Artificial Intelligence leadership : how trust and fairness perceptions impact turnover intentions through psychological safety

Artificial intelligence agent’s intervention in decision making at organizational environments has been increasing rapidly. These agents bring advantages in decision making due to their objectivity, efficiency, and superior capacity of information processing while lacking human weaknesses such as fatigue or self-interest. However, their perception by organizational employees might be less optimistic, as artificial intelligence leaders might be perceived as less fair and just. This dissertation intends to study the effects that this new type of leadership has on employees' turnover intentions, an important variable as high levels of voluntary turnover cause several losses for companies both in terms of cost increase and loss of talented human resources. Additionally, I propose the decrease in employee’s psychological safety to mediate this relationship. Finally, I propose a way to overcome this effect by manipulating the perceptions of trust and justice of these leaders, in order to try to counter the negative effect of non-human leadership. The results of this study revealed a significant effect of the leader agent on the employees' exit intentions as well as on their psychological safety, including as a mediator of the former. Regarding the moderation of trust and justice perceptions, the results showed that these testimonials have a direct effect on psychological safety, and an indirect one in turnover intentions through psychological safety.A intervenção de agentes de inteligência artificial na tomada de decisão em ambientes organizacionais tem aumentado rapidamente. Estes agentes trazem vantagens para a tomada de decisão devido à sua objetividade, eficiência e superior capacidade de processamento de informação, ao mesmo tempo que não possuem fragilidades humanas tais como fadiga ou interesses próprios. No entanto, a sua perceção por parte dos funcionários da organização pode ser menos otimista, pois os líderes de inteligência artificial podem ser vistos como menos justos e confiáveis. Esta dissertação pretende estudar os efeitos que este novo tipo de liderança tem sobre as intenções de saída dos funcionários, uma variável importante, já que altos níveis de rotatividade voluntária causam várias perdas para as empresas, tanto em termos de aumento de custos quanto de perda de recursos humanos talentosos. Além disso, proponho a diminuição da segurança psicológica dos funcionários para mediar esta relação. Por fim, proponho uma forma de superar esse efeito, manipulando as perceções de confiança e justiça desses líderes, a fim de tentar combater o efeito negativo de uma liderança não humana. Os resultados deste estudo revelaram um efeito significativo do agente de liderança nas intenções de saída dos funcionários e em sua segurança psicológica, inclusive como mediador do primeiro. No que se refere à moderação das perceções de confiança e justiça, os resultados mostraram que estes têm um efeito direto na segurança psicológica, e um efeito indireto nas intenções de saída através da segurança psicológica

The Underpinnings of Workload in Unmanned Vehicle Systems

This paper identifies and characterizes factors that contribute to operator workload in unmanned vehicle systems. Our objective is to provide a basis for developing models of workload for use in design and operation of complex human-machine systems. In 1986, Hart developed a foundational conceptual model of workload, which formed the basis for arguably the most widely used workload measurement techniquethe NASA Task Load Index. Since that time, however, there have been many advances in models and factor identification as well as workload control measures. Additionally, there is a need to further inventory and describe factors that contribute to human workload in light of technological advances, including automation and autonomy. Thus, we propose a conceptual framework for the workload construct and present a taxonomy of factors that can contribute to operator workload. These factors, referred to as workload drivers, are associated with a variety of system elements including the environment, task, equipment and operator. In addition, we discuss how workload moderators, such as automation and interface design, can be manipulated in order to influence operator workload. We contend that workload drivers, workload moderators, and the interactions among drivers and moderators all need to be accounted for when building complex, human-machine systems

From Tools to Teammates: Conceptualizing Humans’ Perception of Machines as Teammates with a Systematic Literature Review

The accelerating capabilities of systems brought about by advances in Artificial Intelligence challenge the traditional notion of systems as tools. Systems’ increasingly agentic and collaborative character offers the potential for a new user-system interaction paradigm: Teaming replaces unidirectional system use. Yet, extant literature addresses the prerequisites for this new interaction paradigm inconsistently, often not even considering the foundations established in human teaming literature. To address this, this study utilizes a systematic literature review to conceptualize the drivers of the perception of systems as teammates instead of tools. Hereby, it integrates insights from the dispersed and interdisciplinary field of human-machine teaming with established human teaming principles. The creation of a team setting and a social entity, as well as specific configurations of the machine teammate’s collaborative behaviors, are identified as main drivers of the formation of impactful human-machine teams

Second NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

The Advanced Technology Lifecycle Analysis System (ATLAS), a spreadsheet analysis tool suite, applies parametric equations for sizing and lifecycle cost estimation. Performance, operation, and programmatic data used by the equations come from a Technology Tool Box (TTB) database. In this second TTB Technical Interchange Meeting (TIM), technologists, system model developers, and architecture analysts discussed methods for modeling technology decisions in spreadsheet models, identified specific technology parameters, and defined detailed development requirements. This Conference Publication captures the consensus of the discussions and provides narrative explanations of the tool suite, the database, and applications of ATLAS within NASA s changing environment

Program and Abstracts from the Celebration of Student Scholarship, 2017

Program and Abstracts from the Celebration of Student Scholarship on April 26, 2017

Social Influence in Customer-Robot Interactions

This paper focuses on social influence in customer-robot interactions. Drawing on social impact theory and the computers-are-social-actors (CASA) paradigm, we argue that customers\u27 reluctance to provide information to a service robot decreases when other customers exhibit high information disclosure. The effect of demonstrated information disclosure on customers\u27 reluctance to provide information is enhanced by the application of social norms. The results also show that social influence is stronger in customer-robot interactions than in customer-employee interactions. This article demonstrates the potential of social influence to reduce reluctance towards service robots, which has both theoretical and managerial implications. We extend existing research on the imitation of robot behavior with the imitation of user behavior, and discuss the ethical implications of customers mindlessly following other customers in customer-robot interactions

Conversational Agents in Education – A Systematic Literature Review

Conversational Agents (CAs) are widely spread in a variety of domains, such as health and customer service. There is a recent trend of increasing publications and implementations of CAs in education. We conduct a systematic literature review to identify common methodologies, pedagogical CA roles, addressed target groups, the technologies and theories behind, as well as human-like design aspects. The initially found 3329 records were systematically reduced to 252 fully coded articles. Based on the analysis of the codings, we derive further research streams. Our results reveal a research gap for long-term studies on the use of CAs in education, and there is insufficient holistic design knowledge for pedagogical CAs. Moreover, target groups other than academic students are rarely considered. We condense our findings in a morphological box and conclude that pedagogical CAs have not yet reached their full potential of long-term practical application in education

Mapping Robots to Therapy and Educational Objectives for Children with Autism Spectrum Disorder

The aim of this study was to increase knowledge on therapy and educational objectives professionals work on with children with autism spectrum disorder (ASD) and to identify corresponding state of the art robots. Focus group sessions (n = 9) with ASD professionals (n = 53) from nine organisations were carried out to create an objectives overview, followed by a systematic literature study to identify state of the art robots matching these objectives. Professionals identified many ASD objectives (n = 74) in 9 different domains. State of the art robots addressed 24 of these objectives in 8 domains. Robots can potentially be applied to a large scope of objectives for children with ASD. This objectives overview functions as a base to guide development of robot interventions for these children

The Fuzzy Futures of Neo-Carbon Work : Neo-Carbon Futures Clinique II

This report documents and analyses the results of a Neo-Carbon Futures Clinique held at Hotel President in Helsinki 13 April 2016. At the Futures Clinique workshop groups anticipated possible futures of peer-to-peer work that is self-organised by the workers. The Futures Clinique is part of the Neo-Carbon Energy research project. The foresight part of the project is concerned with studying the futures of peer-to-peer societies enabled by the proposed Neo-Carbon energy system. Such a system would be a distributed, renewable energy system that empowers citizens by providing them with cheap, clean and abundant energy and materials. In this project, possible futures of a peer-to-peer society are studied through four scenarios (Heinonen et al. 2016), which provided the framework also for this Futures Clinique. The results of the Futures Clinique were summarised and refined into seven categories, each illuminating different aspects of the possible futures of peer-to-peer work. Common to the categories is the strengthening of values other than economic as the main drivers in economy and society