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1.
Artificial intelligence (AI) has been in existence for over six decades and has experienced AI winters and springs. The rise of super computing power and Big Data technologies appear to have empowered AI in recent years. The new generation of AI is rapidly expanding and has again become an attractive topic for research. This paper aims to identify the challenges associated with the use and impact of revitalised AI based systems for decision making and offer a set of research propositions for information systems (IS) researchers. The paper first provides a view of the history of AI through the relevant papers published in the International Journal of Information Management (IJIM). It then discusses AI for decision making in general and the specific issues regarding the interaction and integration of AI to support or replace human decision makers in particular. To advance research on the use of AI for decision making in the era of Big Data, the paper offers twelve research propositions for IS researchers in terms of conceptual and theoretical development, AI technology-human interaction, and AI implementation. 相似文献
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Despite heightened interest, integrating artificial intelligence (AI) into businesses remains challenging. Recent surveys show that up to 85 % of AI initiatives ultimately fail to deliver on their promises. Studies on successful AI applications that could provide invaluable lessons for organizations embarking on their AI journey are still lacking. Therefore, this study aims to understand how AI technology, people, and processes should be managed to successfully create value. Building on the resource orchestration perspective, this study analyzes the successful applications of AI at Alibaba's e-commerce fulfillment center. The findings indicate that the key AI resources include data, AI algorithms, and robots. These resources must be orchestrated (e.g., coordinated, leveraged, deployed) to work with other related resources, such as warehouse facilities and existing information systems, to generate strong AI capabilities. The key AI capabilities generated include forecasting, planning, and learning. More importantly, AI capabilities are not independent – they interact and coevolve with human capabilities to create business value in terms of efficiency (e.g., space optimization, labor productivity) and effectiveness (e.g., error reduction). The implications of understanding these social informatics of AI for research and practice are discussed. 相似文献
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Organizations face increasing pressure to implement artificial intelligence (AI) within a variety of business processes and functions. Many perceived benefits surround AI, but a considerable amount of trepidation also exists because of the potential of AI to replace human employees and dehumanize work. Questions regarding the future of work in the age of AI are particularly salient in pre-adoption organizations, before employees have the opportunity to gain direct experience with AI. To cope with this potentially stressful situation, employees engage in cognitive appraisal processes based on their own knowledge and personal use of AI. These pre-adoptive appraisals of AI influence both affective and cognitive attitudes, which in turn trigger behavioral responses that influence an organization’s ability to leverage AI successfully. Our survey of 363 Taiwanese employees shows that perceptions of AI’s operational and cognitive capabilities are positively related to affective and cognitive attitudes toward AI, while concerns regarding AI have a negative relationship with affective attitude only. Interaction effects of employee knowledge and affective attitude are also observed. This work’s main contribution lies in the development of an empirically-tested model of the potential impact of AI on organizations from an employee perspective in the pre-adoption phase. These results have practical implications for how organizations prepare for the arrival of this transformative technology. 相似文献
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数字经济背景下,人工智能（AI）技术的应用正在深入地影响着企业管理变革、业务边界的扩展和管理模式的改变。结合互补资产的观点和组织学习理论,本文提出了一个基于AI应用能力和AI管理能力的分析框架,强调人工智能与人类智慧结合的必要性,阐述了两种能力的功能和作用及其协同对企业效率和创新成本的影响。本文提出,企业必须具备管理AI的能力才能有效应对大数据、数字技术、AI的不断革新及技术带来的组织内部结构和外部环境变化以及风险;企业AI应用与管理能力的有效结合,有利于控制AI应用带来的成本和风险,增强企业在人工人力、协调沟通、和数据搜寻方面的效率,同时降低AI应用带来的数字基建、道德情感、数据安全、组织结构变革方面的成本,进而促进企业的组织学习、对内外部数字技术使能资源的获取和管理以及互补资产的形成,对企业创新绩效发挥正向作用。最后,本文为企业的数字化创新战略提供了新的发展思路。 相似文献
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基于深度学习算法的进步,人工智能逐渐有能力独立进行发明创造和文艺作品创作。本文主要探讨现行专利及著作权制度中规定的保护对象、权利人资格、专利及著作权的权属、侵权判定、侵权责任主体等对人工智能技术快速发展的适应及协调程度,研究指出：现有的专利和版权制度应当对人工智能的发明和作品持鼓励的态度,在排除不适宜作为专利或著作权保护对象的同时,人工智能的发明或作品的权利授予标准应当与人类的有所区分;相关权利人仍须对应自然人或法人,而非人工智能本身;相关专利侵权行为应包括间接侵权,同时应对人工智能作品安排“登记-授权”的著作权制度、参考临摹作品为人工智能绘画作品提供相应的授权使用制度等。本文还探讨了当前的专利法及著作权法在人工智能时代符合公平原则的程度,并提出解决方案：在“强人工智能时代”将人工智能的发明创造或作品作为公共财产,授予相应的开发者“数据处理权”作为一种新的邻接权,赋予人工智能创造物新的特别权利（Sui Generis）,修改专利法与著作权法中关于主要权利的相关规定等。 相似文献
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There is an exponential growth of the use of AI applications in organisations. Due to the machine learning capability of artificial intelligence (AI) applications, it is critical that such systems are used continuously in order to generate rich use data that allow them to learn, evolve and mature into a better fit for their user and organisational context. This research focuses on the actual use of conversational AI, in particular AI chatbot, as one type of workplace AI application to answer the research question: how do employees experience the use of an AI chatbot in their day-to-day work? Through a qualitative case study of a large international organisation and by performing an inductive analysis, the research uncovers the different ways in which users appropriate the AI chatbot and identifies two key dimensions that determine their type of use: the dominant mode of interaction and the understanding of the AI chatbot technology. Based on these dimensions, a taxonomy of users is presented, which classifies users of AI chatbots into four types: early quitters, pragmatics, progressives, and persistents. The findings contribute to the understanding of how conversational AI, particularly AI chatbots, is used in organisations and pave the way for further research in this regard. The implications for practice are also discussed. 相似文献
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《Research Policy》2022,51(7):104555
This paper analyses the link between the use of Artificial Intelligence (AI) and innovation performance in firms. Based on firm-level data from the German part of the Community Innovation Survey (CIS) 2018, we examine the role of different AI methods and application areas in innovation. The results show that 5.8% of firms in Germany were actively using AI in their business operations or products and services in 2019. We find that the use of AI is associated with annual sales with world-first product innovations in these firms of about €16 billion (i.e. 18% of total annual sales of world-first innovations). In addition, AI technologies have been used in process innovation that contributed to about 6% of total annual cost savings of the German business sector. Firms that apply AI broadly (using different methods for different applications areas) and that have already several years of experience in using AI obtain significantly higher innovation results. These positive findings on the role of AI for innovation have to be interpreted with caution as they refer to a specific country (Germany) in a situation where AI started to diffuse rapidly. 相似文献
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我国国家层面2017年已经出台人工智能产业发展的规划计划文件,部分经济发达省市迅速出台了规划计划文件响应,然而,有关区域人工智能产业发展战略的研究甚少,尚未形成系统理论。在进行国内外研究与产业政策现状分析后,分析了人工智能产业的基本理论,凝练了人工智能产业的产业特点、产业关联关系、产业构成和发展所需的基础条件。提出了区域人工智能产业发展战略的构成要素,认为应由“三发一划一策”(即发展定位、发展目标、发展方向、规划计划、扶持政策)构成,给出了每个构成要素的内容及推导方法。以湖南省为例,详细剖析了该区域的人工智能产业现状,提出了该区域的产业发展战略,并提出了针对湖南省发展人工智能产业的系列政策建议。 相似文献
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动漫产业已成为21世纪的朝阳产业之一。归纳黑龙江省现有动漫产业发展模式,在总结美日韩三国动漫产业发展现状基础上,将黑龙江省与美日韩从动漫产业与民族文化结合、与成熟产业共同发展、动漫产业市场运营与产业链整合、政府扶持四个方面进行比较。研究表明,黑龙江动漫产业发展优势在于悠久且独特的民族文化,可与本省旅游业联动、形成符合自身发展的完整产业链,同时仍需加大政府对动漫产业的扶持力度。 相似文献
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以智能化科研（AI for Science）为核心的第五科研范式已经在多个自然科学和高技术领域得到了广泛应用。与人工智能（AI）在自然科学领域的应用强调发现新原理、新机理和新规律不同,高技术领域更强调用AI技术来发明创造新方案、新工具和新产品,以解决特定的领域问题。文章总结了AI在高技术领域的应用——“技术智能”（AI for Technology）的典型特征和科学问题,并以CPU芯片全自动设计为例介绍过往的成功案例。最后,文章指出技术智能的目标不仅是加速创新流程并减少人工投入,同时也希望其具备更强的创造能力,最终超过人类的水平。 相似文献
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科学家学术年龄特征研究——基于学术生产力与影响力的二维视角 《科学学研究》2013,(2):177-183
本文以入选美国科学信息研究所高被引科学家数据库中的物理学科高被引科学家为样本,从学术生产力与影响力的二维视角对科学家的学术年龄特征进行了研究。通过研究,主要有如下发现：（1）学术年龄在区间[1,25]之内时,学术影响力高于学术生产力;（2）学术影响力与生产力均存在较长的衰退期,但学术影响力活跃程度高于学术生产力;（3）学术影响力达到波峰时的学术年龄存在不确定性,而学术生产力可以唯一确定;（4）学术影响力与生产力最佳学术年龄区间均近似符合“黄金分割率”;（5）学术影响力和生产力与学术年龄之间的拟合关系均为三次多项式分布。同时,在文末分析了本文的研究不足;并对未来可能的研究方向进行了展望。 相似文献
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为探究医学人工智能发展态势以及我国医学人工智能存在的问题，从医学人工智能领域论文、临床试验、医疗器械产品3个维度进行态势分析，量化分析结果显示我国和全球医学人工智能发表论文数量均呈迅速增长趋势，发文数量及高被引论文方面我国处于国际前列；人工智能临床试验开展数量和面向疾病种类较多，但临床试验注册质量有待提高；我国人工智能医疗器械获批数量逐年增加，医疗人工智能产品认证稳步推进。医学人工智能发展的同时在理论层面、技术层面、伦理法律层面以及应用层面依旧面临着诸多问题和挑战。 相似文献
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强人工智能(以下简称强AI:Strong Artificial Intelligence)由美国哲学家约翰·塞尔上世纪70年代在其论文《心灵、大脑与程序》中提出,主要是指对人工智能(以下简称AI)持有的这样一种哲学立场:基于心智的计算模型,以通用数字计算机为载体的AI程序可以象人类一样认知和思考,达到或者超过人类智能水平。这种立场与弱人工智能(以下简称弱AI:Weak AI)或应用人工智能相对立,后者认为AI只是帮助人类完成某些任务的工具或助理。随着最近20年来互联网、神经科学、基因工程等技术的飞速发展,强AI从塞尔时代的一种哲学立场逐步向工程实践转变和演进,未来学家甚至设想和描述了强AI的更极端版本:超级智能,这些在IBM、谷歌、Facebook、微软等产业巨头和库兹韦尔、马克拉姆等乐观的技术实践者的双重推动下,藉由大众科学传播的放大作用,渗透到人们的日常生活中构成了对其技术合理性的辩护,但AI本身对人类主体和社会的影响不是价值中立的,它一方面难以吸收和提升人类的创新本质,另一方面其技术合理性带来的后果与其初衷有时相互背离,并在商业行为的推动下,构成对作为文化产物和自我解释的理性人类的单向压制和挑战。 相似文献
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《Research Policy》2022,51(6):104536
The effects of the rapid development of artificial intelligence (AI), a general-purpose technology, on firm performance is an emerging and crucial issue. This study examines the impact of AI technology on firms’ productivity and employee profiles. We use the keyword-matching method to parse the text of Taiwan patent grants, and obtain matched firm-level data on AI innovations in Taiwan's electronics industry for the 2002–2018 period. Empirical estimations indicate that AI technology is positively associated with productivity and employment. Meanwhile, non-AI patents also generate pro-productivity and pro-employment effects with a magnitude similar to that of AI technology. Inventing AI technologies crucially alters firms’ workforce compositions, which reduce the share of labor force with educational qualifications of college level and below. Robustness checks reaffirm these findings. 相似文献
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人工智能伦理准则与治理体系:发展现状和战略建议 总被引：1，自引：0，他引：1
首先,界定人工智能伦理准则的基本概念,分析人工智能发展现状。然后,探讨导致人工智能伦理问题的主要原因,总结人工智能典型应用场景下的伦理问题,包括自动驾驶、智能媒体、智慧医疗、服务机器人等;此外,围绕应对人工智能伦理问题的基本原则探索治理框架体系,包括技术应对、道德规范、政策引导、法律规则等方面。最后,结合我国人工智能发展规划战略部署,指出在社会治理的落地过程中宜采取分层次、多维度的治理体系,并提出在人工智能伦理准则和治理方面的具体措施建议(2020-2035年),包括社会宣传、标准体系、法律法规等方面。 相似文献
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AI has received increased attention from the information systems (IS) research community in recent years. There is, however, a growing concern that research on AI could experience a lack of cumulative building of knowledge, which has overshadowed IS research previously. This study addresses this concern, by conducting a systematic literature review of AI research in IS between 2005 and 2020. The search strategy resulted in 1877 studies, of which 98 were identified as primary studies and a synthesise of key themes that are pertinent to this study is presented. In doing so, this study makes important contributions, namely (i) an identification of the current reported business value and contributions of AI, (ii) research and practical implications on the use of AI and (iii) opportunities for future AI research in the form of a research agenda. 相似文献
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探讨我国人工智能政策特征以优化政策设计思路，以中央部委与地方政府印发的31份人工智能政策文件为研究样本，综合运用文本挖掘、内容分析和PMC指数模型等方法，提炼人工智能领域的研究前沿与热点分布、人工智能的政策特征以及评价结果。研究发现：我国人工智能政策以智能化为主要目标，重点关注科技研发与创新环节，并对“卡脖子”的芯片、机器人产品提出政策规范；政策工具应用不平衡，对政府采购、对外贸易管制、反他国管制、购置补贴四项需求型政策工具重视度不够；总体政策效力较好，但政策之间具有效力差异性，相关政策条款亟待加强和完善。基于以上特征和问题，建议进一步促进人工智能前沿政策的设计与前瞻，加大需求端政策工具的组合性和灵活性应用、优化供需政策工具包，加强对人工智能领域的监管政策力度，开展人工智能政策系统的整体性评估。 相似文献
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美国政府举国家之力发展人工智能技术以保持在世界的领先地位，对此，通过文献梳理的方法，从美国自身发展及其对外政策的视角系统分析美国人工智能战略部署和相关举措。分析发现，美国在人工智能领域的战略部署分为积累和升级两个阶段，均以制定发布政策文件和成立相关机构进行部署，已上升为国家战略并演变为世界领导权的竞争，基本实现人工智能创新价值链各环节全覆盖，各部门积极深耕细作，并日益重视在国防领域的应用；其对华策略主要采取成立专门机构、全面封锁、出口管制、限制人才流动等措施。为此，建议中国从组织管理职能、人才、立法、舆论等方面采取应对策略，增强自身实力、主动赢取先机。 相似文献