Crisis response poses many of the most difficult information technology in crisis management. It requires information and communication-intensive efforts, utilized for reducing uncertainty, calculating and comparing costs and benefits, and managing resources in a fashion beyond those regularly available to handle routine problems. In this paper, we explore the benefits of artificial intelligence technologies in crisis response. This paper discusses the role of artificial intelligence technologies; namely, robotics, ontology and semantic web, and multi-agent systems in crisis response.
Artificial Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges
South China University of Technology（华南理工大学）；Zhongkai University of Agriculture and Engineering（仲恺农业工程学院）；Macau University of Science and Technology（澳门科技大学）；The University of Iowa（爱荷华大学）；Loughborough University（拉夫堡大学）
RMIT University（皇家墨尔本理工大学）；Swinburne University of Technology（斯威本科技大学）
With the breakthroughs in Deep Learning, recent years have witnessed a massive surge in Artificial Intelligence applications and services. Meanwhile, the rapid advances in Mobile Computing and Internet of Things has also given rise to billions of mobile and smart sensing devices connected to the Internet, generating zettabytes of data at the network edge. The opportunity to combine these two domains of technologies to power interconnected devices with intelligence is likely to pave the way for a new wave of technology revolutions. Embracing this technology revolution, in this article, we prese…
In this paper we present a new form of access to knowledge through what we call "hypermediator websites". These hypermediator sites are intermediate between information devices that just scan the book culture and a "real" hypertext writing format.
Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of evolving threats, data deluge, and rapid courses of action. Developing an end-to-end artificial intelligence system involves parallel development of different pieces that must work together in order to provide capabilities that can be used by decision makers, warfighters and analysts. These pieces include data collection, data conditioning, algorithms, computing, robust artificial intelligence, and human-machine teamin…
MOSCOW HEALTH CARE DEPARTMENT RESEARCH AND PRACTICAL CLINICAL CENTER FOR DIAGNOSTICS AND TELEMEDICINE TECHNOLOGIES（莫斯科卫生部诊断与远程医疗技术研究与实践临床中心）；MOSCOW HEALTH CARE DEPARTMENT BEST PRACTICES IN MEDICAL IMAGING（莫斯科卫生部医学影像最佳实践中心）
Aim: provide a methodological framework for the process of clinical tests, clinical acceptance, and scientific assessment of algorithms and software based on the artificial intelligence (AI) technologies. Clinical tests are considered as a preparation stage for the software registration as a medical product. The authors propose approaches to evaluate accuracy and efficiency of the AI algorithms for radiology.
Institute of AI and Robotics, Hefei University of Technology（合肥工业大学人工智能与机器人研究所）
One of the ambitions of artificial intelligence is to root artificial intelligence deeply in basic science while developing brain-inspired artificial intelligence platforms that will promote new scientific discoveries. The challenges are essential to push artificial intelligence theory and applied technologies research forward. This paper presents the grand challenges of artificial intelligence research for the next 20 years which include:~(i) to explore the working mechanism of the human brain on the basis of understanding brain science, neuroscience, cognitive science, psychology and data sc…
University of New South Wales（新南威尔士大学）；BeU Research Group（BeU研究组）；University of Glasgow（格拉斯哥大学）
With the rapid adoption of Internet technologies, digital footprints have become ubiquitous and versatile to revolutionise the financial industry in digital transformation. This paper takes initiatives to investigate a new paradigm of the unified credit assessment with the use of federated artificial intelligence. We conceptualised digital human representation which consists of social, contextual, financial and technological dimensions to assess the commercial creditworthiness and social reputation of both banked and unbanked individuals. A federated artificial intelligence platform is propose…
Artificial intelligence offers superior techniques and methods by which problems from diverse domains may find an optimal solution. The Machine Learning technologies refer to the domain of artificial intelligence aiming to develop the techniques allowing the computers to "learn". Some systems based on Machine Learning technologies tend to eliminate the necessity of the human intelligence while the others adopt a man-machine collaborative approach.
Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future has a dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers will need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustained by the biggest knowledge theft of the recent years. Learning AI machines are extracting knowledge f…
Brief for the Canada House of Commons Study on the Implications of Artificial Intelligence Technologies for the Canadian Labor Force: Generative Artificial Intelligence Shatters Models of AI and Labor
University of Pittsburgh（匹兹堡大学）；Stanford University（斯坦福大学）；Massachusetts Institute of Technology（麻省理工学院）
The COVID-19 crisis has brought about new clinical questions, new workflows, and accelerated distributed healthcare needs. While artificial intelligence (AI)-based clinical decision support seemed to have matured, the application of AI-based tools for COVID-19 has been limited to date. In this perspective piece, we identify opportunities and requirements for AI-based clinical decision support systems and highlight challenges that impact "AI readiness" for rapidly emergent healthcare challenges.
With there being many technical and ethical issues with artificial intelligence (AI) that involve marginalized communities, there is a growing interest for design methods used with marginalized people that may be transferable to the design of AI technologies. Participatory design (PD) is a design method that is often used with marginalized communities for the design of social development, policy, IT and other matters and solutions. However, there are issues with the current PD, raising concerns when it is applied to the design of technologies, including AI technologies. This paper argues for t…
Max Planck Institute for the Science of Light（马克斯·普朗克光科学研究所）；Friedrich-Alexander Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）
In recent years, the dramatic progress in machine learning has begun to impact many areas of science and technology significantly. In the present perspective article, we explore how quantum technologies are benefiting from this revolution. We showcase in illustrative examples how scientists in the past few years have started to use machine learning and more broadly methods of artificial intelligence to analyze quantum measurements, estimate the parameters of quantum devices, discover new quantum experimental setups, protocols, and feedback strategies, and generally improve aspects of quantum c…
Many application domains require representing interrelated real-world activities and/or evolving physical phenomena. In the crisis response domain, for instance, one may be interested in representing the state of the unfolding crisis (e.g., forest fire), the progress of the response activities such as evacuation and traffic control, and the state of the crisis site(s). Such a situation representation can then be used to support a multitude of applications including situation monitoring, analysis, and planning. In this paper, we make a case for an event based representation of situations where …
The General Data Protection Regulation (GDPR) is a European Union regulation that will replace the existing Data Protection Directive on 25 May 2018. The most significant change is a huge increase in the maximum fine that can be levied for breaches of the regulation. Yet fewer than half of UK companies are fully aware of GDPR - and a number of those who were preparing for it stopped doing so when the Brexit vote was announced. A last-minute rush to become compliant is therefore expected, and numerous companies are starting to offer advice, checklists and consultancy on how to comply with GDPR.…
The pervasive application of artificial intelligence and machine learning algorithms is transforming many industries and aspects of the human experience. One very important industry trend is the move to convert existing human dwellings to smart buildings, and to create new smart buildings. Smart buildings aim to mitigate climate change by reducing energy consumption and associated carbon emissions. To accomplish this, they leverage artificial intelligence, big data, and machine learning algorithms to learn and optimize system performance. These fields of research are currently very rapidly evo…
Enhancing Artificial intelligence Policies with Fusion and Forecasting: Insights from Indian Patents Using Network Analysis
CSIR-National Institute of Science Communication and Policy Research（CSIR国家科学传播与政策研究所）；Centre for Studies in Science Policy, School of Social Sciences, Jawaharlal Nehru University（贾瓦哈拉尔·尼赫鲁大学社会科学学院科学政策研究中心）
An ontology for cross-sectoral crisis management: core and public health modules
University of Bologna（博洛尼亚大学）；San Raffaele University of Rome（罗马圣拉斐尔大学）；University of Mannheim（曼海姆大学）；Institute for Cognitive Sciences and Technology, Italian National Research Council（意大利国家研究委员会认知科学与技术研究所）；European Commission（欧盟委员会）
Artificial intelligence (AI) systems attempt to imitate human behavior. How well they do this imitation is often used to assess their utility and to attribute human-like (or artificial) intelligence to them. However, most work on AI refers to and relies on human intelligence without accounting for the fact that human behavior is inherently shaped by the cultural contexts they are embedded in, the values and beliefs they hold, and the social practices they follow. Additionally, since AI technologies are mostly conceived and developed in just a handful of countries, they embed the cultural value…
University of Maryland, Baltimore County（马里兰大学巴尔的摩县分校）
Due to the advancement in technologies, the next-generation wireless network will be very diverse, complicated, and according to the changed demands of the consumers. The current network operator methodologies and approaches are traditional and cannot help the next generation networks to utilize their resources most appropriately. The limited capability of the traditional tools will not allow the network providers to fulfill the demands of the network's subscribers in the future. Therefore, this paper will focus on machine learning, automation, artificial intelligence, and big data analytics f…
Concordia University（康考迪亚大学）；National Research Council Canada（加拿大国家研究委员会）
Early identification of emergent topics is of eminent importance due to their potential impacts on society. There are many methods for detecting emerging terms and topics, all with advantages and drawbacks. However, there is no consensus about the attributes and indicators of emergence. In this study, we evaluate emerging topic detection in the field of artificial intelligence using a new method to evaluate emergence. We also introduce two new attributes of collaboration and technological impact which can help us use both paper and patent information simultaneously. Our results confirm that th…
NTNU（挪威科技大学）；SimulaMet（SimulaMet 研究所）；University of Bergen（卑尔根大学）；Berlin Institute of Health (BIH)（柏林健康研究所）；Charité Universitätsmedizin Berlin（柏林夏里特医学院）；Birmingham City University（伯明翰城市大学）
While the demand for ethical artificial intelligence (AI) systems increases, the number of unethical uses of AI accelerates, even though there is no shortage of ethical guidelines. We argue that a possible underlying cause for this is that AI developers face a social dilemma in AI development ethics, preventing the widespread adaptation of ethical best practices. We define the social dilemma for AI development and describe why the current crisis in AI development ethics cannot be solved without relieving AI developers of their social dilemma. We argue that AI development must be professionalis…
AI Horizon Scanning -- White Paper p3395, IEEE-SA. Part III: Technology Watch: a selection of key developments, emerging technologies, and industry trends in Artificial Intelligence
Athena Research Centre（雅典娜研究中心）；Institute for Astrophysics and Space Sciences, University of Lisbon（里斯本大学天体物理与空间科学研究所）
As the demand for mobility in our society seems to increase, the various issues centered on urban mobility are among those that worry most city inhabitants in this planet. For instance, how to go from A to B in an efficient (but also less stressful) way? These questions and concerns have not changed even during the covid-19 pandemic; on the contrary, as the current stand, people who are avoiding public transportation are only contributing to an increase in the vehicular traffic. The are of intelligent transportation systems (ITS) aims at investigating how to employ information and communicatio…
University of Tasmania, Australia（塔斯马尼亚大学）；Macquarie University, Australia（麦考瑞大学）；University of Electronic Science and Technology of China, China（电子科技大学）；Huazhong University of Science and Technology, China（华中科技大学）；University of California, San Diego, USA（加利福尼亚大学圣地亚哥分校）；University of Technology Sydney, Australia（悉尼科技大学）
Brain-Computer Interface (BCI) is a powerful communication tool between users and systems, which enhances the capability of the human brain in communicating and interacting with the environment directly. Advances in neuroscience and computer science in the past decades have led to exciting developments in BCI, thereby making BCI a top interdisciplinary research area in computational neuroscience and intelligence. Recent technological advances such as wearable sensing devices, real-time data streaming, machine learning, and deep learning approaches have increased interest in electroencephalogra…
Ericsson AB（爱立信公司）；Ericsson Telecomunicações S/A（爱立信电信公司）；Mälardalen University（梅拉达伦大学）
The recent development of artificial intelligence (AI) has increased the interest of researchers and practitioners towards applying its techniques into multiple domains like automotive, health care and air space to achieve automation. Combined to these applications, the attempt to use AI techniques into carrying out safety issues is momentarily at a progressive state. As AI problems are getting even more complex, large processing power is demanded for safety-critical systems to fulfill real-time requirements. These challenges can be solved through edge or cloud computing, which makes the commu…
Systematic Review of Cybersecurity in Banking: Evolution from Pre-Industry 4.0 to Post-Industry 4.0 in Artificial Intelligence, Blockchain, Policies and Practice
Vienna University of Economics and Business（维也纳经济大学）；University of Vienna（维也纳大学）；George Washington University（乔治华盛顿大学）
Throughout their history, homo sapiens have used technologies to better satisfy their needs. The relation between needs and technology is so fundamental that the US National Research Council defined the distinguishing characteristic of technology as its goal "to make modifications in the world to meet human needs". Artificial intelligence (AI) is one of the most promising emerging technologies of our time. Similar to other technologies, AI is expected "to meet [human] needs". In this article, we reflect on the relationship between needs and AI, and call for the realisation of needs-aware AI sy…
Intelligence of Astronomical Optical Telescope: Present Status and Future Perspectives
Nanjing Institute of Astronomical Optics & Technology, Chinese Academy of Sciences（中国科学院南京天文光学技术研究所）；CAS Key Laboratory of Astronomical Optics & Technology（中国科学院天文光学技术重点实验室）；University of Chinese Academy of Sciences（中国科学院大学）
In this chapter, we give an introduction to symbolic artificial intelligence (AI) and discuss its relation and application to multimedia. We begin by defining what symbolic AI is, what distinguishes it from non-symbolic approaches, such as machine learning, and how it can used in the construction of advanced multimedia applications. We then introduce description logic (DL) and use it to discuss symbolic representation and reasoning. DL is the logical underpinning of OWL, the most successful family of ontology languages. After discussing DL, we present OWL and related Semantic Web technologies,…
Data science and machine learning are the key technologies when it comes to the processes and products with automatic learning and optimization to be used in the automotive industry of the future. This article defines the terms "data science" (also referred to as "data analytics") and "machine learning" and how they are related. In addition, it defines the term "optimizing analytics" and illustrates the role of automatic optimization as a key technology in combination with data analytics. It also uses examples to explain the way that these technologies are currently being used in the automotiv…
Content marketing is todays one of the most remarkable approaches in the context of marketing processes of companies. Value of this kind of marketing has improved in time, thanks to the latest developments regarding to computer and communication technologies. Nowadays, especially social media based platforms have a great importance on enabling companies to design multimedia oriented, interactive content. But on the other hand, there is still something more to do for improved content marketing approaches. In this context, objective of this study is to focus on intelligent content marketing, whi…
This literature review identifies indicators that associate with higher impact or higher quality research from article text (e.g., titles, abstracts, lengths, cited references and readability) or metadata (e.g., the number of authors, international or domestic collaborations, journal impact factors and authors' h-index). This includes studies that used machine learning techniques to predict citation counts or quality scores for journal articles or conference papers. The literature review also includes evidence about the strength of association between bibliometric indicators and quality score …
Microarray is one of the essential technologies used by the biologist to measure genome-wide expression levels of genes in a particular organism under some particular conditions or stimuli. As microarrays technologies have become more prevalent, the challenges of analyzing these data for getting better insight about biological processes have essentially increased. Due to availability of artificial intelligence based sophisticated computational techniques, such as artificial neural networks, fuzzy logic, genetic algorithms, and many other nature-inspired algorithms, it is possible to analyse mi…
University of Oxford（牛津大学）；KPMG Huazhen LLP Shanghai Branch（毕马威华振会计师事务所上海分所）；Cardiff University（卡迪夫大学）；University of Northumbria（诺森比亚大学）；Durham University（杜伦大学）
Governments' net zero emission target aims at increasing the share of renewable energy sources as well as influencing the behaviours of consumers to support the cost-effective balancing of energy supply and demand. These will be achieved by the advanced information and control infrastructures of smart grids which allow the interoperability among various stakeholders. Under this circumstance, increasing number of consumers produce, store, and consume energy, giving them a new role of prosumers. The integration of prosumers and accommodation of incurred bidirectional flows of energy and informat…
Stanford University（斯坦福大学）；Indian Institute of Science（印度科学研究院）
Despite the Digital Twin (DT) concept being in the industry for a long time, it remains ambiguous, unable to differentiate itself from information models, general computing, and simulation technologies. Part of this confusion stems from previous studies overlooking the DT's bidirectional nature, that enables the shift of agency (delegating control) from humans to physical elements, something that was not possible with earlier technologies. Thus, we present DTs in a new light by viewing them as a means of imparting intelligence and agency to entities, emphasizing that DTs are not just expert-ce…
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively abou…
University of Pennsylvania（宾夕法尼亚大学）；Center for a New American Security（新美国安全中心）
The potential for advances in information-age technologies to undermine nuclear deterrence and influence the potential for nuclear escalation represents a critical question for international politics. One challenge is that uncertainty about the trajectory of technologies such as autonomous systems and artificial intelligence (AI) makes assessments difficult. This paper evaluates the relative impact of autonomous systems and artificial intelligence in three areas: nuclear command and control, nuclear delivery platforms and vehicles, and conventional applications of autonomous systems with conse…
Institute for Theoretical Physics, University of Innsbruck（因斯布鲁克大学理论物理研究所）；Max Planck Institute of Quantum Optics（马克斯·普朗克量子光学研究所）；Department of Philosophy, University of Konstanz（康斯坦茨大学哲学系）
Quantum information technologies, and intelligent learning systems, are both emergent technologies that will likely have a transforming impact on our society. The respective underlying fields of research -- quantum information (QI) versus machine learning (ML) and artificial intelligence (AI) -- have their own specific challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question to what extent these fields can learn and benefit from each other. QML explores the interaction between quantum computin…
Jozef Stefan Institute（约瑟夫·斯特凡研究所）；Jozef Stefan Institute Postgraduate School（约瑟夫·斯特凡研究所研究生院）；Comsensus（Comsensus公司）；National Technical University of Athens（雅典国立技术大学）
Artificial Intelligence (AI) technologies are moving from customized deployments in specific domains towards generic solutions horizontally permeating vertical domains and industries. For instance, decisions on when to perform maintenance of roads or bridges or how to optimize public lighting in view of costs and safety in smart cities are increasingly informed by AI models. While various commercial solutions offer user friendly and easy to use AI as a Service (AIaaS), functionality-wise enabling the democratization of such ecosystems, open-source equivalent ecosystems are lagging behind. In t…
Teesside University（提赛德大学）；Universidade Nova de Lisboa（里斯本新大学）；Universidade de Lisboa（里斯本大学）；Université Libre de Bruxelles（布鲁塞尔自由大学）；Vrije Universiteit Brussel（布鲁塞尔自由大学）；UC Berkeley（加州大学伯克利分校）；Université Libre de Bruxelles-Vrije Universiteit Brussel（布鲁塞尔自由大学-布鲁塞尔自由大学）
Regulation of advanced technologies such as Artificial Intelligence (AI) has become increasingly important, given the associated risks and apparent ethical issues. With the great benefits promised from being able to first supply such technologies, safety precautions and societal consequences might be ignored or shortchanged in exchange for speeding up the development, therefore engendering a racing narrative among the developers. Starting from a game-theoretical model describing an idealised technology race in a fully connected world of players, here we investigate how different interaction st…
Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；Institute for Applied Informatics and Formal Description Methods（应用信息学与形式化描述方法研究所）
Developments in Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans. DLT has the potential to create consensus over data among a group of participants in uncertain environments. In recent research, both technologies are used in similar and even the same systems. Examples include the design of secure distributed ledgers or the creation of allied learning systems distributed across multiple nodes. This can lead to technological conve…
Existing research highlight the myriad of benefits realized when technology is sufficiently democratized and made accessible to non-technical or novice users. However, democratizing complex technologies such as artificial intelligence (AI) remains hard. In this work, we draw on theoretical underpinnings from the democratization of innovation, in exploring the design of maker kits that help introduce novice users to complex technologies. We report on our work designing TJBot: an open source cardboard robot that can be programmed using pre-built AI services. We highlight principles we adopted in…
