Interactional Structure Applied to the Identification and Generation of Visual Interactive Behavior: Robots that (Usually) Follow the Rules

Peer reviewe

Face the Music and Glance: How Nonverbal Behaviour Aids Human Robot Relationships Based in Music

It is our hypothesis that improvised musical interaction will be able to provide the extended engagement often failing others during long term Human Robot Interaction (HRI) trials. Our previous work found that simply framing sessions with their drumming robot Mortimer as social interactions increased both social presence and engagement, two factors we feel are crucial to developing and maintaining a positive and meaningful relationship between human and robot. For this study we investigate the inclusion of the additional social modalities, namely head pose and facial expression, as nonverbal behaviour has been shown to be an important conveyor of information in both social and musical contexts. Following a 6 week experimental study using automatic behavioural metrics, results demonstrate those subjected to nonverbal behaviours not only spent more time voluntarily with the robot, but actually increased the time they spent as the trial progressed. Further, that they interrupted the robot less during social interactions and played for longer uninterrupted. Conversely, they also looked at the robot less in both musical and social contexts. We take these results as support for open ended musical activity providing a solid grounding for human robot relationships and the improvement of this by the inclusion of appropriate nonverbal behaviours

Towards a comprehensive taxonomy for characterizing robots

Every day a new robot is developed with advanced characteristics and technical qualities. The increasingly rapid growth of robots and their characteristics demands bridging between the application requirements and the robot specifications. This process requires a supporting conceptual structure that can capture as many robot qualities as possible. Presenting robot characteristics through the proposed conceptual structure would enable designers to optimize robot capabilities against application requirements. It would also help application developers to select the most appropriate robot. Without a formal structure, an accurate linking between the robot domain and the application domain is not possible. This paper presents a novel theoretical representation that can capture robot features and capabilities and express them as descriptive dimensions to be used to develop a capability profile. The profile is intended to unify robot description and presentation. The proposed structure is reinforced with several layers, sections, categorizations and levels to allow a detailed explanation of robot characteristics. It is hoped that the proposed structure will influence the design, development, and testing of robots for specific applications. At the same time, it would help in highlighting the corresponding outlines in robot application requirements

Gaze-Based Human-Robot Interaction by the Brunswick Model

We present a new paradigm for human-robot interaction based on social signal processing, and in particular on the Brunswick model. Originally, the Brunswick model copes with face-to-face dyadic interaction, assuming that the interactants are communicating through a continuous exchange of non verbal social signals, in addition to the spoken messages. Social signals have to be interpreted, thanks to a proper recognition phase that considers visual and audio information. The Brunswick model allows to quantitatively evaluate the quality of the interaction using statistical tools which measure how effective is the recognition phase. In this paper we cast this theory when one of the interactants is a robot; in this case, the recognition phase performed by the robot and the human have to be revised w.r.t. the original model. The model is applied to Berrick, a recent open-source low-cost robotic head platform, where the gazing is the social signal to be considered

Artificial Emotion Generation Based on Personality, Mood, and Emotion for Life-Like Facial Expressions of Robots

International audienceWe can't overemphasize the importance of robot's emotional expressions as robots step into human's daily lives. So, the believable and socially acceptable emotional expressions of robots are essential. For such human-like emotional expression, we have proposed an emotion generation model considering personality, mood and history of robot's emotion. The personality module is based on the Big Five Model (OCEAN Model, Five Factor Model); the mood module has one dimension such as good or bad, and the emotion module uses the six basic emotions as defined by Ekman. Unlike most of the previous studies, the proposed emotion generation model was integrated with the Linear Dynamic Affect Expression Model (LDAEM), which is an emotional expression model that can make facial expressions similar to those of humans. So, both the emotional state and expression of robots can be changed dynamically

Robot rights? Towards a social-relational justification of moral consideration \ud

Should we grant rights to artificially intelligent robots? Most current and near-future robots do not meet the hard criteria set by deontological and utilitarian theory. Virtue ethics can avoid this problem with its indirect approach. However, both direct and indirect arguments for moral consideration rest on ontological features of entities, an approach which incurs several problems. In response to these difficulties, this paper taps into a different conceptual resource in order to be able to grant some degree of moral consideration to some intelligent social robots: it sketches a novel argument for moral consideration based on social relations. It is shown that to further develop this argument we need to revise our existing ontological and social-political frameworks. It is suggested that we need a social ecology, which may be developed by engaging with Western ecology and Eastern worldviews. Although this relational turn raises many difficult issues and requires more work, this paper provides a rough outline of an alternative approach to moral consideration that can assist us in shaping our relations to intelligent robots and, by extension, to all artificial and biological entities that appear to us as more than instruments for our human purpose

Theories of parenting and their application to artificial intelligence

© 2019 Copyright is held by the owner/author(s). As machine learning (ML) systems have advanced, they have acquired more power over humans' lives, and questions about what values are embedded in them have become more complex and fraught. It is conceivable that in the coming decades, humans may succeed in creating artificial general intelligence (AGI) that thinks and acts with an open-endedness and autonomy comparable to that of humans. The implications would be profound for our species; they are now widely debated not just in science fiction and speculative research agendas but increasingly in serious technical and policy conversations. Much work is underway to try to weave ethics into advancing ML research. We think it useful to add the lens of parenting to these efforts, and specifically radical, queer theories of parenting that consciously set out to nurture agents whose experiences, objectives and understanding of the world will necessarily be very different from their parents'. We propose a spectrum of principles which might underpin such an effort; some are relevant to current ML research, while others will become more important if AGI becomes more likely. These principles may encourage new thinking about the development, design, training, and release into the world of increasingly autonomous agents