Augmented Humanity: A Systematic Mapping Review

Augmented humanity (AH) is a term that has been mentioned in several research papers. However, these papers differ in their definitions of AH. The number of publications dealing with the topic of AH is represented by a growing number of publications that increase over time, being high impact factor scientific contributions. However, this terminology is used without being formally defined. The aim of this paper is to carry out a systematic mapping review of the different existing definitions of AH and its possible application areas. Publications from 2009 to 2020 were searched in Scopus, IEEE and ACM databases, using search terms “augmented human”, ”human augmentation” and “human 2.0”. Of the 16,914 initially obtained publications, a final number of 133 was finally selected. The mapping results show a growing focus on works based on AH, with computer vision being the index term with the highest number of published articles. Other index terms are wearable computing, augmented reality, human–robot interaction, smart devices and mixed reality. In the different domains where AH is present, there are works in computer science, engineering, robotics, automation and control systems and telecommunications. This review demonstrates that it is necessary to formalize the definition of AH and also the areas of work with greater openness to the use of such concept. This is why the following definition is proposed: “Augmented humanity is a human–computer integration technology that proposes to improve capacity and productivity by changing or increasing the normal ranges of human function through the restoration or extension of human physical, intellectual and social capabilities.”

Playing the piano with a robotic third thumb: assessing constraints of human augmentation

Contemporary robotics gives us mechatronic capabilities for augmenting human bodies with extra limbs. However, how our motor control capabilities pose limits on such augmentation is an open question. We developed a Supernumerary Robotic 3rd Thumbs (SR3T) with two degrees-of-freedom controlled by the user’s body to endow them with an extra contralateral thumb on the hand. We demonstrate that a pianist can learn to play the piano with 11 fingers within an hour. We then evaluate 6 naïve and 6 experienced piano players in their prior motor coordination and their capability in piano playing with the robotic augmentation. We show that individuals’ augmented performance with the SR3T could be explained by our new custom motor coordination assessment, the Human Augmentation Motor Coordination Assessment (HAMCA) performed pre-augmentation. Our work demonstrates how supernumerary robotics can augment humans in skilled tasks and that individual differences in their augmentation capability are explainable by their individual motor coordination abilities.

Special Issue on Augmenting the Human Body and Being

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.

Failures of Fairness in Automation Require a Deeper Understanding of Human-ML Augmentation

Machine learning (ML) tools reduce the costs of performing repetitive, time-consuming tasks yet run the risk of introducing systematic unfairness into organizational processes. Automated approaches to achieving fair- ness often fail in complex situations, leading some researchers to suggest that human augmentation of ML tools is necessary. However, our current understanding of human–ML augmentation remains limited. In this paper, we argue that the Information Systems (IS) discipline needs a more sophisticated view of and research into human–ML augmentation. We introduce a typology of augmentation for fairness consisting of four quadrants: reactive oversight, proactive oversight, informed reliance, and supervised reliance. We identify significant intersections with previous IS research and distinct managerial approaches to fairness for each quadrant. Several potential research questions emerge from fundamental differences between ML tools trained on data and traditional IS built with code. IS researchers may discover that the differences of ML tools undermine some of the fundamental assumptions upon which classic IS theories and concepts rest. ML may require massive rethinking of significant portions of the corpus of IS research in light of these differences, representing an exciting frontier for research into human–ML augmentation in the years ahead that IS researchers should embrace.

The winding path towards symbiotic autonomous systems

Over the next 10 years, we are likely to see the convergence of two independent evolutionary paths: one leading to an augmentation of machine capabilities; the other with the augmentation of human capabilities. This convergence will not happen at a specific point in time; instead, it will be the result of progressive overlapping, to the point that it might be difficult to identify a defining moment. The following decade will likely be quite different from the present one. 5G will probably be remembered as a transitional system, artificial intelligence (AI) as a misplaced objective. We are looking forward to a communications fabric created by autonomous systems that will exist both in the physical world as well as in cyberspace, determining a continuum that gives rise to digital reality and where intelligence is an emerging property of the ambient. Hence, the dichotomy between AI and natural intelligence will no longer exist and AI will be considered as a tool for human augmentation and as the glue connecting minds and machines. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

STRUCTURING HUMAN AUGMENTATION WITHIN PRODUCT DESIGN

Human augmentation is a thriving research field that aims to amplify human abilities through the development of technological improvements as an integral part of the human body. Human augmentation products may be made for anyone, ranging from healthy users wanting to enhance their human abilities to users who face temporary or permanent disabilities, physical impairments, or perilous situations that oblige them to use these products.This article attempts to introduce readers to the domain of human augmentation by providing a thorough formulation of the concept and its related terms to develop a more solid structural basis. Additionally, a categorical and dimensional classification of the field was given. Based on these findings, we then proposed a novel framework in the form of a diagrammatic presentation of both classifications, which could enable product designers to better understand and characterize the type of human augmentation product they are designing by determining its location in the diagram. Finally, the proposed framework was evaluated by introducing and classifying several significant human augmentation products most of which have proven to successfully exceed human abilities.