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This research theorizes the condition of human beings reduced to being users (and only users) in human-computer interaction (HCI), a condition that favors them becoming objects or targets of commercial dark patterns, racialized profiling algorithms, generalized surveillance, gendered interfaces and heteromation.

The reconceptualization of the users’ condition is done by confronting HCI theories on users with a dialectical-existential perspective over human ontology. The research is presented as a conceptual paper that includes analyzing and revising those theories to develop a conceptual framework for the user oppression in HCI.

Most HCI theories contribute to the user oppression with explicit or implicit ontological statements that denies their becoming-more or the possibility of users developing their handiness to the full human potential. Put together, these statements constitute an ideology called userism.

HCI needs to acknowledge its role in structuring oppression not just in sexism, racism, classism and ableism, but also the specific relation that pertains to HCI: userism. Similar to other fields, acknowledging oppression is the first step toward liberating from oppression.

The user is an existential condition for HCI theories, yet few theories can explain in depth how this condition affects human development. From the dialectical-existential perspective, the user condition can be dehumanizing. Computers may intensify existing oppressions through esthetic interactions but these interactions can be subverted for liberation.

The purpose of this paper is to examine how types of virtual brand community (VBC) benefits influence VBC loyalty through specific types of interaction.

The study targeted 250 brand community users to conduct an empirical analysis using SPSS 19.0.

Consumers’ perceived benefits (functional, experiential, and symbolic) were found to be the leading variables in inducing consumer loyalty. Brand community managers should not focus only on the benefits offered by the brand community, but also on how these benefits can be associated with human-to-computer and consumer-to-consumer (C2C) interaction.

The virtual community (VC) has an important role as a marketing tool. As the VC within the virtual space has gradually been increasing, its importance has grown as well, therefore making research studies on heightening members’ brand community site loyalty important.

This study broadens and contextualizes our understanding of what type of VBC interaction can be further activated in the process of enhancing the members’ VBC loyalty, which is affected by consumers’ perceived benefits.

To outline how psychology as one of the original approaches to human‐computer interaction (HCI) has formed a key part of the HCI literature, and to discuss the need for psychological approaches to HCI and system development.

The contributions to the journal Human‐Computer Interaction is examined from the journal's start in 1985 up to the millennium. The analysis focuses the three main elements, task, user and computer, in the classic study “Psychology of human‐computer interaction” from 1983.

Provides information about authorship, and form and focus of research published. The paper concludes that already from the beginning, HCI researchers too narrowly used Card et al.'s analytical framework. Today it has developed into a sub‐theory within a multidisciplinary HCI science and in this role it continues to be an important cumulative factor in HCI.

The main conclusion about the role of psychology in HCI only applies to the mainly US authors who published in the journal investigated in the given period. European research focusing on information technology and people may differ in important ways.

A much needed discussion of a central document of historical importance tying together many HCI researchers and a range of HCI studies.

This paper fulfils partly the need for meta‐analyses of the psychological approach to HCI.

The purpose of this paper is to explore characteristics of human‐computer interaction when the human body and its movements become input for interaction and interface control in pervasive computing settings.

The paper quantifies the performance of human movement based on Fitt's Law and discusses some of the human factors and technical considerations that arise in trying to use human body movements as an input medium.

The paper finds that new interaction technologies utilising human movements may provide more flexible, naturalistic interfaces and support the ubiquitous or pervasive computing paradigm.

In pervasive computing environments the challenge is to create intuitive and user‐friendly interfaces. Application domains that may utilize human body movements as input are surveyed here and the paper addresses issues such as culture, privacy, security and ethics raised by movement of a user's body‐based interaction styles.

The paper describes the utilization of human body movements as input for interaction and interface control in pervasive computing settings.

The purpose of this study is to achieve multi-variety and small-batch assembly through direct cooperation between equipment and people and to improve assembly efficiency as well as flexibility.

Firstly, the concept of the human–computer interaction is designed. Secondly, the machine vision technology is studied theoretically. Skin color filter based on hue, saturation and value color model is put forward to screen out images that meet the skin color characteristics of the worker, and a multi-Gaussian weighted model is built to separate moving objects from its background. Both of them are combined to obtain the final images of the target objects. Then, the key technology is applied to the smart assembly workbench. Finally, experiments are conducted to evaluate the role of the human–computer interaction features in improving productivity for the smart assembly workbench.

The result shows that multi-variety and small-batch considerable increases assembly time and the developed human–computer interaction features, including prompting and introduction, effectively decrease assembly time.

This study proves that the machine vision technology studied in this paper can effectively eliminate the interferences of the environment to obtain the target image. By adopting the human–computer interaction features, including prompting and introduction, the efficiency of manual operation is improved greatly, especially for multi-variety and small-batch assembly.

This research investigates the means of tacit knowledge (TK) communication between the designer and the computer in architectural design. Despite the integration of state-of-the-art computational technologies in different design phases, this integration happens within a limited scope, focusing mainly on tangible aspects of the design process, such as technical systems and visual representations. This lets architectural design miss the wider scope technology provides, where it can help in developing the computational design process through incorporating new intangible knowledge domains that were usually neglected, such as tacit knowledge, and through incorporating more design entities that were not included in the design process before.

The study conducts an interdisciplinary analytical review of the literature to achieve two main research goals. The first goal investigates TK communication between human beings and the second understands approaches of TK communication between humans and computers. For each goal, three phases were implemented; an initial research phase, where main keywords are identified, a sampling and selection of literature phase and an analysis of literature phase.

Through interlinking findings from different disciplines, the study presents a theoretical framework for TK communication. The framework provides architects with an approach to construct and transfer TK while using the computer in a computational design environment, presenting an individual and a social set of conditions and factors revealed from the review of the analyzed literature. The framework particularly emphasizes the significance of a human–computer symbiotic relationship for the process of TK communication to take place.

This paper presents a novel interdisciplinary reading into the literature of fields beyond architectural design, incorporating intangible knowledge domains into the computational design process and expanding the capabilities of computational design tools to allow for the transfer of intangible design attributes between different design entities, particularly tacit design knowledge.

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

The concept of ubiquitous assimilation in e-commerce, denoting the seamless integration of technologies into customer shopping experiences, has played a pivotal role in aiding e-satisfaction and, consequently, fostering patronage intention. Among these, text-based chatbots are significant innovations. In light of this, the paper aims to develop a conceptual framework and comprehend the patronage behaviour of artificial intelligence-enabled chatbot users by using chatbot usability cues and to determine whether the social presence and flow theories impact e-satisfaction, which leads to users’ patronage intention. The current research provides insights into online travel agencies (OTAs), a crucial segment within the travel and tourism sector. Given the significance of building a loyal clientele and cultivating patronage in this industry, these insights are of paramount importance for achieving sustained profitability and growth.

The research framework primarily focused on the factors that precede e-satisfaction and patronage intention among chatbot users, which include social presence, flow, perceived anthropomorphism and need for human interaction. The researchers collected the data by surveying 397 OTA chatbot users by using an online questionnaire. The data of this cross-sectional study were analysed using covariance-based structural equation modelling.

Findings reveal that e-satisfaction is positively linked with patronage intention and the variables of social presence and flow impact e-satisfaction along with chatbot usability cues. There were direct and indirect relations between chatbot usability and e-satisfaction. Moreover, the personal attributes, “need for human interaction” and, “perceived anthropomorphism” were found to moderate relations between chatbot usability cues, social presence and flow.

The impact of chatbot’s usability cues/attributes on e-satisfaction, along with perceived attributes – social presence and flow in the realm of OTAs contributes to the human–chatbot interaction literature. Moreover, the interacting effects of perceived anthropomorphism and the need for human interaction are unique in the current contextual relations.

Artificially intelligent (AI) assistant-enabled smart speaker not only can provide assistance by navigating the massive amount of product and brand information on the internet but also can facilitate two-way conversations with individuals, thus resembling a human interaction. Although smart speakers have substantial implications for practitioners, the knowledge of the underlying psychological factors that drive continuance usage remains limited. Drawing on social response theory and the technology acceptance model, this study aims to elucidate the adoption process of smart speakers.

A field survey of 391 smart speaker users were obtained. Partial least squares structural equation modeling was used to analyze the data.

Media richness (social cues) and parasocial interactions (social role) are key determinants affecting the establishment of trust, perceived usefulness and perceived ease of use, which, in turn, affect attitude, continuance usage intentions and online purchase intentions through AI assistants.

AI assistant-enabled smart speakers are revolutionizing how people interact with smart products. Studies of smart speakers have mainly focused on functional or technical perspectives. This study is the first to propose a comprehensive model from both functional and social perspectives of continuance usage intention of the smart speaker and online purchase intentions through AI assistants.