Cross-National Ethical Concerns Toward AI-Based Well-Being Measurement: A Comparative Study Across Finland, Germany, Japan, and the United States Using the Octagon Framework

Abstract

This study examines public attitudes toward using artificial intelligence to measure human subjective well-being from biometric data, contributing empirical evidence to AI ethics research. Using the eight-dimension “Octagon” ethical framework, we conducted a cross-national survey experiment in Finland, Germany, Japan, and the United States (N = 4,000) across four domains: healthcare, media/entertainment, employment, and governance. A multilingual, scenario-based design with visual aids ensured clarity and comparability, and validated instruments such as the Victorian Segmentation scale were incorporated. Multiple regression analyses revealed consistent cross-country patterns: individuals with lower interest in science and technology and women expressed stronger ethical concerns, particularly regarding safety and security. Scenario acceptability varied contextually, with healthcare applications eliciting the least resistance and governance-related applications the most. Our findings underscore the need for participatory, culturally sensitive, and context-aware approaches to ethical AI design, and contribute a empirical foundation for future research and policy development in AI and well-being.