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Full Description
This book provides a forum for experts to present their latest research in disruptive technologies, promoting knowledge transfer. Due to the important advances in technologies such as artificial intelligence, big data, the Internet of things, or bioinformatics produced in recent years, it is necessary to conduct a thorough review of current ethical patterns. One of the research fields that is in full expansion and with a broad future is technology ethics or tech ethics. Just a few years ago, this type of research was a small part, and they did not have too many technology researchers involved. At present, due to the explosion of new applications of artificial intelligence, their problems and their legal barriers have flourished innumerable initiatives, declarations, principles, guides, and analyses focused on measuring the social impact of these systems and on the development of a more ethical technology. It is, therefore, a problem that needs to be addressed from an academic and multidisciplinary point of view, where experts in ethics and behavior work together with experts in new and disruptive technologies.
The international conference "Disruptive Technologies Tech Ethics and Artificial Intelligence" (DITTET 2022) provides a forum to present and discuss the latest scientific and technical advances and their implications in the field of ethics. It provides a unique opportunity to bring together experts in different fields, academics, and professionals to exchange their experience in the development and deployment of disruptive technologies, artificial intelligence, and their ethical problems.
Contents
Comparing machine learning vs. humans for dietary assessment.- A method to identify graphs containing a specific subgraph.- A Scalable Smart Lighting Framework to Save Energy.- Papal Teaching on the Ethical Challenges of Artificial Intelligence.- European Union fosters ethical AI in the Public Administration.- Bias Analysis on Twitter.- Population-based methods to reduce the colors of an image.- Use of YOLOv4 and Yolov4Tiny for intelligent vehicle detection in Smart City environments.
