Data Protection Privacy And Artificial Intelligence Volume 17
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Data Protection, Privacy and Artificial Intelligence, Volume 17
This book examines the discourse and developments surrounding privacy and data protection in the digital realm, featuring papers and discussions from the 2024 CPDP.ai international conference. The question of governance-whether to lead or be led-has never been more relevant. Thus, the book not only addresses privacy and data protection, but also highlights issues related to the governance of artificial intelligence and the regulatory changes introduced by the EU AI Act. The book features comprehensive discussions on the adequacy and effectiveness of the governance mechanisms established by the EU AI Act, particularly emphasising standardisation, co-regulation, and human oversight, while also identifying existing gaps in protection. Additionally, it pays special attention to the risks to fundamental rights associated with AI usage by law enforcement agencies, examining whether the current legal framework sufficiently safeguards against these risks. Finally, the book provides an in-depth exploration of deepnude and deepfake technology that generates nude images, as well as the role of AI in the EU's migration management systems. The chapters in this book provide readers with an opportunity to explore the challenges and developments related to privacy, data protection, and artificial intelligence. By presenting academic insights alongside contributions from practitioners, civil society, and the European Data Protection Supervisor, this interdisciplinary volume encapsulates the essence of the CPDP.ai 2024 conference.
Privacy, Due Process and the Computational Turn
Privacy, Due process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology engages with the rapidly developing computational aspects of our world including data mining, behavioural advertising, iGovernment, profiling for intelligence, customer relationship management, smart search engines, personalized news feeds, and so on in order to consider their implications for the assumptions on which our legal framework has been built. The contributions to this volume focus on the issue of privacy, which is often equated with data privacy and data security, location privacy, anonymity, pseudonymity, unobservability, and unlinkability. Here, however, the extent to which predictive and other types of data analytics operate in ways that may or may not violate privacy is rigorously taken up, both technologically and legally, in order to open up new possibilities for considering, and contesting, how we are increasingly being correlated and categorizedin relationship with due process – the right to contest how the profiling systems are categorizing and deciding about us.
Privacy and Security Issues in Big Data
This book focuses on privacy and security concerns in big data and differentiates between privacy and security and privacy requirements in big data. It focuses on the results obtained after applying a systematic mapping study and implementation of security in the big data for utilizing in business under the establishment of “Business Intelligence”. The chapters start with the definition of big data, discussions why security is used in business infrastructure and how the security can be improved. In this book, some of the data security and data protection techniques are focused and it presents the challenges and suggestions to meet the requirements of computing, communication and storage capabilities for data mining and analytics applications with large aggregate data in business.