Artificial Intelligence and Predicting Illegal Immigration to the USA

2020 ◽  
Vol 58 (5) ◽  
pp. 183-193
Author(s):  
SeyedSoroosh Azizi ◽  
Kiana Yektansani
Keyword(s):  
Artificial Intelligence ◽  
Illegal Immigration ◽  
The Usa

scholarly journals Application of Artificial Intelligence in COVID-19 Pandemic: Bibliometric Analysis

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 441
Author(s):  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
Belal Alsinglawi ◽  
Li-Fong Lin ◽  
Shuo-Chen Chien ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Bibliometric Analysis ◽  
English Language ◽  
R Package ◽  
Research Area ◽  
Republic Of China ◽  
Comprehensive Picture ◽  
The Usa ◽  
The Republic ◽  
Academy Of Sciences

The application of artificial intelligence (AI) to health has increased, including to COVID-19. This study aimed to provide a clear overview of COVID-19-related AI publication trends using longitudinal bibliometric analysis. A systematic literature search was conducted on the Web of Science for English language peer-reviewed articles related to AI application to COVID-19. A search strategy was developed to collect relevant articles and extracted bibliographic information (e.g., country, research area, sources, and author). VOSviewer (Leiden University) and Bibliometrix (R package) were used to visualize the co-occurrence networks of authors, sources, countries, institutions, global collaborations, citations, co-citations, and keywords. We included 729 research articles on the application of AI to COVID-19 published between 2020 and 2021. PLOS One (33/729, 4.52%), Chaos Solution Fractals (29/729, 3.97%), and Journal of Medical Internet Research (29/729, 3.97%) were the most common journals publishing these articles. The Republic of China (190/729, 26.06%), the USA (173/729, 23.73%), and India (92/729, 12.62%) were the most prolific countries of origin. The Huazhong University of Science and Technology, Wuhan University, and the Chinese Academy of Sciences were the most productive institutions. This is the first study to show a comprehensive picture of the global efforts to address COVID-19 using AI. The findings of this study also provide insights and research directions for academic researchers, policymakers, and healthcare practitioners who wish to collaborate in these domains in the future.

scholarly journals Challenges of digitalization and artificial intelligence for modern economies, societies and management

2020 ◽  
Vol 28 (3) ◽  
pp. 556-567
Author(s):  
Rolf Clauberg
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Technical Information ◽  
Developed Countries ◽  
Negative Effects ◽  
Physical Systems ◽  
Large Numbers ◽  
Official Policy ◽  
The Usa ◽  
New Jobs

This study aims at identifying the challenges of digitalization and artificial intelligence for modern economies, societies and business administration. The implementation of digitalization schemes as Industry 4.0 are presently official policy of many developed countries. The goal is optimization of production processes and supply chains. Artificial intelligence is also affecting many fields. Both technologies are expected to substantially change working conditions for many people. It is important to identify the kind and impact of these changes and possible means to minimize negative effects. For this purpose, this study uses previous results about the disappearance of manufacturing jobs in the USA and their impact on different groups of society together with technical information about the new technologies to deduce expected changes caused by digitalization and artificial intelligence. Results are that both technologies will destroy large numbers of jobs and complete job classes while at the same time creating new jobs very different from the ones destroyed. Extensive permanent education and re-education of employees will be necessary to minimize negative effects, probably even changes to a more broad-based education to improve the potential of job changes into completely new fields. In addition, the technical information about digitalization in cyber-physical systems points to dangers that will require solutions on the international level.

scholarly journals Machine learning challenges and impact: an interview with Thomas Dietterich

2017 ◽  
Vol 5 (1) ◽  
pp. 54-58 ◽  
Author(s):  
Zhi-Hua Zhou
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Driving Force ◽  
Professor Emeritus ◽  
State University ◽  
Learning Society ◽  
Learning Challenges ◽  
The World ◽  
The Usa ◽  
Oregon State University

Abstract Machine learning is the driving force of the hot artificial intelligence (AI) wave. In an interview with NSR, Prof. Thomas Dietterich, the distinguished professor emeritus of computer science at Oregon State University in the USA, the former president of Association of Advancement of Artificial Intelligence (AAAI, the most prestigious association in the field of artificial intelligence) and the founding president of the International Machine Learning Society, talked about exciting recent advances and technical challenges of machine learning, as well as its big impact on the world.

Artificial intelligence: accelerator or panacea for financial crime?

2019 ◽  
Vol 26 (2) ◽  
pp. 634-646 ◽  
Author(s):  
Peter Yeoh
Keyword(s):  
Artificial Intelligence ◽  
Secondary Data ◽  
Financial Crime ◽  
Public And Private ◽  
Content Type ◽  
Competitive Edge ◽  
Business Cases ◽  
The Usa ◽  
The Uk ◽  
Administrative Sanctions

PurposeThis purpose of this viewpoint is to address the intended good and unintended bad impacts of artificial intelligence (AI) applications in financial crime.Design/methodology/approachThe paper relied primarily on secondary data resources, business cases and relevant laws and regulations, and it used a legal-economics perspective.FindingsCurrent AI systems could function as antidotes or accelerator of financial crime, in particular cybercrime. Research suggests criminal law could be applied via three approaches to curb these cybercrimes. However, others considered this to be an inappropriate mechanism to hold AI agents accountable, as present AI systems were not deemed capable of making ethically informed choices. Instead, administrative sanctions would be considered more appropriate for now. While keeping vigilance against AI malicious acts, regulatory authorities in the USA and the UK have opted largely for the innovation-friendly, market-oriented, permissionless approach over the state-interventionist stance so as to maintain their global competitive edge in this domain.Originality/valueThe paper reinforced the growing arguments that AI applications should be deployed more as panacea for financial crimes rather than being abused as crime accelerators. There equally though is the need for both public and private sectors to be mindful of the unintended negative, harmful consequences to society, especially those connected to cybercrime. This implied the further need to beef up attention and resources to help mitigate these risks.

scholarly journals Artificial Intelligence along the New Silk Road

2020 ◽  
pp. 240-254
Author(s):  
Lynda Hardman
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
International Collaboration ◽  
Research Community ◽  
Current Situation ◽  
Silk Road ◽  
Diplomatic Relations ◽  
The Past ◽  
The Usa

Chapter 13 gives an impression of the development of the relatively young AI and computer science fields in Europe and China and how the current situation has developed over the past twenty years, where European and Chinese researchers are equal colleagues on an international stage and where diplomatic relations between the USA and China on the international stage have consequences felt directly by European AI researchers in their labs. In what ways are AI researchers in China and Europe competitors with each other, for example in terms of the global shortage of trained AI researchers and practitioners? At the same time, the AI research community collaborates globally, so how can we ensure that the field continues to benefit from open international collaboration?

scholarly journals Machine learning forecasting of USA and PRC balance of trade in context of mutual sanctions

2020 ◽  
Vol 73 ◽  
pp. 01025
Author(s):  
Zuzana Rowland ◽  
Jaromír Vrbka ◽  
Marek Vochozka
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Time Series ◽  
Multilayer Perceptron ◽  
Traded Goods ◽  
Suitable Tool ◽  
The Usa ◽  
Balance Of Trade ◽  
Trade War ◽  
Multilayer Perceptron Networks

The USA decided to regulate the trade more by imposing tariffs on specific types of traded goods. It is therefore more interesting to find out whether the current technologies based on artificial intelligence with time series influenced by extraordinary factors such as the trade war between two powers are able to work. The objective of the contribution is to examine and subsequently equalize two time series – the USA import from the PRC and the USA export to the PRC. The dataset shows the course of the time series at monthly intervals between January 2000 and July 2019. 10,000 multilayer perceptron networks (MLP) are generated, out of which 5 with the best characteristics are retained. It has been proved that multilayer perceptron networks are a suitable tool for forecasting the development of the time series if there are no sudden fluctuations. Mutual sanctions of both states did not affect the result of machine learning forecasting.

scholarly journals Compliance with medical recommendations depending on the use of artificial intelligence as a diagnostic method

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Michaela Soellner ◽  
Joerg Koenigstorfer
Keyword(s):  
Artificial Intelligence ◽  
Social Presence ◽  
Severe Disease ◽  
Topical Therapy ◽  
Care Process ◽  
Treatment Recommendation ◽  
Diagnostic Process ◽  
Mediation Effects ◽  
Hypothetical Scenario ◽  
The Usa

Abstract Background Advanced analytics, such as artificial intelligence (AI), increasingly gain relevance in medicine. However, patients’ responses to the involvement of AI in the care process remains largely unclear. The study aims to explore whether individuals were more likely to follow a recommendation when a physician used AI in the diagnostic process considering a highly (vs. less) severe disease compared to when the physician did not use AI or when AI fully replaced the physician. Methods Participants from the USA (n = 452) were randomly assigned to a hypothetical scenario where they imagined that they received a treatment recommendation after a skin cancer diagnosis (high vs. low severity) from a physician, a physician using AI, or an automated AI tool. They then indicated their intention to follow the recommendation. Regression analyses were used to test hypotheses. Beta coefficients (ß) describe the nature and strength of relationships between predictors and outcome variables; confidence intervals [CI] excluding zero indicate significant mediation effects. Results The total effects reveal the inferiority of automated AI (ß = .47, p = .001 vs. physician; ß = .49, p = .001 vs. physician using AI). Two pathways increase intention to follow the recommendation. When a physician performs the assessment (vs. automated AI), the perception that the physician is real and present (a concept called social presence) is high, which increases intention to follow the recommendation (ß = .22, 95% CI [.09; 0.39]). When AI performs the assessment (vs. physician only), perceived innovativeness of the method is high, which increases intention to follow the recommendation (ß = .15, 95% CI [− .28; − .04]). When physicians use AI, social presence does not decrease and perceived innovativeness increases. Conclusion Pairing AI with a physician in medical diagnosis and treatment in a hypothetical scenario using topical therapy and oral medication as treatment recommendations leads to a higher intention to follow the recommendation than AI on its own. The findings might help develop practice guidelines for cases where AI involvement benefits outweigh risks, such as using AI in pathology and radiology, to enable augmented human intelligence and inform physicians about diagnoses and treatments.

CONDITIONS FOR THE DEVELOPMENT AND IMPACT OF ARTIFICIAL INTELLIGENCE ON WORK AND OTHER CERTAIN LEGAL SOCIAL, TECHNOLOGICAL AND ECONOMIC ISSUES IN THE EUROPEAN UNION

2021 ◽  
Vol specjalny (XXI) ◽  
pp. 113-127
Author(s):  
Andrzej Świątkowski
Keyword(s):  
Artificial Intelligence ◽  
European Union ◽  
The European Union ◽  
Member States ◽  
Eu Member States ◽  
The Future ◽  
The Usa ◽  
European Values ◽  
Electronic Technologies ◽  
The Eu

The European Union is in the initial phase of managing the conditions for the growth of artificial intelligence. Assuming that the above-mentioned electronic technology of the future should be trustworthy, guarantee the safety of its users and develop under human leadership, the Union should be able to convince the Member States of the necessary need for all interested parties to apply modern electronic technologies in practice while respecting European values, principles and human rights. The above common goal, extremely important for the future of European societies, and a uniform unified strategy for achieving it, binds the EU Member States. The above statement applies to all EU Member States, including those with above-average ambitions to become European leaders in the use of artificial intelligence for economic and social development. Considering that the European Union is competing with the USA and China, it is justified to ask whether the strategy of the development and use of artificial intelligence intended by the European Union will enable the achievement of the above goal?

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