Can We Anticipate Some Unintended Consequences of Big Data?

2016 ◽  
Vol 25 (01) ◽  
pp. 73-86 ◽  
Author(s):  
D. McCaldin ◽  
K. Wang ◽  
G. Schreier ◽  
N.H. Lovell ◽  
M. Marschollek ◽  
...  

Summary Objectives: As wearable sensors take the consumer market by storm, and medical device manufacturers move to make their devices wireless and appropriate for ambulatory use, this revolution brings with it some unintended consequences, which we aim to discuss in this paper. Methods: We discuss some important unintended consequences, both beneficial and unwanted, which relate to: modifications of behavior; creation and use of big data sets; new security vulnerabilities; and unforeseen challenges faced by regulatory authorities, struggling to keep pace with recent innovations.Where possible, we proposed potential solutions to unwanted consequences. Results: Intelligent and inclusive design processes may mitigate unintended modifications in behavior. For big data, legislating access to and use of these data will be a legal and political challenge in the years ahead, as we trade the health benefits of wearable sensors against the risk to our privacy. The wireless and personal nature of wearable sensors also exposes them to a number of unique security vulnerabilities. Regulation plays an important role in managing these security risks, but also has the dual responsibility of ensuring that wearable devices are fit for purpose. However, the burden of validating the function and security of medical devices is becoming infeasible for regulators, given the many software apps and wearable sensors entering the market each year, which are only a subset of an even larger ‘internet of things’. Conclusion: Wearable sensors may serve to improve wellbeing, but we must be vigilant against the occurrence of unintended consequences. With collaboration between device manufacturers, regulators, and end-users, we balance the risk of unintended consequences occurring against the incredible benefit that wearable sensors promise to bring to the world.


2014 ◽  
Vol 23 (01) ◽  
pp. 82-89 ◽  
Author(s):  
H. Monkman ◽  
C. Petersen ◽  
J. Weber ◽  
E. M. Borycki ◽  
S. Adams ◽  
...  

Summary Objectives: While big data offers enormous potential for improving healthcare delivery, many of the existing claims concerning big data in healthcare are based on anecdotal reports and theoretical vision papers, rather than scientific evidence based on empirical research. Historically, the implementation of health information technology has resulted in unintended consequences at the individual, organizational and social levels, but these unintended consequences of collecting data have remained unaddressed in the literature on big data. The objective of this paper is to provide insights into big data from the perspective of people, social and organizational considerations. Method: We draw upon the concept of persona to define the digital persona as the intersection of data, tasks and context for different user groups. We then describe how the digital persona can serve as a framework to understanding sociotechnical considerations of big data implementation. We then discuss the digital persona in the context of micro, meso and macro user groups across the 3 Vs of big data. Results: We provide insights into the potential benefits and challenges of applying big data approaches to healthcare as well as how to position these approaches to achieve health system objectives such as patient safety or patient-engaged care delivery. We also provide a framework for defining the digital persona at a micro, meso and macro level to help understand the user contexts of big data solutions. Conclusion: While big data provides great potential for improving healthcare delivery, it is essential that we consider the individual, social and organizational contexts of data use when implementing big data solutions.


2020 ◽  
pp. 136-148
Author(s):  
Sarah Brayne

This concluding chapter reflects on the major lessons learned from this book. The Los Angeles Police Department’s continued use of big data policing underscores the primary argument running through this book—that big data is fundamentally social. At every phase—from big data’s adoption to collection and analysis, institutional intervention, and reception—there is a social patterning to how data is used. There is a need to curb institutions’ craving for data, because that hunger too often outpaces people’s understanding of the intended and unintended consequences of a data binge. The chapter then offers guidelines for academics, lawmakers, and community groups regarding how data can be leveraged to promote efficiency, fairness, and accountability in criminal justice reform. It also discusses the future of law enforcement; identifies policy and research priorities; and argues that the implications of big data surveillance extend beyond policing into other social sectors.


2017 ◽  
Vol 31 (3) ◽  
pp. 1-4 ◽  
Author(s):  
A. Faye Borthick ◽  
Robin R. Pennington

ABSTRACT Big Data and the data analytical software for analyzing it have developed far enough that some trends have emerged. People are clever. Leave them alone with resources and they will do interesting things with them, giving both intended and unintended consequences. This commentary stems from the 2016 Journal of Information Systems Research Conference (JISC2016) on Big Data. It highlights the landscape of Big Data, including how organizations are starting to use data in different ways. While it is true that some of what this commentary offers does not, strictly speaking, require Big Data with respect to volume, diversity, and structure, the connotations that Big Data bestowed have prompted new ways to stage and use data. For example, “70% of firms now say that big data is of critical importance to their firms” (Malone 2016). The articles in this issue were presented as papers at JISC2016. They treat different aspects of the growing availability and use of data in organizations.


ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  

Find Out About 'Big Data' to Track Outcomes


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org


PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  

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