Human-machine Symbiosis Research Articles

Human-Machine symbiosis in educational leadership in the era of artificial intelligence (AI): Where are we heading?

The issue of Artificial Intelligence (AI) and educational leadership has become a central topic following the shift to knowledge technology and digital literacy in recent years. Despite increasing attention to the topic among scholars and policymakers during the last decade, we lack a comprehensive review of AI and educational leadership. Therefore, by using bibliometric analysis of data derived from the Scopus database, this paper represents a systematic scoping of AI and educational leadership, tracing its development, characteristics, and knowledge accumulation within broad perspectives. Results identify key trends, geographic representation, topical foci, main concepts, themes, and their interconnections, including their implications for targeted Sustainable Development Goals. Implications, limitations, and future research reviewed in the studies are fully discussed.

Analysis of the Causes and Mitigation Paths of Artificial Intelligence Anxiety among Journalism Practitioners

The transformation of news media into intelligent media is in the ascendant, and artificial intelligence (AI) technology has brought news practitioners into the era of intelligent production, but also brought them the psychological worry of AI anxiety. The study analyses the causes of AI anxiety among news practitioners from three aspects: the dissolution of their professional concepts, the prevalence of professional substitution, and the polarisation of professional skill requirements, and proposes a path to alleviate the problem by balancing self-efficacy and psychological expectations through scientific cognition, promoting the human-machine symbiosis model in the field of journalism through multi-party collaboration, and providing special support to improve the protection of news practitioners' profession.

The Impact of AI Usage on University Students' Willingness for Autonomous Learning.

As artificial intelligence (AI) technology becomes increasingly integrated into education, understanding the theoretical mechanisms that drive university students to adopt new learning behaviors through these tools is essential. This study extends the Expectation-Confirmation Model (ECM) by incorporating both cognitive and affective variables to examine students' current AI usage and their future expectations. The model includes intrinsic and extrinsic motivations, focusing on three key factors: positive emotions, digital efficacy, and willingness for autonomous learning. A survey of 721 valid responses revealed that positive emotions, digital efficacy, and satisfaction significantly influence continued AI usage, with positive emotions being particularly critical. Digital efficacy and perceived usefulness also impact satisfaction, but long-term usage intentions are more effectively driven by positive emotions. Furthermore, digital efficacy strongly affects the willingness for autonomous learning. Therefore, higher education institutions should promote AI technology, enhance students' expectation-confirmation levels, and emphasize positive emotional experiences during AI use. Adopting a "human-machine symbiosis" model can foster active learning, personalized learning pathways, and the development of students' digital efficacy and innovation capabilities.

Technological progress and labour welfare: evidence from robot adoption in China

ABSTRACT The widespread integration of robots has raised apprehensions about their influence on labourlabour welfare. Utilizing data from the China Labor-force Dynamic Survey (CLDS) spanning 2014 to 2018 and robot data from the International Federation of Robotics (IFR), we explore the influence of robots on workers’ health and the associated mechanisms. Contrary to prevalent societal concerns, our study reveals that the utilization of robots substantially enhances worker health. Mechanistic tests demonstrate the effectiveness of robots in enhancing worker health through task reallocation and improvements to the work environment. Heterogeneity analysis indicates that the advantages of robot utilization may particularly benefit vulnerable groups, including those with physically demanding jobs, low-skilled workers, and migrant populations. This fosters the gradual development of a “human-machine symbiosis” in the interaction between machines and humans. Subsequent research has demonstrated that the implementation of robots is effective in diminishing work intensity and alleviating negative anxiety among workers, thereby enhancing their mental health. By drawing evidence from developing countries to illuminate the positive aspects of the forces of creative destruction, our study offers a micro-perspective for objectively evaluating intelligent applications and worker welfare. It also provides instructive insights for a comprehensive assessment of the robot-human relationship.

A short review of the ADAS progress in the last decade and the potential concept of Human-Machine Symbiosis (HMS)

Abstract This short review highlights the main sensor structures that are used in the ADAS (Advanced Driver Assisted System) field, in order to outline the progress at this moment (2023). Starting from this achieved level, we have proposed another approach to the ADAS problematics, regarding the prospects for development after the current moment, a different perspective than the one that has AV (Autonomus Vehicle) as its endpoint. Computer Assisted Driving represents a necessary and sufficient solution for increasing traffic safety in the near future. The integrated driver concept in the assisted environment implies a symbiotic human-machine collaboration. This collaboration requires a psychological acceptance of the ADAS system on behalf of humans, as an essential part of the current and future automobile. The progress highlighted by the documentation undertaken allows us to imagine a concept of a symbiotic human-machine system, based on the communication between ADAS and an external computing resource that assists the driver, based on the long analysis of recorded car events. Future automobiles must include an ADAS system that provides a subtle human-machine synapse, based on a series of computerized warnings to the driver generated in a timely manner, resulting from the high predictive capacity of AI-DLM algorithms. The computing speed of the local ADAS algorithms will be supplemented by the external server processing resource, accessed at the right time, to resolve an unexpected deadlock in the car roll.

Elon Musk’s Neuralink Brain Chip: A Review on ‘Brain-Reading’ Device

With its novel bidirectional communication method, Neuralink, the brain-reading gadget created by Elon Musk, is poised to transform human-machine relations. It represents a revolutionary combination of health science, neurology, and artificial intelligence. Neuralink is a potentially beneficial brain implant that consists of tiny electrodes placed behind the ear and a small chip. It can be used to treat neurological conditions and improve cognitive function. Important discussions are nevertheless sparked by ethical worries about abuse, privacy, and security. It is important to maintain a careful balance between the development of technology and moral issues, as seen by the imagined future in which people interact with computers through thinking processes. In order for Neuralink to be widely accepted and responsibly incorporated into the fabric of human cognition and connectivity, ongoing discussions about ethical standards, regulatory frameworks, and societal ramifications are important. Meanwhile, new advancements in Brain-Chip-Interfaces (BCHIs) bring the larger context into focus. By enhancing signal transmission between nerve cells and chips, these developments offer increased signal fidelity and improved spatiotemporal resolution. The potential revolutionary influence of these innovations on neuroscience and human-machine symbiosis raises important considerations about the ethical and societal consequences of these innovations.

Insights from operationalizing, testing and evaluating the ENRICHER method: INSYTE-Cooley Research Lab Case Study

This paper uses the INSYTE-Cooley Research Lab (I-CRL) as a case study. The view of the I-CRL as a Complex Adaptive System is expressed. Preliminary results from the analyzed data present the ‘themes’ and underlying ‘codes’ from a subset of transcripts. The research methodology uses a meta-methodology of Participation Action Research (PAR) and within the PAR framework the research method is qualitative. Reflective Thematic Analysis (RTA) is used on the transcripts. The transcripts come from regular fortnightly meetings of the I-CRL and some informal meetings. These ‘themes’, ‘codes’ and what they identify are discussed. The study is a longitudinal study. The key outcomes are the creation of a Human-Centered Systems approach to the curation and digitization of cultural heritage both tangible and intangible. The knowledge gained shows a framework within which a new method called the ENRICHER method is being operationalized, tested and evaluated. Some of the findings, so far, show tension points between human centric and techno centric world views and the importance of understanding the curation processes as a forerunner to the formation of a human-machine symbiosis.

Path of Improving the Intelligent Literacy of Vocational College Teachers from the Perspective of Human-machine Symbiosis

Path of Improving the Intelligent Literacy of Vocational College Teachers from the Perspective of Human-machine Symbiosis

Human-machine symbiosis: ambivalent intuitions regarding gain and loss of personal control explain acceptance of smart mobility aids

ABSTRACT Smart mobility aids invoke conflicting impressions of enhanced mobility and being restricted and dependent. This ambivalence between perceived gain and loss of personal control might affect the acceptance of these devices. In a preregistered study (N = 194), we investigated people’s expectations on how using a flexible exosuit and a rigid exoskeleton would affect their personal control and tested how this influenced their acceptance of those devices. Overall, participants anticipated a net gain of personal control by using smart mobility aids. There was no difference in anticipations of gain of control between devices, but anticipations of loss of control were higher for the rigid exoskeleton than for the flexible exosuit. Anticipated gain and loss of control explained more than 50% of the variance in the acceptance of the investigated devices. The belief that a smart mobility aid would increase the user’s personal control was more predictive of overall acceptance than the belief that such a device would limit the user’s personal control. Overall, the current findings reveal that potential users’ expectations regarding changes in personal control, in particular the degree to which positive changes are expected, are a key determinant of acceptance of smart mobility aids.

Conceptual scheme of intelligent vessel traffic control system with the human factor included

The subject of the research is the development of technologies for automated and automatic ship traffic control systems, which is of great importance in modern shipping conditions. At the same time, special attention is paid to intelligent control systems based on artificial intelligence methods, such as artificial neural networks, fuzzy logic, machine learning, evolutionary computing and genetic algorithms. As a result, integrated information navigation systems, which provide decision-making on all aspects of navigation tasks, primarily where reception, processing, storage and transmission of navigation information is required, are being created and widely used in practice. However, in such developments, due importance is not given to the human factor, namely, it is often not taken into account that the control system of a moving object is a man-machine and consists of a regulator, which includes a human operator (navigator). The inclusion of the navigator in the vessel control link leads to the need to simultaneously take into account the human factor and the characteristics of the vessel controllability, i. e. human and machine factors in their unity. In connection with the development of artificial intelligence, the concept of “human-machine symbiosis” is becoming increasingly relevant in the study of human-machine systems. The problem is that there is still no single point of view on this issue due to the lack of reasonable methods for taking into account the human factor in the process of controlling the movement of moving objects. The results of the theoretical research on the formalization of some aspects of human mental activity and their implementation in the conceptual scheme of an intelligent vessel control system are reflected in the paper. The results obtained may be of interest to specialists in vessel traffic control automation, artificial intelligence, the creation of intelligent control systems and navigation safety.

How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?

Novel usages of brain stimulation combined with artificially intelligent (AI) systems promise to address a large range of diseases. These new conjoined technologies, such as brain-computer interfaces (BCI), are increasingly used in experimental and clinical settings to predict and alleviate symptoms of various neurological and psychiatric disorders. Due to their reliance on AI algorithms for feature extraction and classification, these BCI systems enable a novel, unprecedented, and direct connection between human cognition and artificial information processing. In this paper, we present the results of a study that investigates the phenomenology of human-machine symbiosis during a first-in-human experimental BCI trial designed to predict epileptic seizures. We employed qualitative semi-structured interviews to collect user experience data from a participant over a six-years period. We report on a clinical case where a specific embodied phenomenology emerged: namely, after BCI implantation, the patient reported experiences of increased agential capacity and continuity; and after device explantation, the patient reported persistent traumatic harms linked to agential discontinuity. To our knowledge, this is the first reported clinical case of a patient experiencing persistent agential discontinuity due to BCI explantation and potential evidence of an infringement on patient right, where the implanted person was robbed of her de novo agential capacities when the device was removed.

Can Action Research Methods Help Address the Digital Social sustainability Gap?: An Evaluation and Refinement of the ENRICHER Methodology using PAR

The digital social sustainability gap narrative (O'Neill, and Stapleton 2022) endeavours to address the digital social sustainability gap by using digital technology for social benefit i.e. opening up dark archives in the digital cultural heritage area. It raises issues of the interoperability between institutions for knowledge sharing, thereby breaking the disciplinary silos and also breaking the data silos within institutions. It argues for multidisciplinary collaborations, the valorisation of tacit knowledge of co-researchers so that technology does not replace the work of the human but forms a beneficial human machine symbiosis. Further it provides an insight into the ethos-centric perspective of the ENRICHER method developed by the INSYTE-Cooley Research Lab (I-CRL). This study uses an experimental technique within the Participation Action Research (PAR) methodology to valorise human tacit knowledge and intellectual capacity so that they are placed at the heart of the development process. Action research with a combination of the Human Centered Systems (HCS) approach to systems development are combined so that a multidisciplinary group with diverse world views can collaborate to create a new human centered framework for the digitisation of cultural heritage.

Human-machine symbiosis: A multivariate perspective for physically coupled human-machine systems

The notion of symbiosis has been increasingly mentioned in research on physically coupled human-machine systems. Yet, a uniform specification on which aspects constitute human-machine symbiosis is missing. By combining the expertise of different disciplines, we elaborate on a multivariate perspective of symbiosis as the highest form of interaction in physically coupled human-machine systems, characterized by a oneness of the human and the machine. Four dimensions are considered: Task, interaction, performance, and experience. First, human and machine accomplish a common objective by completing tasks conceptualized on a decomposition, a decision and an action level (task dimension). Second, each partner possesses an internal representation of the oneness they form, including the partner’s inner states (e.g. experiences) and their joint influence on the environment. This representation constitutes the “symbiotic understanding” between both partners, being the basis of a joint and highly coordinated action (interaction dimension). Third, the symbiotic interaction leads to synergetic effects regarding the complementary strengths of the partners, resulting in a higher overall performance (performance dimension). Fourth, symbiotic systems specifically change the user’s experiences, like flow, acceptance, sense of agency, and embodiment (experience dimension). Our multivariate perspective allows a clear description of symbiotic human-machine systems and helps to bridge barriers between different disciplines.

Misalignment in Semantic User Model Elicitation via Conversational Agents: A Case Study in Navigation Support for Visually Impaired People

Disabled people can benefit greatly from assistive digital technologies. However, this increased human-machine symbiosis makes it important that systems are personalized and transparent to users. Existing work often uses data-oriented approaches. However, these approaches lack transparency and make it hard to influence the system’s behavior. In this paper, we use knowledge-based techniques for personalization, introducing the concept of Semantic User Models for representing the behavior, values and capabilities of users. To allow the system to construct such a user model, we investigate the use of a conversational agent which can elicit the relevant information from users through dialogue. A conversational interface is essential for our case study of navigation support for visually impaired people, but in general, has the potential to enhance transparency as users know what the system represents about them. For such a dialogue to be effective, it is crucial that the user understands what the conversational agent is asking, i.e., that misalignments that decrease the transparency are avoided or resolved. In this paper, we investigate whether we can use a conversational agent for Semantic User Model elicitation, which types of misalignments can occur in this process and how they are related, and how misalignments can be reduced. We investigate this in two (iterative) qualitative studies (n = 7 & n = 8) with visually impaired people in which a personalized user model for navigation support is elicited via a dialogue with a conversational agent. Our results show four hierarchically structured levels of human-agent misalignment. We identify several design solutions for reducing misalignments, which point to the need for restricting the generic user model to what is needed in the domain under consideration. With this research, we lay a foundation for conversational agents capable of eliciting Semantic User Models.

Dual Passive Reactive Brain-Computer Interface: A Novel Approach to Human-Machine Symbiosis.

The present study proposes a novel concept of neuroadaptive technology, namely a dual passive-reactive Brain-Computer Interface (BCI), that enables bi-directional interaction between humans and machines. We have implemented such a system in a realistic flight simulator using the NextMind classification algorithms and framework to decode pilots' intention (reactive BCI) and to infer their level of attention (passive BCI). Twelve pilots used the reactive BCI to perform checklists along with an anti-collision radar monitoring task that was supervised by the passive BCI. The latter simulated an automatic avoidance maneuver when it detected that pilots missed an incoming collision. The reactive BCI reached 100% classification accuracy with a mean reaction time of 1.6 s when exclusively performing the checklist task. Accuracy was up to 98.5% with a mean reaction time of 2.5 s when pilots also had to fly the aircraft and monitor the anti-collision radar. The passive BCI achieved a F1-score of 0.94. This first demonstration shows the potential of a dual BCI to improve human-machine teaming which could be applied to a variety of applications.

Digital cultural heritage standards: from silo to semantic web

This paper is a survey of standards being used in the domain of digital cultural heritage with focus on the Metadata Encoding and Transmission Standard (METS) created by the Library of Congress in the United States of America. The process of digitization of cultural heritage requires silo breaking in a number of areas—one area is that of academic disciplines to enable the performance of rich interdisciplinary work. This lays the foundation for the emancipation of the second form of silo which are the silos of knowledge, both traditional and born digital, held in individual institutions, such as galleries, libraries, archives and museums. Disciplinary silo breaking is the key to unlocking these institutional knowledge silos. Interdisciplinary teams, such as developers and librarians, work together to make the data accessible as open data on the “semantic web”. Description logic is the area of mathematics which underpins many ontology building applications today. Creating these ontologies requires a human–machine symbiosis. Currently in the cultural heritage domain, the institutions’ role is that of provider of this open data to the national aggregator which in turn can make the data available to the trans-European aggregator known as Europeana. Current ingests to the aggregators are in the form of machine readable cataloguing metadata which is limited in the richness it provides to disparate object descriptions. METS can provide this richness.

Brain-machine interface: New challenge for humanity

The aim of this paper is to clarify specific aspects of the impact of the brain-machine interface on our understanding of subjectivity. The brain-machine interface is presented as a phase of cyborgization of humans. Some projects in the field of brain-machine interface are aimed at enabling consensual telepathy - communication without symbolic mediation. Consensual telepathy refers to one of potential ways of transmission of information within singularity. Therefore, consensual telepathy is an important aspect of singularity. Singularity or human-machine symbiosis shows some similarities with child-mother unity. Therefore, the psychodynamic perspective might be considered useful in thinking about human-machine symbiosis. Knowledge from developmental psychodynamic psychology combined with insights by Slavoj Zizek and Jean Baudrillard provides an additional perspective looking at human-machine symbiosis. The paper claims that if consensual telepathy becomes another way of communication, it will have the potential to annihilate subjectivity making it schizophrenic. At the same time, we look at the possibility of an escape from our inner world through the prism of addictions.

Reciprocal Learning in Production and Logistics

Integration of AI technologies and learnable systems in production and logistics transforms the concepts of work organization and task assignments to human and machine agents. Thus, the question arises of what intelligent machines and human workers may be able to achieve as teammates. One answer may be guiding and training the workforce at the workplace to cope with emerging skill mismatches, emphasized by concepts of work-based learning. The extension of cyber-physical production systems towards becoming human-centered and social systems enabling human-machine interaction, creates opportunities for human-machine symbiosis by complementing each other's strengths. In this way, the concept of “Reciprocal Learning” (RL) between humans and intelligent machines has emerged, which is still rather ambiguous and lacks a profound knowledge base. Especially in production and logistics, literature is fragmented. Hence, the objective of this paper is to conduct a systematic literature review to elicit and cluster the knowledge base in RL represented by adjacent interdisciplinary fields of research, such as social and computer sciences. This work contributes to the literature by developing a comprehensive knowledge base on the concept of RL enabling to pursue future research directions towards the realization of human-machine symbiosis through RL in production and logistics.

The Development of Broadcasting and Hosting from the Perspective of Media Intelligence-The Case of AI Anchors for Beijing 2022 Winter Olympics

With the continuous progress of media technology, the media communication environment has undergone profound changes, and media intelligence has become a new trend of media convergence. As an innovative product of the combination of artificial intelligence technology and media communication, AI anchors have been applied to information communication in the Olympic Winter Games Beijing 2022, which has attracted widespread attention from the public. According to the current development of AI anchors, this paper uses embodied cognition theory to investigate the development trend of the broadcasting and hosting industry under the influence of intelligent media. On this basis, the paper takes AI anchors of the Winter Olympics as the research object, analyzes their application reasons and communication characteristics, and then explores the irreplaceability of human broadcasters and hosts by comparing them with AI anchors. The study of this paper will provide a feasible path for the development direction of human-machine symbiosis and a new case for the study of AI anchors.

Humans Are Not Machines—Anthropocentric Human–Machine Symbiosis for Ultra-Flexible Smart Manufacturing

Humans Are Not Machines—Anthropocentric Human–Machine Symbiosis for Ultra-Flexible Smart Manufacturing