Hybrid intelligence: understanding how AI reframes risk and uncertainty in dementia care

Is the future of medical diagnosis in computer algorithms?

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.

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.

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

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.

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

BackgroundBasic life support (BLS) skills are the core competencies of healthcare professionals in responding to emergency situations. Traditional manual assessments suffer from subjective bias, low efficiency, and are affected by examiner fatigue. Artificial intelligence (AI) technology brings innovative opportunities for skill assessment, but currently there is a lack of mature and validated BLS AI assessment systems.AimTo construct a basic life support practice skills evaluation system based on artificial intelligence technology, and verify its equivalence to manual evaluation. The purpose is to construct an evaluation system of basic life support practice skills based on artificial intelligence technology, verify its equivalence with manual evaluation, and analyse the advantages and development direction of artificial intelligence technology in the evaluation of basic life support practice skills.MethodsThe BLS practical skills evaluation system based on AI technology was developed based on RTMPose, ST-GCN, SVM, YOLOX and Whisper AI base models, and the BLS practical skills assessment environment was constructed, which contains audio and video capture systems, CPR simulators with distance sensors, and displays for human–computer interaction with candidates. Using a paired design, the BLS practical skills assessment was conducted in August 2024 among 85 new nurses of the class of 2024 at Ruijin Hospital of Shanghai Jiaotong University School of Medicine, where each candidate's BLS skills performance was assessed by both the examiner and the AI system. The differences between the examiner scores and the AI system scores were compared, and at the same time, the self-assessment results of the Visual Analogue Scale of Fatigue Severity (VAS-F) of the four examiners before and after the scores were collected, as well as the candidates' satisfaction and acceptance of the application of the system for the BLS practical skills assessment.ResultsThere was no significant difference between AI system scores and examiner scores (t = -0.294, p = 0.769), with good absolute agreement further confirmed by an intraclass correlation coefficient of 0.868 (95% CI: 0.803–0.912). Examiner VAS-F self-ratings were 73.50 ± 19.33 before and 82.25 ± 25.10 after the examination, respectively, and 51 (64.56%) of the candidates indicated that the AI system assessment helped to reduce their nervousness.ConclusionAI system marking is consistent with the results of examiner marking and can be used to evaluate BLS practical skills, and, the application of AI system can improve the effectiveness of the assessment organisation. Meanwhile, the candidates' acceptance of the AI system was good, and the application can be expanded after further optimisation of the system. Candidates showed good acceptance of the AI system; however, expansion of application should proceed only after further optimization of system stability to reduce failure rates below 5%.

Artificial intelligence to complement rather than replace radiologists in breast screening

The relevance of the topic of this research lies in the lack of legal papers on the questions of using computer technologies in judicial proceedings. As artificial intelligence (AI) systems continue to advance, there is a growing need to address their potential impact on judicial principles. Various countries try to implement AI technologies in judicial dispute resolution, these processes are progressing intensively, but there is still a significant gap in the existing legal literature on this topic. The subject of this paper is the impact of AI systems’ use in courts on judicial independence. The purpose of the study is to examine the implications of AI technologies on judicial independence and explore how adherence to specific criteria can help maintain the autonomy of the judiciary in the digital age. The topic of this research is highly novel due to the nonexistence of legal papers dedicated to the problem of this study. While many scholars are focused on judicial independence, considering it a crucial principle for the rule of law, there is a growing number of researchers analyzing the implementation of AI technologies in court. However, these scientific works primarily concentrate on the ways of possible using AI systems in courts and other general questions. However, there are only a few papers devoted to the analysis of legal risks associated with the use of AI systems in courts. This work is the first one that opens the door to further discussions on the assessment of judicial independence in AI-assisted proceedings. The research methods used in this paper are typical for legal studies. By analyzing the relationship between AI technologies and judicial independence, this research seeks to shed light on the potential challenges that arise from the integration of such computer systems into judicial systems. The current work addresses different approaches to defining key features of judicial independence and then proposes a list of specific criteria necessary to ensure judicial independence when utilizing AI systems. The key conclusions of this research contribute to the scholarly discussion on judicial independence criteria and provide two new specific criteria for AI-assisted proceedings. The author suggests that adhering to this list of specific criteria can provide independence for AI systems themselves and for judicial systems in general. By exploring the criteria for safeguarding judicial independence in the context of implementing AI technologies, this article aims to offer valuable insights and recommendations for policymakers and stakeholders.

Generating Rembrandt: Artificial Intelligence, Accountability and Copyright - The Human-Like Workers Are Already Here - A New Model

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.

Sustainable education is a crucial aspect of creating a sustainable future, yet it faces several key challenges, including inadequate infrastructure, limited resources, and a lack of awareness and engagement. Artificial intelligence (AI) has the potential to address these challenges and enhance sustainable education by improving access to quality education, creating personalized learning experiences, and supporting data-driven decision-making. One outcome of using AI and Information Technology (IT) systems in sustainable education is the ability to provide students with personalized learning experiences that cater to their unique learning styles and preferences. Additionally, AI systems can provide teachers with data-driven insights into student performance, emotions, and engagement levels, enabling them to tailor their teaching methods and approaches or provide assistance or intervention accordingly. However, the use of AI and IT systems in sustainable education also presents challenges, including issues related to privacy and data security, as well as potential biases in algorithms and machine learning models. Moreover, the deployment of these systems requires significant investments in technology and infrastructure, which can be a challenge for educators. In this review paper, we will provide different perspectives from educators and information technology solution architects to connect education and AI technology. The discussion areas include sustainable education concepts and challenges, technology coverage and outcomes, as well as future research directions. By addressing these challenges and pursuing further research, we can unlock the full potential of these technologies and support a more equitable and sustainable education system.

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.

The article defines the admissibility conditions for the practical use of conclusions (solutions) regarding artificial intelligence in law enforcement activities. A warning was expressed that depending on the circumstances of its specific application and use and the level of technological development, artificial intelligence may create risks and harm state or private interests and the fundamental rights of individuals. The admissibility of using artificial intelligence systems and conclusions (decisions) of artificial intelligence in law enforcement activities is established as a reason for conducting an additional check but not a basis for making a decisive decision by a law enforcement and law enforcement body. Attention is focused on the fact that artificial intelligence systems help law enforcement officers make decisions and not make decisions instead of law enforcement officers. Modern scientific views on using artificial intelligence systems in law enforcement activities are analyzed. The guiding provisions of the draft legislative resolution of the European Parliament on the proposal for the regulation of the European Parliament and the Council on the establishment of harmonized rules on artificial intelligence (Law on artificial intelligence) and separate legal acts of Ukraine in the field of development and use of artificial intelligence technologies are analyzed. It is concluded that there needs to be a proper scientific substantiation of the permissible limits (legal, ethical) of the use of conclusions (decisions) of artificial intelligence in law enforcement activities and the lack of specialists who can create and properly control artificial intelligence technologies. The expediency of developing the Code of Ethics for artificial intelligence with the participation of a wide range of interested parties, including law enforcement officers, is supported. It is noted that there is a need to bring the current legislation in the field of using artificial intelligence technologies into compliance with international legal acts and established standards, in particular regarding the admissibility (acceptability) of using the conclusions (decisions) of artificial intelligence in law enforcement activities and increasing the level of professional training of specialists to provide the field of artificial intelligence technologies with qualified staff capable of monitoring the process of applying artificial intelligence technologies in law enforcement activities. Keywords: artificial intelligence, artificial intelligence technologies, law enforcement activities, law enforcement agencies.