Societal Attitudes Toward Service Robots: Adore, Abhor, Ignore, or Unsure?

TL;DR

This study analyzes societal attitudes toward service robots at the population level, identifying four distinct attitude profiles and their psychological and behavioral implications across diverse real-world datasets.

Contribution

It introduces a comprehensive, multi-study approach to understanding population-level attitudes toward service robots, highlighting heterogeneity and predictive factors.

Findings

Four stable attitude profiles identified: adore, abhor, ignore, unsure.

Attitude profiles predict post-interaction discomfort, satisfaction, and evaluations.

Psychological needs influence attitude profiles and perceptions of robots.

Abstract

Societal or population-level attitudes are aggregated patterns of different individual attitudes, representing collective general predispositions. As service robots become ubiquitous, understanding attitudes towards them at the population (vs. individual) level enables firms to expand robot services to a broad (vs. niche) market. Targeting population-level attitudes would benefit service firms because: (1) they are more persistent, thus, stronger predictors of behavioral patterns and (2) this approach is less reliant on personal data, whereas individualized services are vulnerable to AI-related privacy risks. As for service theory, ignoring broad unobserved differences in attitudes produces biased conclusions, and our systematic review of previous research highlights a poor understanding of potential heterogeneity in attitudes toward service robots. We present five diverse studies (S1-S5), utilizing multinational and "real world" data (Ntotal = 89,541; years: 2012-2024). Results reveal a stable structure comprising four distinct attitude profiles (S1-S5): positive ("adore"), negative ("abhor"), indifferent ("ignore"), and ambivalent ("unsure"). The psychological need for interacting with service staff, and for autonomy and relatedness in technology use, function as attitude profile antecedents (S2). Importantly, the attitude profiles predict differences in post-interaction discomfort and anxiety (S3), satisfaction ratings and service evaluations (S4), and perceived sociability and uncanniness based on a robot's humanlikeness (S5).