The convergence of persistent Augmented Reality (AR), robotics, and biometric analytics is creating a new technological paradigm where the digital and physical worlds are inextricably intertwined. This integration, while promising, introduces profound ethical risks that traditional governance models fail to address. This paper examines the complex challenges of data governance in this new era. Using a multi-method approach that integrates a systematic literature review, four purposive case studies (algorithmic recruitment, AR law enforcement, consumer wearables, and autonomous delivery robots), and thematic analysis, this research investigates four primary risk domains: (1) deep inferential threats from biometric and behavioural data, (2) cognitive manipulation and pervasive surveillance, (3) the "bystander problem" of non-consensual data capture, and (4) the diffusion of accountability in complex autonomous systems. Findings reveal systemic vulnerabilities, including "ambient biometric surveillance," "bystander invisibility," and "distributed responsibility," demonstrating the inadequacy of existing individualistic consent frameworks. The paper concludes by proposing a dual-pronged governance framework. This framework combines technical safeguards, such as dynamic consent architectures and mandatory AI Impact Assessments (AI-IAs), with policy innovations, including new legal categories for bystander data and multi-stakeholder co-regulatory oversight, to steer technological development toward a human-centric, rights-respecting future.

Persistent Augmented Reality (AR), Robotics Ethics, Biometric Data, Ethical Frameworks, Algorithmic Accountability, Bystander Privacy

Raja, U. S., & Al-Baghli, R. (2022). Ethical Issues in Virtual Reality Today and Innovating Responsibly: Ethical Questions for AI in Early Childhood. Journal of Media Ethics, 37(4), 215–229. https://doi.org/10.1080/08900523.2022.2056710

Jawalkar, S. K. (2021). Ethical Horizons in Immersive Technologies: Challenges in AR/VR Governance. International Journal of Ethics in Digital Society, 5(2), 112–130.

Braun, V., & Clarke, V. (2006). Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

European Union. (2016). General Data Protection Regulation (GDPR). Official Journal of the European Union, L119.

European Commission. (2024). Artificial Intelligence Act. COM(2021) 206 final — Regulation of the European Parliament and of the Council on Artificial Intelligence.

U.S. Congress. (2018). California Consumer Privacy Act (CCPA). California Civil Code §§1798.100–1798.199.

IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. (2022). Ethically Aligned Design, First Edition. IEEE Standards Association.

Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1

Bryson, J. J., Diamantis, M. E., & Grant, T. D. (2017). Of, for, and by the People: The Legal Lacuna of Synthetic Persons. Artificial Intelligence and Law, 25(3), 273–291.

Coeckelbergh, M. (2020). AI Ethics. MIT Press.

European Parliamentary Research Service (EPRS). (2023). AI and Robotics: Ethical and Legal Frameworks for the EU. Brussels: European Parliament.

Whittlestone, J., Nyrup, R., Alexandrova, A., Dihal, K., & Cave, S. (2019). Ethical and Societal Implications of Algorithms, Data, and AI: A Roadmap for Research. Nuffield Foundation.

Crawford, K., & Paglen, T. (2021). Excavating AI: The Politics of Images in Machine Learning Training Sets. International Journal of Cultural Studies, 24(6), 931–951.

Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The Ethics of Algorithms: Mapping the Debate. Big Data & Society, 3(2). https://doi.org/10.1177/2053951716679679

Borenstein, J., Herkert, J. R., & Miller, K. W. (2017). The Ethics of Autonomous Cars. The Atlantic Council Journal of Ethics in Engineering, 1(2), 1–15.

Calo, R. (2015). Robotics and the Lessons of Cyberlaw. California Law Review, 103(3), 513–563.

Lin, P., Abney, K., & Bekey, G. (2020). Robot Ethics 2.0: From Autonomous Cars to Artificial Intelligence. Oxford University Press.

Zuboff, S. (2019). The Age of Surveillance Capitalism. PublicAffairs.

Raji, I. D., & Buolamwini, J. (2019). Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 429–435.

United Nations Educational, Scientific and Cultural Organization (UNESCO). (2021). Recommendation on the Ethics of Artificial Intelligence. Paris: UNESCO