Catálogo de publicaciones - libros

What are symbiotic systems? In this short paper, the workshop chairs describe the focus of this workshop and elaborate on the definition of symbiotic human-machine relation.

Symbiotic systems are systems that gather personal data provided by the user, derive a of the user from such data and their output/service according to their notion of what would be desirable to the user thus modeled. Because of these three characteristics, symbiotic systems represent a step forward towards facilitated, simplified, user-friendly digital devices, or do they? Here we propose three cases describing realistic applications of symbiotic systems that potentially encapsulate some serious risk to their users. Experts of five different domains (i.e., ethics, security, law, human-computer interaction and psychology) dissect each case to identify the risks to the users and derive some possible minimization strategies. This panel aims at contributing to a beneficial development of symbiotic systems as it can be achieved by increasing users’ discernment and awareness of their consequences for society and everyday life.

Affective symbiosis for human–computer interaction refers to the dynamic relationship between the user and affective virtual agents. In order to facilitate a true, immersive experience, we believe that it is necessary to adapt the presentation of an affective agent to the user’s affective state. Investigating the experience, behavior, and physiological correlates of affective events, such as winning and losing during a competitive game, therefore might be used to adapt the agent’s emotional states and system events. An experimental virtual reality game environment was designed as a stepping stone toward a system to demonstrate affective symbiosis. Users were invited to play a game of air hockey with affective agents in virtual reality. We collected the electrocardiography, electrodermal activity, and postural data, as well as self-reports, to investigate how emotional events affected physiology, behavior, and experience. The users were found to be engaged in the competition strongly while only paying limited attention to their adversaries’ emotional expressions. We discuss how game events are much stronger causes for affective responses, with the physiological effects of winning and losing becoming more enhanced as the game progresses. We discuss how an affective, symbiotic system could implement both game events and dynamic, affective agents to create a system for total immersion.

The paper analyzes the interaction between humans and computers in terms of response time in solving the image-based CAPT-CHA. In particular, the analysis focuses on the attitude of the different Internet users in easily solving four different types of image-based CAPTCHAs which include facial expressions such as: animated character, old woman, surprised face, worried face. To pursue this goal, an experiment is realized involving 100 Internet users in solving the four types of CAPTCHAs, differentiated by age, Internet experience, and education level. The response times are collected for each user. Then, association rules are extracted from user data, for evaluating the dependence of the response time in solving the CAPTCHA from age, education level and experience in Internet usage by statistical analysis. The results implicitly capture the users’ psychological states showing in what states the users are more sensitive. It reveals to be a novelty and a meaningful analysis in the state-of-the-art.

This work is a pilot study that used neurometric indexes during the listening of selected pieces of Dante’s “Divina Commedia” in 20 participants. Half of them had a literary formation (Humanist; university students of literature) while the other half of is attending other university courses (Not Humanist). The study applied the electroencephalographic (EEG) rhythms variations, the heart rate (HR) and galvanic skin response (GSR) during the listening of the excerpts. The neurometric indexes here employed were the Approach Withdrawal (AW), the Cerebral Effort (CE) and the Emotional indexes (EI). Results for the comparisons of the estimated AW, CE and EI related to the perception of the showed as the Humanist group reported higher AW and EI values when compared to the Not Humanist sample (p < 0.03 and p < 0.01, respectively). Results suggest that the perception of the aesthetic experience is significantly modulated by the previous specific knowledge experienced by the participants. Finally, results of this kind of research could find application in the implementation of software and devices based on symbiotic relation with the perspective reader or listener of a literature opera, in order to personalize and maximize the fruition of them.

We demonstrate that the current Child-Computer Interaction paradigm is not potentiating human development to its fullest. It is linked to several physical and mental health problems and appears not to be maximizing children’s cognitive development and performance. To potentiate children’s physical and mental health (including cognitive development and performance) we conceived a new approach to human development and evolution. This approach proposes a particular synergy between the developing human body, computing machines and natural environments. It emphasizes that children should be encouraged to interact with challenging physical environments offering multiple possibilities for sensory stimulation and increasing physical and mental stress to the organism. We created and tested a new set of robotic devices to operationalize our approach – Biosymtic (Biosymbiotic Robotic) devices.

Recent advances in deep neural networks have given rise to new approaches to content-based image retrieval (CBIR). Their ability to learn universal visual features for any target query makes them a good choice for systems dealing with large and diverse image datasets. However, employing deep neural networks in interactive CBIR systems still poses challenges: either the search target has to be predetermined, such as with hashing, or the computational cost becomes prohibitive for an online setting. In this paper, we present a framework for conducting interactive CBIR that learns a deep, dynamic metric between images. The proposed methodology is not limited to precalculated categories, hashes or clusters of the search space, but rather is formed instantly and interactively based on the user feedback. We use a deep learning framework that utilizes pre-extracted features from Convolutional Neural Networks and learns a new distance representation based on the user’s relevance feedback. The experimental results show the potential of applying our framework in an interactive CBIR setting as well as symbiotic interaction, where the system automatically detects what image features might best satisfy the user’s needs.

For healthy computer use, frequent, short breaks are crucial. This research investigated whether context-aware persuasive technology can identify opportune and effective moments (of high user motivation and ability to perform target behavior) for triggering short breaks fostering symbiotic interactions between e-Coaching e-Health technology and users. In Study 1, office workers rated their motivation and ability to take a short break (probed at random moments). Simultaneously their computer activity was recorded. Results showed that computer activity (time since last break; change in computer activity level) can predict moments of high and low (perceived) ability (but not motivation) to take a short break. Study 2 showed that when office workers received triggers (to take a short break) at moments of high (vs. low) ability (predicted based on computer activity), compliance increased 70%. These results show that context information can be used to identify opportune moments, at which persuasive triggers are more effective.

The human factor plays the key role for safety in many industrial and civil every-day operations in our technologized world. Human failure is more likely to cause accidents than technical failure, e.g. in the challenging job of tugboat captains. Here, cognitive workload is crucial, as its excess is a main cause of dangerous situations and accidents while being highly participant and situation dependent. However, knowing the captain’s level of workload can help to improve man-machine interaction. The main contributions of this paper is a successful workload indication and a transfer of cognitive workload knowledge from laboratory to realistic settings.

Identity verification is nowadays a very sensible issue. In this paper, we proposed a new tool focused on human-mouse interaction to detect fake responses about identity. Experimental results showed that this technique is able to detect fake responses about identities with an accuracy higher than 95%. In addition to a high sensitivity, the described methodology exceeds the limits of the biometric measures currently available for identity verification and the constraints of the traditional lie detection cognitive paradigms. Thanks to the many advantages offered by this technique, its application looks promising especially in field of national and global security as anti-terrorist measure. This paper represents an advancement in the knowledge of symbiotic systems demonstrating that human-machine interaction may be well integrated into security systems.