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Increasingly, groups external to educational systems are offering time, expertise and products, creating an intricate web of educational governance where entities outside of formal education contribute to state-funded education systems. While this involvement and its motivations have been considered in the literature, it has been less common to explore these interactions between school systems and outside organizations as they relate to the transition from the knowledge economy to the intelligent economy. Such research is important to understand the numerous inputs to education, which can then inform future decision-making. This study traces scripts around the commodification of knowledge, which connects education to individual employability or the economy and cyborg dialectic, or the mutual relationship between humans and technology. These scripts intersect to contribute to the perpetuation of data creation and usage as part of the educational intelligent economy. The scripts traced here originate from Battelle, a primarily a Ohio-based research and development organization, also focused on classroom teaching and learning, specifically in STEM (Science, Technology, Engineering and Mathematics) education. Mapping scripts related to the commodification of knowledge and the cyborg dialectic indicates promotion of the intelligent economy broadly and individually for Battelle itself across Ohio and beyond, through investments in educators, students and policy-makers but also Battelle’s potential employees and collaborators. This data-focus creates an educational intelligence not only in students, teachers and policy-makers but also in Battelle itself, legitimating it as an actor in education.

The digital technological revolution offers new ways for classrooms to operate and challenges the concept of whether brick and mortar schools should exist at all. At the same time, the changes to society as we move from a knowledge-based economy to an intelligent and innovation-based economy challenges us to reassess the purpose of education. This chapter investigates an overarching counterfactual question, “What if compulsory schooling was invented in the twenty-first century”? We used a foresight methodology, based on “anticipation,” to conceptualize possible models for a future system of compulsory schooling arising from an analysis of contemporary catalysts for remodeling. While anticipation does not predict the future, the concept is that when a current system and a model of a system interplay, they impact each other to change both the present as well as possible futures. The design principles of cities, such as Freiburg (Germany), Poundbury (England), and Christie Walk (Australia), which have been developed around the idea of ecologically sustainable and decentralized cities, are focused on approaches to living that can provide a springboard for exploring the impact of changing employment, economic, technological, and social change on future schooling models. Magnetic Resonance Imaging (MRI) has opened up a new field of study to investigate neuroscience, which can inform teaching practice. Postmodern and indigenous ways of thinking provide different insights about how schooling might be reconceptualized. Alternative models of future schooling are conceptualized about (i) the role of the learner and teacher, (ii) design of a school, and (iii) the purpose of compulsory schooling. For each area of remodeling, deviations to current practices as well as paradigm shifts are framed as part of scenario building. Related questions include: how schooling might be different if it had been created today for the first time? How might it better meet the needs of contemporary society? What aspects of schooling now might be lost if it was only invented in the twenty-first century? What are possible side effects from any change ideas as part of research practice? A vital aspect of this chapter is to explore the concept of learning as a general concept versus the more specific concept of schooling. We are at the precipice of a new vision of schooling based on a counterfactual way of thinking about the future of schooling as we have known it in the West.

This chapter introduces the concept of an intelligent organization in the context of the twenty-first-century knowledge economy. An intelligent organization is one in which individuals behave intelligently, work is grounded in intelligent methods and choices, and rich stocks of intelligence in the form of knowledge capital to support intelligence work and choices. Intelligence is defined as both a thing and attribute and behavior and way of working. The chapter also highlights examples of intelligent behaviors and or organizational pathologies. The chapter also highlights the importance of becoming aware of intelligent and unintelligent choices.

The implications and impacts of the educational intelligent economy from the vantage point of digital frontierism is explored using a decolonial framework, with a specific focus on Big Data and data sharing in Comparative and International Education (CIE). Recent debates are reviewed about CIE’s past histories and its current directions to tease out their implications for data sharing. The authors demonstrate how data sharing continues to reinforce imperialism through control, dissemination, and application of data, and how electronic and digital colonialism preserve current intellectual and structural hegemonies. Then, we give an example of how donors and funding agencies, including the National Science Foundation, engage in neoliberal scientism and control of data, and how it affects the future of social sciences, including CIE. Our inquiry is at the intersections of economic intelligence and educational intelligence in a rapidly evolving technocentric, data-dominated, and networked economy. The authors demonstrate how educational intelligence in the global economy may exacerbate the asymmetric access to data between the global North and the South, as educational data are increasingly becoming global commodities to be traded between various public and private actors. Finally, the authors argue that decolonial participatory research designs that aim at positive, sustained transformations, as opposed to the stagnancy of Big Data and data mining, should be used to address the problems inherent to the Educational Intelligent Economy.

Educational intelligence can be considered a prized asset in political actors’ careful calculations in setting policy agendas for radical educational transformations in the age of the Fourth Industrial Revolution characterized by Big Data, Artificial Intelligence (AI), machine learning, and the Internet of Things (IoT). As an agent of globalization, the European Union (EU) is uniquely positioned to steer the direction of this new wave of digital technologies for two cardinal objectives in the EU’s rhetorical discourse: social cohesion and economic prosperity. Conversely, its complex governance architecture, which restricts its role in educational policy, tempers its ability to drive policy reforms in education for the strategic and coordinated deployment of Big Data in educational systems to support those twin objectives. This chapter examines this burgeoning policy arena in the European Union by interrogating the most recent policies on the “data economy” enacted at the EU-level and the positionality of education in this newest wave of policy formulation. A content and discourse analysis of policy documents on Big Data reveals that the EU is launching multiple initiatives to regulate these novel technologies across its socio-economic sectors. However, the amorphous nature and unpredictable impact of these technologies, along with the jurisdictional barriers in the education sector stemming from the delimitation of governance layers in the EU, pose difficulties in generating a coordinated approach to policy implementation to engender tangible results. Hence, the contours of an educational intelligent economy in the EU needs considerable policy attention and technical resources in its transition from the current ideational stage to its concrete manifestation.

The authors intend to expand the literature on the relationship between intelligent technology and human resources in operating cost, and firm value of financial institutions in emerging markets by integrating the influence of intelligent technology and contribute to a growing body of literature on the determinants of firm value.

This paper empirically investigates the impact of intelligent technology investment on employment compensation and firm value using a sample of 86 listed financial institutions in China from 2010 to 2019.

This paper reports robust evidence that an increase in intelligent technology investment has a significantly negative effect on employment compensation in financial institutions. In addition, this inhibitory effect is persistent. The increase in intelligent investment has a significant two-year lag effect on firm value, which is positive and sustained. This indicates that intelligent technology investment has a short-term “useless” effect but brings long-term “gains” for Chinese financial institutions.

These findings may shed light on the decision-making processes of financial institutions, which helps practitioners better understand that firms need to reasonably deal with the subsequent cost of growth caused by intelligent technology input. Alternatively, they may wish to select the appropriate accounting method of depreciation or amortization to smooth its impact.

Almost every detail of our lives – where we go, what we do, and with whom – is captured as digital data. Technological advancements in cloud computing, artificial intelligence, and data analytics offer the education sector new ways not only to improve policy and processes but also to personalize learning and teaching practice. However, these changes raise fundamental questions around who owns the data, how it might be used, and the consequences of use. The application of Big Data in education can be directed toward a wide range of stakeholders, such as educators, students, policy-makers, institutions, or researchers. It may also have different objectives, such as monitoring, student support, prediction, assessment, feedback, and personalization. This chapter presents the nuances and recent research trends spurred by technological advancements that have influenced the education sector and highlights the need to look beyond the technical boundaries using a socio-semiotic lens. With the explosion of available information and digital technologies pervading cultural, social, political as well as economic spaces, being a lifelong learner is pivotal for success. However, technology on its own is not sufficient to drive this change. For technology to be successful, it should complement individual learning cultures and education systems. This chapter is broadly divided into two main sections. In the first section, we contemplate a vision for the future, which is deemed possible based on ongoing digital and computing advancements. The second section elaborates the technological, pedagogical, cultural, and political requirements to attain that vision.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.