Towards a privacy impact assessment methodology to support the requirements of the general data protection regulation in a big data analytics context: A systematic literature review

Georgiadis, Georgios; Poels, Geert

doi:10.1016/j.clsr.2021.105640

Cited by 17 publications

(16 citation statements)

References 76 publications

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“…The complexity and thread in the use, acquisition and storage is of particular interest for businesses in general. In particular, a more careful and thoughtful use in the storage of this type of data followed the introduction of the GDPR rules, raising concerns on how this type of information could be stored and shared (Georgiadis and Poels, 2022).…”

Section: Discussionmentioning

confidence: 99%

Big data analysis for decision-making processes: challenges and opportunities for the management of health-care organizations

Fanelli

Pratici

Salvatore

et al. 2022

MRR

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Purpose This study aims to provide a picture of the current state of art in the use of big data for decision-making processes for the management of health-care organizations. Design/methodology/approach A systematic literature review was carried out. The research uses two analyses: descriptive analysis, describing the evolution of citations; keywords; and the ten most influential papers, and bibliometric analysis, for content evaluation, for which a cluster analysis was performed. Findings A total of 48 articles were selected for bibliographic coupling out of an initial sample of more than 5,000 papers. Of the 48 articles, 29 are linked on the basis of their bibliography. Clustering the 29 articles on the basis of actual content, four research areas emerged: quality of care, quality of service, crisis management and data management. Originality/value Health-care organizations believe strongly that big data can become the most effective tool for correctly influencing the decision-making processes. Thus, more and more organizations continue to invest in big data analytics, and the literature on this topic has expanded rapidly. This study seeks to provide a comprehensive picture of the different streams of literature existing, together with gaps in research and future perspectives. The literature is mature enough for an analysis to be made and provide managers with useful insights on opportunities, criticisms and perspectives on the use of big data for health-care organizations. However, to date, there is no comprehensive literature review on the big data analysis in health care. Furthermore, as big data is a “sexy catchphrase,” more clarity on its usage may be needed. It represents an important tool to be investigated and its great potential is often yet to be discovered. This study thus sheds light on emerging issues and suggests further research that may be needed.

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Section: Discussionmentioning

confidence: 99%

Big data analysis for decision-making processes: challenges and opportunities for the management of health-care organizations

Fanelli

Pratici

Salvatore

et al. 2022

MRR

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“…Another application of AI is in conducting accurate evaluations of the possible privacy effects of new technologies and systems, helping organizations identify and reduce any potential risks. Machine Learning algorithms can be developed to perform privacy impact assessments (PIAs) to identify and minimize potential privacy hazards associated with new technologies and systems [ 23 , 51 , 52 ]. PIAs are a methodical procedure for assessing the impact of a new initiative on an individual’s privacy and are often legally required in specific industries.…”

Section: Social Media As a Data Collection Toolmentioning

confidence: 99%

Using AI–ML to Augment the Capabilities of Social Media for Telehealth and Remote Patient Monitoring

Leung

2023

Healthcare

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Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve telehealth, remote patient monitoring, and the well-being of individuals and communities. Previous research has revealed several trends in AI–ML adoption: First, AI can be used to enhance social media marketing. Drawing on sentiment analysis and related tools, social media is an effective way to increase brand awareness and customer engagement. Second, social media can become a very useful data collection tool when integrated with new AI–ML technologies. Using this function well requires researchers and practitioners to protect users’ privacy carefully, such as through the deployment of privacy-enhancing technologies (PETs). Third, AI–ML enables organizations to maintain a long-term relationship with stakeholders. Chatbots and related tools can increase users’ ability to receive personalized content. The review in this paper identifies research gaps in the literature. In view of these gaps, the paper proposes a conceptual framework that highlights essential components for better utilizing AI and ML. Additionally, it enables researchers and practitioners to better design social media platforms that minimize the spread of misinformation and address ethical concerns more readily. It also provides insights into the adoption of AI and ML in the context of remote patient monitoring and telehealth within social media platforms.

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“…Authors in (Georgiadis et al, 2022) reported that Big Data Analytics has improved efficiency and created many opportunities, but it has also ultimately increased the risk of personal data being compromised or breached. The General Data Protection Regulation (GDPR) enforces Data Protection Impact Assessment (DPIA) to identify appropriate controls to mitigate the risks associated with personal data protection.…”

Section: Related Workmentioning

confidence: 99%

An Analysis of Infractions and Fines in the Context of the GDPR

2023

IJMCNM

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The General Data Protection Regulation (GDPR) is the regulation that determines the directives inherent to the collection, processing, and protection of personal data in European Union (EU) countries. It was implemented in May 2018 and over the past few years, several public and private companies have been affected by serious penalties. With more than 1500 fines already registered, it is important to have an analysis and insights about them. This paper proposes a detailed analysis of the public records of fines under GDPR, understanding the average fines imposed, the main causes for their application and how they have evolved over time. It is also intended to understand the most affected sectors and point ways to mitigate these penalties. It is concluded that fines under GDPR have an increasing trend over time, both in number of fines and in value, with Industry and Commerce & Media, Telecoms and Broadcasting being the most affected sectors.

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Towards a privacy impact assessment methodology to support the requirements of the general data protection regulation in a big data analytics context: A systematic literature review

Cited by 17 publications

References 76 publications

Big data analysis for decision-making processes: challenges and opportunities for the management of health-care organizations

Big data analysis for decision-making processes: challenges and opportunities for the management of health-care organizations

Using AI–ML to Augment the Capabilities of Social Media for Telehealth and Remote Patient Monitoring

An Analysis of Infractions and Fines in the Context of the GDPR

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