Avoid Excessive Usage: Examining the Motivations and Outcomes of Generative Artificial Intelligence Usage among Students

This study constructs a moderating mediation model to link public sector employees’ Artificial Intelligence (AI) usage with employees’ moral norms and ethical decision-making behaviors. Based on the theory of public service motivation, this study hypothesizes that the impact of AI usage on employees’ ethical decision-making behaviors acts through the mediating effects of employees’ service motivation, employees’ moral norms, and employees’ ethical perceptions and that the relationship between AI usage and employees’ service motivation, employees’ ethical norms, and employees’ ethical perceptions is moderated by the culture of the public organization. The selected data from 417 public sector employees in China supported most of the research hypotheses. The findings show that employee service motivation, employee moral norms, and employee moral cognition mediate the relationship between AI usage and employee ethical decision-making behavior. Public organization culture moderated the relationship between AI usage and employee service motivation, as well as AI usage and employee ethics. This study reveals the complex mediating and moderating relationships between AI usage and employees’ ethical decision-making behaviors in the public sector. It provides important theoretical and practical insights for further understanding and promoting public sector employees’ ethical behaviors in the era of AI.

This study aims to analyse the influence of artificial intelligence (AI) usage on the design thinking skills of accounting students and the role of academic integrity as a moderator in this relationship. This study uses a quantitative approach with a survey method involving 323 accounting students from various universities in Indonesia. Data analysis was conducted using Partial Least Squares Structural Equation Modelling (PLS-SEM) to test the direct influence of AI usage on design-thinking skills and the role of academic integrity moderation. The results show that AI usage has a positive and significant effect on the design thinking skills of accounting students, which shows that the higher the utilisation of AI in learning, the more developed the design thinking skills of students. Additionally, academic integrity has been shown to strengthen the relationship between AI usage and design thinking skills, suggesting that students with high academic integrity are more likely to use AI responsibly to explore ideas and develop innovative solutions rather than simply seeking instant answers. This research contributes to the literature by describing the role of academic ethics in AI usage in accounting education, which has rarely been discussed in previous research. By integrating Social Cognitive Theory (SCT), this study shows how the interaction between behavioural factors (AI usage) and personal factors (academic integrity) can affect students' design-thinking skills. These findings have implications for educational institutions, lecturers, and students in ensuring that AI is used ethically and responsibly to support the development of high-level thinking skills in accounting.

This study explores the extent of Artificial Intelligence (AI) usage among students and its implications for academic ethics, with a specific focus on STKIP DDI Pinrang. Employing a mixed-methods approach, quantitative data were collected through Likert-scale questionnaires distributed to 40 students, while qualitative insights were gathered via interviews with selected respondents. The findings indicate that students’ AI usage is very high (mean score: 4.45), particularly through tools such as ChatGPT, Grammarly, and Quillbot. However, their ethical awareness remains moderate, both in terms of understanding academic ethics (3.1562) and awareness of the ethical implications of AI use (3.04). Correlation analysis reveals a negative relationship between the intensity of AI usage and students' ethical perceptions. Thematic analysis of interviews confirms that students tend to use AI as a substitute rather than a support, and lack institutional guidance on its ethical boundaries. These findings highlight a critical gap between technological proficiency and ethical literacy. The study recommends integrating digital ethics education across curricula and establishing clear institutional policies to ensure responsible AI use in academic settings.

As Artificial intelligence (AI) becomes increasingly prevalent in modern society, understanding its adoption among older adults is crucial. Therefore, this study examines the relationship between AI usage, Big 5 personality traits, and positive solitude, among adults aged 60 and over in Israel. Grounded in the Technology Acceptance Model (TAM), the study explore how personality traits and positive solitude influences perceived AI usability and adoption. A sample of 260 older adults participated in the study. Data were collected through online validated questionnaires and open-ended questions, using Qualtrics. Results revealed that AI users (mean age 69.91, SD=6.7) were younger than non-users (M=74.91, SD=7.6). Of the AI users, 68% were women, 94% were home-dwelling, 65% married, and 98% independent. Additionally, 76% reported using AI for 30-120 minutes daily. Non-users felt subjectively older both physically (M=62.82, SD=11.7) and mentally (M=62.82, SD=10.7) compared to users (physical: M=54.84, SD=13.5; mental: M=58.65, SD=12.7). Significant correlations were found between attitude to life and perceived ability to use AI (r=0.315, p< 0.01), as well as between attitude to life and aging perception (r=0.495, p< 0.01). The qualitative analysis revealed varied responses to AI use. Participants noted significant benefits, including new opportunities and skill enhancement. However, they also encountered technical challenges, concerns about data reliability, and difficulties in formulating effective queries. These findings offer valuable insights into promoting AI adoption among older adults, potentially enhancing their quality of life and independence in the digital age. Future research should explore interventions to increase AI acceptance and usage among this population.

Human interaction with generative artificial intelligence (AI) is characterized by user’s agency. This paper proposes two approaches for employees in using generative AI and explores how these approaches influence the creative outcomes of AI usage. Through a scale development study, we proposed and validated measurements for the inspiration and shortcut approaches, as well as their theoretical nomological network. In a field study, the results reveal that the usage approaches moderate the indirect effect of AI usage on creative performance through idea generation: when the inspiration approach is higher, the indirect effect of idea generation between AI usage and creative performance is stronger; conversely, when the shortcut approach is lower, the indirect effect is also stronger. The study reveals the moderating role of different approaches in how AI usage fosters creativity, thereby enriching the literature on human-AI interaction.

Living with and without AI: A mixed-methods study on AI usage, addiction, and 'AIlessphobia' in nursing students.

This study investigated the impact of artificial intelligence (AI) usage on communication, intimacy, and relationship satisfaction among married couples, with a particular focus on the mediating roles of communication quality and intimacy. Using a quantitative, descriptive-correlational research design, data were collected from 314 participants (157 married couples) who regularly use AI tools in their relationships. The results revealed that AI usage significantly predicted relationship satisfaction both directly (β = 0.20, p = 0.005) and indirectly through improvements in communication quality (β = 0.35, p = 0.001) and intimacy (β = 0.40, p = 0.003). Communication quality and intimacy were strong predictors of relationship satisfaction (β = 0.50, p< 0.001; β = 0.55, p< 0.001, respectively), demonstrating that the primary benefit of AI lies in its ability to enhance these core relational processes. These findings suggest that AI tools can positively influence marital dynamics by improving communication and emotional closeness. However, challenges remain, particularly for older couples or those married for longer periods, who may struggle with AI integration. Future research should explore the long-term effects of AI on marital relationships and investigate specific AI tools that enhance relationship satisfaction.

Humanizing or mechanizing the self? How mindset moderates AI usage on employee self-perception and job crafting.

Technologically advanced artificial intelligence (AI) is making a significant contribution to strengthening national security. AI algorithms facilitate the processing of vast amounts of information, increasing the speed and accuracy of decision-making. Artificial intelligence and machine learning (AI/ML) are crucial for state and integrated hybrid attacks and protecting new threats in cyberspace. Existing AI capabilities have significant potential to impact national security by leveraging existing machine learning technology for automation in labor-intensive activities such as satellite imagery analysis and defense against cyber attacks. This article examines selected aspects of the impact of artificial intelligence on enhancing a state’s ability to protect its interests and its citizens., artificial intelligence through the use of neutron networks, predictive analytics and machine learning algorithms enables security agencies to analyse vast amounts of data and identify patterns indicative of potential threats. Integrating artificial intelligence into surveillance, border control and threat assessment systems enhances the ability to respond preemptively to security challenges. In addition, artificial intelligence algorithms facilitate the processing of vast amounts of information, increasing the speed and accuracy of decision-making by police authorities. The rapid development of AI raises a number of questions for its use in securing not only national security but protecting all citizens. In particular, it is worth answering the question How does artificial intelligence affect national security and clarifying the issue of how law enforcement agencies can use artificial intelligence to maximise the benefits of the new technology in terms of security and protecting communities from rising crime. The analysis is based on a descriptive method in describing the phenomenon; by explaining the concepts and applications of artificial intelligence to determine its role in the national security sphere. An analysis of the usefulness of artificial intelligence in particular in police operations is undertaken, with the aim of defending the thesis that, despite some threats to the protection of human rights from AI, it is becoming the best tool in the fight against all types of crime in the country. Technological advances in AI can also have many positive effects for law enforcement, and useful for law enforcement agencies, for example in facilitating the identification of persons or vehicles, predicting trends in criminal activities, tracking illegal criminal activities or illegal money flows, flagging and responding to fake news. Artificial intelligence (AI) has emerged as one of the biggest threats to information security, but efforts are being made to mitigate this new threat, but also to find solutions on how AI can become an ally in the fight against cyber-security, crime and terrorist threats. Artificial intelligence algorithms search huge datasets of communication traffic, satellite images and social media posts to identify potential cyber security threats, terrorist activities and organized crime. It is advisable, when analyzing the opportunities and threats that AI poses to national and public security, to gain a strategic advantage in the context of rapid technological change and also to manage the many risks associated with AI. The conclusion highlights the impact of AI on national security, creating a range of new opportunities coupled with challenges that government agencies should be prepared for in addressing ethical and security dilemmas. Furthermore, AI improves predictive analytics, thereby enabling security agencies to more accurately anticipate potential threats and enhance their preparedness by identifying vulnerabilities in the national security infrastructure

Artificial intelligence usage in the communication field is of strategic importance. However, most communication practitioners and academicians have not noticed the gains in momentum substantially artificial intelligence. Through communication journals, this study aims to examine how artificial intelligence is used, its effects, and how important it is in communication. This study was designed as a content analysis and bibliometric analysis study. The sample of this study is AI-based articles in Web of Science Q1 indices communication journals. It selected and examined the first sixteen journals in communication keyword search based on SCImago Journal &amp; Country Rank. This study revealed artificial intelligence usage in the communication industry and field, in addition to AI's impact and significance and AI-based technologies in communication. It was found that the most used method for artificial intelligence-based articles in communication journals was the semi-structured interview method. It is seen that common keywords in AI-based articles and communication journals are announced as human-machine communication, machine learning, artificial agent, artificial intelligence, bias, and social media concepts. In this study, a positive correlation between communication science and artificial intelligence technologies was observed. This study contributes to new studies on artificial intelligence, communication, the impacts of artificial intelligence on communication, new communication technologies, generative AI, human-machine communication, and other related areas.

At this modernity, various applications have been innovated to entertain people and foster romantic connections, with one of the most notable being the increasing integration of artificial intelligence (AI) in romantic relationships. This study, conducted in the Philippines, aims to explore the relationship between relationship satisfaction from using AI in romantic relationships and the level of AI usage, while evaluating its significance in today’s generation. A total of 338 students ranging from Grade 11 to fourth-year college students, participated in this research, which employs a quantitative approach with a descriptive research design. The results revealed that participants were "satisfied" with their relationship satisfaction from using AI (M = 3.71, SD = 0.79), with 67% to 98% agreeing that AI positively influences their romantic relationship satisfaction. The overall AI usage in romantic relationships had a high mean score (M = 3.66, SD = 0.66), suggesting significant engagement with AI in this context. A moderately positive correlation (r = 0.585, p &lt; 0.000, N = 338) was found between AI usage and relationship satisfaction, indicating that as AI usage increases, so does relationship satisfaction, underscoring the role of AI in enhancing emotional aspects of romantic relationships.

BackgroundIn recent years, the integration of artificial intelligence (AI) into the contemporary workplace has transformed the landscape of numerous industries. Despite its benefits, AI usage has also brought about significant controversies, particularly concerns over job displacement and job insecurity. These changes may drive employees to consider alternative work arrangements, including moonlighting.ObjectiveDrawing on Conservation of Resources Theory and Career Construction Theory, this study investigates the relationship between AI usage and employee moonlighting intention. Specifically, it explores the mediating role of job insecurity and the moderating effect of career adaptability.MethodA two-wave questionnaire survey was conducted among 376 employees. Structural equation modeling and PROCESS macro in SPSS were used to test the hypothesized relationships, including mediation and moderation effects.ResultsThe findings indicate that AI usage is positively associated with employee moonlighting intention. Job insecurity mediates this relationship, while career adaptability moderates the effect of AI usage on job insecurity. At high levels of career adaptability, the impact of AI usage on job insecurity is significantly reduced or even reversed.ConclusionThis study bridges the topics of AI usage and employee moonlighting, unveiling the psychological mechanism linking technological change to career behavior. By identifying job insecurity and career adaptability as key factors, the study provides both theoretical insights and practical implications for organizations navigating workforce transformation in the era of AI.

This study explored the factors that affect the adaptation and usage of Artificial Intelligence (AI) among secondary school teachers in Mbeya City Council, Tanzania. A descriptive quantitative research design was used, involving a population of 1,336 teachers, from which 320 were selected through stratified random sampling. Data were collected using structured questionnaires and analyzed using the Statistical Package for the Social Sciences (SPSS) version 26. Descriptive statistics such as frequencies and percentages were used to summarize data, while multiple regression analysis was applied to examine the relationship between perceived usefulness, perceived ease of use, facilitating conditions, social influence, and AI adoption. The results showed that both perceived usefulness and perceived ease of use had a negative but significant influence on AI usage, while facilitating conditions and social influence had weak or insignificant effects. The study concludes that low AI usage among teachers is mainly caused by inadequate training, poor infrastructure, and limited institutional support. It recommends improved teacher training, better digital infrastructure, and stronger policy implementation to promote effective AI use in secondary schools..

Teacher education students play double role as present learners and future educators. Hence, they need targeted training to navigate the growing influence of Generative Artificial Intelligence (GenAI) on teaching, learning and professional identity. However, existing artificial intelligence (AI) literacy programmes predominantly emphasize technical AI knowledge and pre‐GenAI tools or are offered by GenAI platforms that focus on their own technologies' features, thereby lacking pedagogically structured frameworks that address non‐technical dimensions such as ethics, contextual understanding and the development of human‐centered, critical and lifelong learning mindsets to adapt to rapid technology changes. Furthermore, limitation of time in teacher education syllabus and faculty's lack of AI literacy require targeted intervention. This design‐based research (DBR) aims to fill this gap by developing and evaluating a set of design principles for GenAI literacy training in teacher education. Integrating contemporary AI competency frameworks for learners and teachers, the study implements these principles in a workshop that serves as the research prototype. The prototype was first piloted with 14 master's students and then evaluated with 29 teacher education (TE) students. Results show significant gains in participants' AI competence self‐efficacy, attitudes towards GenAI and commitment to critical, ethical and pedagogical engagement with GenAI tools. The findings highlight the need for teacher education programmes to integrate GenAI literacy that supports teachers' evolving roles as reflective practitioners, co‐creators and lifelong learners in an AI‐driven world. Practitioner notes What is already known about this topic Students' self‐efficacy and mindset influence their adoption of GenAI in learning and teaching. GenAI competency is essential for teacher education students, encompassing technological, ethical and sociocultural dimensions. Implementing AI literacy training faces challenges such as educators' limited AI literacy, the lack of pedagogical frameworks and the need to integrate technical knowledge with ethical reasoning, self‐regulated learning and metacognitive skills. Transformative learning is crucial in preparing teacher education students as co‐creators and facilitators in AI‐enhanced education. What this paper adds This study presents the design and evaluation of an AI competency training programme to enhance teacher education students' self‐efficacy, critical and human‐centered AI mindsets and human–AI interaction skills. Using design‐based research, it identifies key principles for AI literacy training, demonstrating how transformative, active and experiential learning approaches can prepare teacher education students for evolving roles in AI‐enhanced education. Implications for practice and/or policy Educational technologists can apply the proposed design principles to develop GenAI tools and AI systems that enhance AI competency and self‐regulated learning (SRL). Educators can integrate these AI training principles into their teaching strategies and enhance their task assignments and assessments to foster deep learning, self‐regulated learning and metacognitive skills in the age of GenAI. Policymakers should update teacher education curriculum to include AI competency, strengthen content and pedagogical knowledge, especially in social emotional learning, formative and authentic assessment methods and establish guidelines for selecting GenAI tools that support human intelligence and mitigate over‐reliance.

As the application of artificial intelligence (AI) in the workplace increases, investigating its impact on work engagement is crucial for optimizing human resource management and enhancing organizational productivity and competitiveness. Based on the Conservation of Resources theory, this study investigated whether AI usage exhibits a double-edged sword effect on work engagement and examined the moderating role of core task characteristics substitution in this relationship. A two-wave study was conducted among 279 employees from China, and Hayes's PROCESS macro was used to test the moderated mediation model. The findings indicated that (1) AI usage enhances work engagement by increasing psychological availability and indirectly increases work engagement by suppressing work alienation; (2) core task characteristics substitution diminishes the enhancing effect of AI usage on psychological availability and the inhibiting effect of AI usage on work alienation; and (3) overall, AI usage tends to suppress work alienation, demonstrating an empowering effect. However, under conditions of high core task characteristics substitution, AI usage can increase work alienation, revealing potential negative effects. The findings enrich our understanding of the complex impact of AI usage on work engagement and offer valuable insights for managers to improve employee experiences in the AI era.