International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 12 | Dec 2024
p-ISSN: 2395-0072
www.irjet.net
Redefining Data Privacy in the Age of Artificial Intelligence: Ethical Frameworks, Technological Innovations, and Regulatory Challenges Sudarshan Prasad Nagavalli1, Sundar Tiwari2, Writuraj Sarma3 Independent Researcher1 Independent Researcher2 Independent Researcher3 --------------------------------------------------------------------------***---------------------------------------------------------------------------Abstract Based on this investigation into data privacy in such an AI era of data privacy, this paper concludes with the presentation of the ultimate nature of data privacy being the combination of ethical infrastructure, technological breakthroughs, and policy considerations. Key findings raise prominent transparency, consent, and accountability principles for developing responsible AI. Some technological advances, such as differential privacy, federated learning, and homomorphic encryption, enable us to achieve data privacy robustly. However, big regulatory hurdles still need to be overcome, requiring international cooperation and new regulatory frameworks. Because the implications of our findings explicitly and implicitly relate to policy, practice, and research, we discuss the relevance of comprehensive and adaptable regulations, ethical approaches to the development of AI, and interdisciplinary research approaches. A multidimensional view of the future of data privacy in AI must provide an integrative ethical, technical, and regulatory outlook that will promote competition for innovation and privacy rather than their clash. Keywords: Data Privacy, Artificial Intelligence (AI), Ethical Frameworks, Technological Innovations, Regulatory Challenges, GDPR (General Data Protection Regulation)
Introduction 1.1 Background Artificial Intelligence (AI) has made unprecedented contributions towards improving business and life in many sectors due to its ability to train machines to do what previously required human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding. In Healthcare, Finance, Transportation, etc., applications of machine learning, natural language processing, and computer vision—some of the main AI technologies are gradually being deployed. However, implementing AI within those domains has brought essential privacy worries. Nowadays, when lots of data are required to train models to improve, many AI systems have become greedy for data. It can be personal: your name, your address, your medical records, and financial transactions. From the point of view of individual privacy, the collection, storage, and processing of the same data represents enormous risks. An example of this misunderstanding is that AI algorithms might disclose protected data, and privacy could be lost. Using AI in surveillance and monitoring extends the ethical challenge between security and privacy. In the era of the digital age, data privacy is an issue that directly concerns us as data privacy has increased a lot due to the ever-increasing amounts of personal information being shared and stored online. Although digital technologies have dramatically expanded the amount of available data to be collected and analyzed, they have significantly expanded the threat of data misuse and breach. Data privacy is very important for protecting rights and preventing the misuse of personal information. Protecting personal information is not just about data privacy but also about building trust in digital services. Individuals will engage with digital platforms and services if they feel secure and like responsible use. On the other hand, loss of data and use can impact trust and deliver great economic and social costs. This implies that whether digital technologies and AI can develop sustainably depends on ensuring data privacy. 1.2 Objectives In the context of the AI system, the primary research questions are: What are the key ethical concerns regarding data privacy in Artificial Intelligence, and which of the identified ethical principles should AI organizations adhere to when collecting,
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