Algorithmically Constructed Identities: Networked Digital Technologies, Dynamic Behavioral Big Data Collection, and Automated Decision-Making

2019 ◽  
Vol 11 (2) ◽  
pp. 49
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Collection ◽  
Digital Technologies ◽  
Automated Decision Making

Evolution of e-participation in Greek local government

2021 ◽  
pp. 1-15
Author(s):  
Constantina Costopoulou ◽  
Maria Ntaliani ◽  
Filotheos Ntalianis
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Local Government ◽  
Local Governments ◽  
Local Community ◽  
New Technologies ◽  
Mobile Apps ◽  
Digital Technologies ◽  
Decision Making Processes ◽  
The Impact

Local governments are increasingly developing electronic participation initiatives, expecting citizen involvement in local community affairs. Our objective was to assess e-participation and the extent of its change in local government in Greece. Using content analysis for 325 Greek municipal websites, we assessed e-participation status in 2017 and 2018 and examined the impact of change between these years. The assessment regards two consecutive years since the adoption of digital technologies by municipalities has been rapid. The main findings show that Greek local governments have made significant small- to medium-scale changes, in order to engage citizens and local societies electronically. We conclude that the integration of advanced digital technologies in municipalities remains underdeveloped. We propose that Greek municipalities need to consider incorporating new technologies, such as mobile apps, social media and big data, as well as e-decision making processes, in order to eliminate those obstacles that hinder citizen engagement in local government. Moreover, the COVID-19 outbreak has highlighted the need for enhancing e-participation and policymakers’ coordination through advanced digital technologies.

scholarly journals Territorial and Digital Borders and Migrant Vulnerability Under a Pandemic Crisis

2021 ◽  
pp. 45-64
Author(s):  
Petra Molnar
Keyword(s):  
Decision Making ◽  
Human Rights ◽  
Big Data ◽  
Private Sector ◽  
Guinea Pigs ◽  
Technological Development ◽  
Forced Migration ◽  
Population Movements ◽  
Humanitarian Crises ◽  
Automated Decision Making

AbstractPeople on the move are often left out of conversations around technological development and become guinea pigs for testing new surveillance tools before bringing them to the wider population. These experiments range from big data predictions about population movements in humanitarian crises to automated decision-making in immigration and refugee applications to AI lie detectors at European airports. The Covid-19 pandemic has seen an increase of technological solutions presented as viable ways to stop its spread. Governments’ move toward biosurveillance has increased tracking, automated drones, and other technologies that purport to manage migration. However, refugees and people crossing borders are disproportionately targeted, with far-reaching impacts on various human rights. Drawing on interviews with affected communities in Belgium and Greece in 2020, this chapter explores how technological experiments on refugees are often discriminatory, breach privacy, and endanger lives. Lack of regulation of such technological experimentation and a pre-existing opaque decision-making ecosystem creates a governance gap that leaves room for far-reaching human rights impacts in this time of exception, with private sector interest setting the agenda. Blanket technological solutions do not address the root causes of displacement, forced migration, and economic inequality – all factors exacerbating the vulnerabilities communities on the move face in these pandemic times.

Big Data and Democracy

2020 ◽  
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Big Data ◽  
Data Collection ◽  
Political Campaigns ◽  
Original Research ◽  
Targeted Advertising ◽  
Echo Chambers ◽  
Political Turmoil ◽  
The Impact

This edited collection tackles subjects that have arisen as a result of new capabilities to collect, analyse and use vast quantities of data using complex algorithms. Questions tackled include what is wrong with targeted advertising in political campaigns, whether echo chambers really are a matter of genuine concern, what is the impact of data collection through social media and other platforms on questions of trust in society and is there a problem of opacity as decision-making becomes increasingly automated? The contributors consider potential solutions to these challenges and discuss whether an ethical compass is available or even feasible in an ever more digitized and monitored world. The editors bring together original research on the philosophy of big data and democracy from leading international authors, with recent examples and case references – including the 2016 Brexit Referendum, the Leveson Inquiry and the Edward Snowden leaks – and combine them in one authoritative volume at time of great political turmoil.

scholarly journals THE DIGITAL ECONOMY AND ITS IMPACT ON THE FINANCIAL MARKET

2020 ◽  
Vol 8 (3) ◽  
pp. 83-87
Author(s):  
N. A. Shevchenko ◽  
V. D. Kalinova
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Stock Market ◽  
Financial Market ◽  
Digital Technologies ◽  
Financial Sector ◽  
Digital Economy ◽  
Significant Patterns

The article discusses the relevance of the introduction of digital technologies in the financial sector. Special attention is paid to the evolution of the stock market due to its digitalization. Various options for the practical use of digital technologies in the described area are shown by analyzing big data and identifying significant patterns. The authors ' proposals will improve the efficiency and validity of decision-making in the financial sector.

Challenges and Solutions of Big Data and IoT

2019 ◽  
pp. 264-272
Author(s):  
Jayashree K. ◽  
Abirami R. ◽  
Rajeswari P.
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Collection ◽  
Internet Of Things ◽  
Data Processing ◽  
The Internet ◽  
Huge Amount ◽  
Collection Data ◽  
Different Sources ◽  
The Internet Of Things

The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.

scholarly journals The “black box” at work

2020 ◽  
Vol 7 (2) ◽  
pp. 205395172096618
Author(s):  
Ifeoma Ajunwa
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Collection ◽  
Equal Opportunity ◽  
Personal Information ◽  
Wearable Technology ◽  
Black Box ◽  
Data Driven ◽  
Mission Creep ◽  
Rawlsian Justice

An oversized reliance on big data-driven algorithmic decision-making systems, coupled with a lack of critical inquiry regarding such systems, combine to create the paradoxical “black box” at work. The “black box” simultaneously demands a higher level of transparency from the worker in regard to data collection, while shrouding the decision-making in secrecy, making employer decisions even more opaque to the worker. To access employment, the worker is commanded to divulge highly personal information, and when hired, must submit further still to algorithmic processes of evaluations which will make authoritative claims as to the workers’ productivity. Furthermore, in and out of the workplace, the worker is governed by an invisible data-created leash deploying wearable technology to collect intimate worker data. At all stages, the worker is confronted with a lack of transparency, accountability, or explanation as to the inner workings or even the logic of the “black box” at work. This data revolution of the workplace is alarming for several reasons: (1) the “black box at work” not only serves to conceal disparities in hiring, but could also allow for a level of “data-laundering” that beggars any notion of equal opportunity in employment and (2) there exists, the danger of a “mission creep” attitude to data collection that allows for pervasive surveillance, contributing to the erosion of both the personhood and autonomy of workers. Thus, the “black box at work” not only enables worker domination in the workplace, it deprives the worker of Rawlsian justice.

scholarly journals Propuesta de una arquitectura para un Smart Campus Universitario

2020 ◽  
pp. 21-27
Author(s):  
José María CRUZ-PARADA ◽  
Víctor Manuel ZAMUDIO-RODRIGUEZ ◽  
Carlos LINO-RAMÍREZ ◽  
David Asael GUTIERREZ-HERNANDEZ
Keyword(s):  
Decision Making ◽  
Control System ◽  
Data Collection ◽  
Intelligent Agents ◽  
Mobile Application ◽  
University Campus ◽  
Information Analysis ◽  
Smart Campus ◽  
The Creation ◽  
Automated Decision Making

A proposal of an architecture is described for the use of intelligent agents connected to a mobile application and the same time is also linked to a control system that is managed by the institution. In this document the idea is analyzed from its conception, through the elaborated development and the tests and the results that have been carried out. This architecture is planned to be used in the creation of an intelligent university campus with data collection, information analysis and automated decision making.

scholarly journals Quality Improvement through Intensive Care Registries: The Value of Big Data in Clinical Decision Making

2019 ◽  
Author(s):  
Ali Sanaei ◽  
Mohammad Mehdi Sepehri
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Critical Care ◽  
Intensive Care ◽  
Quality Improvement ◽  
Data Collection ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Clinical Decision ◽  
Electronic Database

Background: Quality of Intensive care has got more attention in case of the high cost of healthcare and the potential for harm. Poor-quality care causes high cost and quality improvement initiatives in the ICU lead to an improvement in outcomes as well as a decrease in costs. One of the crucial tools that allow physicians and nurses to monitor change in a quality improvement effort is the development of an electronic database for data collection and reporting. The objective of Intensive Care Registries is to create a high-quality registry of patients through a collaboration of academic health centers performing uniform data collection with the purpose of improving the quality and accuracy of healthcare decisions and provide a data-driven clinical decision support system for critical care medicine. Methods: This article reviews real-world data sources in healthcare and considers registry as the main tool to address health services and outcomes research questions in critical care, and briefly describes objective, inputs and outputs of intensive care registries. As it can be comprehended from library research, the combination of patient clinical care data, quality parameters, and ICU operating costs, integrated into an electronic database, provides a valuable tool for quality improvement and overall efficiency of offered care. Results: Using Big Data effectively within ICUs for supporting clinical decision making can lead to predict numerous diseases and help to discover new patterns in healthcare. The ability to process multiple high-speed clinical data streams from multiple centers could dramatically improve both healthcare efficiency and patient outcomes. Conclusion: To gain this goal, developing reliable and standardized health analytics platforms as well as quality improvement processes that translate analytical results into new clinical guidelines, is recommended.

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