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Digital Transformation and Internationalization in Higher Education: A Sociological Study of Artificial Intelligence at Mohamed I University, Morocco
Abstract
The topic of digital technology is considered a wide and primary motivator of cultural capital development in the academic field. The tangible progress of digital technology as an open social framework that supports students’ knowledge development and facilitates their integration into the scientific system. This chapter aims to study the future dimensions in the scientific field in the light of the rapid development of digital technology, and to understand the extent of artificial intelligence’s contribution to the production and reproduction of cultural capital and scientific authority in the scientific field, using a qualitative methodology and the techniques of observation and structured interview with students from Mohammed I University in Oujda, Morocco. Through this sociological study, it has been concluded that artificial intelligence enhances the cultural capital of students in the scientific field, and that the possibility of a new balance of scientific authority in the scientific field due to artificial intelligence is very low.
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Digital transformation has been one of the most studied phenomena in information systems (IS) and organizational science literature. With novel digital technologies emerging at a growing pace, it is important to understand what we have learned in over three decades of research and what we still need to understand in order to harness the full potential of such digital tools. In this chapter, we present a brief overview of digital transformation and develop a conceptual framework which we use as a basis of discussing the extant literature. The conceptual framework is also used as a means of positioning the empirical chapters presented in the rest of this edited volume. Finally, we discuss the role of context in digital transformation and identify some differences that span industry, domain, size class, and country of operation.
Different people have different perceptions about artificial intelligence (AI). It is extremely important to bring together all the alternative frames of thinking—from the various communities of developers, researchers, business leaders, policymakers, and citizens—to properly start acknowledging AI. This article highlights the ‘fruitful collaboration’ that sociology and AI could develop in both social and technical terms. We discuss how biases and unfairness are among the major challenges to be addressed in such a sociotechnical perspective. First, as intelligent machines reveal their nature of ‘magnifying glasses’ in the automation of existing inequalities, we show how the AI technical community is calling for transparency and explainability, accountability and contestability. Not to be considered as panaceas, they all contribute to ensuring human control in novel practices that include requirement, design and development methodologies for a fairer AI. Second, we elaborate on the mounting attention for technological narratives as technology is recognized as a social practice within a specific institutional context. Not only do narratives reflect organizing visions for society, but they also are a tangible sign of the traditional lines of social, economic, and political inequalities. We conclude with a call for a diverse approach within the AI community and a richer knowledge about narratives as they help in better addressing future technical developments, public debate, and policy. AI practice is interdisciplinary by nature and it will benefit from a socio-technical perspective.
The interest of this research is to investigate technological change, new literacies and learning processes which impact future learning. With technological determinism, the members of the university need to have technological knowledge, belief of change and adopt the technology. The problem in this research is the habits in the individual who works within our campus that would not change, because with the new literacies used and introduced in communication, besides learning in using online systems will continue to be implemented. The research sampling is conducted of 76 respondents, consisting of students, lecturers, employees, staff and technicians. And this research method uses is quantitative methods and semi-structured qualitative methods. The result obtained that there are members of campus who are willing to change in communication and the ways of thinking and acting to follow the change in future learning 4.0 industrial revolution 4.0.
Social sciences have been always formed and influenced by the development of society, adjusting the conceptual, methodological, and theoretical frameworks to emerging social phenomena. In recent years, with the leap in the advancement of Artificial Intelligence (AI) and the proliferation of its everyday applications, “non-human intelligent actors” are increasingly becoming part of the society. This is manifested in the evolving realms of smart home systems, autonomous vehicles, chatbots, intelligent public displays, etc. In this paper, we present a prospective research project that takes one of the pioneering steps towards establishing a “distinctively sociological” conception of AI. Its first objective is to extract the existing conceptions of AI as perceived by its technological developers and (possibly differently) by its users. In the second part, capitalizing on a set of interviews with experts from social science domains, we will explore the new imaginable conceptions of AI that do not originate from its technological possibilities but rather from societal necessities. The current formal ways of defining AI are grounded in the technological possibilities, namely machine learning methods and neural network models. But what exactly is AI as a social phenomenon, which may act on its own, can be blamed responsible for ethically problematic behavior, or even endanger people’s employment? We argue that such conceptual investigation is a crucial step for further empirical studies of phenomena related to AI’s position in current societies, but also will open up ways for critiques of new technological advancements with social consequences in mind from the outset.
Actor–network theory (ANT) began at the end of the 1970s as an attempt to account for scientific activity without distinguishing a priori between its so-called social and technical aspects. The concept of actor–network captures the idea that for any actor to act, many others must act as well. In other words, action is shared with a multitude of people and things – for, indeed, things play a part in our collective lives. Actors, whether individual or collective, whether human or not, are therefore a mystery whose constitution must be explained; they are not at all the obvious starting point of action. Those few premises have had a significant impact on some organizational communication scholars, in particular those interested in interorganizational networks and partnerships, in questions of agency, or in the ability of communication to constitute organizations.
This paper examines the way some current artificial intelligence (AI) programs absorb and redefine social practices when deployed in setting where knowledge and intelligence are decisive. Two areas of AI research and development are discussed: expert systems and frame-based natural language processing. Successful performance of AI programs in these areas comes to depend on conditions for knowledge in contemporary society that are the subject of sociological analysis. The design-elements of AI technology are also seen to reflect features of contemporary social organization. While the computerization of society is frequently identified with an interest in social control, AI is shown to have affinities with postmodernist accounts of society stressing social fragmentation and cultural discontinuity. /// Le présent document traite de la façon dont certains programmes courants d'intelligence artificielle (IA) assimilent et redéfinissent les habitudes sociales lorqu'ils sont déployés dans des milieux où le savoir et l'intélligence ont une grande importance. Deux domaines de recherche et développement sont présentés: les systèmes experts et le traitement des langues naturelles sur unité centrale. L'exécution efficace des programmes IA dans ces secteurs repose sur les conditions qui déterminent l'intelligence dans la société contemporaine, qui font l'objet d'analyses sociologiques. Les rubriques utilisées pour la conception de la technologie IA semblent de même reflèter certaines caractéristiques de l'organization sociale contemporaine. Bien que l'informatisation de la société soit identifée comme intervenant pour le contrôle social, nous identifions les affinités de l'IA avec les descriptions post-modernes de la société, lesquelles mettent en lumière la fragmentation sociale et la discontinuité culturelle.
The scientific field.
The seemingly "pure" and "disinterested" universe of science is a social field like any other, with its power relationships and monopolies, its conflicts and strategies, its interests and profits. A kind of game whose particular stakes consist in the monopoly of scientific authority (prestige, recognition, fame and so forth), the scientific field owes its main cha racteristics to the fact that the producers generally have no other possible clients than their direct competitors. For this reason, the latter are the least inclined to accord scientific value to the products offered without first subjecting them to examination. What is always at stake in scientific conflicts, in which each of the actors must engage in order to have the value of his products accepted, is the power of imposing the definition of science best conforming to his own individual interests ; for the definition of what is at stake is itself part and parcel of the stakes in such a conflict. And the form taken by this struggle over scientific legitimacy depends on the structure of the distribution of the specific capital of scientific recognition among the participants. The history of science shows that as the accumulated scientific ressources grow scientific competition tends to assume the form of constant series of minor revolutions rather than that of intermittent great revolutions, and that along with this change the difference between the conservative strategies of the dominant members of the field and the subversive strategies of those first entering it ("the challengers") seems to diminish. Accordingly, the fundamental question which arises for scientific sociology of science is that of defining the social conditions that must be fulfilled for social game to be established in which true ideas possess great force because the participants have an interest in the truth rather than as in other games in the preservation of their interests. Science has no other foundation that the collective belief in its foundations, a belief which is both the result and the presupposition of the very functioning of the scientific field. But depending on the degree of autonomy of the scientific field under consideration with respect to external determinative factors, the proportion of social arbitrariness incorporated in the particular system of presuppositions generating belief can vary widely. In the case of the social sciences progress towards the real autonomy which is the condition of self-regulating and self- sufficient scientific field comes up against obstacles unknown elsewhere.
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