AI and Ethics: Scale Development for Measuring Ethical Perceptions of Artificial Intelligence Across Sectors and Countries

Abstract

Artificial Intelligence (AI) has rapidly become an integral technology across many sectors, including healthcare, finance, research, and manufacturing. AI’s ability to automate processes, analyse large datasets, and make predictive decisions offers significant opportunities for innovation, but it also raises profound ethical challenges. Ethical concerns regarding AI encompass issues of transparency, accountability, fairness, data privacy, and the need for human oversight. Given the diverse applications of AI, these ethical concerns vary not only by sector but also across different cultural and regulatory environments. Despite growing discourse on AI ethics, empirical tools for assessing ethical perceptions of AI across varied organizational contexts remain limited. From that need, this study introduces the AI and Ethics Perception Scale (AEPS), designed to measure individual and collective perceptions of AI ethics across five key dimensions: Transparency, Accountability, Privacy, Fairness, and Human Oversight. The AEPS was developed through a rigorous methodological process, beginning with a pilot study of 112 participants and validated with data from 417 participants across three culturally diverse countries: Turkey, India, and the United Kingdom. The scale was used to assess ethical perceptions in sectors such as healthcare, finance, and manufacturing. Both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to validate the scale’s structure. This study reveals significant cross-cultural and cross-sectoral differences in the prioritization of ethical concerns, demonstrating the need for contextually sensitive ethical frameworks for AI governance.

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