2021年度NSFC人工智能学科基金项目申请资助情况及学科发展展望

对2021年度国家自然科学基金委员会信息科学部二处人工智能（F06）代码下部分基金项目的申请与资助情况进行了统计和说明,统计和分析了F06代码下面上、青年科学基金和地区科学基金项目申请与资助依托单位分布情况、二级代码分布和项目科学属性分类评审试点情况,并对2021年度人工智能学科基金项目部分评审原则与举措进行了介绍。最后对人工智能学科进行了简单总结和展望。     

The role of information technology in achieving the organisation's strategic development goals: A case study

The role of IT in achieving the organisation's strategic development goals has been an area of constant debate. This paper describes the experiences of John Nicholls Builders Ltd, a Cornish building firm, in their attempt to achieve their strategic development goals through the adoption of IT. The implementation stage of the project involved setting a flexible programme and timescale from the start. The company adopted a bottom up approach whereby potential users were consulted and involved in the process. Also the support of top management staff was crucial for the successful transition to the new system. Although there was no single ready-made solution that could fit the organisations requirements, they were able to identify appropriate construction industry software packages and integrate them through development of an intranet and database system. Now, there is greater management control, all departments have greater access to information, enabling them to function more effectively and efficiently, and since projections are more accurate or now available, management can make long-term strategic plans. These improvements and developments to the business system have improved operational efficiency, turnover and profitability of the organisation.     

集对分析在人工智能中的应用与进展

人工智能是我国发展战略,集对分析从自主原创角度为人工智能提供一种基础性思路,具有重要意义。集对分析把确定的数学计算与不确定性系统分析有机结合,已在人工智能基础、模式识别、不确定性推理、智能决策、知识生态学、自然语言理解、专家系统、神经网络、智能工程、智能社会网络社区划分与演化等研究中得到应用。本文在概述集对分析的原理和联系数之后,综述集对分析在人工智能中的应用和进展,以期推动集对分析在人工智能中的进一步应用。     

Flang: A language for artificial intelligence

Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 50–67, September–October, 1993.     

The adoption of artificial intelligence and robotics in the hotel industry: prospects and challenges

Electronic Markets - The growth of technology has resulted in the use of state-of-the-art systems such as artificial intelligence (AI) and robot-based applications and services in the hotel...     

Applications and prospects of artificial intelligence in covert satellite communication: a review

Science China Information Sciences - Due to the privacy preserving capabilities and the low communication costs, federated learning has emerged as an efficient technique for distributed deep...     

智慧能源-----人工智能技术在电力系统中的应用与展望

在环境污染日趋严重,化石能源逐渐枯竭的背景下,能源系统的发展趋向于清洁化、智能化,我国已将智慧能源的发展提升为国家战略.电力系统作为能源系统的核心环节,应用广泛,具有较强的调节能力且控制复杂,其智能化程度将决定能源系统的智能化水平.伴随着分布式电源、电动汽车、分布式储能元件等具有能源生产、存储、消费多种特性的新型能源终端高比例接入电网,现代电力系统呈现出复杂非线性、强不确定性、强耦合性等特点,传统建模、优化、控制技术存在诸多局限性,人工智能技术将是解决复杂系统控制与决策问题的有效措施.鉴于此,首先梳理人工智能在电力系统应用的发展脉络;然后根据人工智能在电力系统的应用热点领域,阐述人工智能技术在电力系统调度、规划以及电力市场等方面的应用,并对各重点研究内容的未来方向进行展望.     

Racing to the precipice: a model of artificial intelligence development

This paper presents a simple model of an AI (artificial intelligence) arms race, where several development teams race to build the first AI. Under the assumption that the first AI will be very powerful and transformative, each team is incentivised to finish first—by skimping on safety precautions if need be. This paper presents the Nash equilibrium of this process, where each team takes the correct amount of safety precautions in the arms race. Having extra development teams and extra enmity between teams can increase the danger of an AI disaster, especially if risk-taking is more important than skill in developing the AI. Surprisingly, information also increases the risks: the more teams know about each others’ capabilities (and about their own), the more the danger increases. Should these results persist in more realistic models and analysis, it points the way to methods of increasing the chance of the safe development of AI.     

多媒体智能：当多媒体遇到人工智能

过去10年中涌现出大量新兴的多媒体应用和服务,带来了很多可以用于多媒体前沿研究的多媒体数据。多媒体研究在图像/视频内容分析、多媒体搜索和推荐、流媒体服务和多媒体内容分发等方向均取得了重要进展。与此同时,由于在深度学习领域所取得的重大突破,人工智能(artificial intelligence,AI)在20世纪50年代被正式视为一门学科之后,迎来了一次“新”的发展浪潮。因此,一个问题就自然而然地出现了：当多媒体遇到人工智能时会带来什么？为了回答这个问题,本文通过研究多媒体和人工智能之间的相互影响引入了多媒体智能的概念。从两个方面探讨多媒体与人工智能之间的相互影响：一是多媒体促使人工智能向着更具可解释性的方向发展;二是人工智能反过来为多媒体研究注入了新的思维方式。这两个方面形成了一个良性循环,多媒体和人工智能在其中不断促进彼此发展。本文对相关研究及进展进行了讨论,并围绕值得进一步探索的研究方向分享见解。希望可以对多媒体智能的未来发展带来新的研究思路。     

Rethinking positive and negative impacts of ‘ICT for development’ through the holistic lens of the sustainable development goals

ABSTRACT

The field of information and communication technologies for development (ICT4D) is driven by the conviction that ICTs can be used to improve peoples’ lives. Yet, it often faces criticism related to the negative effects that are associated with ICTs. Instead of viewing these as arguments against ICT4D, this article presents an integrated approach to incorporating them in our conceptualization of ICT4D impact. For this purpose, we envision a framework that is grounded in the interrelated set of Sustainable Development Goals, which make the complex interdependencies between different development goals explicit. By mapping the potentially harmful impact of ICTs within this network of goals, this framework provides a point of reference for holistically conceptualizing ICTs’ negative impact through the lens of policy coherence. Based on this framework, this article discusses, how to conceptualize ICT4D impact, taking into account the multidimensional implications for the environmental, economic and social dimensions of sustainable development.     

Consciousness,intentionality and intelligence: some foundational issues for artificial intelligence

Three fundamental questions concerning minds are presented. These are about consciousness, intentionality and intelligence. After we present the fundamental framework that has shaped both the philosophy of mind and the Artificial Intelligence research in the last forty years or so regarding the last two questions, we turn to consciousness, whose study still seems evasive to both communities. After briefly illustrating why and how phenomenal consciousness is puzzling, a theoretical diagnosis of the problem is proposed and a framework is presented, within which further research would yield a solution. The diagnosis is that the puzzle stems from a peculiar dual epistemic access to phenomenal aspects (qualia) of our conscious experiences. An account of concept formation is presented such that both the phenomenal concepts (like the concepts RED and SWEET) and the introspective concepts (like the concepts EXPERIENCING RED and TASTING SWEET) are acquired from a firstperson perspective as opposed to the third-person one (the standard concept formation strategy about objective features). We explain the first-person perspective in information-theoretic and computational terms: Nature (the Art whereby God hath made and governes the World) is by the Art of man, as in many other things, so in this also imitated, that it can make an Artificial Animal. For seeing life is but a motion of Limbs, the beginning whereof is in some principall part within; why may we not say, that all Automata (Engines that move themselves by springs and wheels as doth a watch) have an artificiall life? For what is the Heart, but a Spring; and the Nerves but so many Strings; and the Joynts, but so many Wheeles, giving motion to the whole Body, such as was intended by the Artificer? Art goes yet further, imitating that Rationall and most excellent worke of Nature, Man. (Hobbes 1651, p. 81) So declared Thomas Hobbes in 1651 in the Introduction to his well-known work, Leviathan, published one year after Réne Descartes' death. Descartes was also interested in mechanical explanations of bodily processes and organic life. In fact, on the basis of his neuroanatomical and physiological studies, as well as philosophical arguments, Descartes had already argued that human and animal bodies could be mechanically understood as complicated and intricately designed machines (Descartes 1664). What differentiated Descartes from Hobbes lay in his belief that human beings, unlike non-human animals, were not merely bodies; they were unions of material bodies and immaterial souls. The immaterial soul was necessary for Descartes to explain the peculiar capacities and activities of the human mind. As such, materialist mechanical explanations could never be sufficient to account for the whole human being.     

Artificial intelligence in manufacturing: Forecasts for the use of artificial intelligence in the USA

The use of artificial intelligence in manufacturing has finally emerged as a reality in the United States. Buoyed by the general growth of trained computer scientists, the lower cost hardware and software designed for easier use input, a number of experimental programs are under way to exploit artificial intelligence for manufacturing purposes.     

Sharing the solution: The need for generic artificial intelligence decision support development tools in battle management

The Navy conducted a multi-laboratory study to investigate ways in which machine-based technology can provide intelligent decision support to Navy battle management. A key result from this study is that a need exists to develop generic AI decision support development tools for battle management. This paper describes the major requirement areas identified in the study for building such tools.     

A hybrid intelligence approach for sustainable service innovation of smart and connected product: A case study

Nowadays, smart and connected product (SCP) is gradually replacing the traditional functional products, which has attracted widespread attention from the industry and academia. Service innovation, as a crucial part of SCP iterative improvement, is a multi-criteria decision-making (DM) process facilitated by intelligent automation (IA) and cognitive technologies. However, product user’s intelligence (e.g. physiological feeling) that can intuitively reflect and evaluate the product service satisfaction is rarely considered in the process of service innovation. Hence, it is difficult to measure the product users’ preferences with precise numerical terms to make a strategic decision. In order to fill this gap, a hybrid intelligence approach is proposed to perform the service innovation for SCP. The product-user data (e.g. subjective data and physiological data) and product-sensor data are collected and used for the process of service innovation. A smart group spinning bicycle system is presented as an elaborated case study to illustrate the proposed architecture and approach. The service innovation of real-time and dynamic monitoring, user participation improvement and smart feedback manners are achieved. In addition, an ergonomic experiment is conducted to validate the effectiveness of the proposed approach in implementing the service innovation for SCP.     

Hybrid artificial intelligence approach based on metaheuristic and machine learning for slope stability assessment: A multinational data analysis

Slope stability assessment is a critical research area in civil engineering. Disastrous consequences of slope collapse necessitate better tools for predicting their occurrences. This research proposes a hybrid Artificial Intelligence (AI) for slope stability assessment based on metaheuristic and machine learning. The contribution of this study to the body of knowledge is multifold. First, advantages of the Firefly Algorithm (FA) and the Least Squares Support Vector Classification (LS-SVC) are combined to establish an integrated slope prediction model. Second, an inner cross-validation with the operating characteristic curve computation is embedded in the training process to reliably construct the machine learning model. Third, the FA, an effective and easily implemented metaheuristic, is employed to optimize the model construction process by appropriately selecting the LS-SVM's hyper-parameters. Finally, a dataset that contains 168 real cases of slope evaluation, recorded in various countries, is used to establish and confirm the proposed hybrid approach. Experimental results demonstrate that the new hybrid AI model has achieved roughly 4% improvement in classification accuracy compared with other benchmark methods.     

Construction of cultural industry development factor model based on factor analysis,artificial intelligence and big data

The rapid development of the level of social informatization has allowed the content related to computer science to advance with the times and have derived two fields of big data and artificial intelligence. Specifically, the theory and methods of artificial intelligence themselves provide key support for big data. On the other hand, big data also provides auxiliary means for the research and analysis of artificial intelligence. Artificial intelligence will become the mainstream development trend of the future society, and the application of big data technology under the background of artificial intelligence will also be systematic in many fields. This paper analyzes the internal and external factors in the development of cultural industry by means of econometric research methods and big data and artificial intelligence, principal component analysis, factor analysis and multiple regression analysis, establishes the model of cultural industry development factors, breaks through the traditional research methods, analyzes the impact of the core, foundation, environment, kinetic energy, efficiency, potential and other factors on the comprehensive index of the development of cultural industry, and analyzes the comparative advantages and development trend of cultural industry in all provinces and municipalities of China. In this paper, the "three elements" model is comprehensively demonstrated by quantitative and qualitative methods, which solves the problem of lack of qualitative and quantitative research methods in cultural industry.     

Managing the risks of artificial general intelligence: A human factors and ergonomics perspective

Artificial General Intelligence (AGI) is the next and forthcoming evolution of Artificial Intelligence (AI). Though there could be significant benefits to society, there are also concerns that AGI could pose an existential threat. The critical role of Human Factors and Ergonomics (HFE) in the design of safe, ethical, and usable AGI has been emphasized; however, there is little evidence to suggest that HFE is currently influencing development programs. Further, given the broad spectrum of HFE application areas, it is not clear what activities are required to fulfill this role. This article presents the perspectives of 10 researchers working in AI safety on the potential risks associated with AGI, the HFE concepts that require consideration during AGI design, and the activities required for HFE to fulfill its critical role in what could be humanity's final invention. Though a diverse set of perspectives is presented, there is broad agreement that AGI potentially poses an existential threat, and that many HFE concepts should be considered during AGI design and operation. A range of critical activities are proposed, including collaboration with AGI developers, dissemination of HFE work in other relevant disciplines, the embedment of HFE throughout the AGI lifecycle, and the application of systems HFE methods to help identify and manage risks.     

Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives

Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI) tools and data fusion strategies has recently opened new perspectives for environmental monitoring and assessment. This is mainly due to the advancement of machine learning (ML) and data mining approaches, which facilitate extracting meaningful information at a large scale from geo-referenced and heterogeneous sources. This paper presents the first review of AI-based methodologies and data fusion strategies used for environmental monitoring, to the best of the authors’ knowledge. The first part of the article discusses the main challenges of geographical image analysis. Thereafter, a well-designed taxonomy is introduced to overview the existing frameworks, which have been focused on: (i) detecting different environmental impacts, e.g. land cover land use (LULC) change, gully erosion susceptibility (GES), waterlogging susceptibility (WLS), and land salinity and infertility (LSI); (ii) analyzing AI models deployed for extracting the pertinent features from RS images in addition to data fusion techniques used for combining images and/or features from heterogeneous sources; (iii) describing existing publicly-shared and open-access datasets; (iv) highlighting most frequent evaluation metrics; and (v) describing the most significant applications of ML and data fusion for RS image analysis. This is followed by an overview of existing works and discussions highlighting some of the challenges, limitations and shortcomings. To provide the reader with insight into real-world applications, two case studies illustrate the use of AI for classifying LULC changes and monitoring the environmental impacts due to dams’ construction, where classification accuracies of 98.57% and 97.05% have been reached, respectively. Lastly, recommendations and future directions are drawn.