Tackling Privacy Concerns and Data Protection Challenges in the Development and Deployment of Computer Vision Machine Learning Systems

Abstract

Computer vision machine learning systems have gained significant attention in recent years due to their potential to revolutionize various industries and improve processes. However, the development and application of these systems raise critical privacy concerns and data protection challenges that must be addressed to ensure the responsible and ethical use of this technology. This research paper explores the privacy implications of computer vision machine learning systems, focusing on issues such as data collection, consent, and the potential for misuse. It examines the current legal and regulatory frameworks governing data protection and privacy, and discusses the need for robust safeguards and best practices in the development and deployment of these systems. The paper also highlights the importance of transparency, accountability, and user control in building trust and ensuring the responsible use of computer vision technology. By addressing these challenges, we can harness the benefits of computer vision machine learning systems while protecting individual privacy rights and maintaining public trust.