Independent Researcher.
Research Article
World Journal of Advanced Research and Reviews, 2021, 09(03), 377-390
Received on 08 February 2021; revised on 20 March 2021; accepted on 24 March 2021
This article analyzes the conflict of interest between innovation and security concerning evolving data privacy, especially regarding AI and ML techniques. Due to advanced technological developments, AI & ML integrated with data processing and, subsequently, data analysis produced deep concerns about privatizing personal information. The study discusses what is currently known about privacy as provided for in the applicable frameworks, assesses the threats that are brought about by these technologies, and weighs the options available in terms of giving protective measures for data privacy while at the same time promoting innovation. In addition to problem definitions, examples, and cases in this paper, the 'Real-world applications and their practical implications' section provides real-life uses of the technologies and the effects on privacy laws, corporate practices, and protection of users. By using qualitative analysis and comparative evaluation approach, the study provides a comprehension of the existing regulation efficiency, the implementation of AI-based privacy solutions, and the suggestions on effective and safe creation of digital environment. Based on the study's results, it becomes clear that flexible approaches and the inclusion of highly effective ethical approaches to applying AI and ML in organizations prevent privacy breaches.
Federated Learning; Data Processing; Privacy Risks; Data Protection; AI Innovation; Data Privacy
Preview Article PDF
Vishal Sresth, Aakash Srivastava and Sundar Tiwari. Balancing innovation and security: Advancing data privacy in the age of artificial intelligence and machine learning. World Journal of Advanced Research and Reviews, 2021, 9(3), 377-390. Article DOI: https://doi.org/10.30574/wjarr.2021.9.3.0079