Towards a framework for socially interactive robots

250 p.En las últimas décadas, la investigación en el campo de la robótica social ha crecido considerablemente. El desarrollo de diferentes tipos de robots y sus roles dentro de la sociedad se están expandiendo poco a poco. Los robots dotados de habilidades sociales pretenden ser utilizados para diferentes aplicaciones; por ejemplo, como profesores interactivos y asistentes educativos, para apoyar el manejo de la diabetes en niños, para ayudar a personas mayores con necesidades especiales, como actores interactivos en el teatro o incluso como asistentes en hoteles y centros comerciales.El equipo de investigación RSAIT ha estado trabajando en varias áreas de la robótica, en particular,en arquitecturas de control, exploración y navegación de robots, aprendizaje automático y visión por computador. El trabajo presentado en este trabajo de investigación tiene como objetivo añadir una nueva capa al desarrollo anterior, la capa de interacción humano-robot que se centra en las capacidades sociales que un robot debe mostrar al interactuar con personas, como expresar y percibir emociones, mostrar un alto nivel de diálogo, aprender modelos de otros agentes, establecer y mantener relaciones sociales, usar medios naturales de comunicación (mirada, gestos, etc.),mostrar personalidad y carácter distintivos y aprender competencias sociales.En esta tesis doctoral, tratamos de aportar nuestro grano de arena a las preguntas básicas que surgen cuando pensamos en robots sociales: (1) ¿Cómo nos comunicamos (u operamos) los humanos con los robots sociales?; y (2) ¿Cómo actúan los robots sociales con nosotros? En esa línea, el trabajo se ha desarrollado en dos fases: en la primera, nos hemos centrado en explorar desde un punto de vista práctico varias formas que los humanos utilizan para comunicarse con los robots de una maneranatural. En la segunda además, hemos investigado cómo los robots sociales deben actuar con el usuario.Con respecto a la primera fase, hemos desarrollado tres interfaces de usuario naturales que pretenden hacer que la interacción con los robots sociales sea más natural. Para probar tales interfaces se han desarrollado dos aplicaciones de diferente uso: robots guía y un sistema de controlde robot humanoides con fines de entretenimiento. Trabajar en esas aplicaciones nos ha permitido dotar a nuestros robots con algunas habilidades básicas, como la navegación, la comunicación entre robots y el reconocimiento de voz y las capacidades de comprensión.Por otro lado, en la segunda fase nos hemos centrado en la identificación y el desarrollo de los módulos básicos de comportamiento que este tipo de robots necesitan para ser socialmente creíbles y confiables mientras actúan como agentes sociales. Se ha desarrollado una arquitectura(framework) para robots socialmente interactivos que permite a los robots expresar diferentes tipos de emociones y mostrar un lenguaje corporal natural similar al humano según la tarea a realizar y lascondiciones ambientales.La validación de los diferentes estados de desarrollo de nuestros robots sociales se ha realizado mediante representaciones públicas. La exposición de nuestros robots al público en esas actuaciones se ha convertido en una herramienta esencial para medir cualitativamente la aceptación social de los prototipos que estamos desarrollando. De la misma manera que los robots necesitan un cuerpo físico para interactuar con el entorno y convertirse en inteligentes, los robots sociales necesitan participar socialmente en tareas reales para las que han sido desarrollados, para así poder mejorar su sociabilida

Taking Turing by Surprise? Designing Digital Computers for morally-loaded contexts

There is much to learn from what Turing hastily dismissed as Lady Lovelace s objection. Digital computers can indeed surprise us. Just like a piece of art, algorithms can be designed in such a way as to lead us to question our understanding of the world, or our place within it. Some humans do lose the capacity to be surprised in that way. It might be fear, or it might be the comfort of ideological certainties. As lazy normative animals, we do need to be able to rely on authorities to simplify our reasoning: that is ok. Yet the growing sophistication of systems designed to free us from the constraints of normative engagement may take us past a point of no-return. What if, through lack of normative exercise, our moral muscles became so atrophied as to leave us unable to question our social practices? This paper makes two distinct normative claims: 1. Decision-support systems should be designed with a view to regularly jolting us out of our moral torpor. 2. Without the depth of habit to somatically anchor model certainty, a computer s experience of something new is very different from that which in humans gives rise to non-trivial surprises. This asymmetry has key repercussions when it comes to the shape of ethical agency in artificial moral agents. The worry is not just that they would be likely to leap morally ahead of us, unencumbered by habits. The main reason to doubt that the moral trajectories of humans v. autonomous systems might remain compatible stems from the asymmetry in the mechanisms underlying moral change. Whereas in humans surprises will continue to play an important role in waking us to the need for moral change, cognitive processes will rule when it comes to machines. This asymmetry will translate into increasingly different moral outlooks, to the point of likely unintelligibility. The latter prospect is enough to doubt the desirability of autonomous moral agents

An Evaluation Schema for the Ethical Use of Autonomous Robotic Systems in Security Applications

We propose a multi-step evaluation schema designed to help procurement agencies and others to examine the ethical dimensions of autonomous systems to be applied in the security sector, including autonomous weapons systems

Do Chatbots Dream of Androids? Prospects for the Technological Development of Artificial Intelligence and Robotics

The article discusses the main trends in the development of artificial intelligence systems and robotics (AI&R). The main question that is considered in this context is whether artificial systems are going to become more and more anthropomorphic, both intellectually and physically. In the current article, the author analyzes the current state and prospects of technological development of artificial intelligence and robotics, and also determines the main aspects of the impact of these technologies on society and economy, indicating the geopolitical strategic nature of this influence. The author considers various approaches to the definition of artificial intelligence and robotics, focusing on the subject-oriented and functional ones. It also compares AI&R abilities and human abilities in areas such as categorization, pattern recognition, planning and decision making, etc. Based on this comparison, we investigate in which areas AI&R’s performance is inferior to a human, and in which cases it is superior to one. The modern achievements in the field of robotics and artificial intelligence create the necessary basis for further discussion of the applicability of goal setting in engineering, in the form of a Turing test. It is shown that development of AI&R is associated with certain contradictions that impede the application of Turing’s methodology in its usual format. The basic contradictions in the development of AI&R technologies imply that there is to be a transition to a post-Turing methodology for assessing engineering implementations of artificial intelligence and robotics. In such implementations, on the one hand, the ‘Turing wall’ is removed, and on the other hand, artificial intelligence gets its physical implementation

Believing in BERT:Using expressive communication to enhance trust and counteract operational error in physical Human-robot interaction

Strategies are necessary to mitigate the impact of unexpected behavior in collaborative robotics, and research to develop solutions is lacking. Our aim here was to explore the benefits of an affective interaction, as opposed to a more efficient, less error prone but non-communicative one. The experiment took the form of an omelet-making task, with a wide range of participants interacting directly with BERT2, a humanoid robot assistant. Having significant implications for design, results suggest that efficiency is not the most important aspect of performance for users; a personable, expressive robot was found to be preferable over a more efficient one, despite a considerable trade off in time taken to perform the task. Our findings also suggest that a robot exhibiting human-like characteristics may make users reluctant to 'hurt its feelings'; they may even lie in order to avoid this.Comment: 8 pages, 4 figure

Metacognition in Learning

Metacognition skills have been proven to have a positive relationship with learning. The strength of metacognition relies heavily on self-efficacy where a student understands his/her learning style, and the ability to use information gathered and align it with his/her learning style. In addition, knowing what you know and how you know it as a student plays a huge role in knowing what you do not know and linking it with what is close or relevant to it, that you know. It is about having skills and knowledge that empowers you to be an independent learner. Literature on classroom practices show a number of short-comings in diverse areas such as poor teacher knowledge, overcrowded classrooms, and lack of resources for learning. An independent student will strive under such an environment by studying independently, searching for resources, and finding multimodal ways of learning. It is also important to note that naturally, human beings are curious and want to learn in order to conquer their world. Hence, Piaget's work of intellectual autonomy cannot be ignored when exploring metacognition. If learning experiences were ideal and developmental, they would be no need to nurture metacognition. Unfortunately, the education systems remove students' curiosity by bringing fake environments into learning that impede creation and imagination. This book emphasises the power of metacognition at different levels of learning. It can be seen as a parallel intervention approach, with expanded knowledge on how to extend existing skills for young children, which is a pre-intervention. Authors in this book bring diverse viewpoints from diverse fields on how to nurture metacognition, thus giving the reader an opportunity to borrow strategies from other fields. This contribution is a mixture of empirical contributions and opinion pieces informed by review of literature