首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 656 毫秒
1.
Literature shows there is a growing interest in studies involving Artificial Intelligence (AI) in the public sector; and while there is evidence of many governmental initiatives that have been established to harness the power of AI, empirical research on the topic and evidence-based insights are rather lacking. The aim of this Special Issue on Artificial Intelligence for Data-Driven Decision-Making and Governance in Public Affairs is to extend both the theoretical and practical boundaries of AI research in the public sector in order to improve governmental decision-making and governance, thus enhancing public value creation. The papers in this special issue focus on AI risks and guidelines, AI governance, the risks of governmental implementation of AI to citizens' privacy, increasing citizen satisfaction through AI-enabled government services, the enablers and challenges of AI implementation in specific public sectors, and using AI to study political opinion. These papers not only advance our knowledge and understanding of the use of AI in government and public governance, but they also help to set out a renewed research agenda. Future research should, among other things, focus on inter- and multi-disciplinary empirical studies that call for the collaboration of a variety of stakeholders; on the longitudinal dynamics of creating public value through the breadth and depth of AI assimilation; and on the investigation of the ethical challenges (particularly data privacy) in AI implementation.  相似文献   

2.
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   

3.
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   

4.
Various types of algorithms are being increasingly used to support public decision-making, yet we do not know how these different algorithm types affect citizens' attitudes and behaviors in specific public affairs. Drawing on public value theory, this study uses a survey experiment to compare the effects of rule-driven versus data-driven algorithmic decision-making (ADM) on citizens' perceived fairness and acceptance. This study also examines the moderating role of familiarity with public affairs and the mediating role of perceived fairness on the relationship. The findings show that rule-driven ADM is generally perceived as fairer and more acceptable than data-driven ADM. Low familiarity with public affairs strengthens citizens' perceived fairness and acceptance of rule-driven ADM more than data-driven ADM, and citizens' perceived fairness plays a significant mediating role in the effect of rule-driven ADM on citizens' acceptance behaviors. These findings further imply that citizens' perceived fairness and acceptance of ADM is strongly shaped by how they perceive familiarity of the decision-making context. In high-familiarity AI application scenarios, the realization of public values may ultimately not be what matters for ADM acceptance among citizens.  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.
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   

7.
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   

8.
This study explores the determinants of digital innovation in the public sector. Focusing specifically on new digital technologies, such as big data, artificial intelligence, Internet of things, and augmented reality, we explained the wide variation in how Korean local governments used these technologies to transform their services. We found support for four theoretical mechanisms. First, our findings support the existence of demand-pull innovation in the public sector: public organizations respond to citizen demands or needs for innovation. Second, we also find support for an electoral incentive hypothesis, which posits that local governments' motivation for digital innovation is influenced by local politicians' electoral incentives. Third, our results show the existence of isomorphic pressure as a driver for public sector innovation: public organizations emulate their neighbors in adopting innovative practices. Fourth, the results support the upper echelons theory, as younger policymakers are more active innovators.  相似文献   

9.
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   

10.
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   

11.
Governments around the world are adopting facial recognition technology (FRT) to improve public services and law enforcement. Past research has shown that such applications may result in discriminatory effects and threaten privacy. This study shines light on the question of what drives public opinion regarding FRT in different socio-political contexts. Based on an online survey and semi-structured interviews, this study finds that citizens in China, Germany, the United Kingdom, and the United States differ in their acceptance of the official public use of FRT. China has the highest approval rates, Germany and the US have the lowest, and the UK lies in the middle. Our results show that people are generally more willing to accept FRT in public spheres when they trust government institutions, believe the technology should be managed by the central government, and have an affinity for technology. People's awareness of a country's previous history of surveillance further shapes their perceptions of FRT. Across all four countries, we also show that privacy concerns, especially of FRT compromising one's privacy, have the biggest influence on respondents' attitudes. Expanding on existing research into FRT acceptance and usage, our results suggest that policymakers urgently need to address the current regulatory vacuum.  相似文献   

12.
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   

13.
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   

14.
This study investigates the public's initial trust in so-called “artificial intelligence” (AI) chatbots about to be introduced into use in the public sector. While the societal impacts of AI are widely speculated about, empirical testing remains rare. To narrow this gap, this study builds on theories of operators' trust in machines in industrial settings and proposes that initial public trust in chatbot responses depends on (i) the area of enquiry, since expectations about a chatbot's performance vary with the topic, and (ii) the purposes that governments communicate to the public for introducing the use of chatbots. Analyses based on an experimental online survey in Japan generated results indicating that, if a government were to announce its intention to use “AI” chatbots to answer public enquiries, the public's initial trust in their responses would be lower in the area of parental support than in the area of waste separation, with a moderate effect size. Communicating purposes that would directly benefit citizens, such as achieving uniformity in response quality and timeliness in responding, would enhance public trust in chatbots. Although the effect sizes are small, communicating these purposes might be still worthwhile, as it would be an inexpensive measure for a government to take.  相似文献   

15.
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   

16.
Mobile health services are a new direction for public libraries development. However, it is unclear which factors affect users' intention to use the mobile health services of public libraries (MHSPL). Integrating the unified theory of acceptance and use of technology theory along with trust and privacy concerns. This study proposes a conceptual model to investigate factors that affect users' intention to use MHSPL. The conceptual model is empirically examined, and the hypotheses are tested using a survey sample (N = 415). The findings indicate that users' intention to use MHSPL is directly influenced by performance expectancy, effort expectancy, and trust. Trust also mediated users' intention to use MHSPL, leading to an indirect effect of social influence and privacy concerns. Additionally, people with different experiences using MHSPL have significant differences in their intention to use MHSPL. These findings contribute to a deeper understanding of users' behavior of MHSPL and can help facilitate and improve health services provided by public libraries.  相似文献   

17.
Local governments are increasingly establishing functional decentralized agencies, such as autonomous organizations, public companies, foundations and public business entities to provide public services. Furthermore, they are also introducing the private sector, contracting out public services to a private company and creating mixed companies. Our aim is to analyze the effect of functional decentralization and externalization (outsourcing or contracting out) processes on public transparency levels, since theoretically, they are aimed toward good governance and accountability. To do so, we use a sample composed of the 110 largest Spanish cities for the period 2008–2010. The results show that decentralized agencies, especially public companies and foundations, impact positively on levels of public transparency. However, there is no evidence that suggests that the introduction of the private sector, using outsourcing and mixed companies, affects the transparency of local governments.  相似文献   

18.
Delivering public services through the SMS channel is popular in developed and developing countries, and it has demonstrated its benefits. However, citizens' acceptance of the services is still an issue. This paper presents a study on user acceptance of SMS-based e-government services. Constructs of the proposed model were derived from a survey on citizens' motivations for using SMS-based e-government services (142 respondents from 25 countries), prominent theories on individual acceptance of technologies, and current studies on user acceptance of SMS and e-government services. The model was validated using data from 589 citizens in three cities in Indonesia, who are non-adopters. The relationships between the factors then were compared with data from 80 adopters of SMS-based e-government services in Australia. The proposed model explains what factors influence non-adopters to accept SMS-based e-government services, and the comparison explains the relative importance of the factors for the adopters. The findings are promising for governments who wish to evaluate a new SMS-based e-government system very early in its development in order to assess potential acceptability and for governments who would like to diagnose the reasons why an existing SMS-based e-government service is not fully acceptable to citizens and to take corrective action to increase the acceptability of the service.  相似文献   

19.
Mobile applications are becoming a preferred delivery method for the government sector and contributing to more convenient and timely services to citizens. This study examines the intention to use mobile applications for the government services (mG-App) in Oman. This study extended the Unified Theory of Acceptance and Use of Technology (UTAUT) model by including two constructs namely trust and information quality. Data were collected from 513 mobile application users across Oman. The research model was analysed in two stages. First, structural equation modelling (SEM) was employed to determine significant determinants affecting users' acceptance of mG-App. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of determinants of acceptance of mG-App. The findings revealed that trust and performance expectancy are the strongest determinants influencing the acceptance of mG-App. The findings of this research have provided theoretical contributions to the existing research on mG-App and practical implications to decision-makers involved in the development and implementation of mG-App in in Oman.  相似文献   

20.
Developing the capacity to digitally transform through AI is becoming increasingly important for public organizations, as a constantly growing number of their activities is now becoming AI-driven. This prompts an understanding of how public organizations should organize in order to derive value from AI, as well as in which forms can value be realized. Against this background, this paper examines how AI capabilities can lead to organizational performance by inducing change in key organizational activities. Using a survey-based study, we collected data from European public organizations regarding the indirect effect AI capabilities have on organizational performance. Data was collected from 168 municipalities from three European countries (Norway, Germany, and Finland) and analyzed by means of structural equation modeling. Our findings show that AI capabilities have a positive effect on process automation, cognitive insight generation, and cognitive engagement. While process automation and cognitive insights are having a positive effect on organizational performance, we found that cognitive engagement negatively affects organizational performance. Our findings document the key resources that constitute an AI capability and showcase the effects of fostering such capabilities on key organizational activities, and in turn organizational performance.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号