Personalized Empathic Computing (PEC)

Until a decade ago, computers were only used by experts, for professional purposes solely. Nowadays, the personal computer (PC) is standard equipment in most western housekeepings and is used to gather information, play games, communicate, etc. In parallel, users' expectations increase and, consequently, PCs are more and more adapted to our needs. The next phase in PC evolution is Personalized Empathic Computing (PEC). When thinking of PEC, questions emerge such as: Who is the user and how to model his or her characteristics? In addition, both possibilities and constraints of technology have to be taken into account. To unravel human emotional state, psychophysiological techniques are employed. Audio and visual information processing is needed to handle the multimedia input. Virtual Reality can be employed to realize high level interaction between users and PEC systems. The realization of PEC requires the cooperation among a broad range of disciplines; e.g., psychology, physiology, computer science, agent technology, interface design, and multimedia analysis. All will be illustrated by running projects, industrial applications, and the latest scientific research. Both the strength and the limitations of current state-of-the-art techniques will be indicated. With that we will look forward, to the future, which is not that far away anymore ..

Avatars and Lebensform: Kirchberg 2007

Several years ago, after a decade of experiments in the software industry, I returned to academia and found philosophy colleagues troubled by the term “virtual reality” — a term which enjoys wide usage in the ?eld of immersive computing but which raises hackles in post-metaphysical philosophers. Some vocabulary in this paper may create similar unease, so a warning may be in order. What makes sense to software engineers may for philosophers carry too much baggage. Words like “empathetic” or “empathic” may cause similar discomfort for those with an allergy to Romanticism. While these adjectives associated with poets like Wordsworth, the term “empathy” belongs equally to software designers and video-game artists who use it to describe the opposite of “?rst-person shooter” software. Empathic, as opposed to “shoot ‘em up” software, encourages the exchange of viewpoints beyond ?rst-person perspective and may even merge several perspectives. Rather than deepen a user’s ?rst-person point-of-view, empathic software offers a socializing experience, and in fact, is sometimes called “social” software, “Net 2.0,” or “computer supported cooperative work.

Emphatic agents to reduce user frustration: The effects of varying agent characteristics

There is now growing interest in the development of computer systems which respond to users’ emotion and affect. We report three small scale studies (with a total of 42 participants) which investigate the extent to which affective agents, using strategies derived from human-human interaction, can reduce user frustration within human-computer interaction. The results confirm the previous findings of Klein et al (2002) that such interventions can be effective. We also obtained results that suggest that embodied agents can be more effective at reducing frustration than non-embodied agents, and that female embodied agents may be more effective than male embodied agents. These results are discussed in light of the existing research literature

I Probe, Therefore I Am: Designing a Virtual Journalist with Human Emotions

By utilizing different communication channels, such as verbal language, gestures or facial expressions, virtually embodied interactive humans hold a unique potential to bridge the gap between human-computer interaction and actual interhuman communication. The use of virtual humans is consequently becoming increasingly popular in a wide range of areas where such a natural communication might be beneficial, including entertainment, education, mental health research and beyond. Behind this development lies a series of technological advances in a multitude of disciplines, most notably natural language processing, computer vision, and speech synthesis. In this paper we discuss a Virtual Human Journalist, a project employing a number of novel solutions from these disciplines with the goal to demonstrate their viability by producing a humanoid conversational agent capable of naturally eliciting and reacting to information from a human user. A set of qualitative and quantitative evaluation sessions demonstrated the technical feasibility of the system whilst uncovering a number of deficits in its capacity to engage users in a way that would be perceived as natural and emotionally engaging. We argue that naturalness should not always be seen as a desirable goal and suggest that deliberately suppressing the naturalness of virtual human interactions, such as by altering its personality cues, might in some cases yield more desirable results.Comment: eNTERFACE16 proceeding

Sharing emotions and space - empathy as a basis for cooperative spatial interaction

Boukricha H, Nguyen N, Wachsmuth I. Sharing emotions and space - empathy as a basis for cooperative spatial interaction. In: Kopp S, Marsella S, Thorisson K, Vilhjalmsson HH, eds. Proceedings of the 11th International Conference on Intelligent Virtual Agents (IVA 2011). LNAI. Vol 6895. Berlin, Heidelberg: Springer; 2011: 350-362.Empathy is believed to play a major role as a basis for humans’ cooperative behavior. Recent research shows that humans empathize with each other to different degrees depending on several modulation factors including, among others, their social relationships, their mood, and the situational context. In human spatial interaction, partners share and sustain a space that is equally and exclusively reachable to them, the so-called interaction space. In a cooperative interaction scenario of relocating objects in interaction space, we introduce an approach for triggering and modulating a virtual humans cooperative spatial behavior by its degree of empathy with its interaction partner. That is, spatial distances like object distances as well as distances of arm and body movements while relocating objects in interaction space are modulated by the virtual human’s degree of empathy. In this scenario, the virtual human’s empathic emotion is generated as a hypothesis about the partner’s emotional state as related to the physical effort needed to perform a goal directed spatial behavior

Modeling Empathy and Distress in Reaction to News Stories

Computational detection and understanding of empathy is an important factor in advancing human-computer interaction. Yet to date, text-based empathy prediction has the following major limitations: It underestimates the psychological complexity of the phenomenon, adheres to a weak notion of ground truth where empathic states are ascribed by third parties, and lacks a shared corpus. In contrast, this contribution presents the first publicly available gold standard for empathy prediction. It is constructed using a novel annotation methodology which reliably captures empathy assessments by the writer of a statement using multi-item scales. This is also the first computational work distinguishing between multiple forms of empathy, empathic concern, and personal distress, as recognized throughout psychology. Finally, we present experimental results for three different predictive models, of which a CNN performs the best.Comment: To appear at EMNLP 201

Predicting Empathy From Resting State Brain Connectivity: A Multivariate Approach.

Recent task fMRI studies suggest that individual differences in trait empathy and empathic concern are mediated by patterns of connectivity between self-other resonance and top-down control networks that are stable across task demands. An untested implication of this hypothesis is that these stable patterns of connectivity should be visible even in the absence of empathy tasks. Using machine learning, we demonstrate that patterns of resting state fMRI connectivity (i.e. the degree of synchronous BOLD activity across multiple cortical areas in the absence of explicit task demands) of resonance and control networks predict trait empathic concern (n = 58). Empathic concern was also predicted by connectivity patterns within the somatomotor network. These findings further support the role of resonance-control network interactions and of somatomotor function in our vicariously driven concern for others. Furthermore, a practical implication of these results is that it is possible to assess empathic predispositions in individuals without needing to perform conventional empathy assessments