Usage Of Intelligence Research Articles

Reliability and efficiency of ChatGPT 3.5 and 4.0 as a tool for scalenovertebral triangle anatomy education.

As the popularity and the usage of the artificial intelligence (AI) tools is increasing in medical education, it is important to critically evaluate these resources and confirm their reliability. The current study proposes to assess the reliability and effectiveness of ChatGPT 3.5 and 4 for gross anatomical information on scalenovertebral triangle. ChatGPT versions 3.5 and 4 AI tools were used to explore the anatomical information on scalenovertebral triangle eight times on different days. The responses were qualitatively compared to the actual anatomy of the region and comments were made by the authors for each response. The replies given by ChatGPT were not appropriate (either incorrect, partially correct or incomplete) in any of the conversations. There was no major difference between the accuracy of responses, while comparing ChatGPT 3.5 and 4. Almost three out of four times, ChatGPT confused scalenovertebral triangle with scalene or interscalene triangle. None of the responses provided by ChatGPT 3.5 and 4 across all eight instances aligned even once with the standard anatomical description of the scalenovertebral triangle. A novice medical student may not be able to judge the difference between correct and incorrect, consequently may wrongly interpret the anatomy. So cautious planning and educator check is important while it is used. Further development and modifications of this AI tool are required to increase its potential to be used in medical education and healthcare.

Mapping Software-Engineering Industry AI Use to Software-Engineering Curriculum: Developing the AI-USE Framework

Estimates predict a global deficit of 4 million software engineers by 2025, further complicated by the software engineering (SE) industry's escalating use of artificial intelligence (AI). To tackle this issue, our research suggests that computer science (CS) curricula in middle and high schools need to be updated to incorporate SE industry segments that significantly employ AI. This strategic curriculum alignment is significant for preparing a workforce equipped to meet future industry demands. Our initial analysis involved reviewing nine international AI education guidelines to evaluate current methods for integrating AI into SE education. The findings indicated a pronounced lack of specific guidance connecting AI applications in the SE industry with educational content. To address this, we performed a systematic literature review of 12 research papers focusing on AI's role across the SE industry, followed by multiple rounds of inductive content analysis. An industry segment was deemed "essential" if it was referenced in 75% or more of the papers' findings. Through this method, we identified 10 essential SE industry segments for inclusion in CS education: software development, software maintenance, process improvement, software economics, knowledge management, project management, software testing, software security, quality assurance, and deployment and operations (DevOps). These findings led to the creation of the AI-USE (Artificial Intelligence Usage in Software Engineering) framework, which maps these 10 key segments to the predominant uses of SE in the industry as identified in the literature. Further inductive content analysis helped us develop subsegments for these essential areas. Ongoing framework development involves refining these subsegments and gathering feedback from industry and academic professionals. We anticipate that the fully developed AI-USE framework will significantly enhance SE education, equipping the next generation of software engineers with the AI proficiency required to address the industry’s evolving demands.

Artificial Intelligence Usage in Communication Field: An Analysis on Communication Journals

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 & 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.

The Phenomenon of Artificial Intelligence Usage in News Writing Styles by Journalists of Bengkulu Ekspress.com

The Phenomenon of Artificial Intelligence Usage in News Writing Styles by Journalists of Bengkulu Ekspress.com

The green innovation effect of industrial robot applications: Evidence from Chinese manufacturing companies

Artificial intelligence has emerged to revolutionize society in China. Investigating whether industrial robot applications (IRAs) can contribute to Chinese economic prosperity has significant theoretical and practical significance. For this purpose, this study estimates the impact of IRAs on green innovation by decomposing the industry robot stock to the corporate level using global industry robot data and manufacturing data from Chinese manufacturing listed companies by constructing a Bartik instrumental variable. The results show that IRAs notably promote corporate green innovation. However, IRAs do not contribute equally to all corporations in green creation. Its effects on green innovation are mainly observed in larger corporations, technology-intensive industries, and corporations located in developed cities. Digital transformation, management efficiency, and CEO's information technology (IT) background can further strengthen the green innovation effect of IRAs. We conclude that the rational exploitation of artificial intelligence drives the economy towards green development.

Burnout crisis in Chinese radiology: will artificial intelligence help?

To assess the correlation between the use of artificial intelligence (AI) software and burnout in the radiology departments of hospitals in China. This study employed a cross-sectional research design. From February to July 2024, an online survey was conducted among radiologists and technicians at 68 public hospitals in China. The survey utilized general information questionnaires, the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) scale, and a custom-designed AI usage questionnaire. This study analyzed the correlation between AI software usage and occupational burnout, and general information was included as a control variable in a multiple linear regression analysis. The analysis of survey data from 522 radiology staff revealed that 389 (74.5%) had used AI and that 252 (48.3%) had used it for more than 12 months. Only 133 (25.5%) had not yet adopted AI. Among the respondents, radiologists had a higher AI usage rate (82.0%) than technicians (only 59.9%). Furthermore, 344 (65.9%) of the respondents exhibited signs of burnout. The duration of AI software usage was significantly negatively correlated with overall burnout, yielding a Pearson correlation coefficient of -0.112 (p < 0.05). Multiple stepwise regression analysis revealed that salary satisfaction, night shifts, duration of AI usage, weekly working hours, having children, and professional rank were the main factors influencing occupational burnout (all p < 0.05). AI has the potential to significantly help mitigate occupational burnout among radiology staff. This study reveals the key role that AI plays in assisting radiology staff in their work. Questions Although we are aware that radiology staff burnout is intensifying, there is no quantitative research assessing whether artificial intelligence software can mitigate this occupational burnout. Findings The longer staff use deep learning-based artificial intelligence imaging software, the less severe their occupational burnout tends to be. This result is particularly evident among radiologists. Clinical relevance In China, radiologists and technicians experience high burnout rates. Even if there is an artificial intelligence usage controversy, encouraging the use of artificial intelligence software in radiology helps prevent and alleviate this occupational burnout.

Impact of Artificial Intelligence Usage and Technology Competence on Competitive Advantage with Mediating Role of Effective Information Management System

Competitive advantage has been considered as the foremost element for the organizational success and this could be achieved using artificial intelligence (AI) and technological competencies. The current study investigates the impact of AI usage and technology competencies on the competitive advantage of manufacturing industries in China. The paper also investigates the mediating role of effective information management system (IMS) among AI usage, technology competencies and competitive advantage. Data was obtained from a sample comprising employees of manufacturing companies through questionnaires. The data reliability and association among variables were measured with SPSSAMOS. The results exposed that the AI usage and technology competencies have a positive nexus with competitive advantage and also revealed that the effective IMS significantly mediates among AI usage, technology competencies and competitive advantage of manufacturing industry in China. The study provides useful insights to the regulators in establishing regulations towards improving competitive advantage, effective AI usage and technology competencies.

Awareness and Usage of Artificial Intelligence (AI) in Promoting Music Broadcast on Radio in Warri, Nigeria

This paper investigates the level of awareness and usage of artificial intelligence (AI) for promoting music broadcast on radio stations in Warri, Nigeria. The study was prompted by the paradigm shift that is brought about by the advent of artificial intelligence. Despite the advantages inherent in technology most radio stations appear to lack knowledge of the component meant for the broadcast of music. Thus, the study establishes the extent to which the radio station in Warri, Nigeria has become AI compliant in relaying music. To determine the AI awareness level and extent of usage in music promotion on radio stations, the researcher conducted interview sessions using four (4) radio stations, forty-one (41) on Air Personalities (OAP). A Self Respondent Interview Research Instrument was administered via email contact. The study was guided by three (3) research questions. Data were analyzed with the aid of percentage calculation measure to decide the level of awareness and usage of the AI tools connected to music broadcast on radio. The study found that respondents show low level of awareness of significant AI tools and thus could not deploy AI technologies for broadcast of music. The study concludes that it is important to create high level of awareness in the use of AI tools for promotion of music broadcast on radio. The study recommends that OAP should acquire the knowledge of AI tools related to promotion of music on radio stations. The proprietors of radio stations should provide training on the use of AI technologies to enable them become AI compliant in radio broadcasting.

Do Ophthalmology Journals Have AI Policies for Manuscript Writing?

PurposeTo assess the prevalence of Artificial Intelligence (AI) usage policies in manuscript writing in PubMed-indexed ophthalmology journals and examine the relationship between adoption of these policies and journal characteristics. DesignCross-sectional study SubjectsPubMed-indexed ophthalmology journals Main Outcome MeasuresPrevalence of policies in journal guidelines regarding the use of AI in manuscript writing. MethodsWe reviewed the guidelines of 84 ophthalmology journals indexed in PubMed to determine the presence of AI-use policies for manuscript generation. We further compared journal metrics, such as CiteScore, Journal Impact Factor (JIF), Journal Citation Indicator (JCI), Source Normalized Impact per Paper (SNIP), and SCImago Journal Rank (SJR), between journals with and without AI policies. Additionally, we analyzed the association between AI policy adoption and journal characteristics, such as MEDLINE indexing and society affiliation. ResultsAmong the 84 journals, 53 (63.1%) had AI policies for manuscript generation, with no significant changes observed during the study period. Journals indexed in MEDLINE were significantly more likely to have AI policies (68.8%) than non-MEDLINE-indexed journals, where no AI policies were found (0%) (p = 0.0008). There was no significant difference in AI policy adoption between society-affiliated (62.7%) and unaffiliated journals (64.7%) (p = 0.8443). Journals with AI policies had significantly higher metrics, including CiteScore, SNIP, SJR, JIF, and JCI (p < 0.05). ConclusionsWhile many ophthalmology journals have adopted AI policies, the lack of guidelines in over one-third of journals highlights a critical need for consistent and comprehensive AI policies, particularly as the AI landscape rapidly advances.

Artificial Intelligence Usage in Higher Education: Influence on Online Learning

The conceptualization and implementation of artificial intelligence (AI) in online learning have shown the most effective ways to use AI pedagogically. Viewing AI as a tool for online learning is crucial. By integrating AI technologies into teaching practices, educators can create more engaging, effective, and personalized learning experiences for their students. However, it is essential to use AI responsibly, ensuring it complements and enhances the role of educators rather than replacing human interaction and support. This article begins by outlining its purpose and providing an overview of AI history. It will presents a comparative literature analysis, discussing the advantages and disadvantages of using AI in online learning. Finally, the article explores how to incorporate AI into online teaching practices and offers strategies to encourage students to utilize AI effectively.

A Comprehensive IoT Cloud-based Wind Station Ready for Real-time Measurements and Artificial Intelligence Integration

Accurate and efficient wind measurement and monitoring are crucial for various applications, including renewable energy, meteorology, public safety, and environmental research. This paper presents an integrated approach for a cloud-computing Internet of Things-based Automated Weather Station, with edge devices, designed to provide real-time wind measurements in diverse environments. The presented system comprises a dedicated station frame, a self-sufficient solar power setup, an ultrasonic wind sensor, a data transmission node, cloud computing capabilities, and an end-user visualization application. Calibration procedures reduced the maximum mean error of the ultrasonic wind sensors from 0.7 m/s to 0.2 m/s, achieving a 71% improvement in measurement accuracy. Using this method, all station data are processed every 3 seconds and stored ready for Artificial Intelligence usage with an approximate latency of 150–300 milliseconds, representing up to an 85% reduction in processing delay compared to similar solutions with over 1-second latencies. The lightweight and resistant frame design facilitates easy deployment, while the power setup with sub-watt efficiency ensures a reliable energy source. The ultrasonic wind sensor was subjected to calibration procedures and design improvements to increase its performance under specific rain conditions. Internet of Things communication via Hypertext Transfer Protocol enables efficient data transmission between the Automated Weather Station and the cloud server, which processes and stores the data for future analysis. The responsive and auto-adaptive web application allows user-friendly data visualization, making the wind data easily accessible and interpretable. The proposed cloud-computing Internet of Things-based Automated Weather Station framework demonstrates significant potential for accurate and efficient wind measurement and monitoring, paving the way for future advancements in high temporal resolution wind monitoring systems capable of producing big data prepared for subsequent machine learning model approaches.

Getting to know ChatGPT: How business students feel, what they think about personal morality, and how their academic outcomes affect Oman's higher education

The present study develops an integrative framework that investigates the relationship between the acceptability of ChatGPT among business students and their attitude, intention to adopt, and performance. This is achieved by examining the moderating role of business students' moral values and religious ethics. Using data collected from 312 university business students in Oman, we show that perceived usefulness (PU), perceived ease of use (PEOU), and perceived convenience (PC) have a positive effect on their attitudes toward ChatGPT. Business students' attitudes toward ChatGPT have a strong positive influence on their adoption intentions. Notably, university business students’ ChatGPT adoption intentions increased their academic performance. Remarkably, business students' Personal Morality and religion-related ethics trigger them to experience regret or a sense of responsibility for their actions that violate academic integrity or ethical standards in their studies. Establishing explicit ethical standards and procedures for the usage of artificial intelligence (AI) tools such as ChatGPT in educational settings is vital for higher educational institutions (HEIs). This research adds to the theoretical intervention of investigating how personal morality and religion-related ethics interact with AI tools such as ChatGPT, which can add to ethical decision-making theories. The current study has significant implications for theory as well as for practice.

Elevating logistics performance: harnessing the power of artificial intelligence in e-commerce

PurposeArtificial intelligence (AI) usage improves e-commerce logistics efficiency. However, many actors can play significant roles, such as supply chain consistency (SCC), last-mile logistics (LML) performance and collaboration and coordination among logistics firms. This study aims to assess how SCC and LML performance mediate and collaboration and coordination moderate the relationship between AI usage and logistics efficiency.Design/methodology/approachA structured questionnaire was used to collect the data. A total of 245 valid responses were received from Indian e-commerce businesses. The data were then analysed using AMOS v25 and structural equational modelling using SPSS for regression, PROCESS macro for mediation and moderated mediation analysis.FindingsThe findings show that AI usage independently impacts logistics efficiency, with SCC and last-mile delivery performance as mediating variables. Collaboration and coordination among logistic firms are also critical moderators in enhancing AI’s efficacy in logistic operations. The study findings suggest the integration of AI into logistic operations and provide implications to managers on the urgency of fostering a collaborative and synchronised environment to utilise the full potential of AI in e-commerce businesses.Originality/valueThis study not only contributes to the field of logistics theory by presenting empirical data on the various ramifications of AI but also offers practical guidance for logistics firms, particularly those operating in developing economies, on how to strategically employ AI to enhance operational efficiency and attain a competitive advantage in the era of e-commerce logistics in the digital age.

ChatGPT adoption risks and cognitive achievement among tourism and hospitality college students: from faculty member perspective

PurposeDespite ChatGPT usage advantages to complete assignments as quickly as possible with detailed information, its adoption risks are crucial factors that may significantly influence student outcomes, like creative skills and achievement levels. Hence, this paper examines the potential effects of ChatGPT adoption risks on students’ cognitive achievement, underpinned by perceived risk theory (PRT). Further, this paper examines the mediating role of creative thinking levels among hospitality college students.Design/methodology/approachThis paper employed a quantitative approach to collect data. Using an online survey, simple random sampling was employed to ensure bias. Hence, 267 faculty members at tourism and hospitality colleges affiliated with Egyptian public universities responded, and their responses were tested using SmartPLS v.4.FindingsCreative thinking partially mediated five potential risks of students’ ChatGPT adoption effects on their cognitive achievement. More specifically, psychological risks of ChatGPT adoption among students are considered one of the most likely to reduce their levels of creative thinking and their ability to achieve achievement.Practical implicationsThis paper provides insights for policymakers aimed at enhancing higher education quality in tourism and hospitality colleges. Accordingly, this paper concludes by highlighting the importance of addressing ChatGPT adoption’s psychological risks, integrating strategies to promote creative thinking among students and fostering responsible artificial intelligence usage in higher education.Originality/valueThis paper underscores the critical role of faculty members in navigating and mitigating these risks, fostering a more conducive learning environment for responsible ChatGPT usage.

Artificial intelligence and the effectiveness of marketing messages

The lack of scientific research on whether there are, and if so, how big are the differences in the attitudes of population about the effects of artificial intelligence on increasing the effectiveness of marketing messages is a research problem. Descriptions of the strength of attitudes of different groups of respondents are broken down by gender, age, highest level of education and work status on whether does the use of artificial intelligence in marketing increases the effectiveness of marketing messages and explanations of reasoning for such strong attitudes represent goal and science contribution of this research. Results of the research are positive, in other words, there is a general understanding among the respondents that artificial intelligence should be used in marketing to increase its effectiveness. The authors consider that over time there will be an increase of the understanding of the benefits in using artificial intelligence in marketing and overall business because increase of usage of artificial intelligence in business is also trending in Croatia.

A Review on Usage of Artificial Intelligence for Early Detection and Management of Alzheimer's Disease

A Review on Usage of Artificial Intelligence for Early Detection and Management of Alzheimer's Disease

Exploring the Influence of Artificial Intelligence Usage on Ethical Decision Making Among Public Sector Employees: Insights into Moral Identity and Service Motivation

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.

How and when artificial intelligence usage facilitates task performance

This study investigated how the increasing usage of artificial intelligence (AI) in diverse business applications has affected task performance. Building on the job demands–resources model, we employed moderated mediation modeling to investigate the association between AI usage and the task performance of delivery drivers. Participants comprised 251 delivery drivers who completed online surveys over a 1-month period. Hierarchical regression analysis revealed that work engagement played a mediating role in the association between AI usage and the task performance of delivery drivers. Moreover, the mediating role of work engagement was moderated by an individual's concept of their future work self. When an individual had a stronger sense of their future work self, the mediating role of work engagement became more pronounced. This study has introduced a new mediating mechanism linking artificial intelligence with employee performance and has identified boundary conditions that increase its beneficial impact on employee performance, thus contributing theoretically to the extant literatures. The study findings can help companies improve employee engagement and performance.

Artificial Intelligence Tools Usage: A Structural Equation Modeling of Undergraduates’ Technological Readiness, Self-Efficacy and Attitudes

AbstractThis study investigates the relationship between undergraduates’ technological readiness, self-efficacy, attitude, and usage of artificial intelligence (AI) tools. The study leverages the technology acceptance model (TAM) to explore the relationships among the study’s variables. The study’s participants are 176 undergraduate students from a public university in southwestern Nigeria. The Partial Least Square Structural Equation Modeling (PLS-SEM) was used to analyze the responses from the participants. The questionnaire has six constructs measured on a 5-point Likert scale. The results show that undergraduates’ technological self-efficacy determines their usage of AI tools and perception of AI tools’ ease of use, but this does not determine their perception of the AI tools’ usefulness and attitude towards AI tools usage. Also, technological readiness was found to determine the perception of the AI tools’ usefulness, perception of AI tools’ ease of use, and technological self-efficacy among undergraduates but does not determine their usage of AI tools and attitude towards AI tools usage. In addition, undergraduates’ attitude towards AI tools was considered the primary determinant of the usage of AI tools. It was concluded that some factors determine the adoption of AI tools, which are interrelated. Educators can play a pivotal role in empowering students to harness the power of AI tools by encouraging their usage under well-coordinated guidance rather than imposing outright restrictions. By fostering AI literacy and equipping students with the knowledge and skills to navigate these innovative technologies, educators can instil the confidence and competency needed to integrate AI tools into various academic activities seamlessly.

The Possibilities of Artificial Intelligence Usage in Loyalty Programs

From the year 2022, when the GPT 3 model became publicly available, Artificial intelligence (AI) has been a buzzword in marketing. To say it still is influencing the field would be an understatement with new models and technologies continuously emerging and existing ones getting better and better. Loyalty programs as a sales promotion tool have also undergone big changes in recent years and AI is bringing new opportunities and challenges to the field. In this paper, we investigate the possibilities of artificial intelligence usage in loyalty programs. We aim to showcase the diverse opportunities through which AI can enhance loyalty program experiences. Among those usage opportunities we put specific attention on AI personalization and predictive modelling. By harnessing AI capabilities, organizations can possibly find new ways to enhance customer engagement, satisfaction, and build stronger loyalty. In this paper we are also looking at the current state of loyalty programs in the selected market and the way AI is being used in them. It is important to note that we approach the topic from two points of view – customers` and brands`. That means that we are trying to highlight how certain AI technologies can possibly improve customers` experience as well as how AI may be a helpful tool for businesses who want to manage loyalty programs. The final part of our article includes information on the suggested ways AI technologies may be implemented into loyalty programs based on the information provided in previous parts of the paper. Suggested implementation strategies are also appropriate as a starting point for further research, where every single technology would be researched more in detail. The main goal of this article is to provide readers with a comprehensive overview of the possibilities of how Artificial Intelligence can be used in the context of loyalty programs today. The article is theoretical-empirical and is based on external information from trustworthy sources as well as our own research of certain AI technologies in the context of loyalty programs.