Human–Computer Integration: Towards Integrating the Human Body with the Computational Machine

Human–computer integration is an HCI trend in which computational machines can have agency, i.e., take control. Our work focuses on a particular form of integration in which the user and the computational machine share agency over the user's body, that is, can simultaneously (in contrast to a traditional turn-taking approach) control the user's body. The result is a user experience where the agency of the user and the computational machine is so intertwined that it is often no more discernable who contributed what to what extent; we call this “intertwined integration”. Due to the recency of advanced technologies enabling intertwined integration systems, we find that little understanding and documented design knowledge exist. To begin constructing such an understanding, we use three case studies to propose two key dimensions (“awareness of machine's agency” and “alignment of machine's agency”) to articulate a design space for intertwined integration systems. We differentiate four roles that computational machines can assume in this design space (angel, butler, influencer, and adversary). Based on our craft knowledge gained through designing such intertwined integration systems, we discuss strategies to help designers create future systems. Ultimately, we aim at advancing the HCI field's emerging understanding of sharing agency.

Human-Computer Integration (HInt) is a growing paradigm within HCI which seeks to understand how humans can, and already are, merging with computational machines. HInt’s recent inception and evolution has seen much discussion in a variety of symposiums, workshops, and publications for HCI. This has enabled a democratized and decentralised emergence of its core concepts. While this has allowed for rapid growth in our understanding of HInt, there is some discrepancy in how the proponents of this movement might describe its principles, motivations, definitions, and ultimate goals, with many offshoot concepts of HInt beginning to emerge. SIGHint aims to provide a platform to facilitate high level discussion and collation of information between researchers and designers seeking to learn from and contribute to the development of Human-Computer Integration. It is our intention that through this SIG we may better understand how new and emerging, diverging ideas, and perspectives within Human-Computer Integration relate to each other, ultimately facilitating a mapping of the paradigm and a synthesis of its concepts.

Human–computer integration is an emerging area in which the boundary between humans and technology is blurred as users and computers work collaboratively and share agency to execute tasks. The sense of agency (SoA) is an experience that arises by a combination of a voluntary motor action and sensory evidence whether the corresponding body movements have somehow influenced the course of external events. The SoA is not only a key part of our experiences in daily life but also in our interaction with technology as it gives us the feeling of “I did that” as opposed to “the system did that,” thus supporting a feeling of being in control. This feeling becomes critical with human–computer integration, wherein emerging technology directly influences people’s body, their actions, and the resulting outcomes. In this review, we analyse and classify current integration technologies based on what we currently know about agency in the literature, and propose a distinction between body augmentation, action augmentation, and outcome augmentation. For each category, we describe agency considerations and markers of differentiation that illustrate a relationship between assistance level (low, high), agency delegation (human, technology), and integration type (fusion, symbiosis). We conclude with a reflection on the opportunities and challenges of integrating humans with computers, and finalise with an expanded definition of human–computer integration including agency aspects which we consider to be particularly relevant. The aim this review is to provide researchers and practitioners with guidelines to situate their work within the integration research agenda and consider the implications of any technologies on SoA, and thus overall user experience when designing future technology.

Human-Computer Integration (HInt) is an emerging paradigm in which computational and human systems are closely interwoven. Integrating computers with the human body is not new. however, we believe that with rapid technological advancements, increasing real-world deployments, and growing ethical and societal implications, it is critical to identify an agenda for future research. We present a set of challenges for HInt research, formulated over the course of a five-day workshop consisting of 29 experts who have designed, deployed and studied HInt systems. This agenda aims to guide researchers in a structured way towards a more coordinated and conscientious future of human-computer integration.

The human–computer cooperation process guided by natural interaction, intelligent interaction, and human–computer integration is gradually becoming a new trend in human–computer interaction. Cooperative scenarios of human–computer interaction systems often contain multi-interface and multi-device results in edges often interrupt the cognitive ergonomics of interface layout. This research takes typical areas as an example to establish a stepwise regression model to predict reaction time at an arbitrary position on the left interface. It uses a foveal region to position the starting point of attention and a parafoveal region to calculate the radius of each objective area, and design 10 similar tasks to analyze eye-tracking indexes through physiological assessment. Unlike fixed thinking such as spatial proximity on multi-interfaces, this research summarises cognitive features of layout based on the positive and negative effects of edge impact through eye-tracking analysis. It analyzes cognition including input, process, and output in human–computer cooperation from human intelligence and artificial intelligence respectively, and visualises the mapping relationship between these indexes and specific stages of cognition. Besides, the quantitative evaluation of the regression equation and qualitative analysis of the eye-tracking indexes provide a reference for other interfaces around the front interface.

Icon similarity model based on cognition and deep learning

Crowdsourcing markets such as Amazon's Mechanical Turk provide an enormous potential for accomplishing work by combining human and machine computation. Today crowdsourcing is mostly used for massive parallel information processing for a variety of tasks such as image labeling. However, as we move to more sophisticated problem-solving there is little knowledge about managing dependencies between steps and a lack of tools for doing so. As the contribution of this paper, we present a concept of an executable, model-based programming language and a general purpose framework for accomplishing more sophisticated problems. Our approach is inspired by coordination theory and an analysis of emergent collective intelligence. We illustrate the applicability of our proposed language by combining machine and human computation based on existing interaction patterns for several general computation problems.

Human–computer interaction (HCI) is increasingly interested in supporting exertion experiences so more people can benefit from physical activity. So far, most systems have focused on sensing and presenting information to the user via screens to support the exertion experience. Interestingly, emerging technology can also act on the exerting user's body based on sensed information, granting researchers the potential to develop technology that not only “presents” but also “acts” on information throughout an integrated exertion experience. As a result, design opportunities surrounding computing machinery as contextually aware exertion partners are now available. However, there are currently no frameworks to guide the design of human–computer integration in an exertion context. To contribute to closing this gap, we designed three eBike systems to investigate different forms of integration with the exerting user and we studied the resulting user experiences. Based on the results of these three case studies, we present the first framework, including associated design tactics, to offer guidance on how to design human–computer integration in an exertion context.

The paper focuses on human computer integration and the modeling of agent systems using CSP and the VDM specification language. In order to accomplish goals, agents in a given environment must adhere to the societal rules (norms) associated with that environment. The commitment rules governing a society of agents ensures that goals are accomplished and tasks are performed in an orderly fashion and limits the possibility of rogue agents.

The era of Web2.0 remarks the beginning of the industrialization era of data, computing, and products. As the value of data becomes more and more prominent, the impacts of digital diversification (DD) on psychological belongingness (BE) is significant. In this article, Gen-Z, which is defined to be more susceptible to the development of digital technology, is selected as the research object. Based on the ABC theory, a research model is constructed to explore the causal relationships among the five variables, DD, personality, digital self-efficacy (DSE), perceived service value (PSV) (of DD), and sense of BE, and Smart-PLS is applied for analyzing data obtained from 642 respondents. By classifying the results by gender, both male (n = 306) and female (n = 336) respondents showed positive effects on the six direct effects. However, in the verification of DSE and PSV as mediators, the mediating effect of DSE was not significant among male respondents in Generation Z. Predictably, as moving toward Web5.0, that is, the human–computer integration that can resonate with users, the observed benefits of DD, along with the accompanying psychological effects, will also merit attention in future research.

Information technologies, such as IoT, artificial intelligence (AI), and virtual reality (VR), have seen so much development that there is now a wide variety of digital equipment incorporated into the infrastructure of daily life. From the agrarian society (Society 1.0) through the information society (Society 4.0), humankind has created farmlands and cities by structuring natural environments physically and has built information environments by structuring them informationally. However, despite the rapid development of information environments, it may be fair to say that the perspectives of the human body have not changed at all since the industrial revolution. In the context of these recent technological developments, greater attention is being paid to human augmentation studies. These studies aim for a new embodiment of “human-computer integration,” one which can physically and informationally compensate or augment our innate sensory functions, motor functions, and intellectual processing functions by using digital equipment and information systems at will, as if they were our hands and feet. It has also been proposed that the technical systems that enable us to freely do what we want by utilizing human augmentations be called “JIZAI” (freedomization) as opposed to “automation.” The term “JIZAI body” used in these studies represents the new body image of humans who will utilize engineering and informatics technologies to act at will in the upcoming “super smart society” or “Society 5.0.” In these studies, human augmentation technologies are an important component of JIZAI, but JIZAI is not the same as human augmentation. JIZAI is different in scope from human augmentation, as it aims to enable humans to move freely among the five new human body images: “strengthened sense” (augmented perception), “strengthened physical body” (body augmentation), “separately-designed mind and body” (out of body transform), “shadow cloning,” and “assembling.” In the society of the future where JIZAI bodies widely prevail, we will use technologies that enable us to do what we have failed at or given up due to limitations of our physical bodies. We believe that a future society, one in which aging does not reduce our capabilities but instead increased options give us hope, can be realized. This special issue, consisting of two review papers and twelve research papers, deals with diverse and wide-ranging areas, including human augmentation, robotics, virtual reality, and others. We would like to express our sincere appreciation to all the authors and reviewers of the papers contributed to this special issue and to the editorial committee of the Journal of Robotics and Mechatronics for their gracious cooperation.

The advent of internet of things (IoT) and cloud computing coupled with several breakthroughs in the field of artificial intelligence have made ambient intelligence, which incorporates pervasive computing, human-computer interaction, artificial intelligence, and IoT, possible. Whose objective is to tune the environment to understand human needs and seamless integration of technology with life? Which is the bedrock for human technology integration where artificial systems and miniaturized nanotechnology devices are embodied or implanted in human body which can either function as replacement for human body parts or the extension of human capabilities? This chapter will investigate the trends and advancement in human-computer integration. How can human augmentation technologies be used to replicate, supplement, and exceed human abilities? Also the chapter verifies the impact of human technology augmentation on Industry 5.0 and the challenges that contend with human technology integration.

Supporting the exerting body through interactive technology has been the focus of human-computer integration research labelled as “integrated exertion”. Due to advances in technology where integration systems can sense and interpret data in real-time, systems can participate in the experience alongside the user. In this chapter, we discuss integrated exertion through the lens of an eBike rider, where movement data generated from the rider's leaning forward posture results in increased engine support to afford a “superpower”-like experience. We present our learnings from our case study from the perspective of how to practically assist designers and researchers in designing integrated exertion by offering five take-aways that aim to help users to: “self-attribute superpowers acquired from the machine's functionality”, “map movement to machine actuation to facilitate integration”, “move simultaneously with the machine as one continuous expression”, “exploit visceral qualities to ignite imaginaries of integration” and “amplify the sensation of being integrated with the system by engaging other senses that complement the experience”. Finally, we provide reflections on supporting the exerting body through a human-computer integration approach towards enabling engaging integrated exertion experiences.

There is an intensive discussion nowadays about the meaning of effective computability, with implications to the status and provability of the Church–Turing Thesis (CTT). I begin by reviewing what has become the dominant account of the way Turing and Church viewed, in 1936, effective computability. According to this account, to which I refer as the Gandy–Sieg account, Turing and Church aimed to characterize the functions that can be computed by a human computer. In addition, Turing provided a highly convincing argument for CTT by analyzing the processes carried out by a human computer. I then contend that if the Gandy–Sieg account is correct, then the notion of effective computability has changed after 1936. Today computer scientists view effective computability in terms of finite machine computation. My contention is supported by the current formulations of CTT, which always refer to machine computation, and by the current argumentation for CTT, which is different from the main arguments advanced by Turing and Church. I finally turn to discuss Robin Gandy's characterization of machine computation. I suggest that there is an ambiguity regarding the types of machines Gandy was postulating. I offer three interpretations, which differ in their scope and limitations, and conclude that none provides the basis for claiming that Gandy characterized finite machine computation.

CyLog/Game aspect: An approach to separation of concerns in crowdsourced data management