Predictive Quality Management in Nepalese Artificial Intelligence and Data Privacy: Navigating Cyber Laws in the Age of Machine Learning

Abstract

Artificial intelligence (AI) and machine learning requires massive amounts of personal and sensitive information, resulting in important challenges in protecting privacy and cyber-legal governance. This review explores how the relationship between AI, data privacy and regulatory frameworks has developed, particularly within the context of the main privacy risks, individual rights, regulatory bodies and emerging governance issues. Issues of particular concern are the excessive collection of data, algorithmic profiling, surveillance, re-identification of the collected data, training-data leakage, automated decisions, and data processing across borders. It reviews key regulatory strategies, such as the General Data Protection Regulation (GDPR), the European Union (EU) Artificial Intelligence Act (AI Act) and the developing national privacy laws, while noting the fragmentation of regulation, accountability challenges and enforcement issues. Some of the more important tools for mitigating emerging risks are the methods that preserve privacy, such as federated learning, differential privacy, encryption, explainable AI, and algorithmic auditing. Key features of adaptive cyber laws for effective AI Governance include incorporating technological protections, ethical oversight, organizational accountability, and international coordination, along with ensuring a balance between technological innovation and core privacy rights.