Making New "New AI" Friends : Designing a Social Robot for Diabetic Children from an Embodied AI Perspective

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Robin is a cognitively and motivationally autonomous affective robot toddler with "robot diabetes" that we have developed to support perceived self-efficacy and emotional wellbeing in children with diabetes by providing them with positive mastery experiences of diabetes management in a playful but realistic and natural interaction context. Underlying the design of Robin is an "Embodied" (formerly also known as "New") Artificial Intelligence approach to robotics. In this paper we discuss the rationale behind the design of Robin to meet the needs of our intended end users (both children and medical staff), and how "New AI" provides a suitable approach to developing a friendly companion that fulfills the therapeutic and affective requirements of our end users beyond other approaches commonly used in assistive robotics and child-robot interaction. Finally, we discuss how our approach permitted our robot to interact with and provide suitable experiences of diabetes management to children with very different social interaction styles.Peer reviewedFinal Published versio

Examining ecological validity in social interaction: problems of visual fidelity, gaze, and social potential

Social interaction is an essential part of the human experience, and much work has been done to study it. However, several common approaches to examining social interactions in psychological research may inadvertently either unnaturally constrain the observed behaviour by causing it to deviate from naturalistic performance, or introduce unwanted sources of variance. In particular, these sources are the differences between naturalistic and experimental behaviour that occur from changes in visual fidelity (quality of the observed stimuli), gaze (whether it is controlled for in the stimuli), and social potential (potential for the stimuli to provide actual interaction). We expand on these possible sources of extraneous variance and why they may be important. We review the ways in which experimenters have developed novel designs to remove these sources of extraneous variance. New experimental designs using a ‘two-person’ approach are argued to be one of the most effective ways to develop more ecologically valid measures of social interaction, and we suggest that future work on social interaction should use these designs wherever possible

Biosignals reflect pair-dynamics in collaborative work : EDA and ECG study of pair-programming in a classroom environment

Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.Peer reviewe

Brettanomyces bruxellensis yeasts: impact on wine and winemaking

Yeasts belonging to the Brettanomyces/Dekkera genus are non-conventional yeasts, which affect winemaking by causing wine spoilage all over the world. This mini-review focuses on recent results concerning the presence of Brettanomyces bruxellensis throughout the wine processing chain. Here, culture-dependent and independent methods to detect this yeast on grapes and at the very early stage of wine production are encompassed. Chemical, physical and biological tools, devised for the prevention and control of such a detrimental species during winemaking are also presented. Finally, the mini-review identifies future research areas relevant to the improvement of wine safety and sensory profiles

Learning postures through an imitation game between a human and a robot

International audienc

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Agents Behavior Semi-automatic Analysis through Their Comparison to Human Behavior Clustering

10 pages Online ISBN : 978-3-319-09767-1 Print ISBN : 978-3-319-09766-4International audienceThis paper presents a generic method to evaluate virtual agents that aim at reproducing humans behaviors in an immersive virtual environment. We first use automated clustering of simulation logs to extract humans behaviors. We then propose an aggregation of the agents logs into those clusters to analyze the credibility of agents behaviors in terms of capacities, lacks, and errors by comparing them to humans ones. We complete this analysis with a subjective evaluation based on a questionnaire filled by human annotators to draw categories of users, making their behaviors explicit. We illustrate this method in the context of immersive driving simulation

Taxonomy-based detection of user emotions for advanced artificial intelligent applications

Taxonomy-Based Detection of User Emotions for Advanced Artificial Intelligent Application