Affective Motivational Collaboration Theory

Existing computational theories of collaboration explain some of the important concepts underlying collaboration, e.g., the collaborators\u27 commitments and communication. However, the underlying processes required to dynamically maintain the elements of the collaboration structure are largely unexplained. Our main insight is that in many collaborative situations acknowledging or ignoring a collaborator\u27s affective state can facilitate or impede the progress of the collaboration. This implies that collaborative agents need to employ affect-related processes that (1) use the collaboration structure to evaluate the status of the collaboration, and (2) influence the collaboration structure when required. This thesis develops a new affect-driven computational framework to achieve these objectives and thus empower agents to be better collaborators. Contributions of this thesis are: (1) Affective Motivational Collaboration (AMC) theory, which incorporates appraisal processes into SharedPlans theory. (2) New computational appraisal algorithms based on collaboration structure. (3) Algorithms such as goal management, that use the output of appraisal to maintain collaboration structures. (4) Implementation of a computational system based on AMC theory. (5) Evaluation of AMC theory via two user studies to a) validate our appraisal algorithms, and b) investigate the overall functionality of our framework within an end-to-end system with a human and a robot

Influence Of Task-role Mental Models On Human Interpretation Of Robot Motion Behavior

The transition in robotics from tools to teammates has begun. However, the benefit autonomous robots provide will be diminished if human teammates misinterpret robot behaviors. Applying mental model theory as the organizing framework for human understanding of robots, the current empirical study examined the influence of task-role mental models of robots on the interpretation of robot motion behaviors, and the resulting impact on subjective ratings of robots. Observers (N = 120) were exposed to robot behaviors that were either congruent or incongruent with their task-role mental model, by experimental manipulation of preparatory robot task-role information to influence mental models (i.e., security guard, groundskeeper, or no information), the robot\u27s actual task-role behaviors (i.e., security guard or groundskeeper), and the order in which these robot behaviors were presented. The results of the research supported the hypothesis that observers with congruent mental models were significantly more accurate in interpreting the motion behaviors of the robot than observers without a specific mental model. Additionally, an incongruent mental model, under certain circumstances, significantly hindered an observer\u27s interpretation accuracy, resulting in subjective sureness of inaccurate interpretations. The strength of the effects that mental models had on the interpretation and assessment of robot behaviors was thought to have been moderated by the ease with which a particular mental model could reasonably explain the robot\u27s behavior, termed mental model applicability. Finally, positive associations were found between differences in observers\u27 interpretation accuracy and differences in subjective ratings of robot intelligence, safety, and trustworthiness. The current research offers implications for the relationships between mental model components, as well as implications for designing robot behaviors to appear more transparent, or opaque, to humans

Animals, Machines, and Moral Responsibility in a Built Environment

Nature has ended. Acid rain and global warming leave no place untouched by human hands. We can no longer think of \u27the environment\u27 as synonymous with \u27nature\u27. Instead, Steven Vogel argues that the environment is more like a mall: it is built. And because we build the environment, we are responsible for it. Yet, other things build, too. Animals build and use tools. Machines and algorithms build everything from skyscrapers to cell phones. Are they responsible for what they build? While animals and robots are normally considered in distinct philosophical fields, Vogel’s rejection of the natural-artificial split prompts us to question the distinction between natural and artificial agents. I argue, under consistent reasons, that neither animals nor robots are morally responsible for what they do. When machines act in morally consequential ways, then, we cannot blame the robot. However, we usually think to blame those who built the robot. I present a theory of how a builder may be responsible for what they build. Then, I argue that there are cases where neither the robot nor the engineer can be blamed for the robot\u27s actions. Drawing on Vogel, Karl Marx, and Martin Heidegger, I explore moral and environmental responsibility through meditations on animals and machines

Anxieties and artificial women: disassembling the pop culture gynoid

2018 Fall.Includes bibliographical references.This thesis analyzes the cultural meanings of the feminine-presenting robot, or gynoid, in three popular sci-fi texts: The Stepford Wives (1975), Ex Machina (2013), and Westworld (2017). Centralizing a critical feminist rhetorical approach, this thesis outlines the symbolic meaning of gynoids as representing cultural anxieties about women and technology historically and in each case study. This thesis draws from rhetorical analyses of media, sci-fi studies, and previously articulated meanings of the gynoid in order to discern how each text interacts with the gendered and technological concerns it presents. The author assesses how the text equips—or fails to equip—the public audience with motives for addressing those concerns. Prior to analysis, each chapter synthesizes popular and scholarly criticisms of the film or series and interacts with their temporal contexts. Each chapter unearths a unique interaction with the meanings of gynoid: The Stepford Wives performs necrophilic fetishism to alleviate anxieties about the Women's Liberation Movement; Ex Machina redirects technological anxieties towards the surveilling practices of tech industries, simultaneously punishing exploitive masculine fantasies; Westworld utilizes fantasies and anxieties cyclically in order to maximize its serial potential and appeal to impulses of its viewership, ultimately prescribing a rhetorical placebo. The conclusion synthesizes each chapter topically and ruminates on real-world implications. Overall, this thesis urges critical attention toward the gynoids' role in oppressive hierarchies onscreen and in reality

The Interrelationship between Sensorimotor Deficits and Maladaptive Behavior in the Classroom

Mainstreaming special education students has created challenges for teachers, resulting in significant lesson time allocated to classroom disruptions related to maladaptive behavior. This correlational study examined the extent to which specific sensorimotor deficits predict maladaptive behavior among special education students (aged 8-12 years) based on archival data of teacher assessments in New Zealand. Piaget’s cognitive and affective development theory was used as the theoretical foundation. Results from standard multiple regression demonstrated that higher levels of sensorimotor deficits (vision, touch, taste and smell, body awareness, balance and motion) predicted high levels of maladaptive behavior (internalizing, externalizing, and overall maladaptive behavior indices); similarly, higher deficits in taste and smell predicted low levels of adaptive behavior. These results may lead to positive social change by stressing the importance of early sensory assessment among young school children. In addition, the results may also be used to improve interventions or programs designed to reduce maladaptive behavior in the classroom, reducing teachers’ time devoted to managing maladaptive behavior and improving special education students\u27 mental health