Does Political Orientation Affect the Evaluation of Artificial Intelligence?

Han, Haejoo; Park, Su‐Jin; Lee, Kyoung-Mi

doi:10.53728/2765-6500.1180

Cited by 3 publications

(1 citation statement)

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“…The aspects of uniqueness neglect in algorithms intensified algorithm aversion among individualistic cultures, such as South America, while familiarity with algorithms diminished algorithm aversion among collectivistic cultures, like India [16]. Furthermore, consumers who are politically more conservative-leaning tend to evaluate AI-based services poorly [17].…”

Section: Introductionmentioning

confidence: 99%

Maximizers’ Reactance to Algorithm-Recommended Options: The Moderating Role of Autotelic vs. Instrumental Choices

Kim

2023

Behavioral Sciences

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The previous literature has provided mixed findings regarding whether consumers appreciate or are opposed to algorithms. The primary goal of this paper is to address these inconsistencies by identifying the maximizing tendency as a critical moderating variable. In Study 1, it was found that maximizers, individuals who strive for the best possible outcomes, exhibit greater reactance toward algorithm-recommended choices than satisficers, those who are satisfied with a good-enough option. This increased reactance also resulted in decreased algorithm adoption intention. Study 2 replicated and extended the findings from Study 1 by identifying the moderating role of choice goals. Maximizers are more likely to experience reactance to algorithm-recommended options when the act of choosing itself is intrinsically motivating and meaningful (i.e., autotelic choices) compared to when the decision is merely a means to an end (i.e., instrumental choices). The results of this research contribute to a nuanced understanding of how consumers with different decision-making styles navigate the landscape of choice in the digital age. Furthermore, it offers practical insights for firms that utilize algorithmic recommendations in their businesses.

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Section: Introductionmentioning

confidence: 99%