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1.
To lay the foundation for the special issue that this research article introduces, we present 1) a systematic review of existing literature on the implications of the use of Artificial Intelligence (AI) in public governance and 2) develop a research agenda. First, an assessment based on 26 articles on this topic reveals much exploratory, conceptual, qualitative, and practice-driven research in studies reflecting the increasing complexities of using AI in government – and the resulting implications, opportunities, and risks thereof for public governance. Second, based on both the literature review and the analysis of articles included in this special issue, we propose a research agenda comprising eight process-related recommendations and seven content-related recommendations. Process-wise, future research on the implications of the use of AI for public governance should move towards more public sector-focused, empirical, multidisciplinary, and explanatory research while focusing more on specific forms of AI rather than AI in general. Content-wise, our research agenda calls for the development of solid, multidisciplinary, theoretical foundations for the use of AI for public governance, as well as investigations of effective implementation, engagement, and communication plans for government strategies on AI use in the public sector. Finally, the research agenda calls for research into managing the risks of AI use in the public sector, governance modes possible for AI use in the public sector, performance and impact measurement of AI use in government, and impact evaluation of scaling-up AI usage in the public sector.  相似文献   

2.
The nascent adoption of Artificial Intelligence (AI) in the public sector is being assessed in contradictory ways. But while there is increasing speculation about both its dangers and its benefits, there is very little empirical research to substantiate them. This study aims at mapping the challenges in the adoption of AI in the public sector as perceived by key stakeholders. Drawing on the theoretical lens of framing, we analyse a case of adoption of the AI system IBM Watson in public healthcare in China, to map how three groups of stakeholders (government policy-makers, hospital managers/doctors, and Information Technology (IT) firm managers) perceive the challenges of AI adoption in the public sector. Findings show that different stakeholders have diverse, and sometimes contradictory, framings of the challenges. We contribute to research by providing an empirical basis to claims of AI challenges in the public sector, and to practice by providing four sets of guidelines for the governance of AI adoption in the public sector.  相似文献   

3.
The Internet of things (IoT) is the network of objects/things that contain electronics, software, sensors, and actuators, which allows these things to connect, interact, and exchange data. The users, sensors, and networks generate huge amounts of data from which governments can develop applications and gain knowledge using Artificial Intelligence (AI) techniques. Thus, IoT and AI can enable the development of valuable services for citizens, businesses, and public agencies, in multiple domains, such as transportation, energy, healthcare, education, and public safety. This guest editorial for the special issue on IoT and AI for Smart Government, identifies the challenges involved in implementing and adopting these technologies in the public sector, and proposes a comprehensive research framework, which includes both IoT and AI elements for smart government transformation. Subsequently, the editorial provides a brief introduction of the six papers in this special issue. Finally, an agenda for future research on IoT and AI for smart government is presented, based on the proposed framework and gaps in existing literature, supported by the papers that were submitted to this special issue. The agenda comprises four directions i.e., conducting domain-specific studies, going beyond adoption studies to examine implementation and evaluation of these technologies, focusing on specific challenges and thus quick wins, and expanding the existing set of research methods and theoretical foundations used.  相似文献   

4.
Artificial Intelligence (AI) policies and strategies have been designed and adopted in the public sector during the last few years, with Chief Information Officers (CIOs) playing a key role. Using socio-cognitive and institutional approaches on Information Technologies (ITs) in (public) organizations, we consider that the assumptions, expectations, and knowledge (technological frames) of those in charge (CIOs) of designing AI strategies are guiding the future of these emerging systems in the public sector. In this study, we focus on the technological frames of CIOs in the largest Spanish local governments. Based on a survey administered to CIOs leading IT departments, this article presents original data about their technological frames on AI. Our results: (1) provide insights about how CIOs tend to focus on the technological features of AI implementation while often overlook some of the social, political, and ethical challenges in the public sector; (2) expand the theory on AI by enabling the construction of propositions and testable hypotheses for future research in the field. Therefore, the comparative study of technological frames will be key to successfully design and implement AI policies and strategies in the public sector and to tackle future challenges and opportunities.  相似文献   

5.
Artificial Intelligence is increasingly being used by public sector organisations. Previous research highlighted that the use of AI technologies in government could improve policy making processes, public service delivery and the internal management of public administrations. In this article, we explore to which extent the use of AI in the public sector impacts these core governance functions. Findings from the review of a sample of 250 cases across the European Union, show that AI is used mainly to support improving public service delivery, followed by enhancing internal management and only in a limited number assist directly or indirectly policy decision-making. The analysis suggests that different types of AI technologies and applications are used in different governance functions, highlighting the need to further in-depth investigation to better understand the role and impact of use in what is being defined the governance “of, with and by AI”.  相似文献   

6.
Artificial Intelligence (AI) implementation in public administration is gaining momentum heralded by the hope of smart public services that are personalised, lean, and efficient. However, the use of AI in public administration is riddled with ethical tensions of fairness, transparency, privacy, and human rights. We call these AI tensions. The current literature lacks a contextual and processual understanding of AI adoption and diffusion in public administration to be able to explore such tensions. Previous studies have outlined risks, benefits, and challenges with the use of AI in public administration. However, a large gap remains in understanding AI tensions as they relate to public value creation. Through a systematic literature review grounded in public value management and the resource-based view of the firms, we identify technology-organisational-environmental (TOE) contextual variables and absorptive capacity as factors influencing AI adoption as discussed in the literature. To our knowledge, this is the first paper that outlines distinct AI tensions from an AI implementation and diffusion perspective within public administration. We develop a future research agenda for the full AI innovation lifecycle of adoption, implementation, and diffusion.  相似文献   

7.
Artificial Intelligence (AI) has been suggested to have transformative potential for public sector organizations through enabling increased productivity and novel ways to deliver public services. In order to materialize the transformative potential of AI, public sector organizations need to successfully assimilate AI in their operational activities. However, AI assimilation in the public sector appears to be fragmented and lagging the private sector, and the phenomena has really limited attention from academic research community. To address this gap, we adopt the case study approach to explore three Saudi-Arabian public sector organizations and analyze the results using the attention-based view of the organization (ABV) as the theoretical lens. This study elucidates the challenges related AI assimilation in public sector in terms of how organizational attention is focused situated and distributed during the assimilation process. Five key challenges emerged from the cases studied, namely (i) misalignment between AI and management decision-making, (ii) tensions with linguistics and national culture, (iii) developing and implementing AI infrastructure, (iv) data integrity and sharing, and (v) ethical and governance concerns. The findings reveal a re-enforcing relationship between the situated attention and structural distribution of attention that can accelerate the successful assimilation of AI in public sector organizations.  相似文献   

8.
The growing Artificial Intelligence (AI) age has been flooded with several innovations in algorithmic machine learning that may bring significant impacts to industries such as healthcare, agriculture, education, manufacturing, retail etc. But challenges such as data quality, privacy and lack of a skilled workforce limit the scope of AI implementation in emerging economies, particularly in the Public Manufacturing Sector (PMS). Therefore, to enhance the body of relevant literature, this study examines the existing challenges of AI implementation in PMS of India and explores the inter-relationships among them. The study has utilized the DEMATEL method for identification of the cause-and-effect group factors. The findings reveal that poor data quality, managers' lack of understanding of cognitive technologies, data privacy, problems in integrating cognitive projects and expensive technologies are the main challenges for AI implementation in PMS of India. Moreover, a model is proposed for industrial decision-makers and managers to take appropriate decisions to develop intelligent AI enabled systems for manufacturing organizations in emerging economies.  相似文献   

9.
This study addresses the growing challenge of governing artificial intelligence (AI) arising from the risks that it increasingly poses to the public sector and society. Based on an in-depth literature analysis, we first identify AI risks and guidelines and classify them into six categories, including technological, data, and analytical risks and guidelines, informational and communicational risks and guidelines, economic risks and guidelines, social risks and guidelines, ethical risks and guidelines, as well as legal and regulatory risks and guidelines. These risks and guidelines are then elaborated and transferred into a four-layered conceptual framework for AI governance. The framework interrelates AI risks and AI guidelines by means of a risk management and guidance process, resulting in an AI governance layer depicting the process for implementation of customised risk mitigation guidelines. The framework constitutes a comprehensive reference point for developing and implementing AI governance strategies and measures in the public sector.  相似文献   

10.
Artificial Intelligence (AI) is gradually becoming an integral part of the digital strategy of organizations. Yet, the use of AI in public organizations in still lagging significantly compared to private organizations. Prior literature looking into aspects that facilitate adoption and use of AI has concentrated on challenges concerning technical aspects of AI technologies, providing little insight regarding the organizational deployment of AI, particularly in public organizations. Building on this gap, this study seeks to examine what aspects enable public organizations to develop AI capabilities. To answer this question, we built an integrated and extended model from the Technology-Organization-Environment framework (TOE) and asked high-level technology managers from municipalities in Europe about factors that influence their development of AI capabilities. We collected data from 91 municipalities from three European countries (i.e., Germany, Norway, and Finland) and analyzed responses by means of structural equation modeling. Our findings indicate that five factors – i.e. perceived financial costs, organizational innovativeness, perceived governmental pressure, government incentives, regulatory support – have an impact on the development of AI capabilities. We also find that perceived citizen pressure and perceived value of AI solutions are not important determinants of AI capability formation. Our findings bear the potential to stimulate a more reflected adoption of AI supporting managers in public organizations to develop AI capabilities.  相似文献   

11.
Driven by ‘success stories’ reported by private sector firms, government agencies have also started adopting various Artificial Intelligence (AI) technologies in diverse domains (e.g. health, taxation, and education); however, extensive research is required in order to exploit the full potential of AI in the public sector, and leverage various AI technologies to address important problems/needs. This paper makes a contribution in this direction: it presents a novel approach, as well as the architecture of an ICT platform supporting it, for the advanced exploitation of a specific AI technology, namely chatbots, in the public sector in order to address a crucial issue: the improvement of communication between government and citizens (which has for long time been problematic). The proposed approach builds on natural language processing, machine learning and data mining technologies, and leverages existing data of various forms (such as documents containing legislation and directives, structured data from government agencies' operational systems, social media data, etc.), in order to develop a new digital channel of communication between citizens and government. Making use of appropriately structured and semantically annotated data, this channel enables ‘richer’ and more expressive interaction of citizens with government in everyday language, facilitating and advancing both information seeking and conducting of transactions. Compared to existing digital channels, the proposed approach is appropriate for a wider range of citizens' interactions, with higher levels of complexity, ambiguity and uncertainty. In close co-operation with three Greek government agencies (the Ministry of Finance, a social security organization, and a big local government organization), this approach has been validated through a series of application scenarios.  相似文献   

12.
To obtain benefits in the provision of public services, managers of public organizations have considerably increased the adoption of artificial intelligence (AI) systems. However, research on AI is still scarce, and the advance of this technology in the public sector, as well as the applications and results of this strategy, need to be systematized. With this goal in mind, this paper examines research related to AI as applied to the public sector. A review of the literature covering articles available in five research databases was completed using the PRISMA protocol for literature reviews. The search process yielded 59 articles within the scope of the study out of a total of 1682 studies. Results show a growing trend of interest in AI in the public sector, with India and the US as the most active countries. General public service, economic affairs, and environmental protection are the functions of government with the most studies related to AI. The Artificial Neural Networks (ANN) technique is the most recurrent in the investigated studies and was pointed out as a technique that provides positive results in several areas of its application. A research framework for AI solutions for the public sector is presented, where it is demonstrated that policies and ethical implications of the use of AI permeate all layers of application of this technology and the solutions can generate value for functions of government. However, for this, a prior debate with society about the use of AI in the public sector is recommended.  相似文献   

13.
Artificial intelligence (AI) is regarded as the next digital frontier in government, with many potential applications for economic development as well as sustainable urbanization. Governments have started experimenting with AI, but empirical research on how to leverage and implement AI remains limited. This study analyzed two cases of AI implementation in a large city and identified various AI capabilities useful for government. More importantly, purposeful orchestration of AI-related resources such as data, knowledge, algorithms, and information systems is necessary for developing strong AI capabilities. The findings indicate two different types of orchestration: policy-driven orchestration focuses on the integration of resources, while innovation-driven orchestration focuses on triangulation. This study contributes to the growing body of knowledge on AI in government by revealing and conceptualizing different paths and approaches to AI implementation. They also serve to inform practitioners' planning of AI implementation.  相似文献   

14.
A growing body of literature shows that despite the significant benefits of artificial intelligence (AI), its adoption has many unknowns and challenges. However, theoretical studies dominate this topic. Completing the recent works, this article aims to identify challenges faced by public organizations when adopting AI based on the PRISMA Framework and an empirical assessment of these challenges in the opinion of public managers using survey research. The adopted research procedure is also an added value because it could be replicated in other context scenarios. To achieve this paper's aim, the Systematic Literature Review (SLR) and survey research among authorities in 414 Polish cities were carried out. As a result, a list of 15 challenges and preventive activities proposed by researchers to prevent these challenges have been identified. Empirical verification of identified challenges allows us to determine which of them limit AI adoption to the greatest extent in public managers' opinion. These include a lack of strategy or plans to initial adoption / continued usage of AI; no ensuring that AI is used in line with human values; employees' insufficient knowledge of how to use AI; insufficient AI policies, laws, and regulations; and different expectations of stakeholders and partners about AI. These findings could help practitioners to prioritize AI adoption activities and add value to digital government theory.  相似文献   

15.
政府大数据治理规则体系构建研究构想   总被引：2，自引：1，他引：1  
[目的/意义] 弥补大数据发展应用背景下政府大数据治理规则体系缺失及其研究的不足。[方法/过程] 从大数据认知多维视角出发,分析大数据治理主体、治理客体、治理活动和治理风险4个方面所面临的挑战及其大数据规则制定需求;诊断政府大数据治理规则体系构建研究的阻碍问题及原因。以公共价值理论、数字连续性理论和多元价值理论为主要理论支持,提出政府大数据治理规则体系构建研究的基本框架。[结果/结论] 明晰了政府大数据治理规则体系构建的关键性要素及其关系,对构建政府大数据治理的长效规则体系提供了一种多维视角的研究思路和一个综合集成的研究方案。  相似文献   

16.
Cyber-incidents threaten the confidentiality, efficiency, and integrity of digital information systems, causing privacy risks, economic losses, and reputational damages, and exposing managerial limitations. Although these phenomena are becoming more frequent in public agencies, research to date has mainly focused on private sector organizations and individuals. In this study, we contribute to the broader literature on cyber-incidents by exploring the drivers of both security breaches and unauthorized data disclosures in public organizations. Drawing from routine activity theory, we develop hypotheses on the determinants of cyber-incidents in departments in small and medium-sized US cities and test them using data from a national survey of public managers. Our findings suggest that both environmental and organizational factors are key determinants of cyber-incidents in city government. The results demonstrate the application of routine activity theory to public sector organizations and identify external and internal elements related to cyber-incidents in city government departments.  相似文献   

17.
In today's global culture where the Internet has established itself as the main tool for communication and commerce, the capability to massively analyze and predict citizens' behavior has become a priority for governments in terms of collective intelligence and security. At the same time, in the context of novel possibilities that artificial intelligence (AI) brings to governments in terms of understanding and developing collective behavior analysis, important concerns related to citizens' privacy have emerged. In order to identify the main uses that governments make of AI and to define citizens' concerns about their privacy, in the present study, we undertook a systematic review of the literature, conducted in-depth interviews, and applied data-mining techniques. Based on our results, we classified and discussed the risks to citizens' privacy according to the types of AI strategies used by governments that may affect collective behavior and cause massive behavior modification. Our results revealed 11 uses of AI strategies used by the government to improve their interaction with citizens, organizations in cities, services provided by public institutions or the economy, among other areas. In relation to citizens' privacy when AI is used by governments, we identified 8 topics related to human behavior predictions, intelligence decision making, decision automation, digital surveillance, data privacy law and regulation, and the risk of behavior modification. The paper concludes with a discussion of the development of regulations focused on the ethical design of citizen data collection, where implications for governments are presented aimed at regulating security, ethics, and data privacy. Additionally, we propose a research agenda composed by 16 research questions to be investigated in further research.  相似文献   

18.
Despite the exponential growth in the popularity of artificial intelligence (AI), our knowledge on the public perception of AI, especially in the context of local government services, is still limited. To bridge this gap, this study aims to provide empirical evidence and insights into public perceptions concerning the use of AI in local government services. Our methodological approach involves collecting data via an online survey from the residents of three major Australian cities—i.e., Sydney, Melbourne, Brisbane—and Hong Kong (n = 850), and performing statistical analyses. We found that: (a) Ease of using AI is significantly and positively influenced by attitude towards AI; (b) Attitude towards AI significantly and positively influences perceived usefulness of AI in local government services; (c) AI is seen useful in resource management and to improve delivery of service, reduction of cost to provide urban-service, improvement of public safety, and monitoring the effectiveness of strategies to manage environmental crisis, and; (d) AI is more positively perceived by Australians in comparison to Hong Kongers, indicating the impact of contextual and cultural differences. The research findings inform local government authorities—e.g., urban policymakers, managers, and planners—on their AI policy, planning and implementation decisions.  相似文献   

19.
Calls for public engagement and participation in AI governance align strongly with a public value management approach to public administration. Simultaneously, the prominence of commercial vendors and consultants in AI discourse emphasizes market value and efficiency in a way often associated with the private sector and New Public Management. To understand how this might influence the consolidation of AI governance regimes and decision-making by public administrators, 16 national strategies for AI are subjected to content analysis. References to the public's role and public engagement mechanisms are mapped across national strategies, as is the articulation of values related to professionalism, efficiency, service, engagement, and the private sector. Though engagement rhetoric is common, references to specific engagement mechanisms and activities are rare. Analysis of value relationships highlights congruence of engagement values with professionalism and private sector values, and raises concerns about neoliberal technology frames that normalize AI, obscuring policy complexity and trade-offs.  相似文献   

20.
The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements. However, they all rely on data which is not only big, open and linked but varied, dynamic and streamed at high speeds in real-time. Managing such data is challenging. To overcome such challenges and utilize opportunities for BDAS, organizations are increasingly developing advanced data governance capabilities. This paper reviews challenges and approaches to data governance for such systems, and proposes a framework for data governance for trustworthy BDAS. The framework promotes the stewardship of data, processes and algorithms, the controlled opening of data and algorithms to enable external scrutiny, trusted information sharing within and between organizations, risk-based governance, system-level controls, and data control through shared ownership and self-sovereign identities. The framework is based on 13 design principles and is proposed incrementally, for a single organization and multiple networked organizations.  相似文献   

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