Accumulations of Artificial Intelligence in East Asia: An Archaeology of Experiments, Institutions, and Policies in Taiwan and Japan

The article is devoted to the history of the development of Information and Communication Technologies (ICT) and Artificial Intelligence (AI), their current and probable future achievements, and the problems (which have already arisen, but will become even more acute in the future) associated with the development of these technologies and their active introduction in society. The close connection between the development of AI and cognitive science, the penetration of ICT and AI into various fields, in particular the field of health care, is shown. A significant part of the article is devoted to the analysis of the concept of ‘artificial intelligence’, including the definition of generative AI. We analyze recent achievements in the field of Artificial Intelligence, describe the basic models, in particular the Large Linguistic Models (LLM), and forecast the development of AI and the dangers that await us in the coming decades. We identify the forces behind the aspiration to create artificial intelligence, which is increasingly approaching the capabilities of the so-called general/universal AI, and also suggest desirable measures to limit and channel the development of artificial intelligence. The authors emphasize that the threats and dangers of the development of ICT and AI are particularly aggravated by the monopolization of their development by the state, intelligence services, large corporations and those often referred to as globalists. The article forecasts the development of computers, ICT and AI in the coming decades, and also shows the changes in society that will be associated with them. The study consists of two articles. The first, presented below, provides a brief historical overview and characterizes the current situation in the field of ICT and AI, it also analyzes the concepts of artificial intelligence, including generative AI, changes in the understanding of AI related to the emergence of the so-called large language models and related new types of AI programs (ChatGPT). The article discusses the serious problems and dangers associated with the rapid and uncontrolled development of artificial intelligence. The second article, to be published in the next issue of the journal, describes and comments on current assessments of breakthroughs in the field of AI, analyzes various forecasts, and the authors give their own assessments and forecasts of future developments. Particular attention is given to the problems and dangers associated with the rapid and uncontrolled development of AI, the fact that achievements in the field of AI are becoming a powerful means of controlling the population, imposing ideology and choice, influencing the results of elections, and a weapon for undermining security and geopolitical struggle.

Artificial intelligence (AI) promises to change health care, with some studies showing proof of concept of a provider-level performance in various medical specialties. However, there are many barriers to implementing AI, including patient acceptance and understanding of AI. Patients' attitudes toward AI are not well understood. We systematically reviewed the literature on patient and general public attitudes toward clinical AI (either hypothetical or realised), including quantitative, qualitative, and mixed methods original research articles. We searched biomedical and computational databases from Jan 1, 2000, to Sept 28, 2020, and screened 2590 articles, 23 of which met our inclusion criteria. Studies were heterogeneous regarding the study population, study design, and the field and type of AI under study. Six (26%) studies assessed currently available or soon-to-be available AI tools, whereas 17 (74%) assessed hypothetical or broadly defined AI. The quality of the methods of these studies was mixed, with a frequent issue of selection bias. Overall, patients and the general public conveyed positive attitudes toward AI but had many reservations and preferred human supervision. We summarise our findings in six themes: AI concept, AI acceptability, AI relationship with humans, AI development and implementation, AI strengths and benefits, and AI weaknesses and risks. We suggest guidance for future studies, with the goal of supporting the safe, equitable, and patient-centred implementation of clinical AI.

The brave new world of artificial intelligence: dawn of a new era

근대 이후의 SF 작품은 인간 특유의 탐구심과 호기심을 자극하여 새로운 발명이나 발견을 촉진시키기도 했다. SF작품은 대중들의 공감을 얻기 위해 가까운 미래에 등장할 과학기술의 발전에 대해서 묘사하거나, 과학기술상의 쟁점을 차용하기도 한다. 따라서 SF영화의 시대적 변천을 통해, 과학기술의 대중적 인식에 접근하는 것은 중요한 의의가 있다. 이 논문에서는 인공지능 캐릭터가 본격적으로 등장한 1960년대 이후의 영화를 소재로, 인공지능 캐릭터의 특징을 시기에 따라 정리하고, 현재 벌어지고 있는 낙관론과 비관론에 관련시켜 검토하였다. 1960-80년대 전반기까지의 인공지능은 네트워크에 의존하지 않고 디바이스가 독립적으로 작동하는 형태였다. 그리고 초지능(superintelligence)을 가진 존재가 아니라 한정된 기능에 전문화되어 있었다. 인공지능의 반란은 스스로의 판단에 의해서가 아니라, 인간의 탐욕이나 오류의 결과였다. 1980년대 후반부터는 AGI(범용인공지능) 수준의 능력을 지닌 캐릭터가 등장하였다. 또한 AI를 과신한 나머지, 인간이 AI를 통제할 필요성을 망각하면서 야기되는 오류에 대해서도 문제를 제기하였다. 1990년대에는 인터넷이 보편화되면서 인공지능은 네트워크에 기반한 존재로 묘사되었다. 초인공지능이 등장하여 인간에게 전쟁을 도발하거나, 인공지능이 생명체의 인지능력이나 감정을 동기화시켜 인간성을 말살하는 존재로 묘사되기도 하였다. 영화 속 인공지능은 부정적 측면을 조금 더 부각시킨 것이 사실이다. 인공지능의 오류나 반란을 소재로 한 SF영화가 많기 때문이다. 선한 인공지능 캐릭터를 등장시키더라도, 언제든 인류의 존속을 위협할 수 있는 위험성을 내포한 존재로 묘사되는 경우가 많다. 이는 인공지능이 진실로 인류의 실존을 위협하기 때문이 아니라, 신기술에 대한 막연한 공포감을 이용해 흥행성을 높이는 장치로 인공지능 캐릭터를 창조했기 때문이다. 인류 역사에서 신기술에 대한 공포와 논쟁은 오래 전부터 이어져 왔으며, SF영화의 인공지능 캐릭터는 제작 당시의 과학기술 인식에 의해 상상되었을 뿐이다. 따라서 인공지능을 주제로 한 논쟁에서 영화적 묘사에 집착하기보다는 인류에게 유익한 방향으로 발전을 이끄는 자극제 역할로 국한시키는 것이 필요하다.The Science Fiction(SF) work since post-modern has stimulated a unique curiosity and spirit of inquiry to promote new inventions and discoveries. The SF works describe the development of science and technology that will emerge in the near future or borrow issues on science and technology in order to gain public sympathy. Thus, it is critical to approach the popular perception of science and technology through the transformation of the SF movies. This paper examines the characteristics. This paper summarizes the characteristics of Artificial Intelligence(AI) characters in movies since the 1960s when the AI characters emerged in earnest and examined them in relation to current optimism and pessimism. Until the 1960s and early 1980s, AI was not dependent on the network but operated independently. It was not existed with superintelligence but specialized in limited functions. The revolt of AI was not the result of its self-judgement, but of human greed or error. From the late 1980s, characters with the same level of Artificial General Intelligence (AGI) appeared. Due to the overconfidence of AI, they raised questions about errors caused as human forgets the need to control AI. In the 1990s, the AI was portrayed as existence which was based on network as the internet became popularized. The superintelligence has appeared to provoke war on humans, or AI has been described as one that destroys humanity by synchronizing the cognitive ability and emotions of life. It is true that AI in movies has emphasized its negative aspects. This is because there are many SF movies that are based on AI errors or revolts. Even if a good AI character is introduced, it is often described as a danger that could threaten the continuation of mankind at any time. The reason is that AI is not truly a threat to the existence of mankind, but it was created as a device that enhance popularity by using vague fear of new technology. The fear and debate over new technologies has long been occurred in human history and the AI characters in SF movies have only been imagined by the awareness of science and technology at the time of production. Therefore, it is necessary to limit the AI-themed debate to the role of stimulant that leads to development in a direction beneficial to human rather than focusing on cinematic depictions.

Predictive modeling in reproductive medicine: Where will the future of artificial intelligence research take us?

The research relevance is determined by the importance of a thorough study of methods, schemes and models used by artificial intelligence to mechanise creativity in modern conditions of active technological development. The study aims to analyse the main processes taking place in modern art in connection with active technologization of work processes, to identify the leading concepts regarding the possibility of creating machine art in the future, etc. The employed methods are theoretical, such as analysis, systematisation, generalisation, etc., for studying key problems and further development of creativity based on artificial intelligence. The study examines in detail the main developments of Artificial General Intelligence and Artificial Narrow Intelligence, in particular the achievements of Generative adversarial networks and Creative adversarial networks. Artificial intelligence-generated art demonstrates the remarkable capabilities of technologies. The evolving artificial intelligence in the arts introduces “digital art”. Generative Adversarial Networks are used as a foundational tool for artists who use digital methods and texture generation to create unique compositions. Furthermore, sculptors collaborate with artificial intelligence tools to convert drawings into 3D models or transform historical art databases into sculptures. Creative thinking, a hallmark of human intelligence, is determined as artificial intelligence’s ability to generate new and original ideas. The development of emotional intelligence in artificial intelligence enables empathetic responses and the identification of human emotions through voice and facial expressions. The issues of authorised internationality, awareness of the creative process, psychological foundations of artificial empathy and emotional intelligence define the prospects for the development of neuroscience. Challenges persist in defining creativity, authorship, and legal aspects of artificial intelligence-generated art. The study materials may be useful for artists, art educators, technologists, and researchers interested in the intersection of technology and art, legal professionals (especially intellectual property law), and individuals involved in artificial intelligence development may find these findings valuable

The research relevance is determined by the importance of a thorough study of methods, schemes and models used by artificial intelligence to mechanise creativity in modern conditions of active technological development. The study aims to analyse the main processes taking place in modern art in connection with active technologization of work processes, to identify the leading concepts regarding the possibility of creating machine art in the future, etc. The employed methods are theoretical, such as analysis, systematisation, generalisation, etc., for studying key problems and further development of creativity based on artificial intelligence. The study examines in detail the main developments of Artificial General Intelligence and Artificial Narrow Intelligence, in particular the achievements of Generative adversarial networks and Creative adversarial networks. Artificial intelligence-generated art demonstrates the remarkable capabilities of technologies. The evolving artificial intelligence in the arts introduces “digital art”. Generative Adversarial Networks are used as a foundational tool for artists who use digital methods and texture generation to create unique compositions. Furthermore, sculptors collaborate with artificial intelligence tools to convert drawings into 3D models or transform historical art databases into sculptures. Creative thinking, a hallmark of human intelligence, is determined as artificial intelligence’s ability to generate new and original ideas. The development of emotional intelligence in artificial intelligence enables empathetic responses and the identification of human emotions through voice and facial expressions. The issues of authorised internationality, awareness of the creative process, psychological foundations of artificial empathy and emotional intelligence define the prospects for the development of neuroscience. Challenges persist in defining creativity, authorship, and legal aspects of artificial intelligence-generated art. The study materials may be useful for artists, art educators, technologists, and researchers interested in the intersection of technology and art, legal professionals (especially intellectual property law), and individuals involved in artificial intelligence development may find these findings valuable

List of Contributors vii Series Editors Preface x 1 Introduction: Locating Neoliberalism in East Asia 1 Richard Child Hill, Bae-Gyoon Park, and Asato Saito 2 Industry Clusters and Transnational Networks: Japan s New Directions in Regional Policy 27 Kuniko Fujita and Richard Child Hill 3 State-Space Relations in Transition: Urban and Regional Policy in Japan 59 Asato Saito 4 Developmental Neoliberalism and Hybridity of the Urban Policy of South Korea 86 Byung-Doo Choi 5 Spatially Selective Liberalization in South Korea and Malaysia: Neoliberalization in Asian Developmental States 114 Bae-Gyoon Park and Josh Lepawsky 6 Clusters as a Policy Panacea? Critical Reflections on the Cluster Policies of South Korea 148 Yong-Sook Lee 7 Moving toward Neoliberalization? The Restructuring of the Developmental State and Spatial Planning in Taiwan 167 Chia-Huang Wang 8 Neoliberalism, the Developmental State, and Housing Policy in Taiwan 196 Yi-Ling Chen and William Derhsing Li 9 Reforming Health: Contrasting Trajectories of Neoliberal Restructuring in the City-States 225 Stephen W.K. Chiu, K.C. Ho, and Tai-lok Lui 10 Detroit of the East : A Multiscalar Case Study of Regional Development Policy in Thailand 257 Richard Child Hill and Kuniko Fujita 11 Concluding Remarks 294 Bae-Gyoon Park and Asato Saito Index 303

BackgroundResearch on technologies based on artificial intelligence in healthcare has increased during the last decade, with applications showing great potential in assisting and improving care. However, introducing these technologies into nursing can raise concerns related to data bias in the context of training algorithms and potential implications for certain populations. Little evidence exists in the extant literature regarding the efficacious application of many artificial intelligence -based health technologies used in healthcare. ObjectivesTo synthesize currently available state-of the-art research in artificial intelligence -based technologies applied in nursing practice. DesignScoping review MethodsPubMed, CINAHL, Web of Science and IEEE Xplore were searched for relevant articles with queries that combine names and terms related to nursing, artificial intelligence and machine learning methods. Included studies focused on developing or validating artificial intelligence -based technologies with a clear description of their impacts on nursing. We excluded non-experimental studies and research targeted at robotics, nursing management and technologies used in nursing research and education. ResultsA total of 7610 articles published between January 2010 and March 2021 were revealed, with 93 articles included in this review. Most studies explored the technology development (n = 55, 59.1%) and formation (testing) (n = 28, 30.1%) phases, followed by implementation (n = 9, 9.7%) and operational (n = 1, 1.1%) phases. The vast majority (73.1%) of studies provided evidence with a descriptive design (level VI) while only a small portion (4.3%) were randomised controlled trials (level II). The study aims, settings and methods were poorly described in the articles, and discussion of ethical considerations were lacking in 36.6% of studies. Additionally, one-third of papers (33.3%) were reported without the involvement of nurses. ConclusionsContemporary research on applications of artificial intelligence -based technologies in nursing mainly cover the earlier stages of technology development, leaving scarce evidence of the impact of these technologies and implementation aspects into practice. The content of research reported is varied. Therefore, guidelines on research reporting and implementing artificial intelligence -based technologies in nursing are needed. Furthermore, integrating basic knowledge of artificial intelligence -related technologies and their applications in nursing education is imperative, and interventions to increase the inclusion of nurses throughout the technology research and development process is needed.

Human or machine? The perception of artificial intelligence in journalism, its socio-economic conditions, and technological developments toward the digital future

Since the emergence of Artificial intelligence (AI), despite a common expectation that AI should be ‘ethical’ [1], there are many different interpretations, assumptions, and expectations about what constitutes "ethical AI" and which ethical problems and requirements are pointed out by the public. Even though many private companies and research institutions have highlighted present and possible future problems, needs, and guidelines associated with AI ethics, relevant public visions regarding how "ethical AI" can be constituted [1] have not been explored sufficiently. For obtaining public opinions, although questionnaires and interviews are commonly used, the questions in these methods are designed based on only the researchers' preferences, and this could be a limitation. Social media data, however, are produced by users freely [2], and many people share their ideas in social media discussions [3]. Social media data usage, therefore, has been growing in various research studies. Researchers intending to utilize social media as a data source predominantly harness Twitter data, yet in recent years Reddit has also gained the attention of scholars with the same research purpose, as in [2], [3]. Reddit is a huge social media platform involving over 50 million daily active users with diverse mentalities shaped by different backgrounds, prior beliefs, personal experiences, and personalities, from various geographical locations, and 100 thousand active communities, thereby it brings different segments of the public together. Moreover, users benefit from a level of anonymity on Reddit not typically accomplished on other social media platforms [4], thereby users may feel more secure and share more honest thoughts on a topic, thus the Reddit data have been used to gather public opinions in prior research as in [3]. Through the lens of technological frames [5], to explore social media users' interpretations, assumptions, and expectations about how ethical AI is built, and which problems hinder building ethical AI, Reddit conversations were analyzed. More specifically, a corpus consisting of 998 unique Reddit post titles and their corresponding 16611 comments extracted from 15 AI-related subreddits were identified by using topic modelling supported by human judgment for frame identification as in [6] based on BERTopic [7]. The findings show that perceptions about AI ethics are clustered around several themes (AI's gender bias; humans' gender bias about perceived gender of bots; regulation and patent laws related to AI use; AI spreading disinformation; AI making fake faces, videos, music; misuse of personal data; and AI impact on crime), with deviations about how these themes are interpreted, what problems or actors they pertain to, and what appropriate measures should be taken to address problems pointed out by the public. While some of these ethical issues were also highlighted in prominent AI ethics literature as in [8], the findings of this study indicated new insights such as humans' gender bias about the perceived gender of bots. The findings offer important implications. First, as a practical implication, the findings can enrich current public voice-centric explorations of AI ethics. Also, they could help designing suitable interfaces that allow proper human-AI task coordination and collaboration and deploying innovative solutions for existing or anticipated ethical problems. Second, expected outcomes can demonstrate areas where misconceptions and unrealistic visions about AI ethics are widespread, which may trigger speculative fears or concerns. Researchers may be encouraged to more focus on the areas where public misconceptions are more common; educational programs may be arranged to reduce speculative fears or concerns or take necessary measures for real ethical risks. Academia, industry and government communities may collaborate for research and policy arrangements in those areas. Third, through employing computeraided textual analysis, this study reveals frames in social media conversations to showcase the latest perceptions from different viewpoints. This method may be an example method for relevant future research.

Nanotechnology, which is a cross-border technology transforming the worldpsilas economy, plays a crucial role in recent science and technology developments. Japan and Taiwan which have paid a lot of attention on material research and development, together with the emerging mainland China, have been the three key players in nanotechnology and material developments in east Asia. This study is to compare Delphi studies on material and nanotechnology fields for the three countries which share the similarities in the aspects of language, culture and geography. In additions, the linkage between Delphi study and Sci-Tech policy will also be discussed in this study in order to approach the social contexts of national Sci-Tech developments in the three countries.

AI telemedicine screening in ophthalmology: health economic considerations

List of Contributors. Preface. Part I: Introduction. 1. Overview: The Lessons from Taiwan: Relevance, Limitations and Transferability E. Thorbecke, H. Wan. 2. The 'Miracle' That Did Happen: Understanding East Asia in Comparative Perspective J. Bhagwati. Part II: Key Macro Policies and Reforms in Taiwan's Development. 3. Government Policy in the Taiwanese Development Process: The Past 50 Years S.W.Y. Kuo. 4. Taiwan's Industrialization Policies: Two Views, Two Types of Subsidy A.H. Amsden. 5. The Trade-Growth Nexus in Taiwan's Development G. Ranis. 6. A Balanced Budget, Stable Prices and Full Employment: The Macroeconomic Environment for Taiwan's Growth Tzong-shian Yu. 7. Comparative Advantage Development Strategy and the Economic Development of Taiwan J. Yifu Lin. Part III: The Liu-Tsiang Policy Proposals. 8. The Liu-Tsiang Proposals for Economic Reform in Taiwan: A Retrospective Jia-Dong Shea. 9. Liberalization Promotes Development: Evidence from Taiwan J.C.H. Fei, Yun-Peng Chu. Part IV: The Role of Agriculture, Industrial Policy, Human Capital and Labor Institutions in Taiwan's Development. 10. Agriculture as the Foundation for Development: The Taiwanese Story Tsu-tan Fu, Shun-yi Shei. 11. The Role of Industrial Policy in Taiwan's Development Pochih Chen. 12. Human Capital Creation and Utilization in Taiwan G. Ren-juei Tsiang. 13. The Labor Market in Taiwan: Manpower, Earnings, and Market Institutions W. Galenson. PartV: Relevance of the Taiwanese Experience to Other Third World Regions. 14. State and Market in the Economic Development of Korea and Taiwan I. Adelman. 15. Latin America and East Asia: Revisiting the Evidence A.C. Harberger. 16. What Can Sub-Saharan Africa Learn from the Taiwanese Development Experience? T. Ademola Oyejide. 17. The Relevance and Comparability of Taiwan's Development Experience to Indonesia M. Sadli, Kian Wie Thee. Part VI: Conclusions and Epilogue. 18. Some Further Thoughts on Taiwan's Development Prior to the Asian Financial Crisis and Concluding Remarks H. Wan, E. Thorbecke. 19. Epilogue: How Did Taiwan Withstand the Asian Financial Crisis? E. Thorbecke, H. Wan.

Artificial intelligence (AI) has transitioned from the lab to the bedside, and it is increasingly being used in healthcare. Radiology and Radiography are on the frontline of AI implementation, because of the use of big data for medical imaging and diagnosis for different patient groups. Safe and effective AI implementation requires that responsible and ethical practices are upheld by all key stakeholders, that there is harmonious collaboration between different professional groups, and customised educational provisions for all involved. This paper outlines key principles of ethical and responsible AI, highlights recent educational initiatives for clinical practitioners and discusses the synergies between all medical imaging professionals as they prepare for the digital future in Europe. Responsible and ethical AI is vital to enhance a culture of safety and trust for healthcare professionals and patients alike. Educational and training provisions for medical imaging professionals on AI is central to the understanding of basic AI principles and applications and there are many offerings currently in Europe. Education can facilitate the transparency of AI tools, but more formalised, university-led training is needed to ensure the academic scrutiny, appropriate pedagogy, multidisciplinarity and customisation to the learners' unique needs are being adhered to. As radiographers and radiologists work together and with other professionals to understand and harness the benefits of AI in medical imaging, it becomes clear that they are faced with the same challenges and that they have the same needs. The digital future belongs to multidisciplinary teams that work seamlessly together, learn together, manage risk collectively and collaborate for the benefit of the patients they serve.