Designing Women: Essentializing Femininity in AI Linguistics

Since the eighties, feminists have considered technology a force capable of subverting sexism because of technology’s ability to produce unbiased logic. Most famously, Donna Haraway’s “A Cyborg Manifesto” posits that the cyborg has the inherent capability to transcend gender because of its removal from social construct and lack of loyalty to the natural world. But while humanoids and artificial intelligence have been imagined as inherently subversive to gender, current artificial intelligence perpetuates gender divides in labor and language as their programmers imbue them with traits considered “feminine.” A majority of 21st century AI and humanoids are programmed to fit female stereotypes as they fulfill emotional labor and perform pink-collar tasks, whether through roles as therapists, query-fillers, or companions. This paper examines four specific chat-based AI --ELIZA, XiaoIce, Sophia, and Erica-- and examines how their feminine linguistic patterns are used to maintain the illusion of emotional understanding in regards to the tasks that they perform. Overall, chat-based AI fails to subvert gender roles, as feminine AI are relegated to the realm of emotional intelligence and labor

Artificial Intelligence in Higher Education: Perspicacity Relation between Educators and Students

Artificial intelligence is a system with the nature of human intelligence that can automatically provide knowledge and information to create intelligent applications to make it easier to solve problems such as problem-solving, speech recognition, and learning. This research was investigated to find out and understand the relationship of intelligence between educators and students in applying artificial intelligence in universities. The method used is a phenomenological type of qualitative method. This research was conducted at Nurul Jadid University (UNUJA), with the subject of research being PAI lecturers and students in semester V. This research phase was carried out by preliminary studies, observation, data collection (interviews), data verification, and drawing conclusions. As for the results of this study, in its application, artificial intelligence in universities has a positive and negative impact on the relationship of intelligence to learning when it is carried out outside conventional learning. The intelligence relationship between educators and students, which includes Intelligence Quotient (IQ), Emotional Quotient (EQ), and Spiritual Quotient (SQ) contained in it, is also a positive thing that coexists and is directed

Emotional Intelligence in Robotics: A Scoping Review

Research suggests that emotionally responsive machines that can simulate empathy increase de acceptance of users towards them, as the feeling of affinity towards the machine reduces negative perceptual feedback. In order to endow a robot with emotional intelligence, it must be equipped with sensors capable of capturing users’ emotions (sense), appraisal captured emotions to regulate its internal state (compute), and finally perform tasks where actions are regulated by the computed “emotional” state (act). However, despite the im-pressive progress made in recent years in terms of artificial intelligence, speech recognition and synthesis, computer vision and many other disciplines directly and indirectly related to artificial emotional recognition and behavior, we are still far from being able to endow robots with the empathic capabilities of a human being. This article aims to give an overview of the implications of intro-ducing emotional intelligence in robotic constructions by discussing recent ad-vances in emotional intelligence in robotics

The perception of emotion in artificial agents

Given recent technological developments in robotics, artificial intelligence and virtual reality, it is perhaps unsurprising that the arrival of emotionally expressive and reactive artificial agents is imminent. However, if such agents are to become integrated into our social milieu, it is imperative to establish an understanding of whether and how humans perceive emotion in artificial agents. In this review, we incorporate recent findings from social robotics, virtual reality, psychology, and neuroscience to examine how people recognize and respond to emotions displayed by artificial agents. First, we review how people perceive emotions expressed by an artificial agent, such as facial and bodily expressions and vocal tone. Second, we evaluate the similarities and differences in the consequences of perceived emotions in artificial compared to human agents. Besides accurately recognizing the emotional state of an artificial agent, it is critical to understand how humans respond to those emotions. Does interacting with an angry robot induce the same responses in people as interacting with an angry person? Similarly, does watching a robot rejoice when it wins a game elicit similar feelings of elation in the human observer? Here we provide an overview of the current state of emotion expression and perception in social robotics, as well as a clear articulation of the challenges and guiding principles to be addressed as we move ever closer to truly emotional artificial agents

Significance of Emotional Intelligence in Occupational Perspective: A Critical Review

With the beginning of the fifth industrial revolution, Artificial Intelligence has changed the nature of work where human needs to be more creative, innovative, and relationship oriented. For a sustainable working environment, the value of emotional and social competencies has increased day by day while Emotional Intelligence (EI) has captured as a pinnacle in Human Resource Development literature. The study focused on the significance of Emotional Intelligence from an occupational perspective.  The findings reveal why an organization should care about the emotional intelligence of its employees. Since an organization can attain a competitive advantage through the people, hence Emotional intelligence could make a difference from an average performer to high-value performer.  In this study, the role of Emotional Intelligence has critically analyzed with the evidence of empirical researches published in peer-reviewed journals.  The study underlines the essentials of EI in job performance, job satisfaction, Organization citizenship behavior, leadership effectiveness, Team Management, Work-life balance and Employee wellbeing. From the Human Resource Development perspective, organization should emphasize on developing Emotional Intelligence of its employees to make them productive, satisfied and committed for achieving organization’s goals and maintaining better working environment. Keywords: Emotional Intelligence, Organizational effectiveness, Human Resource Development DOI: 10.7176/EJBM/11-18-14 Publication date:June 30th 201

Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives

Over the past few years, adversarial training has become an extremely active research topic and has been successfully applied to various Artificial Intelligence (AI) domains. As a potentially crucial technique for the development of the next generation of emotional AI systems, we herein provide a comprehensive overview of the application of adversarial training to affective computing and sentiment analysis. Various representative adversarial training algorithms are explained and discussed accordingly, aimed at tackling diverse challenges associated with emotional AI systems. Further, we highlight a range of potential future research directions. We expect that this overview will help facilitate the development of adversarial training for affective computing and sentiment analysis in both the academic and industrial communities

Simulation of Human and Artificial Emotion (SHArE)

The framework for Simulation of Human and Artificial Emotion (SHArE) describes the architecture of emotion in terms of parameters transferable between psychology, neuroscience, and artificial intelligence. These parameters can be defined as abstract concepts or granularized down to the voltage levels of individual neurons. This model enables emotional trajectory design for humans which may lead to novel therapeutic solutions for various mental health concerns. For artificial intelligence, this work provides a compact notation which can be applied to neural networks as a means to observe the emotions and motivations of machines

Metonymization Procedures in Artificial Intelligence (in English and Romanian Languages)

In this article, we address term creation in 3 terms from the domain of artificial intelligence, which are representative and revelatory for the study of reterminologization in the triad of the specialized domains of emotional intelligence, cognitive intelligence and artificial intelligence. The study of reterminologization in the announced triad traces conceptual interferences to state-of-the-art terms created in the domain of artificial intelligence, in particular, through metonymization. The domain of artificial intelligence is a dynamic and prolific one, with a terminological variety that allows the study of conceptual interferences inspired from the domain of human intelligence. The terms that are subject to analysis in the article have a high degree of complexity and conceptually encompass the triad of emotional, cognitive and artificial intelligence