Public Perception of Accountability for AI Systems: The Influence of Age and Education

Ng, Shi Yun, Crockett, Keeley ORCID: https://orcid.org/0000-0003-1941-6201, Latham, Annabel ORCID: https://orcid.org/0000-0002-8410-7950 and Kaleem, Mohammed (2025) Public Perception of Accountability for AI Systems: The Influence of Age and Education. In: IEEE IJCNN 2025: International Joint Conference on Neural Networks, 30 June 2025 - 5 July 2025, Rome, Italy. (In Press)

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Abstract

Accountability in the context of AI systems is a much-debated topic, especially in the context of current (i.e. EU AI Act) and emerging global legislation. This paper describes a study that investigates public perceptions of responsibility, accountability and trust in AI systems. The study surveyed 107 participants from the public between June and November 2024 with diverse ages and educational attainment levels. The study was developed around two case studies of AI: one on the use of an AI system in the healthcare industry, and the other on autonomous vehicles (AVs). The results show that there are some significant differences in public perceptions towards accountability AI systems, particularly in terms of, responsibility and trust. Perceptions varied based on respondents’ age and education level. Additionally, the study identified key themes in the responses based on the case study context, such as the importance of legal consultation, transparency in AI systems and shared responsibility in the development and deployment of AI technologies. The results highlight how individuals prioritize accountability and assert their rights, emphasizing the importance of protecting human rights within the AI space. The findings offer valuable insights for researchers, policymakers, and legal practitioners about the views of the public regarding responsibility and trust in AI systems.