LEADER 05160nam 22006735 450 001 9910619276703321 005 20230810175633.0 010 $a9783031093678$b(electronic bk.) 010 $z9783031093661 024 7 $a10.1007/978-3-031-09367-8 035 $a(MiAaPQ)EBC7120435 035 $a(Au-PeEL)EBL7120435 035 $a(CKB)25181489400041 035 $a(DE-He213)978-3-031-09367-8 035 $a(PPN)26585752X 035 $a(EXLCZ)9925181489400041 100 $a20221020d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data, Algorithms and Food Safety $eA Legal and Ethical Approach to Data Ownership and Data Governance /$fby Salvatore Sapienza 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (225 pages) 225 1 $aLaw, Governance and Technology Series,$x2352-1910 ;$v52 311 08$aPrint version: Sapienza, Salvatore Big Data, Algorithms and Food Safety Cham : Springer International Publishing AG,c2022 9783031093661 320 $aIncludes bibliographical references. 327 $aChapter 1:Food, Big Data, Artificial Intelligence -- Chapter 2:Data Ownership in Food-related Information -- Chapter 3:Food Consumption Data Protection -- Chapter 4:Current and Foreseeable Trends in Food Safety Data Governance -- Chapter 5: The P-SAFETY Model: a Unifying Ethical Approach -- Chapter 6: Conclusion: a Responsible Food Innovation. 330 $aThis 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 safety system. A recent legislative reform, supported by new legal cases, aims to restore confidence in the risk analysis system by reshaping the meaning of data ownership in this domain. While this regulatory approach is being established, breakthrough analytics techniques are encouraging thinking about the next steps in managing food safety data in the age of machine learning. The book focuses on two core topics ? data ownership and data governance ? by evaluating how the regulatory framework addresses the challenges raised by Big Data and its analysis in an applied, significant, and overlooked domain. To do so, it adopts an interdisciplinary approach that considers both the technological advances and the policy tools adopted in the European Union, while also assuming an ethical perspective when exploring potential solutions. The conclusion puts forward a proposal: an ethical blueprint for identifying the principles ? Security, Accountability, Fairness, Explainability, Transparency and Privacy ? to be observed when processing Big Data for food safety purposes, including by means of machine learning. Possible implementations are then discussed, also in connection with two recent legislative proposals, namely the Data Governance Act and the Artificial Intelligence Act. 410 0$aLaw, Governance and Technology Series,$x2352-1910 ;$v52 606 $aInformation technology$xLaw and legislation 606 $aMass media$xLaw and legislation 606 $aArtificial intelligence 606 $aBig data 606 $aFood$xSafety measures 606 $aIT Law, Media Law, Intellectual Property 606 $aArtificial Intelligence 606 $aBig Data 606 $aFood Safety 615 0$aInformation technology$xLaw and legislation. 615 0$aMass media$xLaw and legislation. 615 0$aArtificial intelligence. 615 0$aBig data. 615 0$aFood$xSafety measures. 615 14$aIT Law, Media Law, Intellectual Property. 615 24$aArtificial Intelligence. 615 24$aBig Data. 615 24$aFood Safety. 676 $a005.7 676 $a005.7 700 $aSapienza$b Salvatore$01262886 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910619276703321 996 $aBig Data, Algorithms and Food Safety$92954919 997 $aUNINA