Intentional Mindset Toward Robots—Open Questions and Methodological Challenges

Natural and effective interaction with humanoid robots should involve social cognitive mechanisms of the human brain that normally facilitate social interaction between humans. Recent research has indicated that the presence and efficiency of these mechanisms in human-robot interaction (HRI) might be contingent on the adoption of a set of attitudes, mindsets, and beliefs concerning the robot's inner machinery. Current research is investigating the factors that influence these mindsets, and how they affect HRI. This review focuses on a specific mindset, namely the "intentional mindset" in which intentionality is attributed to another agent. More specifically, we focus on the concept of adopting the intentional stance toward robots, i.e., the tendency to predict and explain the robots' behavior with reference to mental states. We discuss the relationship between adoption of intentional stance and lower-level mechanisms of social cognition, and we provide a critical evaluation of research methods currently employed in this field, highlighting common pitfalls in the measurement of attitudes and mindsets

Integrating Artificial Intelligence into Creativity Education: Developing a Creative Problem-Solving Course for Higher Education

This project aims to develop an introductory college course that integrates Artificial Intelligence (AI) to enhance the Creative Problem Solving (CPS) process. Drawing on best practices for teaching CPS and the latest research of AI, the project outcomes are prototypes of a Master Course Development Document, Student Syllabus, and Lesson Plan with accompanying PowerPoint slides. The course will equip students with the knowledge and skills to apply AI techniques to the CPS process. This project aims to begin to bridge the gap between AI and CPS education, preparing students for the demands of the modern workforce while fostering interdisciplinary thinking

Mind(sets) over machine? The influence of implicit self-theories in human-robot interaction.

Implicit self-theory asserts that an individual’s underlying beliefs about whether self-attributes (e.g., personality and intelligence) are fixed (entity theory) or mutable (incremental theory) causally affect motivation and behavior—with the most profound effects emerging in situations that involve challenges and setbacks. In support of this notion, several lines of research suggest that these beliefs hold some influence over people’s perception and behavior in diverse domains such as education, brand acceptance, and financial decision-making, among others. It is, however, presently unknown whether implicit self-theories exert such influence on people’s experiences of social robots. To address this gap, this research tested, in a series of three studies, the proposition that implicit self-theories represent an important variable, that influences the manner in which one perceives and responds to social robots. Study 1 provided the first evidence that an individual’s implicit self-theory orientation influences their perception of emerging social robots developed for everyday use. In particular, those endorsing more of an entity theory expressed greater robot anxiety than those endorsing more of an incremental theory. This finding held even when controlling for a range of covariate influences. In addition, incremental theorists, compared to entity theorists responded more favorably to social robots in general. Study 2 built on and substantively extended the findings of Study 1 by examining the effects of implicit self-theories on people’s responses to a robot that praised them for ability (i.e., intelligence), or for effort (i.e., hard work), after completing a difficult task. Results revealed that entity theorists evaluated a robot that delivered ability praise as more likable and intelligent than one that delivered effort praise. However, incremental theorists were unaffected by either praise type and rated the robot favorably regardless of the praise it delivered. Study 3, expanded the findings of Studies 1 and 2 to investigate the impact of implicit self-theories on people’s responses to a robot that defeats human beings in a general knowledge quiz game. Results showed that incremental theorists, compared to entity theorists were more likely to indicate an interest in playing against the robot after imagining losing to it. Whereas entity theorists rated such robots as presenting more identity and realistic threats. Together, these studies extend and enrich the Human-Robot Interaction (HRI) literature by establishing implicit self-theories as an important and meaningful variable for which to advance the understanding of HRI today. In so doing, this research attempts to respond to the ever-increasing demand for research on the psychological variables that underlie how people perceive and interact with robots—which, in many ways, has special urgency given the inexorable rise of AI and robotics in the social domain of everyday experience. In consequence, findings may contribute to the design of new or improved social robots that can reflect or shape beliefs, and, hence, build a greater sense of identification and trust with the intended human user

Attitudes Toward Robots as Equipment and Coworkers and the Impact of Robot Autonomy Level

Increasingly, people must interact with robot technologies. In this research, we examined attitudes toward robots as equipment and as coworkers and whether these attitudes are affected by the autonomy of the robot among participants living in the United States (Study 1: N = 1003; Study 2: N = 969). Study 1 revealed that respondents had a more positive attitude toward robots as equipment than as coworkers. Technology use self-efficacy and prior robot use experience were associated with more positive attitudes toward both robot positions. Having a degree in engineering or technology was associated with a positive attitude toward robot coworkers, while neuroticism was associated with a negative attitude. Additionally, technology use self-efficacy was found to have a significant indirect effect on the associations between openness and attitudes toward robots as well as conscientiousness and attitudes toward robots. In Study 2, a three-group online survey experiment showed that teleoperated robots and semi-autonomous robots were preferred as equipment over fully autonomous robots. The robots’ autonomy level did not impact attitude toward robot coworkers. Overall, the results suggest that people prefer non-autonomous robots over autonomous robots in the work-life context. The studies provide a comprehensive overview of attitudes toward robots as both equipment and coworkers, and the key predictors of the noted attitudes. The results suggest a readiness for shared autonomy between a human operator and a robot. This should be considered in the design and successful implementation of new robot technologies in workplaces.</p

Appreciative Administration: How the Appreciative Education Theory-to-Practice Framework is Being Infused into Higher Education Administrative Practices

This qualitative grounded theory study updated the framework, including a definition, of Appreciative Administration. Bloom et al. (2013) first introduced the concept of Appreciative Education in a New Directions for Student Services article. Appreciative Education’s framework is harnessed by the power of the organizational development theory of Appreciative Inquiry (Cooperrider & Srivastva, 1987), the relationship-building theory-to-practice framework of Appreciative Advising (Bloom & Martin, 2002; Bloom et al., 2008), and an Appreciative Mindset. Bloom and McClellan (2016) coined the phrase Appreciative Administration to describe how higher education administrators could lead their organizations by harnessing the power of Appreciative Education. To date, there is no research on how higher education administrators are using Appreciative Education in their administrative practices. The purpose of this grounded theory study was to examine how higher education administrators infuse the Appreciative Education framework into their daily administrative practices. The study included 21 professionals, who met the following criteria: (1) had at least one full-time person reporting to them; (2) had participated in a formal Appreciative Education training. The experiences of the 21 study participants were captured through semi-structured 60-minute Zoom interviews. Subsequently, eight of the 21 participants participated in a focus group via Zoom to provide feedback on the study’s initial themes and sub-themes. Data was analyzed through three rounds of coding: (1) initial coding, (2) focused coding, and (3) theoretical coding. Three themes emerged from the analysis to develop the updated framework for Appreciative Administration showing how higher education administrators are infusing Appreciative Education into their daily administrative practices: establish trusting relationships, foster relationships to achieve personal and organizational goals, and “positive restlessness” (Kuh et al., 2005). After synthesis, I offer a new definition of Appreciative Administration. Appreciative Administration is, “fundamentally situated as a human experience and involves the intentional, consistent, and aspirational practice of establishing trusting relationships in which team members’ strengths and skills are identified and leveraged to co-create and achieve personal and organizational goals.” The findings of this grounded theory study may be helpful for higher education institutions and administrators looking for a framework to lead their institutions. This study may also inform administrators with information about how to provide professional development, recognize employees, create policy changes, make time to build trusting relationships, and develop pockets of greatness

I Am Looking for Your Mind: Pupil Dilation Predicts Individual Differences in Sensitivity to Hints of Human-Likeness in Robot Behavior

The presence of artificial agents in our everyday lives is continuously increasing. Hence, the question of how human social cognition mechanisms are activated in interactions with artificial agents, such as humanoid robots, is frequently being asked. One interesting question is whether humans perceive humanoid robots as mere artifacts (interpreting their behavior with reference to their function, thereby adopting the design stance) or as intentional agents (interpreting their behavior with reference to mental states, thereby adopting the intentional stance). Due to their humanlike appearance, humanoid robots might be capable of evoking the intentional stance. On the other hand, the knowledge that humanoid robots are only artifacts should call for adopting the design stance. Thus, observing a humanoid robot might evoke a cognitive conflict between the natural tendency of adopting the intentional stance and the knowledge about the actual nature of robots, which should elicit the design stance. In the present study, we investigated the cognitive conflict hypothesis by measuring participants’ pupil dilation during the completion of the InStance Test. Prior to each pupillary recording, participants were instructed to observe the humanoid robot iCub behaving in two different ways (either machine-like or humanlike behavior). Results showed that pupil dilation and response time patterns were predictive of individual biases in the adoption of the intentional or design stance in the IST. These results may suggest individual differences in mental effort and cognitive flexibility in reading and interpreting the behavior of an artificial agent

How Content Teachers Transition to Teaching a STEAM Curriculum

An increasing number of educators are supporting the STEAM approach to education, so that students will have the necessary skills and abilities needed for the 21st century workforce. Entire schools as well as school districts have transitioned to STEAM. The purpose of this multiple case study was to explore how content teachers make the transition from their traditional educational approach to implementing a STEAM curriculum. The researcher used purposeful sampling to select one participant from the arts discipline and one teacher from the STEM discipline at two research sites used in the multiple case study. Data collection methods included one-on-one interviews, a focus group, and observations of corroborating artifacts and documents. Findings led to four themes which depicted the process that teachers went through to transition to STEAM. Teachers developed a mindset to teach from STEAM perspective, started small and built up, used collaboration as a resource, and participated in ongoing professional development. The transition process appeared to support Mezirow’s (1991) steps involved in transformational learning theory and the STEAM movement. Future research could include a deeper look at how teachers transition to STEAM, how non-STEM classes are involved in STEAM, and how educational leaders make decisions to transition a school’s curricular approach

Improving blue economy through industry 4.0: a service science perspective

Desenvolver a Economia Azul pela Indústria 4.0: Uma Perspetiva Service Science O objetivo desta dissertação é a avaliação do impacto das tecnologias digitais “Indústria 4.0” (I4.0), na competitividade da Economia Azul (BE) na União Europeia (EU). Nos Relatórios de 2018 e 2018 sobre Economia Azul a Comissão Europeia apresentou os desafios e o potencial da BE, propondo diretrizes para políticas e, identificou os facilitadores da competitividade nos diferentes sectores da BE no espaço Europeu. Da revisão sistemática da literatura efetuada, verificou-se que a Service Science (S-S), é uma área científica emergente e interdisciplinar que combina a organização dos sistemas, o conhecimento tecnológico com a Sustentabilidade do Planeta, permitindo suportar cientificamente novas abordagens à criação de valor. Ainda da revisão de literatura, foram identificadas diferentes tecnologias digitais, designadas por tecnologias Indústria 4.0. Orientada pelo paradigma pragmatista e utilizando uma metodologia mista de convergência paralela, nesta investigação foi conceptualizado um modelo empírico. Da aplicação deste modelo a onze casos-de-estudo da BE, conclui-se que o impacto na competitividade setorial da BE Europeia poderá ser de 26,5%. Conclui-se ainda, nesta investigação, que as tecnologias I4.0 poderão representar uma oportunidade as empresas da BE, sendo por isso mesmo, recomendável a sua adoção