scholarly journals Big Data: From modern fears to enlightened and vigilant embrace of new beginnings

2020 ◽  
Vol 7 (2) ◽  
pp. 205395172093670
Author(s):  
Nicole Dewandre
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Black Box ◽  
Optimal Policies ◽  
Three Stages ◽  
Asymmetrical Power ◽  
New Beginnings ◽  
The One

In The Black Box Society, Frank Pasquale develops a critique of asymmetrical power: corporations’ secrecy is highly valued by legal orders, but persons’ privacy is continually invaded by these corporations. This response proceeds in three stages. I first highlight important contributions of The Black Box Society to our understanding of political and legal relationships between persons and corporations. I then critique a key metaphor in the book (the one-way mirror, Pasquale’s image of asymmetrical surveillance), and the role of transparency and ‘watchdogging’ in its primary policy prescriptions. I then propose ‘relational selfhood’ as an important new way of theorizing interdependence in an era of artificial intelligence and Big Data, and promoting optimal policies in these spheres.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

Unconditional and conditional as categories of the dialectic of law

2021 ◽  
pp. 58
Author(s):  
Grigory N. Utkin
Keyword(s):  
Theoretical Analysis ◽  
Social Life ◽  
The Other ◽  
Other Hand ◽  
Dialectical Relationship ◽  
Three Stages ◽  
The One ◽  
Dialectical Analysis ◽  
Conceptual Meaning

The article reveals the conceptual, meaning-forming role of the categories of the unconditional and conditional in law. At the same time, their dialectical relationship with each other and with other categories is put in the center of attention. The dialectic of the unconditional and conditional is revealed by achieving the unity of the three stages of theoretical analysis, which allows us to present the unconditional and conditional, on the one hand, as the content of all concepts, through which the idea of law is generally expressed in various aspects and elements; on the other hand, the entire set of categories subject to dialectical analysis appears as elements of the content of the unconditional and conditional as semantic units that Express the universal characteristics of law in its features, isolation from other forms of social life.

Big Data, Artificial Intelligence, and the Internet of Things in Cross-Border E-Commerce

2021 ◽  
pp. 257-272
Author(s):  
Aboobucker Ilmudeen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Economic Globalization ◽  
The Internet ◽  
Technological Revolution ◽  
Cross Border ◽  
Wide Range ◽  
The Internet Of Things

Today, the terms big data, artificial intelligence, and internet of things (IoT) are many-fold as these are linked with various applications, technologies, eco-systems, and services in the business domain. The recent industrial and technological revolution have become popular ever before, and the cross-border e-commerce activities are emerging very rapidly. As a result, it supports to the growth of economic globalization that has strategic importance for the advancement of e-commerce activities across the globe. In the business industry, the wide range applications of technologies like big data, artificial intelligence, and internet of things in cross-border e-commerce have grown exponential. This chapter systematically reviews the role of big data, artificial intelligence, and IoT in cross-border e-commerce and proposes a conceptually-designed smart-integrated cross-border e-commerce platform.

Smart Technology for Smart Response During Pandemic Times

2022 ◽  
pp. 261-278
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Big Data ◽  
Smart City ◽  
Critical Role ◽  
Communication Strategy ◽  
Smart Technology ◽  
Information And Communication ◽  
Remote Learning

The formal response to COVID-19 through ICT is presented with a focus on testing COVID-19, ICTs and tracking COVID-19, ICTs and COVID-19 treatment, and policies and strategies. The chapter highlights the critical role of ICTs and e-government for technologies to fight coronavirus. It covers delivery of remote learning, ICT trends, artificial intelligence (AI), and big data in fighting the pandemic, in addition to social media application for awareness of citizens such as emergencies, protection, and pandemic news. The notion of developing an information and communication strategy for redesigning smart city transformation in a pandemic is highlighted.

Role of 5G network technology and artificial intelligence for research and reform of english situational teaching in higher vocational colleges

2020 ◽  
pp. 1-12
Author(s):  
Xiaoru Gao
Keyword(s):  
Artificial Intelligence ◽  
Data Processing ◽  
Teaching Method ◽  
Network Technology ◽  
5G Network ◽  
Backhaul Link ◽  
Vocational Colleges ◽  
The Many ◽  
The One

In order to study the role of English situational teaching in higher vocational colleges, based on information technology and artificial intelligence, this research combines with the needs of English teaching to construct a English situation teaching in higher vocational colleges with the support of 5G network technology and artificial intelligence. Moreover, this research builds a data processing model based on the system architecture diagram of cache placement, uses storage space and computing resources to save more backhaul link bandwidth, and adopts the “many to many” algorithm extended by the “one to many” algorithm, and uses the on-demand method to obtain scenario teaching data from the cloud. In addition, this research constructs the intermediate link of data processing, and uses 5G network transmission to solve the problem of data transmission speed. Finally, this study uses a controlled experiment to evaluate the effectiveness of the artificial intelligence teaching model constructed in this study. The research shows that the English situation teaching method based on 5G network technology and artificial intelligence in vocational colleges has a certain effect and can effectively improve the English scores of vocational college students.

scholarly journals Artificial Intelligence and Hypertension: Recent Advances and Future Outlook

2020 ◽  
Vol 33 (11) ◽  
pp. 967-974
Author(s):  
Thanat Chaikijurajai ◽  
Luke J Laffin ◽  
Wai Hong Wilson Tang
Keyword(s):  
Artificial Intelligence ◽  
Risk Factors ◽  
Big Data ◽  
Public Health Problem ◽  
Patient Specific ◽  
Medication Regimen ◽  
Factors Associated ◽  
Promising Tool ◽  
Prevention And Treatment

Abstract Prevention and treatment of hypertension (HTN) are a challenging public health problem. Recent evidence suggests that artificial intelligence (AI) has potential to be a promising tool for reducing the global burden of HTN, and furthering precision medicine related to cardiovascular (CV) diseases including HTN. Since AI can stimulate human thought processes and learning with complex algorithms and advanced computational power, AI can be applied to multimodal and big data, including genetics, epigenetics, proteomics, metabolomics, CV imaging, socioeconomic, behavioral, and environmental factors. AI demonstrates the ability to identify risk factors and phenotypes of HTN, predict the risk of incident HTN, diagnose HTN, estimate blood pressure (BP), develop novel cuffless methods for BP measurement, and comprehensively identify factors associated with treatment adherence and success. Moreover, AI has also been used to analyze data from major randomized controlled trials exploring different BP targets to uncover previously undescribed factors associated with CV outcomes. Therefore, AI-integrated HTN care has the potential to transform clinical practice by incorporating personalized prevention and treatment approaches, such as determining optimal and patient-specific BP goals, identifying the most effective antihypertensive medication regimen for an individual, and developing interventions targeting modifiable risk factors. Although the role of AI in HTN has been increasingly recognized over the past decade, it remains in its infancy, and future studies with big data analysis and N-of-1 study design are needed to further demonstrate the applicability of AI in HTN prevention and treatment.

An Empirical Analysis of Artificial Intelligence, Big Data and Analytics Applications in Exploration and Production Operations

2021 ◽  
Author(s):  
Armstrong Lee Agbaji
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Empirical Analysis ◽  
Oil And Gas ◽  
Oil Industry ◽  
Digital Transformation ◽  
Deep Dive ◽  
Exploration And Production ◽  
Oil And Gas Operations

Abstract Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an organization's ability to extract value from data. Extracting and analyzing data is getting harder as the volume, variety, and velocity of data continues to increase. Analytics can help us make better decisions, only if we can trust the integrity of the data going into the system. As digital technology continues to play a pivotal role in the oil industry, the role of reliable data and analytics has never been more consequential. This paper is an empirical analysis of how Artificial Intelligence (AI), big data and analytics has redefined oil and gas operations. It takes a deep dive into various AI and analytics technologies reshaping the industry, specifically as it relates to exploration and production operations, as well as other sectors of the industry. Several illustrative examples of transformative technologies reshaping the oil and gas value chain along with their innovative applications in real-time decision making are highlighted. It also describes the significant challenges that AI presents in the oil industry including algorithmic bias, cybersecurity, and trust. With digital transformation poised to re-invent the oil & gas industry, the paper also discusses energy transition, and makes some bold predictions about the oil industry of the future and the role of AI in that future. Big data lays the foundation for the broad adoption and application of artificial intelligence. Analytics and AI are going to be very powerful tools for making predictions with a precision that was previously impossible. Analysis of some of the AI and analytics tools studied shows that there is a huge gap between the people who use the data and the metadata. AI is as good as the ecosystem that supports it. Trusting AI and feeling confident with its decisions starts with trustworthy data. The data needs to be clean, accurate, devoid of bias, and protected. As the relationship between man and machine continues to evolve, and organizations continue to rely on data analytics to provide decision support services, it is imperative that we safeguard against making important technical and management decisions based on invalid or biased data and algorithm. The variegated outcomes observed from some of the AI and analytics tools studied in this research shows that, when it comes to adopting AI and analytics, the worm remains buried in the apple.

scholarly journals Role of Artificial Intelligence in Shaping Consumer Demand in E-Commerce

2020 ◽  
Vol 12 (12) ◽  
pp. 226
Author(s):  
Laith T. Khrais
Keyword(s):  
Artificial Intelligence ◽  
Black Box ◽  
Customer Behavior ◽  
Corpus Analysis ◽  
Detailed Understanding ◽  
Contentious Issue ◽  
Word Cloud ◽  
Decision Points ◽  
Innovative Tool

The advent and incorporation of technology in businesses have reformed operations across industries. Notably, major technical shifts in e-commerce aim to influence customer behavior in favor of some products and brands. Artificial intelligence (AI) comes on board as an essential innovative tool for personalization and customizing products to meet specific demands. This research finds that, despite the contribution of AI systems in e-commerce, its ethical soundness is a contentious issue, especially regarding the concept of explainability. The study adopted the use of word cloud analysis, voyance analysis, and concordance analysis to gain a detailed understanding of the idea of explainability as has been utilized by researchers in the context of AI. Motivated by a corpus analysis, this research lays the groundwork for a uniform front, thus contributing to a scientific breakthrough that seeks to formulate Explainable Artificial Intelligence (XAI) models. XAI is a machine learning field that inspects and tries to understand the models and steps involved in how the black box decisions of AI systems are made; it provides insights into the decision points, variables, and data used to make a recommendation. This study suggested that, to deploy explainable XAI systems, ML models should be improved, making them interpretable and comprehensible.

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