Socio-Cognitive and Affective Computing

Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli. Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science. Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm. This book integrates proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems. The design of this kind of systems combines knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems

The Effects of Mid-range Visual Anthropomorphism on Human Trust and Performance Using a Navigation-based Automated Decision Aid

University of Minnesota Ph.D. dissertation. April 2018. Major: Human Factors/Ergonomics. Advisors: Barry Kudrowitz, Thomas Stoffregen. 1 computer file (PDF); vi, 104 pages.The majority of us use personal assistant technology every day. From calendar alerts to fitness goal reminders, we have come to depend on this automation to provide us with information about our lives and help us to make “better” decisions. Research has been published on how to best represent recommender information to users, but not much has been done in the way of studying decision aids for low risk daily use. This research aims to explore how users of this technology trust computer-generated suggestions and how best to display those suggestions to optimize trust and favorable performance outcomes for continued use

The development of a human-robot interface for industrial collaborative system

Industrial robots have been identified as one of the most effective solutions for optimising output and quality within many industries. However, there are a number of manufacturing applications involving complex tasks and inconstant components which prohibit the use of fully automated solutions in the foreseeable future. A breakthrough in robotic technologies and changes in safety legislations have supported the creation of robots that coexist and assist humans in industrial applications. It has been broadly recognised that human-robot collaborative systems would be a realistic solution as an advanced production system with wide range of applications and high economic impact. This type of system can utilise the best of both worlds, where the robot can perform simple tasks that require high repeatability while the human performs tasks that require judgement and dexterity of the human hands. Robots in such system will operate as “intelligent assistants”. In a collaborative working environment, robot and human share the same working area, and interact with each other. This level of interface will require effective ways of communication and collaboration to avoid unwanted conflicts. This project aims to create a user interface for industrial collaborative robot system through integration of current robotic technologies. The robotic system is designed for seamless collaboration with a human in close proximity. The system is capable to communicate with the human via the exchange of gestures, as well as visual signal which operators can observe and comprehend at a glance. The main objective of this PhD is to develop a Human-Robot Interface (HRI) for communication with an industrial collaborative robot during collaboration in proximity. The system is developed in conjunction with a small scale collaborative robot system which has been integrated using off-the-shelf components. The system should be capable of receiving input from the human user via an intuitive method as well as indicating its status to the user ii effectively. The HRI will be developed using a combination of hardware integrations and software developments. The software and the control framework were developed in a way that is applicable to other industrial robots in the future. The developed gesture command system is demonstrated on a heavy duty industrial robot

Human-in-the-Loop Operations over Time Delay: NASA Analog Missions Lessons Learned

Teams at NASA have conducted studies of time-delayed communications as it effects human exploration. In October 2012, the Advanced Exploration Systems (AES) Analog Missions project conducted a Technical Interchange Meeting (TIM) with the primary stakeholders to share information and experiences of studying time delay, to build a coherent picture of how studies are covering the problem domain, and to determine possible forward plans (including how to best communicate study results and lessons learned, how to inform future studies and mission plans, and how to drive potential development efforts). This initial meeting s participants included personnel from multiple NASA centers (HQ, JSC, KSC, ARC, and JPL), academia, and ESA. It included all of the known studies, analog missions, and tests of time delayed communications dating back to the Apollo missions including NASA Extreme Environment Mission Operations (NEEMO), Desert Research and Technology Studies (DRATS/RATS), International Space Station Test-bed for Analog Research (ISTAR), Pavilion Lake Research Project (PLRP), Mars 520, JPL Mars Orbiters/Rovers, Advanced Mission Operations (AMO), Devon Island analog missions, and Apollo experiences. Additionally, the meeting attempted to capture all of the various functional perspectives via presentations by disciplines including mission operations (flight director and mission planning), communications, crew, Capcom, Extra-Vehicular Activity (EVA), Behavioral Health and Performance (BHP), Medical/Surgeon, Science, Education and Public Outreach (EPO), and data management. The paper summarizes the descriptions and results from each of the activities discussed at the TIM and includes several recommendations captured in the meeting for dealing with time delay in human exploration along with recommendations for future development and studies to address this issue

Machine Medical Ethics

In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? The essays in this collection by researchers from both humanities and science describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility, and accurately modeling essential physician-machine-patient relationships. This collection is the first book to address these 21st-century concerns

Human-Machine Communication: Complete Volume. Volume 2

This is the complete volume of HMC Volume 2

Toward Building A Social Robot With An Emotion-based Internal Control

In this thesis, we aim at modeling some aspects of the functional role of emotions on an autonomous embodied agent. We begin by describing our robotic prototype, Cherry--a robot with the task of being a tour guide and an office assistant for the Computer Science Department at the University of Central Florida. Cherry did not have a formal emotion representation of internal states, but did have the ability to express emotions through her multimodal interface. The thesis presents the results of a survey we performed via our social informatics approach where we found that: (1) the idea of having emotions in a robot was warmly accepted by Cherry\u27s users, and (2) the intended users were pleased with our initial interface design and functionalities. Guided by these results, we transferred our previous code to a human-height and more robust robot--Petra, the PeopleBot--where we began to build a formal emotion mechanism and representation for internal states to correspond to the external expressions of Cherry\u27s interface. We describe our overall three-layered architecture, and propose the design of the sensory motor level (the first layer of the three-layered architecture) inspired by the Multilevel Process Theory of Emotion on one hand, and hybrid robotic architecture on the other hand. The sensory-motor level receives and processes incoming stimuli with fuzzy logic and produces emotion-like states without any further willful planning or learning. We will discuss how Petra has been equipped with sonar and vision for obstacle avoidance as well as vision for face recognition, which are used when she roams around the hallway to engage in social interactions with humans. We hope that the sensory motor level in Petra could serve as a foundation for further works in modeling the three-layered architecture of the Emotion State Generator