| 期刊全稱 | Big Data, Algorithms and Food Safety | | 期刊簡稱 | A Legal and Ethical | | 影響因子2023 | Salvatore Sapienza | | 視頻video | http://file.papertrans.cn/186/185723/185723.mp4 | | 發(fā)行地址 | Provides an innovative research on Food Safety, Big Data and Machine Learning.Offers an interdisciplinary approach to data ownership and data governance to Food Safety.Provides legal and ethical refle | | 學(xué)科分類 | Law, Governance and Technology Series | | 圖書封面 |  | | 影響因子 | This book identifies the principles that should be applied when processing Big Data in the context of food safety risk assessments. Food safety is a critical goal in the protection of individuals’ right to health and the flourishing of the food and feed market. Big Data is fostering new applications capable of enhancing the accuracy of food safety risk assessments. An extraordinary amount of information is analysed to detect the existence or predict the likelihood of future risks, also by means of machine learning algorithms. Big Data and novel analysis techniques are topics of growing interest for food safety agencies, including the European Food Safety Authority (EFSA). This wealth of information brings with it both opportunities and risks concerning the extraction of meaningful inferences from data. However, conflicting interests and tensions among the parties involved are hindering efforts to find shared methods for steering the processing of Big Data in a sound, transparent and trustworthy way. While consumers call for more transparency, food business operators tend to be reluctant to share informational assets. This has resulted in a considerable lack of trust in the EU food | | Pindex | Book 2022 |
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