scholarly journals Disinformation, social media, bots, and astroturfing: the fourth wave of digital democracy

2021 ◽  
Author(s):  
Berta García-Orosa
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Political Action ◽  
Social Imaginary ◽  
Political Strategy ◽  
Technological Determinism ◽  
Audience Engagement ◽  
Digital Platforms ◽  
Political Actors ◽  
Fourth Wave

This article reflects on the conceptualization and the salient features of the ecology of e-democracy. The authors identify four distinct waves marked by technological innovations and studied under the control–participation dichotomy. In the first wave, during the 1990s, political actors begin to establish their online presence but without any other notable changes in communication. The second wave takes place from 2004 to 2008 and features the consolidation of social networks and the increasing commodification of audience engagement. The third wave begins to take shape during Obama’s 2008 election campaign, which featured micro-segmentation and the use of big data. The fourth wave, starting in 2016 with the Brexit campaign and the Cambridge Analytica scandal, has been defined by the front and center use of Artificial Intelligence. Some recent phenomena that challenge or buttress the make-up of critical public opinion are the following: a) digital platforms as political actors; b) the marked use of Artificial Intelligence and big data; c) the use of falsehoods as a political strategy, as well as other fake news and deep fake phenomena; d) the combination of hyperlocal and supranational issues; e) technological determinism; f) the search for audience engagement and co-production processes; and g) trends that threaten democracy, to wit, the polarization of opinions, astroturfing, echo chambers and bubble filters. Finally, the authors identify several challenges in research, pedagogy and politics that could strengthen democratic values, and conclude that democracy needs to be reimagined both under new research and political action frameworks, as well as through the creation of a social imaginary on democracy.

Digital Transformation Journey of HR

2022 ◽  
pp. 94-115
Author(s):  
Tuğba Karaboğa ◽  
Hasan Aykut Karaboğa ◽  
Dogan Basar ◽  
Songul Zehir
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Human Resources ◽  
Digital Transformation ◽  
Digital Culture ◽  
Digital Workplace ◽  
Digital Platforms ◽  
Digital Management ◽  
Employee Experience

Big data and artificial intelligence (AI) technologies have changed how we live, how we work, and how we organize businesses. Thus, it is no surprise that it is also changing how we manage human resources (HR). For HR leaders, digital transformation is a very hot topic, having the potential to create high value for businesses. First, HR can transform all functions, processes, and systems by leveraging digital platforms and applications. Second, HR can lead business digitalization, enabling a compelling employee experience where a digital culture, a digital workplace, and digital management are welcomed. To provide a more pragmatic perspective, this chapter discusses digitalization of HR with big data and artificial intelligence (AI) technologies and identifies key digital HR strategies and roles needed to sustain the digital transformation. Also, this chapter presents the advantages of digital HR and the basic pitfalls HR faces in the digital transformation of HR.

scholarly journals Education, Big Data and Artificial Intelligence: Mixed methods in digital platforms

Comunicar ◽  
2020 ◽  
Vol 28 (65) ◽  
pp. 43-52
Author(s):  
Beatrice Bonami ◽  
Luiz Piazentini ◽  
André Dala-Possa
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Research Application ◽  
Digital Platforms ◽  
Academic Field ◽  
Qualitative And Quantitative ◽  
Methodological Considerations ◽  
Complex Scenario ◽  
The Impact ◽  
Educational Field

Digital technology has provided users with new connections that have reset our understanding of social architectures. As a reaction to Artificial Intelligence (AI) and Big Data, the educational field has rearranged its structure to consider human and non-human stakeholders and their actions on digital platforms. In light of this increasingly complex scenario, this proposal aims to present definitions and discussions about AI and Big Data from the academic field or published by international organizations. The study of AI and Big Data goes beyond the search for mere computational power and instead focuses upon less difficult (yet perhaps more complex) areas of the study social impacts in Education. This research suggests an analysis of education through 21st century skills and the impact of AI development in the age of platforms, undergoing three methodological considerations: research, application and evaluation. To accomplish the research, we relied upon systematic reviews, bibliographic research and quality analyses conducted within case studies to compose a position paper that sheds light on how AI and Big Data work and on what level they can be applied in the field of education. Our goal is to offer a triangular analysis under a multimodal approach to better understand the interface between education and new technological prospects, taking into consideration qualitative and quantitative procedures. La tecnología digital ha traído características de conexión que restablecen nuestra comprensión de arquitecturas sociales. Sobre la Inteligencia Artificial (IA) y Big Data, el campo educativo reorganiza su estructura para considerar a los actores humanos y no humanos y sus acciones en plataformas digitales. En este escenario cada vez más complejo, esta propuesta tiene como objetivo presentar definiciones y debates sobre IA y Big Data de naturaleza académica o publicados por organizaciones internacionales. El estudio de IA y Big Data puede ir más allá de la búsqueda de poder computacional / lógico y entrar en áreas menos difíciles (y quizás más complejas) del campo científico para responder a sus impactos sociales en la educación. Esta investigación sugiere un análisis de la educación a través de las habilidades del siglo XXI y los impactos del desarrollo de IA en la era de las plataformas, pasando por tres ejes de grupos metodológicos: investigación, aplicación y evaluación. Para llevar a cabo la investigación, confiamos en revisiones sistemáticas, investigaciones bibliográficas y análisis de calidad de estudios de casos para componer un documento de posición que arroje luz sobre cómo funcionan la IA y el Big Data y en qué nivel se pueden aplicar en el campo de la educación. Nuestro objetivo es ofrecer un análisis triangular bajo un enfoque multimodal para comprender mejor la interfaz entre la educación y las nuevas perspectivas tecnológicas.

A PLATFORM FOR APPLIED ANALYSIS OF THE EFFECTIVENESS OF VIOC CLIENTS AS AN ARTIFICIAL INTELLIGENCE ENVIRONMENT

2021 ◽  
pp. 80-86
Author(s):  
Andrey V. Lapin ◽  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Oil Products ◽  
Digital Platforms ◽  
Communication Platform ◽  
Information And Communication ◽  
The Subject ◽  
Oil Company

In the article, the author examines the possibilities of digital platforms for analyzing applied data on the oil products market using the example of a vertically integrated oil company (VOC). The subject of the research is an information and communication platform for applied analysis of big data in an artificial intelligence environment.

A Study on the Development of Appointment Algorithm of CT With Big Data using AI (Artificial Intelligence)

2018 ◽  
Vol 20 (2) ◽  
pp. 1-5
Author(s):  
Sang-ho Jeon ◽  
Sung-yeul Yang ◽  
In-beom Shin ◽  
Dae-mok Son ◽  
Tae-han Kwon ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data

scholarly journals Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery

2021 ◽  
Author(s):  
Manish Kumar Tripathi ◽  
Abhigyan Nath ◽  
Tej P. Singh ◽  
A. S. Ethayathulla ◽  
Punit Kaur
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Drug Discovery

scholarly journals Blockchain Disrupting Fintech and the Banking System

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 24
Author(s):  
Eduard Alexandru Stoica ◽  
Daria Maria Sitea
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Financial Institutions ◽  
New World ◽  
Great Part ◽  
Banking System ◽  
Daily Activities ◽  
Blockchain Technology ◽  
Almost All

Nowadays society is profoundly changed by technology, velocity and productivity. While individuals are not yet prepared for holographic connection with banks or financial institutions, other innovative technologies have been adopted. Lately, a new world has been launched, personalized and adapted to reality. It has emerged and started to govern almost all daily activities due to the five key elements that are foundations of the technology: machine to machine (M2M), internet of things (IoT), big data, machine learning and artificial intelligence (AI). Competitive innovations are now on the market, helping with the connection between investors and borrowers—notably crowdfunding and peer-to-peer lending. Blockchain technology is now enjoying great popularity. Thus, a great part of the focus of this research paper is on Elrond. The outcomes highlight the relevance of technology in digital finance.

scholarly journals Anomaly Identification during Polymerase Chain Reaction for Detecting SARS-CoV-2 Using Artificial Intelligence Trained from Simulated Data

Molecules ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 20
Author(s):  
Reynaldo Villarreal-González ◽  
Antonio J. Acosta-Hoyos ◽  
Jaime A. Garzon-Ochoa ◽  
Nataly J. Galán-Freyle ◽  
Paola Amar-Sepúlveda ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Real Time ◽  
Binary Classification ◽  
Simulated Data ◽  
Classification Model ◽  
Rt Pcr ◽  
Simon Bolivar ◽  
Polymerase Chain ◽  
Available Information

Real-time reverse transcription (RT) PCR is the gold standard for detecting Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), owing to its sensitivity and specificity, thereby meeting the demand for the rising number of cases. The scarcity of trained molecular biologists for analyzing PCR results makes data verification a challenge. Artificial intelligence (AI) was designed to ease verification, by detecting atypical profiles in PCR curves caused by contamination or artifacts. Four classes of simulated real-time RT-PCR curves were generated, namely, positive, early, no, and abnormal amplifications. Machine learning (ML) models were generated and tested using small amounts of data from each class. The best model was used for classifying the big data obtained by the Virology Laboratory of Simon Bolivar University from real-time RT-PCR curves for SARS-CoV-2, and the model was retrained and implemented in a software that correlated patient data with test and AI diagnoses. The best strategy for AI included a binary classification model, which was generated from simulated data, where data analyzed by the first model were classified as either positive or negative and abnormal. To differentiate between negative and abnormal, the data were reevaluated using the second model. In the first model, the data required preanalysis through a combination of prepossessing. The early amplification class was eliminated from the models because the numbers of cases in big data was negligible. ML models can be created from simulated data using minimum available information. During analysis, changes or variations can be incorporated by generating simulated data, avoiding the incorporation of large amounts of experimental data encompassing all possible changes. For diagnosing SARS-CoV-2, this type of AI is critical for optimizing PCR tests because it enables rapid diagnosis and reduces false positives. Our method can also be used for other types of molecular analyses.

Impact of Big Data and Artificial Intelligence on Industry: Developing a Workforce Roadmap for a Data Driven Economy

2021 ◽  
Author(s):  
Marina Johnson ◽  
Rashmi Jain ◽  
Peggy Brennan-Tonetta ◽  
Ethne Swartz ◽  
Deborah Silver ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Data Driven
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