Automated Decision Making and Profiling

Abstract

This literature review examines the public attitudes toward Automated Decision-Making (ADM) and how people feel about having the human element completely removed from seemingly important contexts. The use of ADM is an unstoppable innovation that is being seen and tested in areas such as health care, criminal sentencing, financial and job hiring. The successful use of these technologies critically relies on how the public perceives its use. Focusing on the connections of how much ADM is trusted, if it's considered fair or biased, and the overall clarity of how it works. The review covers multiple research studies that not only analyze the perceived trustworthiness and fairness of ADM but also looks into the background of the demographic being surveyed, outlining the main factors influencing public acceptance of AMD systems.

One of the key ideas in the research is examining the context in which these ADM systems are used and gauging the perceived trust and fairness of them with greater trust in some areas and less trust in others. These contextual ideas also introduce the factors of risk and the necessity of human empathy in some situations including health and criminal sentencing. ADM is perceived to be more trusted in things like loan allocation as it is more unbiased by humans, but in cases like judging a criminal machine bias has been observed. By then recording the individuals experiences such as computer literacy, age, and understanding of data privacy influenced ADM perceptions of trust and fairness.

This paper examines the legal issues arising from the collection and processing of Health Big Data in the light of the European legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation, i.e., Regulation 679/ 2016. Whether Big Health Data are "personal data" or not is really the heart of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Moreover, data subject's rights, e.g., the right not to be subject to a decision based solely on automated processing, are heavily impacted by the use of AI, algorithms and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have substantial impact on individuals. On the other hand, as the Covid-19 pandemic has revealed, Big Data analytics can offer crucial source of information. In this respect, this paper identifies and applies the legal provisions to algorithms used in big health data processing, providing an interpretation to address risks to data subject's rights, while embracing the opportunities that Big Health Data has to offer.

Τhis paper explores the legal issues that arise from the collection and processing of Big Health Data in the light of the EU legislation on Data Protection, placing particular emphasis on the General Data Protection Regulation. Whether Big Health Data can be characterised as “personal data” or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Moreover, data subject’s rights, e.g., the right not to be subject to a decision based solely on automated processing, are heavily impacted by the use of AI, algorithms and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial source of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subjects’ rights while embracing the opportunities that Big Health Data have to offer.

The processing of Big Health and Genetic Data can bring significant benefits to medical research. However, thanks to advanced processing techniques and analytics the ever-growing big data sets provide unprecedented insight into human behaviour, private life and our societies. The endless and unpredictable uses and results of datasets may compromise fundamental rights, such as the right to privacy, the right to the protection of personal data, the right to non-discrimination, which are all enshrined in the European Charter of Fundamental Rights. Consequently, this paper will analyse whether the GDPR provides interpretative solutions which guarantee that risks deriving from Big Health and Genetic Data will be addressed, while data subjects’ rights are enforced; at the same time, it should be ensured that the opportunities that Big Health Data have to offer will not be missed.

Τhis paper explores the legal issues that arise from the collection and processing of Big Health Data in the light of the EU law on Data Protection, placing particular emphasis on the General Data Protection Regulation. Whether Big Health Data can be characterised as "personal data" or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Moreover, data subject's rights, e.g., the right not to be subject to a decision based solely on automated processing, are heavily impacted by the use of AI, algorithms and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial source of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subjects' rights while embracing the opportunities that Big Health Data have to offer.