Masada performances : the contested indentities of touristic spaces

Masada, a Herodian fortress and the site of an ancient struggle between Jews and Romans that culminated in a mass suicide by 960 Jews, is a symbolically important site for the country of Israel and for the Jewish people. Previous research on Masada has focused on how the story about the site, told through popular culture, in history books, and at the site, has been used to create and maintain a national Israeli and, more broadly, Jewish identity. Masada is the second most visited site in Israel, attracting over 800,000 people each year, and the number of visitors to the site has steadily increased over the last thirty years. When tourists visit Masada, they hear the story of the site and the story is framed so tourists will have a meaningful experience. While some scholars have looked at how the Masada story gets told to tourists who visit the site, these studies all tend to ignore what tourists do at the site. The research, presented this way, seems to assume that tourists and others who hear the story are passive recipients. I argue that tourists who visit Masada take a more active role in the meaning they get from their visit. In this dissertation I focus on what tourists and others do at Masada. I frame these actions as performances, conscious and deliberate acts that constitute who a person is and how they want to be seen. I argue that the touristic performances at Masada are expressions of the meaning that people get from the site and from being on tour. I conclude that being on tour encourages a fluid approach to individual and national identity. As tourists contend with the site, other tourists, and their own identity, tourist sites can be productive spaces to explore who a person is and who they want to be

Presenting in Virtual Worlds: Towards an Architecture for a 3D Presenter explaining 2D-Presented Information

Entertainment, education and training are changing because of multi-party interaction technology. In the past we have seen the introduction of embodied agents and robots that take the role of a museum guide, a news presenter, a teacher, a receptionist, or someone who is trying to sell you insurances, houses or tickets. In all these cases the embodied agent needs to explain and describe. In this paper we contribute the design of a 3D virtual presenter that uses different output channels to present and explain. Speech and animation (posture, pointing and involuntary movements) are among these channels. The behavior is scripted and synchronized with the display of a 2D presentation with associated text and regions that can be pointed at (sheets, drawings, and paintings). In this paper the emphasis is on the interaction between 3D presenter and the 2D presentation

The Interpersonal Effects of Emotions in Money versus Candy Games

Emotional expressions significantly influence perceivers’ behavior in economic games and negotiations. The current research examined the interpersonal effects of emotions when such information cannot be used to guide behavior for increasing personal gain and when monetary rewards are made salient. For this, a one-shot Public Goods Game (Studies 1, 2, and 3) and Dictator Game (Studies 4 and 5) were employed, in which the dominant strategy to maximize personal payoff is independent from the counterplayers’ intention signaled through their facial expressions (happiness, sadness, and anger). To elicit a monetary mindset, we used money (vs. candy) as the mode of exchange in the games with (Studies 1 and 2) or without (Studies 3, 4, and 5) additional contextual framing (i.e. Wall Street Game vs. Community Game). Across five studies (N = 1211), participants were found to be more generous towards happy and sad targets compared to angry ones. Such behavioral response based on emotional information was accounted for by the trait impressions (i.e. likability, trustworthiness) formed of the counterplayer. This effect was significantly reduced when money acted as the mode of exchange, thereby making participants focus more on their selfgain. Together, the findings extend previous work by highlighting the social functional role of emotions in human exchange and its moderation by money as a transaction medium

Predicting folds in poker using action unit detectors and decision trees

Predicting how a person will respond can be very useful, for instance when designing a strategy for negotiations. We investigate whether it is possible for machine learning and computer vision techniques to recognize a person’s intentions and predict their actions based on their visually expressive behaviour, where in this paper we focus on the face. We have chosen as our setting pairs of humans playing a simplified version of poker, where the players are behaving naturally and spontaneously, albeit mediated through a computer connection. In particular, we ask if we can automatically predict whether a player is going to fold or not. We also try to answer the question of at what time point the signal for predicting if a player will fold is strongest. We use state-of-the-art FACS Action Unit detectors to automatically annotate the players facial expressions, which have been recorded on video. In addition, we use timestamps of when the player received their card and when they placed their bets, as well as the amounts they bet. Thus, the system is fully automated. We are able to predict whether a person will fold or not significantly better than chance based solely on their expressive behaviour starting three seconds before they fold

An End-to-End Conversational Style Matching Agent

We present an end-to-end voice-based conversational agent that is able to engage in naturalistic multi-turn dialogue and align with the interlocutor's conversational style. The system uses a series of deep neural network components for speech recognition, dialogue generation, prosodic analysis and speech synthesis to generate language and prosodic expression with qualities that match those of the user. We conducted a user study (N=30) in which participants talked with the agent for 15 to 20 minutes, resulting in over 8 hours of natural interaction data. Users with high consideration conversational styles reported the agent to be more trustworthy when it matched their conversational style. Whereas, users with high involvement conversational styles were indifferent. Finally, we provide design guidelines for multi-turn dialogue interactions using conversational style adaptation

Haunting stories of abuse: revealing ghosts through critical performance ethnography

This project explores what it means to be haunted by a history of abuse. Through critical performance ethnography I explore the incommunicability of intimate abuse. In an effort to make meaning out of these acts, we work to label past experiences and place them into an easily explainable context. In so doing, many mundane acts of abuse might not be viewed as legitimate by the people who experienced these acts of abuse. This project employed a performance centered research method. A staged performance was created that juxtaposed ethnographic research, theories of victimization, memory, and haunting, and a traditional ghost story. This opened up conversations of how histories of abuse continue to effect people long after the physical abuse stops. This analysis suggests that focusing on the relationship aspect of intimate abuse offers methods of praxis that are absent when our focus rests on labels

Social decisions and fairness change when people’s interests are represented by autonomous agents

There has been growing interest on agents that represent people’s interests or act on their behalf such as automated negotiators, self-driving cars, or drones. Even though people will interact often with others via these agent representatives, little is known about whether people’s behavior changes when acting through these agents, when compared to direct interaction with others. Here we show that people’s decisions will change in important ways because of these agents; specifically, we showed that interacting via agents is likely to lead people to behave more fairly, when compared to direct interaction with others. We argue this occurs because programming an agent leads people to adopt a broader perspective, consider the other side’s position, and rely on social norms—such as fairness—to guide their decision making. To support this argument, we present four experiments: in Experiment 1 we show that people made fairer offers in the ultimatum and impunity games when interacting via agent representatives, when compared to direct interaction; in Experiment 2, participants were less likely to accept unfair offers in these games when agent representatives were involved; in Experiment 3, we show that the act of thinking about the decisions ahead of time—i.e., under the so-called “strategy method”—can also lead to increased fairness, even when no agents are involved; and, finally, in Experiment 4 we show that participants were less likely to reach an agreement with unfair counterparts in a negotiation setting. We discuss theoretical implications for our understanding of the nature of people’s social behavior with agent representatives, as well as practical implications for the design of agents that have the potential to increase fairness in society

Teacher Perception of Project-Based Learning in a Technology-infused Secondary School Culture: a Critical Ciné-ethnographic Study

Project-based learning has long been used in the educational realm as it emphasis a student-centered strategy which promotes meaning, enriched learning that enhances inquiry and problem-solving skills in a rich, authentic environment. The relevance and authentic design of projects may further be enhanced by the use of technology in the classroom. Technology is rapidly changing the face of American education in ways that were barely thinkable as little as five years before and provides the possibility for student to collaborate and complete complex project-based tasks with further level of authenticity which connects to the students preferred method of learning and productivity outside the classroom. At New Tech high school in Coppell, Texas, the entire curriculum is based around this project-based learning in a technology-infused classroom. This qualitative, case-based study is designed to explore and examine the teachers' perceptions of the use of project-based learning, technology in this non-traditional environment. The study also investigates the teacher perceptions of students' response to project-based learning and the technology available to them in their project-based tasks. Finally the study discusses the finding and their possible implications for traditional educational environments

Human cooperation when acting through autonomous machines

Recent times have seen an emergence of intelligent machines that act autonomously on our behalf, such as autonomous vehicles. Despite promises of increased efficiency, it is not clear whether this paradigm shift will change how we decide when our self-interest (e.g., comfort) is pitted against the collective interest (e.g., environment). Here we show that acting through machines changes the way people solve these social dilemmas and we present experimental evidence showing that participants program their autonomous vehicles to act more cooperatively than if they were driving themselves. We show that this happens because programming causes selfish short-term rewards to become less salient, leading to considerations of broader societal goals. We also show that the programmed behavior is influenced by past experience. Finally, we report evidence that the effect generalizes beyond the domain of autonomous vehicles. We discuss implications for designing autonomous machines that contribute to a more cooperative society