Responsible AI usage for academic integrity in China

Technology based on artificial intelligence (AI) is a revolutionary force that is changing economies, civilizations, and industries all over the world. AI, which has its roots in computer science and cognitive psychology, is a wide range of tools and methods designed to make robots capable of doing activities that have historically required human intellect. This abstract examines the many facets of artificial intelligence (AI) technology, including its fundamentals, uses, difficulties, and ramifications. Artificial Intelligence (AI) technology comprises several subfields such as robotics, computer vision, natural language processing, machine learning, and expert systems. Particularly, machine learning techniques have propelled incredible progress by allowing computers to learn from data and make judgments or predictions without the need for explicit programming. Natural language processing allows machines to comprehend, interpret, and produce human language, hence facilitating human-computer interaction. Machines can now see, analyze, and interpret visual data from the real world thanks to computer vision technology. Applications of AI technology may be found in a wide range of industries, including manufacturing, healthcare, finance, transportation, agriculture, education, and entertainment. AI-powered solutions help in drug discovery, medical imaging analysis, diagnosis, and customized therapy in the healthcare industry. AI algorithms are used in finance to power automated trading, fraud detection, risk assessment, and customer support. AI makes it possible for transportation to include predictive maintenance, traffic management, and driverless cars. Artificial Intelligence enhances supply chain management, quality assurance, and production processes in manufacturing. AI technology has the potential to revolutionize many industries, but it also comes with dangers and problems. These include privacy concerns, security hazards, ethical dilemmas, issues with prejudice and fairness, and effects on society and employment. Responsible AI methods, legal frameworks, multidisciplinary cooperation, and ethical standards are all necessary to meet these issues. Future prospects for AI technology development include the ability to solve challenging issues, spur creativity, increase productivity, and improve quality of life. But to fully utilize AI, one must take a comprehensive strategy that strikes a balance between the advancement of technology and ethical issues, human values, and social well-being. In summary, artificial intelligence (AI) technology is at the vanguard of innovation, presenting never-before-seen possibilities to transform whole sectors, spur economic expansion, and tackle global issues. AI has the ability to usher in a future of greater human-machine collaboration, innovation, and wealth through the promotion of collaboration, transparency, and ethical stewardship. the Ranking of the Artificial Intelligence using the TOPSIS Method . Interpretable Models is got the first rank whereas is the Ethical AI is having the Lowest rank. Keywords: Explainable AI (XAI), Interpretable Models, Ethical AI ,Responsible AI, Robustness and Adversarial Defense, Continual Learning, Federated Learning, Human-Centric AI, AI Governance and Policy

Masters or Slaves? AI and the Future of Humanity

We are glad to introduce you that the 2021 3rd International Conference on Artificial Intelligence Technologies and Applications (ICAITA 2021) was successfully held on September 10-12, 2021. In light of worldwide travel restriction and the impact of COVID-19, ICAITA 2021 was carried out in the form of virtual conference to avoid personnel gatherings. Because most participants were still highly enthusiastic about participating in this conference, we chose to carry out ICAITA 2021 via online platform according to the original schedule instead of postponing it.ICAITA 2021 is to bring together innovative academics and industrial experts in the field of Artificial Intelligence Technologies and Applications to a common forum. The primary goal of the conference is to promote research and developmental activities in Artificial Intelligence Technologies and Applications and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Artificial Intelligence Technologies and Applications and related areas.This scientific event brings together more than 100 national and international researchers in artificial intelligence technologies and applications. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches.We were pleased to invite three distinguished experts to present their insightful speeches. Our first keynote speaker, Prof. Yau Kok Lim, from Sunway University, Malaysia. His research interests include Applied artificial intelligence, 5G networks, Cognitiveradio networks, Routing and clustering, Trust and reputation, Intelligent transportation system. And then we had Prof. Peter Sincak, from Technical University of Kosice, Slovakia. His research includes Artificial Intelligence and Intelligent Systems. Lastly, we were glad to invite Chinthaka Premachandra, from Shibaura Institute of Technology, Sri Lanka. His research interests include Artificial Intelligence, image processing and robotics. In the last part of the conference, all participants were invited to join in a WeChat group to discuss and explore the academic issues after the presentations. The online discussion was lasted for about 30-60 minutes. The first two parts were conducted via online collaboration tool, Zoom, while the online discussion was carried out through instant communication tool, WeChat. The online platform enabled all participants to join this grand academic event from their own home.We are glad to share with you that we still received lots of submissions from the conference during this special period. Hence, we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewed them. These papers feature following topics but are not limited to: Artificial Intelligence Applications & Technologies, Computing and the Mind, Foundations of Artificial Intelligence and other related topics. All the papers have been through rigorous review and process to meet the requirements of international publication standard.Lastly, we would like to express our sincere gratitude to the Chairman, the distinguished keynote speakers, as well as all the participants. We also want to thank the publisher for publishing the proceedings. May the readers could enjoy the gain some valuable knowledge from the proceedings. We are expecting more and more experts and scholars from all over the world to join this international event next year.The Committee of ICAITA 2021List of titles Committee member, General Conference Chair, Technical Program Committee Chair, Academic Committee Chair, Technical Program Committee Member, Academic Committee Member are available in this Pdf.

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

BACKGROUND: The medical market offers interesting solutions that use artificial intelligence (AI) technologies; however, such solutions often remain at the startup level or are used locally. The question is how to achieve the maximum when introducing AI systems into medical practice. AIM: To answer the question of why the large number of existing developments in AI and medical decision support systems are not used as widely as medical information systems, telemedical consultations, and other health IT solutions. Possible ways to improve the efficiency of implementing AI technologies and medical decision support systems in the work of physicians were presented. METHODS: Theoretical and general scientific (analysis of literature and Internet sources on the problem of research, synthesis, generalization, comparison, and systematization) and empirical (observation, interview, and testing) methods were used. RESUTLS: The main barriers to the effective implementation of AI systems in medical practice and possible options to solve the following problems were highlighted. Problem 1: incorrect data collection. Solution: care must be taken with the accumulation of materials used for the analysis and training by AI systems in medicine. Problem 2: incompetent developers. Solutions: involvement of effective third-party specialists or training ones own. Problem 3: medical workers and/or patients aversion to AI technologies. Solutions: education in the successful application of AI technologies and medical decision support systems in healthcare and involvement of practicing physicians as experts during the AI conceptualization. CONCLUSIONS: If the above criteria for the development and use of AI technologies and medical decision support systems are met, the effect of their introduction into medical practice will tend to be maximized.

Artificial Intelligence and Corporate Social Responsibility: Employees’ Key Role in Driving Responsible Artificial Intelligence at Big Tech

This chapter explores the concept of responsibility in artificial intelligence (AI). Being fundamentally tools, AI systems are fully under the control and responsibility of their owners or users. However, their potential autonomy and capability to learn require that design considers accountability, responsibility, and transparency principles in an explicit and systematic manner. The main concern of Responsible AI is thus the identification of the relative responsibility of all actors involved in the design, development, deployment, and use of AI systems. Firstly, society must be prepared to take responsibility for AI impact. Secondly, Responsible AI implies the need for mechanisms that enable AI systems to act according to ethics and human values. Lastly, Responsible AI is about participation. It is necessary to understand how different people work with and live with AI technologies across cultures in order to develop frameworks for responsible AI.

Performance of an artificial intelligence tool with real-time clinical workflow integration - Detection of intracranial hemorrhage and pulmonary embolism.

The article is devoted to the study of the application of artificial intelligence technologies in law enforcement activities in Ukraine and the world. The purpose of the article is to analyze the international and domestic experience of using digital technologies in law enforcement activities, to identify the shortcomings of the legal regulation of the use of artificial intelligence in this area, to provide proposals for its improvement in Ukraine. It was found that one of the countries that is actively expanding the use of artificial intelligence and successfully introducing relevant technologies into public administration is China. The artificial intelligence system which is used in China called «Zero Trust». The purpose of using this system is to prevent the commission of corruption offenses. It is emphasized, that the disadvantage of the «Zero Trust» system is that artificial intelligence, identifying the cause of corruption, does not indicate the algorithms and principles of this process. At the same time, the experience of using artificial intelligence in the field of preventing and combating corruption in Ukraine is considered when carrying out automated verification of persons declarations of authorized to perform state and local government functions. Ways of improving legal regulation when conducting financial control of declarations using artificial intelligence technologies are proposed. It has been found that artificial intelligence is widely used in the USA to predict the prevalence and state of crime. It was emphasized that Ukraine also has experience in the application of artificial intelligence technologies in law enforcement activities. Artificial intelligence is used in the development and implementation of departmental specialized intelligent software, the implementation of operative and investigative actions (for the recognition of video objects observation by comparing images in social networks, etc). It was concluded that artificial intelligence and digital technologies help to quickly process large volumes of information in the investigation and prevention of criminal activity. Modern developments in the field of artificial intelligence and advanced digital technologies, which are implemented in foreign countries to prevent and fight crime, are of great importance for the improvement of legal regulation in this field in Ukraine.

Purpose The purpose of this paper is to introduce the artificial intelligence (AI) Citizenship Framework, a model that equips teachers and school library professionals with the tools to develop AI literacy and citizenship in students. As AI becomes increasingly prevalent, it is essential to prepare students for an AI-driven future. The framework aims to foster foundational knowledge of AI, critical thinking and ethical decision-making, empowering students to engage responsibly with AI technologies. By providing a structured approach to AI literacy, the framework helps educators integrate AI concepts into their lessons, ensuring students develop the skills needed to navigate and contribute to an AI-driven society. Design/methodology/approach This paper presents a theoretical framework, developed from the author’s experience as an information and digital literacy coach and teacher librarian across Asia, the Middle East and Europe. The AI Citizenship Framework was created without following specific empirical methodologies, drawing instead on practical insights and educational needs observed in diverse contexts. It outlines a scope and sequence for integrating AI literacy into school curricula. The framework’s components build on existing pedagogical practices while emphasising critical, ethical and responsible AI engagement. By providing a structure for AI education, it serves as a practical resource for school librarians and educators. Findings While no empirical data was collected for this theoretical paper, the AI Citizenship Framework offers a structured approach for school librarians and educators to introduce and develop AI literacy. It has the potential to influence AI education by fostering critical and ethical awareness among students, empowering them to participate responsibly in an AI-driven world. The framework’s practical application can be expanded beyond school librarians to include classroom teachers, offering a comprehensive model adaptable to various educational settings. Its real-world implementation could enhance students’ readiness to engage with AI technologies, providing long-term benefits for both educational institutions and the broader society. Research limitations/implications One limitation of the AI Citizenship Framework is that it has not yet been empirically validated. Future research could focus on testing its practical effectiveness in real-world settings, offering insights that may inform refinements and adaptations to better support school librarians and educators in fostering AI literacy and AI citizenship. Practical implications The practical implication of the AI Citizenship Framework is its application in educational settings to equip students with AI literacy and responsible citizenship skills. School library professionals and teachers can use the framework to integrate AI concepts into curricula, fostering critical thinking, ethical understanding and informed decision-making about AI technologies. The framework provides ready-to-use curriculum plans, enabling educators to prepare students for an AI-driven world. Its adaptability also allows classroom teachers to lead AI literacy initiatives, making it a versatile tool for embedding AI education across subjects and promoting responsible use and engagement with AI technologies in real-world contexts. Originality/value The originality and value of the AI Citizenship Framework lie in its approach to integrate AI literacy into educational contexts, specifically tailored for teacher librarians and school librarians. To the best of the authors’ knowledge, it is the first framework that comprehensively addresses the need for AI literacy from an ethical, critical and societal perspective, while also promoting active participation and leadership in AI governance. The framework equips educators with practical tools and curriculum plans, fostering responsible AI use and engagement. Its adaptable structure ensures it can be implemented by classroom teachers as well, adding significant value to AI education across disciplines and age groups.

Is the future of medical diagnosis in computer algorithms?

BackgroundAs artificial intelligence (AI) technology permeates health care settings, nurse leaders must position themselves to shape its development, implementation, and impact, guiding meaningful change that benefits nurses and care delivery. Nurse leaders possess the capacity to influence decisions, shape practice, and ensure the delivery of ethical, safe, and high-quality care. While AI technology is reshaping many aspects of health care delivery, there is limited knowledge on how nurse leaders perceive and experience this shift.ObjectiveThis scoping review aimed to explore the intersection of nursing leadership and AI technology in health care by mapping current evidence, identifying key concepts, and highlighting knowledge gaps within the literature.MethodsThis scoping review was guided by the Joanna Briggs Institute methodology and reported on using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. A systematic search of 4 electronic databases (CINAHL [EBSCO Information Services], Ovid MEDLINE [Wolters Kluwer], PsycINFO [American Psychological Association], and Scopus [Elsevier]) was conducted for English-language, peer-reviewed literature published between 2014 and 2025. Gray literature was also reviewed. Articles were included if they met the inclusion criteria by exploring the population of nurse leaders and the concept of AI technology within the context of health care settings and were published in English from May 2014 forward. A total of 26 articles were included in the analysis. Qualitative content analysis and numerical summary supported the inductive identification and synthesis of data categories.ResultsOf the 26 articles included, 8 were empirical (qualitative, quantitative, or mixed methods), and 18 were conceptual or theoretical articles. Although 1 article was Canadian, there were no empirical studies conducted by Canadian researchers. The qualitative content analysis of the primary search findings revealed 6 overarching data categories: (1) leading digital transformation and technology integration, (2) AI technology and the nursing role: reshaping practice, (3) ethical considerations of AI technology for nurse leaders, (4) AI technology as a facilitator of innovative leadership, (5) education and training on AI technology in nursing practice, and (6) influence of AI technology on the work environment.ConclusionsThis review confirms that nurse leaders play an essential role in shaping the future of health care in the context of AI technology. Although this review highlights a growing recognition of nursing leadership as a crucial driver of AI technology integration in health care, there is a lack of research to guide practice, policy, and leadership development through education, despite emerging interest and a recent increase in empirical work. The findings accentuate the need for increased investment in nurse-led research and leadership development to ensure that AI systems are designed, implemented, and evaluated in a manner that upholds ethical care, equity, and professional nursing values. As health care systems increasingly adopt AI technology, nurse leaders must be equipped with the knowledge, tools, and support required to lead transformative change and act as AI technology directors.

Artificial intelligence (AI) has quickly become a transformational force that is reshaping several sectors and changing how work is done. Automating jobs is a crucial component of AI's effect. As artificial intelligence (AI) technology develops, it has the potential to automate operations that are now done by people, creating both possibilities and difficulties for the employment market. AI's influence on job automation has many different facets. However, automation powered by AI has the potential to improve many industries' productivity, efficiency, and accuracy. AI systems may be used to do repetitive and boring activities, freeing up human employees to concentrate on more important, creative, and strategic duties. Increased work satisfaction and creativity may result from this. Automation fueled by artificial intelligence has already had a substantial impact on sectors including manufacturing, shipping, and customer service. However, there are also worries regarding the displacement of human labor as a result of job automation. Certain predictable and regular jobs may be carried out more effectively by robots as AI technology develops. This may lead to changes in work patterns as well as job losses. Manual labor-intensive jobs and routine data processing tasks are especially susceptible to automation. Discussions regarding the future of work and the need of retraining and upskilling the workforce to stay relevant in an AI-driven economy have been triggered by concerns about widespread unemployment. While AI may automate certain employment tasks, it also increases the need for human labor and opens up new possibilities. Intelligent experts that can design, develop, and maintain these technologies are needed for the integration of AI systems. Data scientists, machine learning engineers, and AI experts are in high demand right now. New businesses and employment categories will develop as AI technology advances, highlighting the need of lifelong learning and adaptation in the workforce. Additionally, AI-driven automation may improve the quality and security of employment. Robots may be used to do hazardous and physically taxing activities, lowering workplace injury risk and creating safer working conditions for people. AI may help employees make decisions by giving them insightful information and enhancing their talents. Increased productivity and job satisfaction may result from collaborative work settings where humans and AI systems play to one other's strengths. The difficulties must be addressed by legislators, educators, and corporations in order to minimize the possible negative effects of AI-driven job automation. Investments in education and programs for lifelong learning may provide people the tools they need to adapt to a changing labor market. Governments may aid employees impacted by automation by supporting reskilling programmes and offering social safety nets. To guarantee ethical AI deployment and reduce prejudice and discrimination, laws and regulations must also be in place. In summary, the influence of AI on job automation is profound and intricate. While technology presents chances for improved effectiveness, productivity, and creativity, it also presents problems in terms of job displacement. It's critical to strike a balance between the advantages of automation and the necessity to assist and retrain the workforce. Societies can use AI to their advantage by fostering collaboration between people and AI systems, investing in education and skill development, and enacting thoughtful policies. This will result in a future where people and machines coexist peacefully and a more prosperous and inclusive economy.

Artificial intelligence (AI) and blockchain technology (BCT) are considered two of the most trending and disruptive technologies. BCT, although commonly associated with cryptocurrencies, has shown a tremendous impact among many other distributed applications domains. BCT characteristics, such as the distribution of data storage among independent nodes and the use of consensus algorithms offer immutability and transparency and remove the need for a central authority making BCT trustworthy. However, decision-makers and stakeholders currently lack the confidence to overcome uncertainty related to AI technology, which affects the acceptance of AI technology in wider application domains, such as the recruitment process. Furthermore, current research literature does not adequately investigate the role of trust as an integral part of an AI-based recruitment application. Therefore, this paper aims to investigate how emerging BCT and AI technologies can improve decision making and stakeholder trust in a job recruitment system that is traditionally focused on just human expert decision-making. In this paper we propose the design of a new solution for trusting AI in recruitment applications through the use of Blockchain Smart Contracts (TAIRA-BSC). TAIRA-BSC integrates Blockchain Smart Contracts (BSC) with the Data Lake (DL), Machine Learning (ML) and AI technologies in our AI Recruitment Model (AIRM) architecture. TAIRA-BSC improves transparency and interoperability in the recruitment process while protecting sensitive job candidate data and ensures data integrity delivery and traceability in the recruiting process through a verifiable decentralized ledger, i.e., the blockchain and associated smart contracts. The paper presents a discussion on the state-of-the-art of integrating AI with BCT focusing on how BCT can be used to bridge trust concerns with AI systems. We also present a conceptual architecture TAIRA-BSC proof of concept that is developed to serve as a foundation for future studies focused on enhancing trust in AI applications through the integration of BCT.

SummaryThe recent sale of an artificial intelligence (AI)-generated portrait for $432,000 at Christie's art auction has raised questions about how credit and responsibility should be allocated to individuals involved and how the anthropomorphic perception of the AI system contributed to the artwork's success. Here, we identify natural heterogeneity in the extent to which different people perceive AI as anthropomorphic. We find that differences in the perception of AI anthropomorphicity are associated with different allocations of responsibility to the AI system and credit to different stakeholders involved in art production. We then show that perceptions of AI anthropomorphicity can be manipulated by changing the language used to talk about AI—as a tool versus agent—with consequences for artists and AI practitioners. Our findings shed light on what is at stake when we anthropomorphize AI systems and offer an empirical lens to reason about how to allocate credit and responsibility to human stakeholders.