From Dataveillance to Data Economy: Firm View on Data Protection

The increasing availability of electronic records and the expanded reliance on online communications and services have made available a huge amount of data about people’s behaviours, characteristics, and preferences. Advancements in data processing technology, known as big data, offer opportunities to increase organisational efficiency and competitiveness. Analytically sophisticated companies excel in their ability to extract value from the analysis of digital data. However, in order to exploit the potential economic benefits produced by big data and analytics, issues of data privacy and information security need to be addressed. In Europe, organisations processing personal data are being required to implement basic data protection principles, which are considered difficult to implement in big data environments. Little is known in the privacy studies literature about how companies manage the trade-off between data usage and data protection. This study contributes to explore the corporate data privacy environment, by focusing on the interrelationship between the data protection legal regime, the application of big data analytics to achieve corporate objectives, and the creation of an organisational privacy culture. It also draws insights from surveillance studies, particularly the idea of dataveillance, to identify potential limitations of the current legal privacy regime. The findings from the analysis of survey data show that big data and data protection support each other, but also that some frictions can emerge around data collection and data fusion. The demand for the integration of different data sources poses challenges to the implementation of data protection principles. However, this study finds no evidence that data protection laws prevent data gathering. Implications relevant for the debate on the reform of European data protection law are also drawn from these findings

What’s in it for us? Benevolence, national security and digital surveillance

This article challenges suggestions that citizens should accept digital surveillance technologies (DSTs) and trade their privacy for better security. Drawing on data from nine EU countries, this research shows that citizens’ support for DSTs varies not only depending on the way their data are used but also depending on their views of the security agency operating them. Using an institutional trustworthiness lens, this research investigates three DST cases – smart CCTV, smartphone location tracking, and deep packet inspection – that present escalating degrees of privacy risk to citizens. The findings show that the perceived benevolence of security agencies is essential to acceptability in all three cases. For DSTs with greater privacy risk, questions of competence and integrity enter citizens’ assessments.Publisher PDFPeer reviewe

The role of life cycle thinking-based methodologies in the development of waste management plans

The aim of this article is to examine how Life Cycle Thinking (LCT) contributes to the development of Waste Management Plans (WMPs). The case of Italy has been deeply investigated. The article first analyses whether and how the LCT methodologies were applied to the 21 regional WMPs; then, it draws indications for using LCT in the preparation of a WMP. Moreover, it outlines why the Life Cycle Assessment (LCA) methodology could be used as a powerful tool for regional planning in the waste field, analysing the indications for preparing a WMP that already exist at the European level and in the Italian National WM Programme. Results reveal that only four of the 21 regional WMPs include comprehensive and site-specific LCA studies. Building on these case study results, insights into the opportunities and benefits associated with incorporating LCT methodologies into WMP development and implementation are provided. This study underscores the critical importance of LCT and LCA in promoting sustainable waste management practices, ensuring compliance with European directives, and offering a foundation for more informed regional planning strategies

APPLICAZIONI DELLA METODOLOGIA LCA NEL CAMPO DELLA GESTIONE E DEL TRATTAMENTO DEI RIFIUTI

L\u2019articolo nasce da un\u2019iniziativa del gruppo di lavoro \u201cGestione e trattamento dei rifiuti\u201d dell\u2019Associazione Rete Italiana LCA (Life Cycle Assessment). L\u2019obiettivo principale del gruppo di lavoro \ue8 quello di ampliare le conoscenze relative alla specificit\ue0 della metodologia LCA applicata ai processi di gestione e di trattamento dei rifiuti. L\u2019articolo riporta otto casi studio condotti da alcuni dei partecipanti al gruppo di lavoro, con il duplice obiettivo di mostrare il vasto campo di applicazione della metodologia LCA pur mantenendosi all\u2019interno del settore rifiuti e le specificit\ue0 dell\u2019applicazione di tale metodologia ai processi di gestione e trattamento dei rifiuti. Gli otto casi studio sono stati raggruppati per macro-finalit\ue0 dell\u2019applicazione, ossia: LCA applicata per valutare i benefici ottenibili dal recupero di varie tipologie di rifiuti, LCA a supporto della pianificazione regionale e/o nazionale e LCA a supporto dell\u2019economia circolare

Challenge 6: Ethical, legal, economic, and social implications

In six decades of history, AI has become a mature and strategic discipline, successfully embedded in mainstream ICT and powering innumerable online applications and platforms. Several official documents stating specific AI policies have been produced by international organisations ( like the OCDE ), regional bodies ( EU ), several countries ( US, China, Spain, Germany, UK, Sweden, Brazil, Mexico...) as well as major AI-powered firms ( Google, Facebook, Amazon ). These examples demonstrate public interest and awareness of the economic and societal value of AI and the urgency of discussing the ethical, legal, economic and social implications of deploying AI systems on a massive scale. There is widespread agreement about the relevancy of addressing ethical aspects of AI, an urgency to demonstrate AI is used for the common good, and the need for better training, education and regulation to foster responsible research and innovation in AI. This chapter is organised around four main areas : ethics, law, economics and society ( ELES ). These areas shape the development of AI research and innovation, which in turn, influence these four areas of human activity. This interplay opens questions and demands new methods, objectives and ways to design future technologies. This chapter identifies the main impacts and salient challenges in each of these four areas.Peer reviewe

Beyond the security paradox:Ten criteria for a socially informed security policy

This article is based on a research that has been funded by the EU project “SurPriSe: Surveillance, Privacy and Security: A large scale participatory assessment of criteria and factors determining acceptability and acceptance of security technologies in Europe”, which received funding from the FP7 program, under the grant number: 285492.This article investigates the normative and procedural criteria adopted by European citizens to assess the acceptability of surveillance-oriented security technologies. It draws on qualitative data gathered at 12 citizen summits in nine European countries. The analysis identifies 10 criteria, generated by citizens themselves, for a socially informed security policy. These criteria not only reveal the conditions, purposes and operation rules that would make current European security policies and technologies more consistent with citizens’ priorities. They also cast light on an interesting paradox: although people feel safe in their daily lives, they believe security could, and should, be improved.PostprintPeer reviewe

Challenge 8: Smart Cybersecurity

Peer reviewe