Big Data and discrimination: perils, promises and solutions. A systematic review

Favaretto, Maddalena; Clercq, Eva M. De; Elger, Bernice Simone

doi:10.1186/s40537-019-0177-4

Cited by 110 publications

(67 citation statements)

References 74 publications

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“…In the past few years, alongside the ambitious promises of digital technologies in healthcare, the research community has also highlighted many of the potential ethical issues that Big Data and ICT are raising for both patients and other members of society. In the biomedical context, data technologies have been claimed to exacerbate issues of informed consent for both patients and research participants [17,18], and to create new issues regarding privacy, confidentiality [19][20][21], data security and data protection [22], and patient anonymization [23] and discrimination [24][25][26]. In addition, recent research has also emphasized additional pressing challenges that could emerge from the inattentive use of increasingly sophisticated digital technologies, such as issues of accuracy and accountability in the use of diagnostic algorithms [27] and the exacerbation of healthcare inequalities [25].…”

Section: Introductionmentioning

confidence: 99%

Big Data and Digitalization in Dentistry: A Systematic Review of the Ethical Issues

Favaretto

Shaw

Clercq

et al. 2020

IJERPH

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Big Data and Internet and Communication Technologies (ICT) are being increasingly implemented in the healthcare sector. Similarly, research in the field of dental medicine is exploring the potential beneficial uses of digital data both for dental practice and in research. As digitalization is raising numerous novel and unpredictable ethical challenges in the biomedical context, our purpose in this study is to map the debate on the currently discussed ethical issues in digital dentistry through a systematic review of the literature. Four databases (Web of Science, Pub Med, Scopus, and Cinahl) were systematically searched. The study results highlight how most of the issues discussed by the retrieved literature are in line with the ethical challenges that digital technologies are introducing in healthcare such as privacy, anonymity, security, and informed consent. In addition, image forgery aimed at scientific misconduct and insurance fraud was frequently reported, together with issues of online professionalism and commercial interests sought through digital means.

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Section: Introductionmentioning

confidence: 99%

Big Data and Digitalization in Dentistry: A Systematic Review of the Ethical Issues

Favaretto

Shaw

Clercq

et al. 2020

IJERPH

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“…As digital technologies are becoming more and more entwined with people's personal characteristics, their daily actions and future opportunities, Big Data research creates pressing ethical and societal issues such as privacy and data anonymity [31,55], respect for personhood and personal identity [56], discrimination [44,57], and informed consent [58,59]. It is therefore of the utmost importance that scholars and regulatory bodies are aware of the harm that could be inflicted on research participants and that sustainable regulations are put in place.…”

Section: Discussionmentioning

confidence: 99%

“…For this purpose, we compiled a list of keywords linked to Big Data. The list was compiled by two of the authors while performing a systematic review on Big Data that assisted the identification of the main terms related to Big Data research and technology [44]. The first author then systematically browsed the professional pages of all professors affiliated to the departments of psychology and sociology of all twelve Swiss Universities (ten Universities and two Federal Institutes of Technology) and the top ten US Universities according to the Times Higher Education University Ranking 2018 (accessed on 13.12.2018) and selected those that had these specific keywords appearing in their personal page (See Table 1):…”

Section: Samplingmentioning

confidence: 99%

“…A semi-structured interview guide was used to conduct the interview, that was built on the experiences of the research team during prior phases of the overall project. The guide was designed through discussion and consensus within the research team after they had the time to gain familiarity with the literature and studies on Big Data research in the fields of the social sciences and psychology, and on the knowledge gained through the conduction of a systematic literature review [44].…”

Section: Data Collectionmentioning

confidence: 99%

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What is your definition of Big Data? Researchers’ understanding of the phenomenon of the decade

et al. 2020

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The term Big Data is commonly used to describe a range of different concepts: from the collection and aggregation of vast amounts of data, to a plethora of advanced digital techniques designed to reveal patterns related to human behavior. In spite of its widespread use, the term is still loaded with conceptual vagueness. The aim of this study is to examine the understanding of the meaning of Big Data from the perspectives of researchers in the fields of psychology and sociology in order to examine whether researchers consider currently existing definitions to be adequate and investigate if a standard discipline centric definition is possible. Methods Thirty-nine interviews were performed with Swiss and American researchers involved in Big Data research in relevant fields. The interviews were analyzed using thematic coding. Results No univocal definition of Big Data was found among the respondents and many participants admitted uncertainty towards giving a definition of Big Data. A few participants described Big Data with the traditional "Vs" definition-although they could not agree on the number of Vs. However, most of the researchers preferred a more practical definition, linking it to processes such as data collection and data processing.

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“…How to use robotics to dig out the knowledge that can guide practice from piecemeal information has become the hottest topic. 5,6 Many colleges and universities in the campus network operation and maintenance will enable some servers for students to access the Internet for authentication and billing, to prevent hackers from invading the local area network (LAN), monitoring the campus network download upload traffic and detecting sensation in the LAN. While these servers serve the LAN, a large amount of log data is stored in the back-end database.…”

Section: Introductionmentioning

confidence: 99%

User online behavior based on big data distributed clustering algorithm

Wang

2020

International Journal of Advanced Robotic Systems

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With the development of big data technology more and more perfect, many colleges and universities have begun to use it to analyze the construction work. In daily life, such as class, study, and entertainment, the campus network exists. The purpose of this article is to study the online behavior of users, analyze students' use of the campus network by analyzing students, and not only have a clear understanding of the students' online access but also feedback on the operation and maintenance of the campus network. Based on the big data, this article uses distributed clustering algorithm to study the online behavior of users. This article selects a college online user as the research object and studies and analyzes the online behavior of school users. This study found that the second-year student network usage is as high as 330,000, which is 60.98% more than the senior. In addition, the majority of student users spend most of their online time on the weekend, and the other time is not much different. The duration is concentrated within 1 h, 1-2 h, 2-3 h in these three time periods. By studying the user's online behavior, you can understand the utilization rate of the campus network bandwidth resources and the distribution of the use of the network, to prevent students from indulging in the virtual network world, and to ensure that the network users can improve the online experience of the campus network while accessing the network resources reasonably. The research provides a reference for network administrators to adjust network bandwidth and optimize the network.

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Big Data and discrimination: perils, promises and solutions. A systematic review

Cited by 110 publications

References 74 publications

Big Data and Digitalization in Dentistry: A Systematic Review of the Ethical Issues

Big Data and Digitalization in Dentistry: A Systematic Review of the Ethical Issues

What is your definition of Big Data? Researchers’ understanding of the phenomenon of the decade

User online behavior based on big data distributed clustering algorithm

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