The effect of conversation on altruism: A comparative study with different media and generations.

Despite the overwhelming evidence of climate change and its effects on future generations, most individuals are still hesitant to make environmental changes that would especially benefit future generations. In this study, we investigate whether dialogue can influence people's altruistic behavior toward future generations of humans, and how it may be affected by participant age and the appearance of the conversation partner. We used a human, an android robot called Telenoid, and a speaker as representatives of future generations. Participants were split among an old age group and a young age group and were randomly assigned to converse with one of the aforementioned representatives. We asked the participants to play a round of the Dictator Game with the representative they were assigned, followed by an interactive conversation and another round of the Dictator Game in order to gauge their level of altruism. The results show that, on average, participants gave more money after having an interactive conversation, and that older adults tend to give more money than young adults. There were no significant differences between the three representatives. The results show that empathy might have been the most important factor in the increase in altruistic behavior for all participants.

Social robot for older adults with cognitive decline: a preliminary trial.

The number of older adults living alone is rapidly increasing. Loneliness in older adults not only degrade their quality of life but also causes troubles such as heavy burden on the medical staff, especially when cognitive decline is present. Social robots could be used in several ways to reduce such problems. As a first step towards this goal, we introduced conversation robots into the homes of older adults with cognitive decline to evaluate the robot's availability and acceptance during several months. The study involved two steps, one for evaluating the robustness of the proposed robotic system, and the second one to examine the long-term acceptance of social robots by older adults with cognitive decline living alone. Our data shows that after several weeks of human-robot interaction, the participants continued to use the robot and successfully integrated them into their lives. These results open the possibility of further research involving how sustained interaction can be achieved, as well as which factors contributed to the acceptance of the robot.

Information Content of Prefrontal Cortex Activity Quantifies the Difficulty of Narrated Stories.

The ability to realize the individuals' impressions during the verbal communication allows social robots to significantly facilitate their social interactions in such areas as child education and elderly care. However, such impressions are highly subjective and internalized and therefore cannot be easily comprehended through behavioural observations. Although brain-machine interface suggests the utility of the brain information in human-robot interaction, previous studies did not consider its potential for estimating the internal impressions during verbal communication. In this article, we introduce a novel approach to estimation of the individuals' perceived difficulty of stories using the quantified information content of their prefrontal cortex activity. We demonstrate the robustness of our approach by showing its comparable performance in face-to-face, humanoid, speaker, and video-chat settings. Our results contribute to the field of socially assistive robotics by taking a step toward enabling robots determine their human companions' perceived difficulty of conversations, thereby enabling these media to sustain their communication with humans by adapting to individuals' pace and interest in response to conversational nuances and complexity.

Multiscale Entropy Quantifies the Differential Effect of the Medium Embodiment on Older Adults Prefrontal Cortex during the Story Comprehension: A Comparative Analysis.

Todays' communication media virtually impact and transform every aspect of our daily communication and yet the extent of their embodiment on our brain is unexplored. The study of this topic becomes more crucial, considering the rapid advances in such fields as socially assistive robotics that envision the use of intelligent and interactive media for providing assistance through social means. In this article, we utilize the multiscale entropy (MSE) to investigate the effect of the physical embodiment on the older people's prefrontal cortex (PFC) activity while listening to stories. We provide evidence that physical embodiment induces a significant increase in MSE of the older people's PFC activity and that such a shift in the dynamics of their PFC activation significantly reflects their perceived feeling of fatigue. Our results benefit researchers in age-related cognitive function and rehabilitation who seek for the adaptation of these media in robot-assistive cognitive training of the older people. In addition, they offer a complementary information to the field of human-robot interaction via providing evidence that the use of MSE can enable the interactive learning algorithms to utilize the brain's activation patterns as feedbacks for improving their level of interactivity, thereby forming a stepping stone for rich and usable human mental model.

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory.

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli.

A Non-parametric Approach to the Overall Estimate of Cognitive Load Using NIRS Time Series.

We present a non-parametric approach to prediction of the n-back n ∈ {1, 2} task as a proxy measure of mental workload using Near Infrared Spectroscopy (NIRS) data. In particular, we focus on measuring the mental workload through hemodynamic responses in the brain induced by these tasks, thereby realizing the potential that they can offer for their detection in real world scenarios (e.g., difficulty of a conversation). Our approach takes advantage of intrinsic linearity that is inherent in the components of the NIRS time series to adopt a one-step regression strategy. We demonstrate the correctness of our approach through its mathematical analysis. Furthermore, we study the performance of our model in an inter-subject setting in contrast with state-of-the-art techniques in the literature to show a significant improvement on prediction of these tasks (82.50 and 86.40% for female and male participants, respectively). Moreover, our empirical analysis suggest a gender difference effect on the performance of the classifiers (with male data exhibiting a higher non-linearity) along with the left-lateralized activation in both genders with higher specificity in females.

Intimacy in Phone Conversations: Anxiety Reduction for Danish Seniors with Hugvie.

There is a lack of physical contact in current telecommunications such as text messaging and Internet access. To challenge the limitation and re-embody telecommunication, researchers have attempted to introduce tactile stimulation to media and developed huggable devices. Previous experiments in Japan showed that a huggable communication technology, i.e., Hugvie decreased stress level of its female users. In the present experiment in Denmark, we aim to investigate (i) whether Hugvie can decrease stress cross-culturally, i.e., Japanese vs. Danish participants (ii), investigate whether gender plays a role in this psychological effect (stress reduction) and (iii) if there is a preference of this type of communication technology (Hugvie vs. a regular telephone). Twenty-nine healthy elderly participated (15 female and 14 male, M = 64.52 years, SD = 5.67) in Jutland, Denmark. The participants filled out questionnaires including State-Trait Anxiety Inventory, NEO Five Factor Inventory (NEO-FFI), and Becks Depression Inventory, had a 15 min conversation via phone or Hugvie and were interviewed afterward. They spoke with an unknown person of opposite gender during the conversation; the same two conversation partners were used during the experiment and the Phone and Hugvie groups were equally balanced. There was no baseline difference between the Hugvie and Phone groups on age or anxiety or depression scores. In the Hugvie group, there was a statistically significant reduction on state anxiety after meeting Hugvie (p = 0.013). The change in state anxiety for the Hugvie group was positively correlated with openness (r = 0.532, p = 0.041) as measured by the NEO-FFI. This indicates that openness to experiences may increase the chances of having an anxiety reduction from being with Hugvie. Based on the results, we see that personality may affect the participants' engagement and benefits from Hugvie. We discuss the implications of the results and further elaborations.

Attitudinal Change in Elderly Citizens Toward Social Robots: The Role of Personality Traits and Beliefs About Robot Functionality.

Attitudes toward robots influence the tendency to accept or reject robotic devices. Thus it is important to investigate whether and how attitudes toward robots can change. In this pilot study we investigate attitudinal changes in elderly citizens toward a tele-operated robot in relation to three parameters: (i) the information provided about robot functionality, (ii) the number of encounters, (iii) personality type. Fourteen elderly residents at a rehabilitation center participated. Pre-encounter attitudes toward robots, anthropomorphic thinking, and personality were assessed. Thereafter the participants interacted with a tele-operated robot (Telenoid) during their lunch (c. 30 min.) for up to 3 days. Half of the participants were informed that the robot was tele-operated (IC) whilst the other half were naïve to its functioning (UC). Post-encounter assessments of attitudes toward robots and anthropomorphic thinking were undertaken to assess change. Attitudes toward robots were assessed with a new generic 35-items questionnaire (attitudes toward social robots scale: ASOR-5), offering a differentiated conceptualization of the conditions for social interaction. There was no significant difference between the IC and UC groups in attitude change toward robots though trends were observed. Personality was correlated with some tendencies for attitude changes; Extraversion correlated with positive attitude changes to intimate-personal relatedness with the robot (r = 0.619) and to psychological relatedness (r = 0.581) whilst Neuroticism correlated negatively (r = -0.582) with mental relatedness with the robot. The results tentatively suggest that neither information about functionality nor direct repeated encounters are pivotal in changing attitudes toward robots in elderly citizens. This may reflect a cognitive congruence bias where the robot is experienced in congruence with initial attitudes, or it may support action-based explanations of cognitive dissonance reductions, given that robots, unlike computers, are not yet perceived as action targets. Specific personality traits may be indicators of attitude change relating to specific domains of social interaction. Implications and future directions are discussed.