BIG DATA, PRIVACY AND THE STATE IN EUROPE

Abstract
Big data are large sets of data that may be analysed in order to find patterns, trends and associations especially relating to human behaviour. The State in most European countries manages big data repositories, and provides public services on the basis of them; education, social security and health services are the most challenging fields of study for public entities. In fact, the information coming from data can reveal important trends that impact on public spending, and (actual and perspective) public debt. Which is the limit to the privacy of data that a Government can set in order to improve the management of its services? The recent regulation (GDPR) has addressed this delicate issue.

Big Data https://www.big-data-europe.eu/about/
The growing digitization and networking process within the European and global societies has a large influence on all aspects of life. Large amounts of data are being produced permanently, and when these are analysed and interlinked they have the potential to create new knowledge and intelligent solutions for economy and society. Big Data can make important contributions to the technical progress in our societal key sectors and help shape business. What is needed are innovative technologies, strategies and competencies for the beneficial use of Big Data to address societal needs.
Climate, Energy, Food, Health, Transport, Security, and Social Sciences – are the most important societal challenges tackled by the European Union within the new research and innovation framework program “Horizon 2020”. In every one of these fields, the processing, analysis and integration of large amounts of data plays a growing role – such as the analysis of medical data, the decentralized supply with renewable energies or the optimization of traffic flow in large cities.

Privacy of data in Europe https://ec.europa.eu/commission/priorities/justice-and-fundamental-rights/data-protection/2018-reform-eu-data-protection-rules_en
The Regulation (EU) 2016/679 of the European Parliament and of the Council, the European Union’s ('EU') new General Data Protection Regulation (‘GDPR’), regulates the processing by an individual, a company or an organisation of personal data relating to individuals in the EU. It doesn’t apply to the processing of personal data of deceased persons or of legal persons. The rules don’t apply to data processed by an individual for purely personal reasons or for activities carried out in one's home, provided there is no connection to a professional or commercial activity. When an individual uses personal data outside the personal sphere, for socio-cultural or financial activities, for example, then the data protection law has to be respected.
The biggest way GDPR legislation will affect data collection is that it will lead to an increased reliance on real-time analytics. Real-time analytics takes data that has just been collected and puts it to immediate use and analysis. With collected data getting an immediate turnaround, there is no need for keeping said data around for any great length of time, which is one of the issues that the GDPR seeks to address.
Fortunately, researchers have made huge strides in making real-time analytics faster and more effective as compared to post-dated analytics, so there’s hope that this particular change can be made with a minimum of fuss.
Social media, an avenue that many businesses use for the purpose of building customer loyalty and increasing engagement, will also be affected. This is hardly surprising, considering how much personal information ends up residing on social media accounts. Witness the recent news of Facebook releasing new privacy tools, and it becomes obvious that the rules of engagement are changing. Businesses wanting to do business with EU customers will have to be more careful about what they ask for and be more forthright with how long they are holding onto that data and what they will be doing with it.
Furthermore, all of that Big Data being collected will have to not only be stored securely but will need to be gathered by customers who want to remove it and switch it over to another vendor. Businesses of all sizes will need to come to terms with the idea that customers will gain greater control over their own personal data.
Digital Public Services
The development of big data analytics improves the supply of public services; according to the IMF (2017) there are more than 400 digital public service programs worldwide. These are implemented by 'governments, non-governmental organizations, the private sector, and public-private partnerships. These programs span public services in sectors including agriculture, civic education, education, environment, health, financial services, social protection, and utilities. In addition, they use a variety of digital technologies, from computers to mobile phones to radios to smartphones' (IMF 2017, p. 210).
Despite of the size and social relevance, it is a under-investigated field; while the impact depends on the sector, and technologies the gain in efficiency of public services seems to be positive, especially in social services, and education.
Education
'In education, digital technology has primarily been used for one of two purposes: as a pedagogical tool in the classroom and as a tool for monitoring teacher attendance. Overall, most studies of the impact of digital technology as a pedagogical tool suggest that digital technology improves student learning in the short term, but that these impacts diminish in the medium term. Studies in digital monitoring suggest that these programs improve teacher attendance and improve learning outcomes, where they are measured' (IMF 2017, p.212).
Social Protection
'Digital technology has been used in social protection in one of two ways: as a mechanism for implementing such programs, either through digital national identification schemes or electronic income transfers; or as an alternative means for targeting potential beneficiaries of such programs, primarily through big data. While there are a number of initiatives in this area, existing studies suggest that digital can reduce the costs associated with implementing these programs, allowing the public sector to provide these transfers at a lower cost' (IMF 2017, p.213).
Civic Education
'In civic education, digital technology has been primarily used in one of three ways: (1) providing more frequent transmission of information between citizens and the state, often during elections; (2) verifying polling results digitally during elections; and (3) digitalizing electoral ballots. Overall, these studies have found that digital approaches have effectively increased voter participation during elections and reduced fraud' (IMF 2017, p. 214).
Agriculture
'Digital technology in the agricultural sector has primarily been used in three ways: (1) to provide information to farmers about agricultural techniques, prices or weather; (2) to provide agricultural extension advice; and (3) to monitor agricultural extension agents (Aker, Ghosh, and Burrell 2016). Overall, studies on digital agriculture initiatives suggest that such services increase farmers’ knowledge in particular areas—such as prices and cropping systems—but have little to no impact on agricultural practices, production, or farm-gate prices' (IMF 2017, p. 214).
Health
'While digital technology in the health sector has been used in a variety of ways—for medical devices, record-keeping, and providing information and reminders—the majority of studies in developing countries has been in the latter area. Similar to digital agriculture interventions, these studies have found that digital technology is associated with improvements in knowledge, with mixed evidence on behavioural change and other health outcomes' (IMF 2017, p. 215).

References
International Monetary Fund (IMF) 2017. Digital revolutions in public finance. Edited by Sanjeev Gupta, Washington, DC, ISBN 9781484315224.