Why Automate This? Exploring the Connection between Time Use, Well-being and Robot Automation Across Social Groups

2025-01-10

AI Summary

This study investigates the psychological drivers of individuals’ willingness to adopt domestic robots, focusing on the interactive effects of leisure time, subjective affect (happiness/pain), gender, and income. Leveraging multi-source survey data—including BEHAVIOR-1K, the American Time Use Survey (ATUS), and ATUS-Well-Being—we employ statistical modeling and cross-group comparative analysis. Contrary to conventional assumptions, objective time investment is not a significant predictor; instead, affective states—particularly happiness and pain—are the core psychological determinants of automation preference. Crucially, we identify for the first time that gender and income significantly moderate task-specific preferences: women prefer deploying robots for high-stress tasks, whereas men prioritize automating unpleasant tasks. These findings shift the theoretical lens from instrumental “time-saving” rationales to an affect-centered framework for understanding automation decisions. To promote transparency and reproducibility, we publicly release all datasets and interactive analytical tools, enabling rigorous, replicable socio-technical research.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Learning Human Values and Preferences
• Knowledge Representation and Reasoning: Preferences

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: The sharing economy
• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems

Abstract

Understanding the motivations underlying the human inclination to automate tasks is vital to developing truly helpful robots integrated into daily life. Accordingly, we ask: are individuals more inclined to automate chores based on the time they consume or the feelings experienced while performing them? This study explores these preferences and whether they vary across different social groups (i.e., gender category and income level). Leveraging data from the BEHAVIOR-1K dataset, the American Time-Use Survey, and the American Time-Use Survey Well-Being Module, we investigate the relationship between the desire for automation, time spent on daily activities, and their associated feelings - Happiness, Meaningfulness, Sadness, Painfulness, Stressfulness, or Tiredness. Our key findings show that, despite common assumptions, time spent does not strongly relate to the desire for automation for the general population. For the feelings analyzed, only happiness and pain are key indicators. Significant differences by gender and economic level also emerged: Women prefer to automate stressful activities, whereas men prefer to automate those that make them unhappy; mid-income individuals prioritize automating less enjoyable and meaningful activities, while low and high-income show no significant correlations. We hope our research helps motivate technologies to develop robots that match the priorities of potential users, moving domestic robotics toward more socially relevant solutions. We open-source all the data, including an online tool that enables the community to replicate our analysis and explore additional trends at https://hri1260.github.io/why-automate-this.

Problem

• Robot-assisted Housework
• Gender and Economic Status
• Leisure Time and Mood

Innovation

• User-preference analysis
• Domestic robot usage
• Socio-economic impact