Computers in Human Behavior: Artificial Humans最新文献

To foster the development of pedagogically potent and ethically sound AI-integrated learning landscapes, it is pivotal to critically explore the perceptions and experiences of the users immersed in these contexts. In this study, we perform a thorough qualitative content analysis across four key social media platforms. Our goal is to understand the user experience (UX) and views of early adopters of ChatGPT across different educational sectors. The results of our research show that ChatGPT is most commonly used in the domains of higher education, K-12 education, and practical skills training. In social media dialogues, the topics most frequently associated with ChatGPT are productivity, efficiency, and ethics. Early adopters' attitudes towards ChatGPT are multifaceted. On one hand, some users view it as a transformative tool capable of amplifying student self-efficacy and learning motivation. On the other hand, there is a degree of apprehension among concerned users. They worry about a potential overdependence on the AI system, which they fear might encourage superficial learning habits and erode students’ social and critical thinking skills. This dichotomy of opinions underscores the complexity of Human-AI Interaction in educational contexts. Our investigation adds depth to this ongoing discourse, providing crowd-sourced insights for educators and learners who are considering incorporating ChatGPT or similar generative AI tools into their pedagogical strategies.

As human-AI interactions become more pervasive, conversational agents are increasingly relevant in our communication environment. While a rich body of research investigates the consequences of one-shot, single interactions with these agents, knowledge is still scarce on how these consequences evolve across regular, repeated interactions in which these agents make use of AI-enabled techniques to enable increasingly personalized conversations and recommendations. By means of a longitudinal experiment (N = 179) with an agent able to personalize a conversation, this study sheds light on how perceptions – about the agent (anthropomorphism and trust), the interaction (dialogue quality and privacy risks), and the information (relevance and credibility) – and behavior (self-disclosure and recommendation adherence) evolve across interactions. The findings highlight the role of interplay between system-initiated personalization and repeated exposure in this process, suggesting the importance of considering the role of AI in communication processes in a dynamic manner.

Interactions between human beings and digital humans have become a new network phenomenon, and these relationships have gradually become a topic of research. There is still a lack of sufficient research on whether and what kind of attachment relationship exists in these situations. Based on this problem, in this study, a digital human was designed that was oriented to social software and put into chat groups for interaction and research. A questionnaire survey, case analysis, and netnography analysis were used to collect and examine relevant data. The study found a correlation between the type of attachment of users and the degree of attachment to the digital human. In addition, users who were heavily dependent on the network were more likely to try to complete their attachment with the digital human. Attachment with the digital human was able to calm the users’ emotional intensity. This attachment was considered as close to a skewed desire projection. Through the intermediary of a digital human, Internet users have been better able to fulfill some of their own desires.

Artificial intelligence (AI) tools are quickly transforming the traditional fields of fine arts and raise questions of AI challenging human creativity. AI tools can be used in creative processes and analysis of fine art, such as painting, music, and literature. They also have potential in enhancing artistic events, installations, and performances. In this systematic review, we investigated empirical studies on the use of AI in fine arts We gathered the data from three major bibliographic databases. After an initial search, we screened 723 articles based on pre-established inclusion criteria, resulting in 44 studies. Over half concerned visual arts, such as paintings and drawings, and one quarter concerned music. Experimental studies focused on human responses to AI art showed that people generally do not recognize the difference between human-made and AI-made art, but human-made art was valued more than AI-made art in some studies. The power of AI lies in the analysis of large-scale datasets. Case studies have reported development of an AI painter, DJ, performance artist, and music accompaniment for improvisations. AI tools have been applied to enhance consumer experience in online art shops and to provide virtual reality (VR) access to historical cathedrals. Fast development of AI will likely pose a challenge for the current concept and understanding of fine arts. AI challenging human creativity is one of the most powerful signs of the cultural and societal transformation stemming from AI.

In the vast digital landscape of the Metaverse, users can create and personalize their avatars as virtual representations of themselves. This study delves into the emotions users experience in relation to their avatars and examines how this attachment influences their consumption behaviors within the virtual world. The research employed a sample of 214 active users participating in Second Life, a prominent virtual world platform. By analyzing survey data, we explore the dynamics of self-presentation and attachment between users and their virtual personas across this well-established platform. Our research offers valuable contributions to the existing literature on the Metaverse, providing empirical evidence on how virtual reality platforms like Second Life foster avatar customization and how this, in turn, affects consumer behavior. As the Metaverse gains prominence in the business world, understanding the habits and preferences of virtual reality users is increasingly crucial. We aim to enhance our understanding of consumer behavior by incorporating attachment theory into our research on long-standing virtual environments like Second Life. Our study of Second Life provides valuable insights into the dynamics of consumer behavior within a well-established virtual world, which can be applied to the emerging Metaverse platforms. This knowledge helps businesses identify consumer profiles, address their needs, and enhance their virtual presence and success.

Valid measurement of AI literacy is important for the selection of personnel, identification of shortages in skill and knowledge, and evaluation of AI literacy interventions. A questionnaire is missing that is deeply grounded in the existing literature on AI literacy, is modularly applicable depending on the goals, and includes further psychological competencies in addition to the typical facets of AIL. This paper presents the development and validation of a questionnaire considering the desiderata described above. We derived items to represent different facets of AI literacy and psychological competencies, such as problem-solving, learning, and emotion regulation in regard to AI. We collected data from 300 German-speaking adults to confirm the factorial structure. The result is the Meta AI Literacy Scale (MAILS) for AI literacy with the facets Use & apply AI, Understand AI, Detect AI, and AI Ethics and the ability to Create AI as a separate construct, and AI Self-efficacy in learning and problem-solving and AI Self-management (i.e., AI persuasion literacy and emotion regulation). This study contributes to the research on AI literacy by providing a measurement instrument relying on profound competency models. Psychological competencies are included particularly important in the context of pervasive change through AI systems.

Technology advancements have enabled humans to go beyond restauration leading to a new reality where human enhancement is no longer fiction. Besides the major societal impacts they will have, these evolutions of technology are also raising complex philosophical and ethical questions. Notwithstanding the widespread interest for augmentation technologies, there are few frameworks available to categorise and compare the varied variety of existing and prospective technologies in this field. A structured framework is needed to harness the full potential of sensory technologies while facilitating the discussion and management of potential risks and challenges. This article presents a framework that aims to bridge the gap between technologies designed for compensating disabilities, enhancing human perception beyond the abilities of individuals without disabilities, and those intended for entertainment purposes. Furthermore, in the past, research on sensory perception tended to isolate sensory modalities based on the stimuli to which they are most sensitive. This new proposed framework allows for the analysis of technologies on a continuum ranging from unimodality to transmodality and to take in account the degree of integration with biological system. In addition, this framework answers the need to classify these technologies based on the crucial aspect of social acceptability, specifically by taking into consideration their varying degrees of invasiveness. All of these elements included into the suggested framework will enable researchers to map and analyse not just existing technologies, but also those that have not even been invented yet.

In virtual environments, people tend to behave in line with the virtual avatars they embody. For example, when an individual embodies an attractive and physically fit avatar, they might show an increase in self-esteem. This phenomenon is called the Proteus effect. While prior research shows support for this effect with humanlike avatars, it is unclear whether non-humanlike avatars can also induce it. In this study, we examine the Proteus effect in the context of non-humanlike avatars and test whether the level of attractiveness of a non-humanlike avatar affects social participation. Two underlying mechanisms of the Proteus effect are considered: the mediating role of avatar identification and the moderating role of level of embodiment. To test our hypotheses, a 2 x 2 between-subjects lab experiment (N = 134) was conducted. Participants were randomly assigned to one of two non-humanlike avatars differing in level of attractiveness (attractive vs. unattractive) and one of two levels of embodiment (head-mounted display VR vs. desktop). The results showed that participants embodying the attractive non-humanlike avatar perceived higher levels of avatar identification via self-similarity, which increased social participation. Also, this study found that level of embodiment did not moderate the effect of attractiveness of the non-humanlike avatar on social participation.

In the not-so-distant future, when we are expected to be increasingly engaged in interactions with service robots, it can also be expected that such interactions will require that we identify ourselves. That is to say, given that identification demands occur frequently when we use computers, mobile telephones and websites, it is expected that this will be the case also for service robots. So far, however, the effects of such demands have not been examined in existing research on human-to-robot interactions. Yet, identification is an issue with potentially profound implications, and demands for identification appear to have mainly a negative charge in many settings beyond human-to-robot interactions. Therefore, the purpose of the present study is to explore what happens when a user of a service robot is asked by the robot to identify him/herself. To this end, two experiments were conducted in which a service robot’s demand for user identification was manipulated (no demand for identification before usage vs. demand for identification before usage). The results indicate that the robot’s demand for identification attenuated perceived robot warmth, usefulness, and trust; enhanced privacy concerns; and reduced the overall evaluation of the robot. A proposed mechanism behind these outcomes, priming, was assessed empirically. The results with respect to the latter indicate that a robot’s request for identification makes accessible mainly negatively charged material about identification in other contexts than human-to-robot interactions, and that this material informs responses to the robot.

With the diversification of generative artificial intelligence (AI) applications, the interest in their use in every segment and field of society in recent years has been increasing rapidly. One of these areas is programming learning and program writing processes. One of the generative AI tools used for this purpose is ChatGPT. The use of ChatGPT in program writing processes has become widespread, and this tool has a certain potential in the programming process. However, when the literature is examined, research results related to using ChatGPT for this purpose have yet to be found. The existing literature has a gap that requires exploration. This study aims to analyze the students' perspectives on using ChatGPT in the field of programming and programming learning. The study encompassed a cohort of 41 undergraduate students enrolled in a public university's Computer Technology and Information Systems department. The research was carried out within the scope of the Object-Oriented Programming II course for eight weeks. Throughout the research process, students were given project assignments related to the course every week, and they were asked to use ChatGPT while solving them. The research data was collected using a form consisting of open-ended questions and analyzed through content analysis. The research findings revealed both the advantages and disadvantages of ChatGPT usage, as perceived by the students. The students stated that the main benefits of using ChatGPT in programming learning are providing fast and mostly correct answers to questions, improving thinking skills, facilitating debugging, and increasing self-confidence. On the other hand, the main limitations of using ChatGPT in programming education were getting students used to laziness, being unable to answer some questions, or giving incomplete/incorrect answers, causing professional anxiety in students. Based on the results of the research, it can be said that it would be useful to integrate generative AI tools into programming courses considering the advantages they provide in programming teaching. However, appropriate measures should be taken regarding the limitations it brings. Based on the research findings, several recommendations were proposed regarding the integration of ChatGPT into lessons.