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Название: Data Protection: The Wake of AI and Machine Learning
Автор: Chaminda Hewage, Lasith Yasakethu, Dushmantha Nalin K. Jayakody
Издательство: Springer
Год: 2024
Страниц: 309
Язык: английский
Формат: pdf (true), epub
Размер: 26.9 MB
This book provides a thorough and unique overview of the challenges, opportunities and solutions related with data protection in the age of AI and ML technologies. It investigates the interface of data protection and new technologies, emphasising the growing need to safeguard personal and confidential data from unauthorised access and change. The authors emphasize the crucial need of strong data protection regulations, focusing on the consequences of AI and ML breakthroughs for privacy and individual rights. This book emphasizes the multifarious aspect of data protection, which goes beyond technological solutions to include ethical, legislative and societal factors. The core concept behind AI is to simulate human-like intelligence in machines, allowing them to analyze complex data, recognize patterns, and make informed decisions. This field has evolved significantly, from early symbolic AI systems that relied on predefined rules to modern AI systems that leverage ML algorithms for data-driven learning. ML algorithms play a pivotal role in AI development by enabling machines to learn from data.
Автор: Chaminda Hewage, Lasith Yasakethu, Dushmantha Nalin K. Jayakody
Издательство: Springer
Год: 2024
Страниц: 309
Язык: английский
Формат: pdf (true), epub
Размер: 26.9 MB
This book provides a thorough and unique overview of the challenges, opportunities and solutions related with data protection in the age of AI and ML technologies. It investigates the interface of data protection and new technologies, emphasising the growing need to safeguard personal and confidential data from unauthorised access and change. The authors emphasize the crucial need of strong data protection regulations, focusing on the consequences of AI and ML breakthroughs for privacy and individual rights. This book emphasizes the multifarious aspect of data protection, which goes beyond technological solutions to include ethical, legislative and societal factors. The core concept behind AI is to simulate human-like intelligence in machines, allowing them to analyze complex data, recognize patterns, and make informed decisions. This field has evolved significantly, from early symbolic AI systems that relied on predefined rules to modern AI systems that leverage ML algorithms for data-driven learning. ML algorithms play a pivotal role in AI development by enabling machines to learn from data.