Handbook Of Research On Lifestyle Sustainability And Management Solutions Using Ai Big Data Analytics And Visualization
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Handbook of Research on Lifestyle Sustainability and Management Solutions Using AI, Big Data Analytics, and Visualization
Author: Iyer, Sailesh Suryanarayan
language: en
Publisher: IGI Global
Release Date: 2021-12-24
The sudden outbreak of the COVID-19 pandemic has curbed human lifestyle by imposing restrictions on regular daily movements that had been taken for granted. Due to the pandemic, the welfare segment has received more attention, and every possible effort is being made to prioritize the services at the top. This can be made possible while using the latest tools, technologies, and resources that impact the human culture and welfare of well-being. Novel methods and devices that make the welfare services more efficient, adaptive, transparent, and cost-effective need to be explored. The Handbook of Research on Lifestyle Sustainability and Management Solutions Using AI, Big Data Analytics, and Visualization offers extensive research on lifestyle management and services that contribute towards indication, detection, conduction, protection, and technological enhancement including machine learning, deep learning, artificial intelligence, big data analytics, and visualization. It also provides mechanisms that can improve lifestyle monitoring and help in increasing the immunity of the human body. Covering topics such as big data, robot therapy, and wearable technology, it is ideal for students, researchers, technologists, IT specialists, computer engineers, systems engineers, data scientists, doctors, hospital administrators, engineers, academicians, and technology providers.
Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices
The rapid advancement of generative artificial intelligence (AI) has brought about significant ethical challenges. As machines become more adept at creating human-like content, concerns about misuse, bias, privacy, and accountability have emerged. Without clear guidelines and regulations, there is a risk of unethical use, such as creating deepfake videos or disseminating misinformation, which could have severe societal consequences. Additionally, questions about intellectual property rights and the ownership of AI-generated creations still need to be solved, further complicating the ethical landscape. The book, Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices, comprehensively solves these ethical challenges. By providing insights into the historical development and key milestones of Generative AI, the book lays a foundation for understanding its complex ethical implications. It examines existing ethical frameworks and proposes new ones tailored to AI's unique characteristics, helping readers apply traditional ethics to AI development and deployment.
Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning
As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.