Japan's Population Decline and the Robotics Revolution

2020 ◽  
Vol 11 (4) ◽  
pp. 63-71
Author(s):  
Patrick Doherty ◽  
Nigel McKelvey ◽  
Thomas C. Dowling
Keyword(s):  
Artificial Intelligence ◽  
Food Processing ◽  
Autonomous Robots ◽  
Large Population ◽  
Population Decline ◽  
The United States ◽  
Service Robots ◽  
Human Beings ◽  
World Record ◽  
Global Leader

Japan is experiencing a large population decline. The current population of 127 million will, at current estimates, drop by one-third to 88 million by 2065. At the same time, the population is ageing greatly with 28% aged 65 or over, a world record. Japan is pioneering the widespread introduction of robotics into many areas of society to compensate for the population fall. It aims to replace humans in many sectors like manufacturing and food processing. It also plans to introduce service robots that work closely with human beings in settings like care homes and hospitals. It is the largest such program of its kind globally. The ultimate success of this program depends on creating truly autonomous robots and will require Japan to become a global leader in artificial intelligence alongside the United States and China.

scholarly journals Reverse Migration to Mexico Led to US Undocumented Population Decline: 2010 to 2018

2020 ◽  
Vol 8 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Robert Warren
Keyword(s):  
United States ◽  
New York ◽  
Large Population ◽  
Population Decline ◽  
New York State ◽  
The United States ◽  
Executive Summary ◽  
Reverse Migration ◽  
The Us ◽  
Almost All

Executive Summary This report presents estimates of the undocumented population residing in the United States in 2018, highlighting demographic changes since 2010. The Center for Migration Studies of New York (CMS) compiled these estimates based primarily on information collected in the US Census Bureau’s American Community Survey (ACS). The annual CMS estimates of undocumented residents for 2010 to 2018 include all the detailed characteristics collected in the ACS. 1 A summary of the CMS estimation procedures, as well as a discussion of the plausibility of the estimates, is provided in the Appendix . The total undocumented population in the United States continued to decline in 2018, primarily because large numbers of undocumented residents returned to Mexico. From 2010 to 2018, a total of 2.6 million Mexican nationals left the US undocumented population; 2 about 1.1 million, or 45 percent of them, returned to Mexico voluntarily. The decline in the US undocumented population from Mexico since 2010 contributed to declines in the undocumented population in many states. Major findings include the following: The total US undocumented population was 10.6 million in 2018, a decline of about 80,000 from 2017, and a drop of 1.2 million, or 10 percent, since 2010. Since 2010, about two-thirds of new arrivals have overstayed temporary visas and one-third entered illegally across the border. The undocumented population from Mexico fell from 6.6 million in 2010 to 5.1 million in 2018, a decline of 1.5 million, or 23 percent. Total arrivals in the US undocumented population from El Salvador, Guatemala, and Honduras — despite high numbers of Border Patrol apprehensions of these populations in recent years — remained at about the same level in 2018 as in the previous four years. 3 The total undocumented population in California was 2.3 million in 2018, a decline of about 600,000 compared to 2.9 million in 2010. The number from Mexico residing in the state dropped by 605,000 from 2010 to 2018. The undocumented population in New York State fell by 230,000, or 25 percent, from 2010 to 2018. Declines were largest for Jamaica (−51 percent), Trinidad and Tobago (−50 percent), Ecuador (−44 percent), and Mexico (−34 percent). The results shown here reinforce the view that improving social and economic conditions in sending countries would not only reduce pressure at the border but also likely cause a large decline in the undocumented population. Two countries had especially large population changes — in different directions — in the 2010 to 2018 period. The population from Poland dropped steadily, from 93,000 to 39,000, while the population from Venezuela increased from 65,000 to 172,000. Almost all the increase from Venezuela occurred after 2014.

scholarly journals Digitalization: potential risks for civil society

2020 ◽  
Vol 186 (11-12) ◽  
pp. 36-47
Author(s):  
Irina Aseeva ◽  
◽  
Vladimir Budanov ◽  
Keyword(s):  
Artificial Intelligence ◽  
Civil Society ◽  
Small Businesses ◽  
Population Decline ◽  
Well Being ◽  
Network Society ◽  
Digital Information ◽  
Human Beings ◽  
Integral Basis ◽  
Potential Risks

Transition to the digital economy involves the restructuring of industries, transport and agriculture and gives new opportunities for work with Big Data and optimization the processes in the economy via smart environments, cryptocurrencies and hybrid forms of interaction between human beings and artificial intelligence. Such global transformations could not but cause a massive change in both consciousness at the socio-anthropological level and traditional forms of management at the civilizational level. Speaking about the civil society in the era of digitalization, it should be understood that this is, first of all, a network society, and without understanding this type of society it is pointless to talk about new forms of civil society. The network society was considered a well-studied object of research by the early 2000s, however today the radical acceleration of ICT and other processes are connected with digital information-network revolution involving artificial intelligence, the possibility of which was not even thought about 20 years ago. Therefore, the main purpose of our paper is an attempt to conceptualize potential risks for civil society connected with the development, testing and implementation of digital services and technologies in the global economy. To achieve this, we used system and synergistic philosophical and methodological approaches developed by the modern post-non-classical science and applied for self-developing systems. To reveal the global trends in the economy and related social problems, we undertook comparative and interdisciplinary analyses based on sources available. Sociological, philosophical and methodological reflections about radical changes in the anthropotechnosphere during the COVID-19 pandemic have revealed a number of serious problems that threaten the well-being of civil society, such as the aggravation of economic inequality, the collapse of many small businesses due to the quarantine and the introduction of remote forms of work, mass layoffs of qualified specialists, job cuts including the area of intellectual work, transport and service, as well as a significant decrease in the income of the population, decline in the quality of education, a sharp reduction in tourist flows, the ban on mass demonstrations and gatherings, which is an integral basis of the life of civil society. Thus, during the period of pandemic lockdowns, there is a significant change in the economic and socio-cultural environment of modern civilization. At the same time, the crisis situation provides means not only for the development of civil society, but also for the maintenance of enforcing and regulating functions of the state, which can upset the harmonious balance of interaction between society and any state (capitalist, socialist) or the global state of TNCs. An analysis of the world economic development in the 21st century has revealed some signs of a systemic crisis of civilization, along with the processes of digitalization as a catalyst for the shift of the paradigm of civilizational development and a catalyst for civil movements. The most striking Umwelts («perceptual environment») of civil society emerging in the digital realm are described in the paper.

Top 100 most-cited articles on medical imaging applications of artificial intelligence: a bibliometric analysis (Preprint)

2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Bibliometric Analysis ◽  
Clinical Medicine ◽  
Medical Physics ◽  
Medical Image Analysis ◽  
The United States ◽  
Independent Learning ◽  
Learning Ability ◽  
Core Technology

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.

scholarly journals Symbiosis with artificial intelligence via the prism of law, robots, and society

2021 ◽  
Author(s):  
Stamatis Karnouskos
Keyword(s):  
Artificial Intelligence ◽  
Social Economic ◽  
Autonomous Robots ◽  
Law And Society ◽  
Citizenship Rights ◽  
Legal Entity ◽  
Profound Impact ◽  
The People ◽  
Physical Presence ◽  
And Robotics

AbstractThe rapid advances in Artificial Intelligence and Robotics will have a profound impact on society as they will interfere with the people and their interactions. Intelligent autonomous robots, independent if they are humanoid/anthropomorphic or not, will have a physical presence, make autonomous decisions, and interact with all stakeholders in the society, in yet unforeseen manners. The symbiosis with such sophisticated robots may lead to a fundamental civilizational shift, with far-reaching effects as philosophical, legal, and societal questions on consciousness, citizenship, rights, and legal entity of robots are raised. The aim of this work is to understand the broad scope of potential issues pertaining to law and society through the investigation of the interplay of law, robots, and society via different angles such as law, social, economic, gender, and ethical perspectives. The results make it evident that in an era of symbiosis with intelligent autonomous robots, the law systems, as well as society, are not prepared for their prevalence. Therefore, it is now the time to start a multi-disciplinary stakeholder discussion and derive the necessary policies, frameworks, and roadmaps for the most eminent issues.

scholarly journals Interventional radiology and artificial intelligence in radiology: Is it time to enhance the vision of our medical students?

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Pierre Auloge ◽  
Julien Garnon ◽  
Joey Marie Robinson ◽  
Sarah Dbouk ◽  
Jean Sibilia ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Interventional Radiology ◽  
Clinical Practice ◽  
Medical Students ◽  
Medical Curriculum ◽  
New Technology ◽  
Large Population ◽  
The Other ◽  
Clinical Phase ◽  
Preclinical Phase

Abstract Objectives To assess awareness and knowledge of Interventional Radiology (IR) in a large population of medical students in 2019. Methods An anonymous survey was distributed electronically to 9546 medical students from first to sixth year at three European medical schools. The survey contained 14 questions, including two general questions on diagnostic radiology (DR) and artificial intelligence (AI), and 11 on IR. Responses were analyzed for all students and compared between preclinical (PCs) (first to third year) and clinical phase (Cs) (fourth to sixth year) of medical school. Of 9546 students, 1459 students (15.3%) answered the survey. Results On DR questions, 34.8% answered that AI is a threat for radiologists (PCs: 246/725 (33.9%); Cs: 248/734 (36%)) and 91.1% thought that radiology has a future (PCs: 668/725 (92.1%); Cs: 657/734 (89.5%)). On IR questions, 80.8% (1179/1459) students had already heard of IR; 75.7% (1104/1459) stated that their knowledge of IR wasn’t as good as the other specialties and 80% would like more lectures on IR. Finally, 24.2% (353/1459) indicated an interest in a career in IR with a majority of women in preclinical phase, but this trend reverses in clinical phase. Conclusions Development of new technology supporting advances in artificial intelligence will likely continue to change the landscape of radiology; however, medical students remain confident in the need for specialty-trained human physicians in the future of radiology as a clinical practice. A large majority of medical students would like more information about IR in their medical curriculum; almost a quarter of students would be interested in a career in IR.

The perception of humanness in conversational journalism: An algorithmic information-processing perspective

2021 ◽  
pp. 146144482199380
Author(s):  
Donghee Shin
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Cognitive Model ◽  
Human Beings ◽  
User Perception ◽  
User Experiences ◽  
Step Flow ◽  
Algorithmic Information ◽  
Information Processing Perspective ◽  
Practical Implications

How much do anthropomorphisms influence the perception of users about whether they are conversing with a human or an algorithm in a chatbot environment? We develop a cognitive model using the constructs of anthropomorphism and explainability to explain user experiences with conversational journalism (CJ) in the context of chatbot news. We examine how users perceive anthropomorphic and explanatory cues, and how these stimuli influence user perception of and attitudes toward CJ. Anthropomorphic explanations of why and how certain items are recommended afford users a sense of humanness, which then affects trust and emotional assurance. Perceived humanness triggers a two-step flow of interaction by defining the baseline to make a judgment about the qualities of CJ and by affording the capacity to interact with chatbots concerning their intention to interact with chatbots. We develop practical implications relevant to chatbots and ascertain the significance of humanness as a social cue in CJ. We offer a theoretical lens through which to characterize humanness as a key mechanism of human–artificial intelligence (AI) interaction, of which the eventual goal is humans perceive AI as human beings. Our results help to better understand human–chatbot interaction in CJ by illustrating how humans interact with chatbots and explaining why humans accept the way of CJ.

scholarly journals Gargantuan Hail in Argentina

2020 ◽  
Vol 101 (8) ◽  
pp. E1241-E1258 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Rachel Gutierrez ◽  
Joshua S. Soderholm ◽  
Stephen W. Nesbitt ◽  
Paula Maldonado ◽  
...  
Keyword(s):  
Social Media ◽  
Large Population ◽  
Laser Scanner ◽  
Meteorological Conditions ◽  
Dimension Stone ◽  
World Record ◽  
Maximum Dimension ◽  
Supercell Storm ◽  
The World ◽  
Local Residents

Abstract On 8 February 2018, a supercell storm produced gargantuan (>15 cm or >6 in. in maximum dimension) hail as it moved over the heavily populated city of Villa Carlos Paz in Córdoba Province, Argentina. Observations of gargantuan hail are quite rare, but the large population density here yielded numerous witnesses and social media pictures and videos from this event that document multiple large hailstones. The storm was also sampled by the newly installed operational polarimetric C-band radar in Córdoba. During the RELAMPAGO campaign, the authors interviewed local residents about their accounts of the storm and uncovered additional social media video and photographs revealing extremely large hail at multiple locations in town. This article documents the case, including the meteorological conditions supporting the storm (with the aid of a high-resolution WRF simulation), the storm’s observed radar signatures, and three noteworthy hailstones observed by residents. These hailstones include a freezer-preserved 4.48-in. (11.38 cm) maximum dimension stone that was scanned with a 3D infrared laser scanner, a 7.1-in. (18 cm) maximum dimension stone, and a hailstone photogrammetrically estimated to be between 7.4 and 9.3 in. (18.8–23.7 cm) in maximum dimension, which is close to or exceeds the world record for maximum dimension. Such a well-observed case is an important step forward in understanding environments and storms that produce gargantuan hail, and ultimately how to anticipate and detect such extreme events.

The ideological divide in public perceptions of self-driving cars

2020 ◽  
Vol 29 (4) ◽  
pp. 436-451
Author(s):  
Yilang Peng
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Scientific Literacy ◽  
Autonomous Vehicles ◽  
The United States ◽  
Public Perceptions ◽  
New Information ◽  
Nationally Representative ◽  
Self Driving Cars ◽  
Social Conservatism

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars. Compared with liberals and Democrats, conservatives and Republicans express more concern about autonomous vehicles and more support for restrictively regulating autonomous vehicles. This ideological gap is largely driven by social conservatism. Moreover, both familiarity with driverless vehicles and scientific literacy reduce respondents’ concerns over driverless vehicles and support for regulation policies. Still, the effects of familiarity and scientific literacy are weaker among social conservatives, indicating that people may assimilate new information in a biased manner that promotes their worldviews.

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