Unveiling the Mind of the Machine
Journal
Journal of Consumer Research
ISSN
0093-5301
Type
journal article
Date Issued
2023-11-24
Author(s)
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
smart products
artificial intelligence
mind perception
creativity
machine learning
HSG Classification
contribution to scientific community
Refereed
Yes
Volume
51
Number
2
End page
341
Pages
361
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open.access
Name
Clegg2024.pdf
Size
915.07 KB
Format
Adobe PDF
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