PRIVACY RISKS IN THE DIGITAL AGE: CYBERSECURITY CHALLENGES AND SOLUTIONS IN AI, AR AND BIG DATA

The rapid pace of digital transformation has created unprecedented vulnerabilities for privacy and autonomy, especially in data‑intensive technologies such as artificial intelligence (AI), augmented reality (AR) and big data analytics. Advanced systems enable continuous data collection, inference and behavioral prediction, challenging traditional privacy theories developed for e‑commerce and social networking. A recent systematic review of some studies on privacy in AI, AR, big data and related technologies identifies key psychological antecedents, outcomes and theoretical frameworks, and shows that static, context‑free views of privacy are inadequate in these environments (Herriger et al., 2025). This article synthesizes that work and related reviews on AI and big data, behavioral data science, and online privacy paradox research to outline contemporary risks, user privacy behaviors, and cybersecurity solutions (Herriger et al., 2025; Tudoran, 2024; Amin et al., 2024; Saura et al., 2022; Quach et al., 2022; Romansky & Noninska, 2020). It argues that traditional models such as privacy calculus and APCO still matter but must be extended with context‑contingent, behavioral‑economic and “privacy‑by‑default” perspectives to protect privacy and personal integrity in AI‑, AR‑ and big‑data‑driven ecosystems (Herriger et al., 2025; Tudoran, 2024; Saura et al., 2021; El-Hajj, 2024).