Human-machine communication cultures: Introduction

This review article examines two recent publications that explore the relationship between Artificial Intelligence (AI) and communication. Discussing Human–Machine Communication (HMC) as an emerging area of inquiry within communication and media studies, two important implications of this body of work are highlighted. First, the "human" component still plays a key role in HMC, since what we call “AI” derives from the technical and material functioning of computing technologies as much as from the contribution of the humans who enter in communication with AI technologies. Second, HMC challenges the very concept of medium, because the machine is at the same time the channel as well as the producer of communication messages. A potential way to solve this challenge is to mobilize existing approaches in media history and theory that expand the concept of medium beyond its conceptualization as mere channel.

The study of the Artificial Intelligence (AI) phenomenon has developed rapidly in recent years by placing various multi-disciplinary perspectives including Communication. The question then arises, how to study the AI phenomenon with a Communication approach? What kind of communication theories can be used to explain the AI phenomenon? Can the existing perspective of communication theory, which emphasizes the notion of communication as an interaction in which two communicators, using some medium of communication, move towards a better understanding of each other through the exchange of messages, still be used? Is the communication theory domain in terms of elements, levels and contexts of communication still relevant to studying the AI phenomenon? Is there a possibility of developing a new group of theories in studying AI phenomena?. This paper will provide an inspiring perspective on the development of a group of communication theories called "Beyond Human Communication" (Littlejohn, 2021). This broader view of communication includes interactions between humans and other animate and inanimate entities. It provides opportunities to examine different ways and different reasons for communicating. AI phenomena in the "Beyond Human Communication" theoretical domain can be explained through what is referred to as "human-machine communication". Understanding the theoretical domain of "Beyond Human Communication" places the study of the AI phenomenon into a special study in Communication science.

Introduction. Daya Kishan Thussu. Part I. Internationalizing Media Research 1. Why Internationalize Media Studies and How? 2. What Should Comparative Media Research Be Comparing? Towards a Transcultural Approach to 'Media Cultures' 3. Globalization Theories and Media Internationalization: A Critical Appraisal 4. Frames for Internationalizing Media Research 5. Media and Communication Studies Going Global. Part II. Broadening the Field of Media Studies 6. Globalizing Media Law and Policy 7. Changing Paradigms of Media Research and Practice in Contexts of Globalization and Terror 8. Comparative Media Law and Policy: Opportunities and Challenges 9. The Labouring of International Communication. Part III. Regional Perspectives on Internationalization 10. Asian Media Studies: The Struggle for International Legitimacy 11. Rethinking Chinese Media Studies: History, Political Economy and Culture 12. Media and Cultural Studies in the Arab World: Making Bridges to Local Discourses of Modernity 13. De-Sovietizing Russian Media Studies 14. Citizens' Media as Political Subjects: Case of Community Radio in Colombia. Part IV. Pedagogic Parameters: Internationalizing Media Syllabi 15. Internationalizing Media Ethics Studies 16. Media Studies as an Academic Discipline 17. International Media Studies in the US Academy: A Sampling of Programmes and Textbooks 18. Re-Conceptualizing Media Studies in Africa 19. The Internationalization of the Internet and its Implications for Media Studies.

This study investigates how news organizations perceive the integration of artificial intelligence (AI) technologies in news production, focusing on the synthesis of traditional journalistic values with AI advancements. By conducting a meta-analysis of 59 scholarly articles published between 2020 and 2024 in the field of journalism, the research examines the perceptions of journalists, editors, and decision-makers regarding AI. The primary research question explores the general findings of previous studies on journalists’ perceptions of AI in their workflows and the frameworks used to reconcile AI with journalistic values. The findings indicate that AI is regarded as a transformative tool, enhancing efficiency, effectiveness, and fostering a new organizational culture. However, it raises concerns about costs and job security. Attitudes toward AI are polarized, with optimism about efficiency gains and skepticism due to potential impacts on employment and ethical standards. Three theoretical models—field theory, human–machine communication, and the technology acceptance model—are employed to understand these dynamics, with field theory addressing power shifts and human–machine communication and the technology acceptance model examining human–AI interaction. To effectively integrate AI with journalistic values, the study proposes three strategies: AI technologists should embed journalistic ethics into their processes, journalists should acquire basic AI technical skills, and collaborative platforms should be established to bridge gaps between journalists and technicians. These strategies aim to create a balanced framework where AI-driven news production can uphold essential journalistic standards while embracing technological innovation.

This study aims to analyze the collaboration between Artificial Intelligence (AI) and journalists in online media using the Human-Machine Communication (HMC) approach. The research method used is a literature study. Data is processed using Miles and Huberman data analysis techniques. The results of this study indicate that AI is used in three primary stages of journalism: news gathering, news production, and news distribution. At the news gathering stage, AI assists journalists in collecting news materials from various sources and analyzing audience interest in specific topics. AI is used in news script creation, editing, and proofreading at the news production stage. AI chatbots and NLP programs help with automatic news writing and factual verification. Meanwhile, at the news distribution stage, AI is used for content personalization, news recommendations, and SEO optimization in online media. From the HMC perspective, collaboration between AI and journalists can be conceptualized as a unidirectional and two-way process. Collaboration between AI and journalists in a social context also occurs at the micro, meso, and macro levels, where interactions between humans and machines affect the social situation, the immediate reality of individuals, and the structure of society as a whole.

Artificial intelligence usage in the communication field is of strategic importance. However, most communication practitioners and academicians have not noticed the gains in momentum substantially artificial intelligence. Through communication journals, this study aims to examine how artificial intelligence is used, its effects, and how important it is in communication. This study was designed as a content analysis and bibliometric analysis study. The sample of this study is AI-based articles in Web of Science Q1 indices communication journals. It selected and examined the first sixteen journals in communication keyword search based on SCImago Journal & Country Rank. This study revealed artificial intelligence usage in the communication industry and field, in addition to AI's impact and significance and AI-based technologies in communication. It was found that the most used method for artificial intelligence-based articles in communication journals was the semi-structured interview method. It is seen that common keywords in AI-based articles and communication journals are announced as human-machine communication, machine learning, artificial agent, artificial intelligence, bias, and social media concepts. In this study, a positive correlation between communication science and artificial intelligence technologies was observed. This study contributes to new studies on artificial intelligence, communication, the impacts of artificial intelligence on communication, new communication technologies, generative AI, human-machine communication, and other related areas.

As machines are becoming more interactive, such as Artificial Intelligence (AI) agents, the importance of interactions between humans and AI increases as a new type of communication. However, unlike most studies have examined the influence of AI on individuals, fewer studies about how human-AI interactions will impact society have been conducted. It should be acknowledged that we attribute social roles to AI when assigning social tasks, and there are power dynamics within an interaction between humans and AI because of it. Also, we should ask whether the current society is ready for AI to take responsibility for its actions. Finally, limitations on existing human-machine communication (HMC) studies, an unclear definition of AI as an interlocutor and a lack of theoretical frameworks, were pointed out with suggestions. It is expected that considering a machine’s social roles and powers in human-AI interactions will broaden the theoretical realm of HMC.

Existential threats to human work and leadership have been expressed over intensifying human-machine communication, and the development of robots and artificial intelligence (AI). Yet popular texts and techno-centric approaches to AI assume a flat ontology in human-machine communication which obscures power relations governing new technologies, necessitating a bounded automation approach integrating socio-economic influences that shape AI diffusion in distinctive occupational settings. This article advances three critical lines of enquiry to interrogate abstract labor displacement propositions by contextualizing human authority and communication in spiritual work. By explicating the dynamic and relational ways in which clerics strategically manage emerging social robotics, discussion of the case of ‘the world’s first robot monk’ illustrates how organizational leaders can influence AI agents to (re)produce values and cultural realities. In the process, priests strengthen normative regulation of power by aligning epistemic knowledge shared about AI and during human-machine communication to extant understandings of collective ideals.

Amid mounting interest in artificial intelligence (AI) technology, communication scholars have sought to understand humans’ perceptions of and attitudes toward AI’s predictions, recommendations, and decisions. Meanwhile, scholars in the nascent but growing field of explainable AI (XAI) have aimed to clarify AI’s operational mechanisms and make them interpretable, visible, and transparent. In this conceptual article, we suggest that a conversation between human–machine communication (HMC) and XAI is advantageous and necessary. Following the introduction of these two areas, we demonstrate how research on XAI can inform the HMC scholarship regarding the human-in-the-loop approach and the message production explainability. Next, we expound upon how communication scholars’ focuses on message sources, receivers, features, and effects can reciprocally benefit XAI research. At its core, this article proposes a two-level HMC framework and posits that bridging the two fields can guide future AI research and development.

The study for the first time endeavours to elucidate the distinct conceptual nuances of AI-driven journalism, exploring how it reshapes the core technological and communicative attributes of the field while influencing societal dynamics. The crisis within AI-driven human-machine interaction in journalism rooted in the essence and processing of information is defined. Despite the paradigm of journalism is rooted in a human-centered approach, its AI-driven paradigm is the same - but in a reversible mode. Journalism involves the translation of personal perspectives and experiences through the filter of memory. Algorithms function without the nuances of personal and social memory, thereby undermining the core principles of the journalistic profession. The loss of genuine, “analog” memory among journalists and their audiences, alongside the digital “memory” of algorithms, jeopardizes the fundamental societal role of journalism-upholding social order. Re-thinking the AI phenomenon as artificial communication, the authors propose the term “artificial journalism”. At the basic technological level it is based on various forms of automation and embedded within digital infrastructures; at the societal level it is designed for the central purpose of journalism and entangled with human practices. Both the levels are reversible. The term could serve as an umbrella term for all the AI-driven journalism activities. Also it removes contradictions not only in human-machine communication but clarify the essence of AI performance in journalism and media studies, and for the users. The emergence of AI-driven media practices opens the basic crisis conceptual contradictions which provokes new realms of research and necessitates the establishment of critical AI media studies.

This article explores the evolution of approaches in English language teaching, starting from traditional approaches, communicative approaches, and culminating in the integration of Artificial Intelligence (AI)-based approaches. Traditional approaches, which emphasize linguistic structures and forms, have proven insufficient in achieving the main goal of language education—enhancing students’ oral and written communication skills. As a response, the communicative approach emerged, focusing on meaningful language use in real contexts and centering learners as active participants in the learning process. Over time, the communicative approach has been enriched by the integration of AI, which offers personalization, interactivity, and efficiency through tools such as chatbots, virtual assistants, and automated evaluation systems. AI enables more adaptive learning, instant feedback, and a more authentic language learning experience. Nevertheless, integrating AI into language education also presents challenges, including technological accessibility gaps, the need for teacher training, and concerns regarding data ethics. This article concludes that a hybrid model combining communicative and AI-based approaches can create more effective and relevant English language instruction in the digital age, provided it is supported by inclusive educational policies and well-prepared human resources

Semiotics, Media Studies and Communication Studies are three closely interlinked fields. Briefly stated, Semiotics, the science of signs, looks at how humans search for and construct meaning; Communication Studies is concerned with how meaning is conveyed; and Media Studies considers the ways in which messages are transmitted and received. This dictionary is designed to help students and general readers unlock the significance of the terminology and jargon commonly used in these fields. Being interdisciplinary in nature, Semiotics, Media, and Communication Studies are cluttered with notions derived from other disciplines. Hence, this dictionary also encompasses basic concepts from the fields of anthropology, archaeology, psychology, psychoanalysis, linguistics, philosophy, artificial intelligence, computer science, and biology. Collected here are the terms, concepts, personages, schools of thought, and historical movements that appear frequently in the relevant literature. The basis of each entry is a simple definition, which often includes the term's origin. Illustrations are provided where necessary, along with historical sketches of movements or schools of thought. The commentary on personages consists of brief statements about their contribution and relevance. Thus, the dictionary not only defines what a term means, but often goes into its history, applications, and broad implications. Terms are cross-referenced and their etymology is given where possible. This is a compact, practical research manual that will relieve much tension for students in semiotics and related fields. Because of its interdisciplinary approach, it will also provide a range of scholars with a handy reference to disciplines distinct from but related to their own.

Introduction. The article presents the rationale for identifying a special subject area in human-machine communication research – studying it as a social role interaction. Key provisions for describing the relational mechanism for the emergence of social roles in the performance of human-machine communication agents are formulated. Data on expert examinations of the use of artificial intelligence technologies in human-machine communication are used.Methodology and sources. The study is based on the relational paradigm of explaining the nature of the phenomenon of social roles in human-machine communication, arising and constructed exclusively in the space of their interactions. For conceptualization, the concepts of social role, role simulation, role imitation, imitation, assimilation, relation, situational action are proposed. Expert reports on the study of human communications with artificial intelligence devices were used as sources.Results and discussion. It has been established that human social roles and machine functions are formed in the process of mutual simulation, imitation, emulation and assimilation taking into account the situation. A person as a communicator is included in the performance of two roles, but performs one of them, which arises in communication. Two roles are combined into one – a social role, which can be performed only by both participants together and in a special hybrid format of communication. The nature of the sociality of these roles is in the communication situation.Conclusion. The relational mechanism of the emergence of social roles in the performance of a person and a machine is manifested in a change in human behavior and a modification of machine functions. When performing social roles, technomorphization of human behavior and anthropo(socio)morphization of machine functioning occur. A person rethinks the role of a communicator, changing its meaning upon contact with the technical form of activity of the machine-communicator. The role turns into a synthesis of anthropo- and technomorphic manifestations. The machine begins to be present as an agent and declares itself by demands to take into account its specificity. A person strives not to lose the social basis of his their behavior, and at the same time is forced to adapt to the options of the machine.

The article presents the theoretical foundations for studying the cultural and linguistic environment as an object of public administration in the context of socio-cultural transformations. It analyzes the conceptual and categorical framework that defines the cultural and linguistic environment as a component of the socio-cultural system, which serves as the foundation for communicative interaction, individual socialization, and the reproduction of cultural norms and values within society. The study examines the influence of the cultural and linguistic environment on socio-cultural transformations in Ukraine amid globalization challenges and European integration. Key theoretical approaches and contributions of prominent scholars–such as E. Tylor, P. Bourdieu, and J. Habermas–are considered, highlighting the multidimensional nature of culture and the role of language in shaping social identity and communication. The research establishes that the cultural and linguistic environment reflects societal processes and actively contributes to the formation of new models of civic identity, political culture, educational systems, and media practices. A multi-level structure of the cultural and linguistic environment is proposed, encompassing individual, group, and institutional levels. The institutional level captures the influence of governmental, educational, cultural, and media institutions, which shape policies aimed at preserving and developing linguistic and cultural diversity. The group level reflects the interactions of social communities, ethnic and linguistic groups, where intercultural dialogue occurs and collective identity is constructed. At the individual level, the cultural and linguistic environment shapes processes of self-identification, worldview formation, and linguistic identity. The article substantiates mechanisms of public influence on socio-cultural transformations, with a central role played by language policy, educational programs, media spaces, and legal regulation of cultural activity. These mechanisms help preserve cultural uniqueness while promoting adaptation to new societal challenges and integration into the European socio-cultural space. The need for a balanced approach between preserving national cultural heritage and openness to intercultural dialogue is emphasized, as it is essential for Ukraine's adaptation to European value-normative standards.

In this article, we argue that journalism studies, and particularly research focused on automated journalism, has much to learn from Human-Machine Communication (HMC), an emerging conceptual framework and empirically grounded research domain that has formed in response to the growing number of technologies—such as chatbots, social bots, and other communicative agents enabled by developments in artificial intelligence (AI)—that are designed to function as message sources, rather than as message channels. While the underlying, but often unquestioned, theoretical assumption in most communication research is that humans are communicators and machines are mediators, within HMC this assumption is challenged by asking what happens when a machine steps into this formerly human role. More than merely a semantic move, this theoretical reorientation opens up new questions about who or what constitutes a communicator, how social relationships are established through exchange among humans and machines, and what the resulting implications may be for self, society, and communication. In the particular case of automated journalism—in which software assumes a news-writing role that has long been considered a distinctly central, and indeed human, element of journalism—the introduction of HMC offers a generative starting point for theory development, advancing our understanding of humans, machines, and news for an oncoming era of AI technologies.