on algorithm perception, this research investigates how consumers respond to different types of algorithms within these products. This research compares high-adaptivity algorithms, which can learn and adapt, versus low-adaptivity algorithms, which are entirely pre-programmed, and explore their impact on consumers’ product preferences. Six empirical studies show that, in general, consumers prefer products with high-adaptivity algorithms. However, this preference depends on the desired level of product outcome range—the number of solutions a product is expected to provide within a task or across tasks. The findings also demonstrate that perceived algorithm creativity and predictability drive the observed effects. This research highlights the distinctive role of algorithm types in the perception of consumer goods and reveals the consequences of unveiling the mind of the machine to consumers.

Keywords: algorithm, artificial intelligence, generative AI, smart products, mind perception, creativity

Suggested Citation

Clegg, Melanie and Hofstetter, Reto and de Bellis, Emanuel and Schmitt, Bernd H., Unveiling the Mind of the Machine (September 7, 2023). Available at SSRN: https://ssrn.com/abstract=4564832 or http://dx.doi.org/10.2139/ssrn.4564832

Melanie Clegg (Contact Author)

Vienna University of Economics and Business ( email )

Welthandelsplatz 1
Vienna, Wien 1020
Austria

University of Lucerne ( email )

Frohburgstrasse 3
Luzern, CH - 6002
Switzerland

Reto Hofstetter

University of Lucerne - Faculty of Economics and Management ( email )

Frohburgstrasse 3
Postfach 4466
Luzern, LU 6002
Switzerland
412295880 (Phone)

Emanuel De Bellis

Institute of Behavioral Science and Technology, University of St.Gallen ( email )

St.Gallen, 9000
Switzerland

Bernd H. Schmitt

Columbia Business School - International Business ( email )

New York, NY
United States
212-854-3468 (Phone)
212-854-7647 (Fax)

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

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
446
Abstract Views
1,358
Rank
125,773
PlumX Metrics