Analysis of Research on Artificial Intelligence in Public Administration:

Purpose: This study aims to investigate how analysing academic research through digital tools can improve our understanding of the applications, functions, and challenges related to the use of advanced artificial technologies (AI) in public administration.Methodology: The applied methodology relies on the use of digital tools, specifically Voyant-Tools and Chat Generative Pre-Trained Transformer (GPT-4), for text analysis in conjunction with a selection of scientific literature on artificial intelligence and public administration.Findings: The results of our study show that researchers equally report advantages and disadvantages of using AI in public administration. Moreover, the research highlights the benefits of using artificial intelligence while emphasising the importance of the ethical and appropriate regulation thereof.Practical implications: Our innovative approach of developing and using a combined methodology involving specialised digital tools to analyse scientific literature introduces a new dimension to the examination of scientific texts and has the potential to shape public policy in the field of public administration.Originality: The existing body of research on public administration and artificial intelligence is limited. Our study expands the scientific field by delving into the use of artificial intelligence in public administration

Social technologies and collective intelligence

Social Technologies and Collective Intelligence is a monograph written by 24 international researchers in the field of Social Technologies and edited by prof. dr. Aelita Skaržauskienė from Mykolas Romeris University in Vilnius, Lithuania. As an academic discipline, social technologies is a highly interdisciplinary research field that focuses on applying existing ICT as well as newly emerging technologies to improve society. This work highlights the dominance of the non-technological social aspect of technology and its interaction with people, emphasizing the institutional power of Collective Intelligence through soft technology. By going through the book, the reader will gain insight and knowledge into the challenges and opportunities provided by this new exciting research field. Scientists will appreciate the comprehensive treatment of the research challenges in a multidisciplinary perspective. Practitioners and applied researchers will welcome the novel approaches to tackle relevant problems in their field. And policy-makers will better understand how technological advances can support them in supporting the progress of society and economy. The book is divided into six parts, each dealing with a well-defined research area at the intersection of Social Technologies and Collective Intelligence. Instead of being split up five ways among particular groups of collaborating authors, each individual author contributes to all five parts of the book their specific knowledge and insights, which makes this monograph a truly collaborative effort and a prime example of collective intelligence

RETHINKING EFFECTS OF INNOVATION IN COMPETITION IN THE ERA OF NEW DIGITAL TECHNOLOGIES

The new technologies, digitalization, algorithms, big data, artificial intelligence are already changing our lives and commercial habits. The technological revolution with new products and services is transforming the market and business operators. There is a general understanding that new technological improvements benefit competition. The question is, whether competition models are adequate and ready to deal with the challenges associated with new technologies. In recent years, there has been a revived interest in the concept of innovation and its application in competition policy and law. However, proper examination of its influence on competition policy is lacking. During the last decades, there have been attempts to explain the relationship between competition and innovation by including various innovation models in competition analysis. The innovation instruments have developed. Despite these developments, there are still diametrically opposed theoretical approaches, from completely ignoring the concept of innovation in competition law to the ones that develop a specific economic test in competition analysis. This paper will try to analyze and compare different approaches to the intersection of competition and innovation. Systematic theories that assess innovation in the context of competition are scarce. Competition authorities have been focused on issues of consumer and social welfare, rather than on the impact of innovation on the competition. The idea is to try to define the role of innovation in competition analysis. The question is whether competition law needs new tools in order to understand new developments and innovations. The authors argue that competition has its own instruments that can be applied to new models with certain adaptations. Certain regulatory instruments are necessary, but they can be implemented without stifling innovation and the development of new technologies. The authors attempt to offer possible solutions for the existing challenges based on the state of art research. The challenges associated with the market definition and market power are explained. It is argued that competition analyses should acknowledge that innovation is essential for competition in the digital era

An Analysis of the Effects of the Fourth Industrial Revolution on Vietnamese Enterprises

The objective of this empirical study is to analyze the role of the industrial revolution 4.0 (IR4.0) on Vietnamese enterprises. The IR4.0, which relates to the breakthrough of the Internet of Things and artificial intelligence, has brought about changes in the manufacturing industry and had a significant impact on Vietnamese enterprises. A review of previous studies combined with secondary data has been applied for analyzing and supporting the evidence of the impact of IR4.0 on Vietnamese enterprises. The analysis has provided evidence that aside from its beneficial opportunities, the IR4.0 will create many challenges for Vietnamese enterprises, impacting management, operations, and the manufacturing sector. The concept of IR4.0 and its impact on enterprises and economies should be considered and the IR4.0 will accelerate the process of technological innovation. This is derived from the nature of the IR4.0, which is based on digital technology and integrates all intelligent technologies. It is evident from the data analysis and the synthesized information that Vietnamese enterprises in IR4.0 have advantages and opportunities to access the new technologies. In adapting to the requirements stemming from this revolution, enterprises should increase their investment in applying new technologies to take opportunities into the current market. Due to this issue, Vietnamese enterprises need to change and be innovative in their overall strategy, adapt and make good use of the benefits and opportunities, provide solutions to the new challenges, and achieve the competitive advantages within the IR4.0. Based on the outcomes of this study, management practitioners and researchers can refer to and apply these findings for future in-depth studies of how IR4.0 is affecting Vietnamese enterprises and make relevant recommendations

Legal Regulation of Algorithms From the Perspective of Interpretability

The human life in the age of artificial intelligence has undergone tremendous changes. Algorithm technology is widely developed and applied as one of the core technologies of artificial intelligence. However, a series of problems such as algorithm discrimination, algorithm killing, and “information cocoon” caused by unexplainable algorithms represented by artificial neural networks needed to be solved urgently,which forms a risk society. The algorithmic order is gradually “offside” into a new social order, which challenges the existing legal order. Because the existing legal order upholds the neutral value of technology tools and does not pay attention to the legal regulations of technology itself, it cannot make ethical prejudgment of unexplainable algorithms to prevent and control social risks. With the deepening of the “intelligence” of algorithm technology, social risk is expanding. The field of algorithm technology creates interpretable algorithms to respond to social risks. However, due to the lack of legal value and institutional design support, the technological advantages of interpretable algorithms to prevent and control algorithm black boxes, “Offside order” and coping with a risky society cannot be confirmed and guided by law. Therefore, it is an effective way to solve the risks in the age of artificial intelligence by taking the technical critical theory of risk society as the value basis and taking the interpretability of algorithms as a necessary condition for algorithm regulation

The Digital Divide in Process Safety: Quantitative Risk Analysis of Human-AI Collaboration

Digital technologies have dramatically accelerated the digital transformation in process industries, boosted new industrial applications, upgraded the production system, and enhanced operational efficiency. In contrast, the challenges and gaps between human and artificial intelligence (AI) have become more and more prominent, whereas the digital divide in process safety is aggregating. The study attempts to address the following questions: (i)What is AI in the process safety context? (ii)What is the difference between AI and humans in process safety? (iii)How do AI and humans collaborate in process safety? (iv)What are the challenges and gaps in human-AI collaboration? (v)How to quantify the risk of human-AI collaboration in process safety? Qualitative risk analysis based on brainstorming and literature review, and quantitative risk analysis based on layer of protection analysis (LOPA) and Bayesian network (BN), were applied to explore and model. The importance of human reliability should be stressed in the digital age, not usually to increase the reliability of AI, and human-centered AI design in process safety needs to be propagated

Perspective chapter: Internet of Things in Healthcare - New Trends, Challenges and Hurdles

Applied to health field, Internet of Things (IoT) systems provides continuous and ubiquitous monitoring and assistance, allowing the creation of valuable tools for diagnosis, health empowerment, and personalized treatment, among others. Advances in these systems follow different approaches, such as the integration of new protocols and standards, combination with artificial intelligence algorithms, application of big data processing methodologies, among others. These new systems and applications also should face different challenges when applying this kind of technology into health areas, such as the management of personal data sensed, integration with electronic health records, make sensing devices comfortable to wear, and achieve an accurate acquisition of the sensed data. The objective of this chapter is to present the state of the art, indicating the most current IoT trends applied to the health field, their contributions, technologies applied, and challenges faced

Applications of AI and ML in Construction Industry

Artificial Intelligence is opening up new avenues in the construction industry. Machine learning is an emerging AI research paradigm, and it is important to making buildings smart. Machine learning technologies have the potential to offer up a plethora of new opportunities in the construction industry, such as site surveillance, automated detection, and intelligent maintenance. The purpose of this study was to examine the new areas where AI and ML are being employed in the construction sector and how their implementation would aid in the improvement of work sites. However, due to the difficulties in collecting annotated data, ML applications face a variety of challenges, especially when applied in a highly complicated building project. This study also looks at how machine learning grew from shallow to deep learning and how it is used in the construction industry. Following the completion of this study, it was determined conclusively that the use of AI and ML in construction projects improves work safety, increases productivity, and so on, and its implications are presently being employed to conduct research around the world