Gender digital divide in Rwanda: A qualitative analysis of socioeconomic factors

This study aims at exploring how information and communications technology (ICT) is accessed and used by women and men in Rwanda. Specifically, we analyze the factors that contribute to the gender digital divide in Rwanda. In addition, we assess the importance of equal access to ICTs between genders. Rwanda is a particulary interesting case study, since previous studies on gender differences in the usage and accessibility of ICTs have focused on Western countries, while Africa, and Rwanda in particular, have been less covered. The qualitative method of in-depth interviews was used to collect the data. Interviews were analyzed using a thematic analysis technique. The findings of this study reveal that a gender digital divide still exists in Rwanda, even though the government puts forth much effort to eradicate this phenomenon. Reasons for barriers for women’s access to ICTs were found in social, economic and cultural factors, such as feelings of lack of self-worth, self-confidence, and proper educations; heavy domestic responsibilities; and computer anxiety. The findings also indicated that equal access to ICTs would be a shortcut to economic growth in Rwanda. This study concludes that Rwandan women need to be better educated in the use of computer technologies. Certain gender-sensitive strategies that guide the use of ICTs in this way also need to be established.     

Technology Use as a Status Cue: The Influences of Mundane and Novel Technologies on Knowledge Assessments in Organizations

This study explores the relationship between the use of information and communication technologies (ICTs) and assessments of workers' knowledge and abilities in 2 knowledge‐intensive organizations. Drawing on expectation states theory, the article argues that a worker's communication through mundane, widely diffused ICTs may lead to status assessments from colleagues that are different than when he or she communicates through novel ICTs. Data from interviews and observations at both organizations revealed that mundane ICT use influenced assessments about the general level of proficiency of workers, and use of novel ICTs influenced assessments about a specialist type of proficiency. Additionally, workers expressing communicative cues indicative of higher statuses played larger roles in organizational tasks than workers who were viewed as lower‐status.     

Artificial intelligence for optical transport networks: architecture,application and challenges

Optical network plays an important role in telecommunication networks, which supports high-capacity and long-distance transmission of Internet traffic. However, as the scaling and evolving of optical networks, it faces great challenges in terms of network operation, optimization and maintenance. Artificial intelligence(AI) has been proved to have superiority on addressing complex problems, by mimicking cognitive skills similar with human mind. In this paper, we provide a comprehensive investigat...     

Does the digital divide matter? Factors and conditions that promote ICT literacy

Individuals’ computer skills have long been noteworthy for both education and the labor market. Although the support provided through curricula in schools develops these skills to a certain extent, digital divide still exists for individuals with different socio-demographic characteristics. The concept of digital divide, used to define individuals who do not have equal access to digital technologies, has started to be seen as a determining factor for digital competencies with its expanding scope. The current study aims to take a perspective to investigate the effect of socio-demographic variables, which may cause digital divide, on students' ICT literacy. With this study, it is sought to explain the effect of current inequalities regarding digital access on students' ICT skills. To this end, the socio-demographic characteristics of the students in the sample of Korea and Chile from the participating countries of the International Computer and Information Literacy Study (ICILS) were examined in the context of ICT literacy. The characteristics of the models created were compared for both countries. While parents’ level of education variable stands out for the Chilean model, the internet connection variable is remarkable for the Korean model. It is anticipated that the findings of the research will contribute to understanding the dynamics of the digital divide and its possible consequences, and can be a source for preventive policy steps to be developed.     

Digital inequality in the Appalachian Ohio: Understanding how demographics,internet access,and skills can shape vital information use (VIU)

Access to information and resources via the Internet is an increasingly vital dimension of contemporary life. However, there can be several impediments to optimal Internet utilization in the form of access, skills, and motivation. Even when access is available, several digital inequalities arise as citizens often lack the skills and motivations to pursue those vital uses through the Internet to the best of their advantage. Digital inequalities in the hills of the Appalachian area of Ohio are often manifested in terms of social, cultural and geographic divides. Not only do the hills block wireless signals and make cables expensive to install, but regional poverty also drives away telecom investment. We conducted a survey of Appalachian Ohio to explore digital inequity issues and the determinants of online participation for things that matter. Through a number of analyses, we explore how Internet access and digital skills impact online contribution to the community in terms of services and resources considered to be basic social needs: health, employment, education, and social media. These social needs, what we have called Vital Internet Use (VIU) can determine citizens’ political and civic participation, societal contribution, and overall benefit to their communities. Centered on the concepts of digital access, Internet skills, and benefit outcomes, we extend knowledge in this domain and propose a comprehensive framework of VIU.     

“OK,Google, why do I use you?” Motivations,post-consumption evaluations,and perceptions of voice AI assistants

Voice-activated, artificial intelligence–based assistants (voice AI assistants) have become an integral part of everyday life because they can be easily activated to complete numerous tasks. However, little is known about what motivates people to use them or how these motivations influence users’ post-consumption evaluations and perceptions. This study develops measures to capture uses and gratifications related to voice AI assistants. It identifies five primary motivations for use—social interaction, personal identity, conformity, life efficiency, and information. Results show that the utilitarian motivations of life efficiency and information influence all post-consumption evaluations and behavioral intentions positively (i.e., users’ attitudes, satisfaction, and intentions to continue using voice AI assistants). However, social motivations are also important. Social interaction and conformity motivations also influence user satisfaction, and the conformity motivation shapes individuals’ intentions to continue using voice AI assistants. The findings further demonstrate that users’ motivations influence perceptions of their voice AI assistants’ roles. In keeping with the “Computers Are Social Actors” (CASA) paradigm, users motivated by social interaction are likely to perceive a voice AI assistant as socially attractive and as a friend, whereas users motivated by life efficiency are likely to perceive it as an assistant. Users motivated by information are more likely to perceive a voice AI assistant as technology, while those motivated by social interaction are less likely to do so. The implications of these findings are discussed, and recommendations for future research are provided.     

Identifying relevant segments of AI applications adopters – Expanding the UTAUT2’s variables

Artificial intelligence (AI) is a future-defining technology, and AI applications are becoming mainstream in the developed world. Many consumers are adopting and using AI-based apps, devices, and services in their everyday lives. However, research examining consumer behavior in using AI apps is scant. We examine critical factors in AI app adoption by extending and validating a well-established unified theory of adoption and use of technology, UTAUT2. We also explore the possibility of unobserved heterogeneity in consumers’ behavior, including potentially relevant segments of AI app adopters. To augment the knowledge of end users’ engagement and relevant segments, we have added two new antecedent variables into UTAUT2: technology fear and consumer trust. Prediction-orientated segmentation was used on 740 valid responses collected using a pre-tested survey instrument. The results show five segments with different behaviors that were influenced by the variables of the proposed model. Once known, the profiles were used to propose apps to AI developers to improve consumer engagement. The moderating effects of the added variables—technology fear and consumer trust—are also shown. Finally, we discuss the theoretical and managerial implications of our findings and propose priorities for future research.     

Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products

The rapid growth of artificial intelligence (AI) technology has prompted the development of AI-based intelligent products. Accordingly, various technology acceptance theories have been used to explain acceptance of these products. This comparative study determines which models best explain consumer acceptance of AI-based intelligent products and which factors have the greatest impact in terms of purchase intention. We assessed the utility of the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Value-based Adoption Model (VAM) using data collected from a survey sample of 378 respondents, modeling user acceptance in terms of behavioral intention to use AI-based intelligent products. In addition, we employed decomposition analysis to compare each factor included in these models in terms of influence on purchase intention. We found that the VAM performed best in modeling user acceptance. Among the various factors, enjoyment was found to influence user purchase intention the most, followed by subjective norms. The findings of this study confirm that acceptance of highly innovative products with minimal practical value, such as AI-based intelligent products, is more influenced by interest in technology than in utilitarian aspects.     

Managed Innovation in Korea in telecommunications – Moving towards 4G mobile at a national level

The Korean experience offers a case study in the necessary drivers behind rapid economic development based on ICTs, through insights into how alternative wireless technologies (AWTs) and their services have not just been developed, but have been popularised and brought to market. This paper examines the Korean success in telecommunications and summarises certain key lessons on innovation that we may draw from its development of new radio technologies. Managed innovation with long-term programmes is the key to Korea’s transition towards a knowledge based society. Some elements of the Korean model of innovation and its application are specific to Korea’s socio-political condition and cannot be replicated, while others offer opportunities for new thinking on long-term policy, especially in telecommunications.     

Energy-efficient cluster-based artificial intelligence routing for wireless sensor networks

Artificial intelligence (AI)-based wireless sensor network technology is the future of advancement for real-time applications. With AI wireless sensor network technology, it is possible to collect data from any environment, analyze in real time, and use it to optimize processes and operations. AI wireless sensor network technology provides an unprecedented level of accuracy as well as the ability to detect even the slightest changes in a given environment. The AI-based approach uses clustering-based techniques with self-organizing map (SOM) for energy conservation in resource-constrained networks. By clustering the network, it becomes more energy efficient, as data can be shared among members of a cluster without needing to be transmitted across multiple nodes. The proposed AI cluster-based routing approach outperforms in terms of energy consumption and computational challenges of the network. The results obtained demonstrate the proposed approach to achieve lower energy consumption than the existing algorithms while providing the same level of performance in terms of throughput and latency, as well as a comparison with traditional justification techniques.     

Can AI be a content generator? Effects of content generators and information delivery methods on the psychology of content consumers

Considering the rapidly improving technologies in artificial intelligence (AI), researchers in mass communication and journalism have paid attention to the use of AI technologies. However, there are still notable concerns about the particular use of AI technologies in this field. Put simply, can AI technologies reduce human tasks? In order to address this question, this study investigates the effects of content generators (human vs. AI) and information delivery methods (text vs. audio vs. video) on users’ perceptions of content. The results indicate that the generators and methods play a notable role in eliciting greater quality, satisfaction, and readability of the content. Based on the findings, the implications are addressed.     

AI在5G行业专网的应用场景和使能技术

行业专网是5G网络的重要组成部分,电信运营商通过AI与行业专网应用场景结合实现业务SLA保障和网络优化。面向数字化、智能化的新一代行业专网发展目标,基于行业用户的体验保障和网络安全需求探讨了AI在5G行业专网典型应用场景,分析了基于AI的5G行业专网应用的关键使能技术,包括算力网络、自适应优化AI算法、意图驱动的网络织造、原生多主体群等,构建自适应持续进化的行业专网,为5G行业专网的智能化提供了有效、可行的实现方法。     

Determinants of Internet skills,uses and outcomes. A systematic review of the second- and third-level digital divide

Recently, several digital divide scholars suggested that a shift is needed from a focus on binary Internet access (first-level digital divide) and Internet skills and use (second-level digital divide) to a third-level digital divide in which the tangible outcomes of Internet use are highlighted. A plethora of studies have been conducted to identify determinants of digital divides. Unfortunately, there is a lack of consistency in the terminology used. Moreover, terms are often not theoretically grounded. Therefore, we conducted a systematic literature review of digital divide determinants. The results show that the third-level digital divide was underexposed. The primary focus is on Internet use. More importantly, the identified determinants show that digital divide research is largely limited to sociodemographic and socioeconomic determinants.     

AI as a friend or assistant: The mediating role of perceived usefulness in social AI vs. functional AI

Advents of new technology have transformed how we currently view and use artificial intelligence (AI). Originally, AI was first developed to assist humans to complete tasks, but AI now takes on more social roles, such as functioning as a companion. However, little is known about how individuals view these different types of AI. Thus, the present study conducted an online experiment to explore people’s perceptions about social AI vs. functional AI. Primary results suggest that individuals have more positive attitudes toward functional AI than social AI. Perceived usefulness of AI is found to have a mediation effect, suggesting functional AI, compared to social AI, leads to stronger perceived usefulness, which consequently fosters more positive attitudes and stronger perceived realism of AI. The results collectively suggest meaningful implications for human-AI communication and human–machine communication research.     

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.     

Corporate attitudes and commitments to telecommuting

The increased use of telecommuting by information and knowledge workers in many fields has been fostered by the availability of enabling technologies. Notebook sized computers, easy-to-use software, access to information both private or public, and electronic mail capabilities available worldwide have made telecommuting possible. This paper examines some of the key factors involved in the telecommuting evolution. Coverage includes background on how telecommuting started and which current technologies lend themselves to telecommuting. Also, the article reviews the trends that are stimulating dramatic double-digit growth and describes corporate attitudes toward and experiences with telecommuting. Topics covered include corporate commitments, motivation, productivity, supervision and employee satisfaction     

Bridging the digital divide among low income urban communities. Leveraging use of Community Technology Centers

To fully leverage the availability of the internet services in Kenya, all the citizens need to be able to access and use the internet and related services. The availability of 4G networks, cyber cafés and fiber connectivity in most residential areas of Nairobi has allowed many Nairobi residents to be part of its information-based society. But, as with the other existing social inequalities in Nairobi, many people residing in the city’s low-income areas lack access to the internet. This has a negative impact on the residents’ prospects as the governments and businesses are increasingly delivering their services online. Using a pre-tested questionnaire, data were collected from five hundred and fifty respondents on their internet access and digital literacy skills among the residents of the Mathare Slum. From the survey, the study found existence of limited digital literacy skills and lack of internet access among the residents of the Mathare Slum. The study then used the Community Technology Centers (CTCs) intervention approach to narrowing the digital divide by setting up a CTC in the Mathare Slum to offer free community internet access and digital literacy skills training. Eight cohorts, each of eighteen residents, were offered free digital literacy training for five weeks and free unlimited internet access for four months. The study then evaluated the trainees’ internet usage continuance intentions after four months of continued use of the internet at the CTC. The results indicate that perceived enjoyment, perceived usefulness, internet self-efficacy, and confirmation of expectations all significantly influence the participants’ satisfaction with use of the internet. The results also show that continuance intentions of the participants from low income household to continue using internet beyond the CTC can be predicted by perceived service cost, satisfaction, internet self-efficacy and perceived usefulness. The study demonstrates the effectiveness of CTCs as an intervention approach and a replicable model that can be used to bridge the urban digital divide among low income urban communities for the development of an all-inclusive information-based society. Implications and recommendations for policy, practice and research are provided.     

Geodemographic classifications, the digital divide and understanding customer take-up of new technologies

The imperatives of social cohesion make it necessary to consider the highly variable characteristics of users alongside the design and implementation of IT networks and services. In this context much has been written on the so-called ‘digital divide’ in society. Recent ESRC-funded research at UCL has illustrated how it is simplistic to think of the impacts of new information and communication technologies (ICTs) in terms of a single, or even small number of, ‘digital divides’. As developments in what has been termed the ‘e-society’ reach wider and more generalised audiences, so it becomes appropriate to think of digital media as having wider-ranging but differentiated impacts upon consumer transactions, information gathering and citizen participation. This paper describes the development of a detailed, nationwide household classification based on levels of awareness of different ICTs, levels of use of ICTs, and their perceived impacts upon human capital formation and the quality of life. It illustrates how geodemographic classification makes it possible to provide context for detailed case studies, and hence identify how policy might best improve both the quality and degree of society’s access to ICTs. We have provided a more detailed overview of the methodology elsewhere [1, 2] and here we also illustrate how the classification may be used to investigate a range of regional and sub-regional policy issues. A particularly innovative aspect of this classification is the Web resource hosted at www.spatial-literacy.org/esocietyprofiler. This site makes it possible to look at the classification system, aggregated to unit postcodes, across Great Britain. Users can look at national distributions for each of the groups and types in the classification, and offer feedback as to whether the classification appears to work for any locality.     

Technology literacy: A model for identifying abilities in telecommunications

To function well in the Information Age, one needs to understand the importance of being literate in telecommunications technology. Although academic programs concerned with telecommunications must address this need, rapid technical developments and applications make it difficult to identify abilities associated with technology literacy. This study created and tested a model with potential for generating an index of knowledge, skills, and attitudes perceived as important to the understanding of telecommunications technologies. The model's use is demonstrated in a survey of industry professionals, educators, and students. The results provide a potential basis for curriculum planning and reveal a pattern of relationships among the three profiles (industry, educator, student).     

Perception of Artificial Intelligence in Spain

This paper analyses the perception of Artificial Intelligence (AI) by individuals in Spain and the factors associated with it. It uses data from 6308 individuals from a 2018 Spanish survey. A binary logit regression model is formulated and estimated for the attitude towards robots and AI and its possible determinants. As main results are that a gender gap is detected, and that people have a negative attitude if they are not interested in scientific discoveries and technological developments and if AI and robots are not useful at work.