Effects Of Artificial Intelligence Research Articles

Effectiveness Of Artificial Intelligence In Management Accounting

This academic review paper aims to investigate the possibility of integrating artificial intelligence into the daily workflow of management accounting, and to what extent this would increase the effectiveness and efficiency of the business operations. By focusing on aspects such as management accounting, artificial intelligence, the advantages and disadvantages of utilising artificial intelligence for management accounting, ethical considerations of utilising AI while handling sensitive financial information, and various real-world businesses which use AI in their day-to-day operations, this paper is able to clearly identify and explain the possibility of human accountants and artificial intelligence working together in order to maximise the accuracy and efficiency of outcome. This paper also provides an overview regarding some of the essential accounting tools equipped with AI that are currently being used by management accountants, and also discusses the possibility of AI replacing human management accountants completely. By covering all of these components and providing necessary explanations, this academic review paper aims to answer the research question “To what extent will AI be more effective than traditional methods of management accounting?”

The Effect of Artificial Intelligence on Patient-Physician Trust: Cross-Sectional Vignette Study.

Clinical decision support systems (CDSSs) based on routine care data, using artificial intelligence (AI), are increasingly being developed. Previous studies focused largely on the technical aspects of using AI, but the acceptability of these technologies by patients remains unclear. We aimed to investigate whether patient-physician trust is affected when medical decision-making is supported by a CDSS. We conducted a vignette study among the patient panel (N=860) of the University Medical Center Utrecht, the Netherlands. Patients were randomly assigned into 4 groups-either the intervention or control groups of the high-risk or low-risk cases. In both the high-risk and low-risk case groups, a physician made a treatment decision with (intervention groups) or without (control groups) the support of a CDSS. Using a questionnaire with a 7-point Likert scale, with 1 indicating "strongly disagree" and 7 indicating "strongly agree," we collected data on patient-physician trust in 3 dimensions: competence, integrity, and benevolence. We assessed differences in patient-physician trust between the control and intervention groups per case using Mann-Whitney U tests and potential effect modification by the participant's sex, age, education level, general trust in health care, and general trust in technology using multivariate analyses of (co)variance. In total, 398 patients participated. In the high-risk case, median perceived competence and integrity were lower in the intervention group compared to the control group but not statistically significant (5.8 vs 5.6; P=.16 and 6.3 vs 6.0; P=.06, respectively). However, the effect of a CDSS application on the perceived competence of the physician depended on the participant's sex (P=.03). Although no between-group differences were found in men, in women, the perception of the physician's competence and integrity was significantly lower in the intervention compared to the control group (P=.009 and P=.01, respectively). In the low-risk case, no differences in trust between the groups were found. However, increased trust in technology positively influenced the perceived benevolence and integrity in the low-risk case (P=.009 and P=.04, respectively). We found that, in general, patient-physician trust was high. However, our findings indicate a potentially negative effect of AI applications on the patient-physician relationship, especially among women and in high-risk situations. Trust in technology, in general, might increase the likelihood of embracing the use of CDSSs by treating professionals.

Transforming Cybersecurity into Critical Energy Infrastructure: A Study on the Effectiveness of Artificial Intelligence

This work explores the integration and effectiveness of artificial intelligence in improving the security of critical energy infrastructure, highlighting its potential to transform cybersecurity practices in the sector. The ability of artificial intelligence solutions to detect and respond to cyber threats in critical energy infrastructure environments was evaluated through a methodology that combines empirical analysis and artificial intelligence modeling. The results indicate a significant increase in the threat detection rate, reaching 98%, and a reduction in incident response time by more than 70%, demonstrating the effectiveness of artificial intelligence in identifying and mitigating cyber risks quickly and accurately. In addition, implementing machine learning algorithms has allowed for the early prediction of failures and cyber-attacks, significantly improving proactivity and security management in energy infrastructure. This study highlights the importance of integrating artificial intelligence into energy infrastructure security strategies, proposing a paradigmatic change in cybersecurity management that increases operational efficiency and strengthens the resilience and sustainability of the energy sector against cyber threats.

Comparing the Performance of ChatGPT-4 and Medical Students on MCQs at Varied Levels of Bloom's Taxonomy.

This research investigated the capabilities of ChatGPT-4 compared to medical students in answering MCQs using the revised Bloom's Taxonomy as a benchmark. A cross-sectional study was conducted at The University of the West Indies, Barbados. ChatGPT-4 and medical students were assessed on MCQs from various medical courses using computer-based testing. The study included 304 MCQs. Students demonstrated good knowledge, with 78% correctly answering at least 90% of the questions. However, ChatGPT-4 achieved a higher overall score (73.7%) compared to students (66.7%). Course type significantly affected ChatGPT-4's performance, but revised Bloom's Taxonomy levels did not. A detailed association check between program levels and Bloom's taxonomy levels for correct answers by ChatGPT-4 showed a highly significant correlation (p<0.001), reflecting a concentration of "remember-level" questions in preclinical and "evaluate-level" questions in clinical courses. The study highlights ChatGPT-4's proficiency in standardized tests but indicates limitations in clinical reasoning and practical skills. This performance discrepancy suggests that the effectiveness of artificial intelligence (AI) varies based on course content. While ChatGPT-4 shows promise as an educational tool, its role should be supplementary, with strategic integration into medical education to leverage its strengths and address limitations. Further research is needed to explore AI's impact on medical education and student performance across educational levels and courses.

Tourists’ Willingness to Adopt AI in Hospitality—Assumption of Sustainability in Developing Countries

This study explores the impact of artificial intelligence (AI) on customer perceptions and behavior in restaurants, airline companies, and hotel sectors within the hospitality industry of Iran. The primary objective is to analyze how AI affects customer trust, brand engagement, electronic word-of-mouth (eWOM), and tourists’ readiness to use AI technologies. Using a comparative analysis approach and surveys, this research tests hypotheses about the effects of artificial intelligence on various dimensions of customer interaction. The findings highlight significant relationships between the quality of artificial intelligence and customer engagement metrics, such as trust and brand loyalty, which are crucial for understanding and predicting customer behavior in response to technological advancements. This study lays the groundwork for theoretical assumptions about sustainability in these sectors in developing countries, providing a basis for future empirical research that could validate these assumptions and explore broader implications of AI integration in enhancing sustainable practices within the hospitality industry.

The Effect of Artificial Intelligence on Developing the Interior Designer&amp;#039;s Performance in Interior Architecture

The Effect of Artificial Intelligence on Developing the Interior Designer&amp;#039;s Performance in Interior Architecture

The Impact of Artificial Intelligence on Economic Growth From the Perspective of Population External System

Artificial intelligence has sophisticated social and economic effects that cannot be ignored. Based on a thorough review of the development of artificial intelligence, this paper systematically explores the mechanism of the impact of artificial intelligence on economic growth through technology, value and application three paths, which is starting from the perspective of the population external system. In order to verify the rationality of the paths, the effect of artificial intelligence on economic growth from the perspective of population external system is rigorously estimated using artificial intelligence and macroeconomic data for China from 2011 to 2019. The findings are as follows. Firstly, there is a significant positive effect of artificial intelligence on the economic growth from the perspective of the population external system. This positive effect is sufficiently robust over the sample-wide period. Secondly, there is significant regional heterogeneity in the effect of artificial intelligence on economic growth from the perspective of the population external system. The low levels of artificial intelligence development impeded the economic growth, the middle levels of artificial intelligence development contributed significantly to the economic growth, and the high levels of artificial intelligence development did not show a significant contribution to the economic growth. In view of this, future policies should be designed in terms of revitalizing the value of the artificial intelligence stock, exploring the value potential of artificial intelligence and regulating it in a hierarchical manner.

Can Artificial Intelligence Be Utilized to Predict Real-Time Adverse Outcomes in Individuals Arriving at the Emergency Department With Hyperglycemic Crises?: Implications for APRN Practice.

This column on translating research into practice is crafted to offer advanced practice registered nurses an analysis of current research topics that hold practical relevance for emergency care settings. The article titled "Using Artificial Intelligence to Predict Adverse Outcomes in Emergency Department Patients With Hyperglycemic Crises in Real Time," authored by C. Hsu etal. (2023), investigates through a randomized control trial, the effectiveness of artificial intelligence as a practical tool compared with the traditional predicting hyperglycemic crisis death score to clinically predict adverse outcomes in individuals presenting to the emergency department with hyperglycemic crises. The results are discussed in the context of averting adverse outcomes associated with sepsis/septic shock, intensive care unit admission, and all-cause mortality within a 1-month time frame.

The work of art in the age of artificial intelligibility

AbstractThe emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical, aesthetic, epistemological and legal frameworks we have so far used to categorise art. To begin tackling these issues and identifying a role for AI in the production and protection of human artwork, it is necessary to take a multidisciplinary approach which considers current legal precedents, the practice of software engineering, historical attitudes towards technological innovation and a sustained technical analysis of the models themselves. This paper queries the location and nature of substantive artistic work in the developmental stages of an AI-generated image, offering critiques of existing assumptions and posing questions for future research. The emergence of convincing AI creative output, artistic or literary, has significant long-term implications for the humanities, including the need for re-appraisal of foundational ideas about authorship and creativity in general. The effects of artificial intelligence, whether generalised or task-specific, cannot be ignored or displaced now that easy-access, scalable image and text production is a reality.

THE IMPACT OF ARTIFICIAL INTELLIGENCE ON FMCG DISTRIBUTION

Economic Impact-Many examinations have investigated the monetary ramifications of man-made intelligence and ML reception. Research frequently centres around efficiency gains, work market elements, and the potential for work uprooting and creation. A few examinations propose that while Artificial intelligence and ML can prompt expanded effectiveness and development, they may likewise disturb customary business designs, requiring labour force transformation and re-skilling. Business and Industry: Writing in this space looks at how Artificial intelligence and ML advances are changing business tasks, including promoting, finance, store network the board, and client care. Reads up feature the potential for artificial intelligence and ML to improve dynamic cycles, enhance asset designation, customize client encounters, and drive upper hand. Medical care: Artificial intelligence and ML have huge ramifications for medical care, including sickness determination, therapy arranging, drug disclosure, and customized medication. Research in this space investigates the potential for Artificial intelligence and ML to work on clinical results, diminish clinical blunders, lower medical services expenses, and upgrade patient consideration through prescient examination, picture acknowledgment, and normal language handling. Education and Learning: The effect of Artificial intelligence and ML on schooling and learning is likewise a subject of interest. Writing in this field looks at how artificial intelligence fueled devices and stages can work with customized growth opportunities, versatile coaching, robotized reviewing, and instructive substance creation. Research additionally investigates the difficulties and moral contemplations related with man-made intelligence driven instructive innovations. Ethical and social implications-Researchers have raised worries about the moral and cultural ramifications of Artificial intelligence and ML, including issues connected with protection, predisposition, decency, straightforwardness, responsibility, and algorithmic administration. Research in this space looks to foster structures, rules, and guidelines to alleviate likely dangers and guarantee capable man-made intelligence advancement and arrangement. Environmental Impact few examinations explore how simulated intelligence and ML can be utilized to address natural difficulties, for example, environmental change, asset preservation, contamination control, and manageable turn of events. Research in this area investigates uses of computer based intelligence and ML in energy the board, savvy horticulture, natural checking, and preservation endeavours’ lawful and administrative parts of simulated intelligence and ML are likewise a subject of insightful request. Writing in this field looks at licensed innovation privileges, risk issues, information assurance regulations, and the moral and lawful obligations of artificial intelligence designers and clients. Research intends to lay out legitimate systems and rules to successfully administer artificial intelligence and ML advancements.

Determining the ability of artificial intelligence to establish authorship of artistic ukrainian texts using significant fragments

Artificial intelligence is becoming an integral part of everyday life and profes-sional activity of a person. Bing, as an intelligent search system, can serve as a tool for determining the authorship of artistic text in Ukrainian. Bing helps to uncover in-formation about a text fragment and its author, although the search results may be inaccurate or incomplete. This work aims to explore the effectiveness of determining the authorship of ar-tistic texts using modern artificial intelligence tools based on significant fragments of works. Ten Ukrainian authors with a rich body of artistic works, reflecting various as-pects of Ukrainian culture and history, were selected for the experiment. Random fragments up to 500 words in length were selected from various works of these au-thors. An experiment was conducted to determine the authorship of 360 fragments. Using the Python programming language and the skpy package, software was created that sends queries and receives responses from the Bing bot embedded in Microsoft Skype. The presence of the author’s name and the corresponding title of the work were checked in the response texts. This work introduces, for the first time, a method of verifying the authorship of Ukrainian-language text fragments using the Bing bot equipped with artificial intelli-gence. A comparative analysis was conducted and experiments were carried out to identify the authorship of significant long fragments. It was found that long fragments allow the author of the artistic Ukrainian text to be determined with high accuracy. Ivan Franko has the highest percentage of re-sponses where the author’s name and the title of the work were mentioned - 87%. The proposed hypothesis regarding the effectiveness of artificial intelligence in establishing authorship of works has not been confirmed. Artificial intelligence has slightly lower efficiency than expected, which indirectly exposes its means of opera-tion. Namely, when establishing authorship, a sequential research comparison of the proposed fragment with a bank of works that are widespread in the Internet environ-ment is not performed.

The Effect of Artificial Intelligence in Improving Student Learning Achievement in High School

Artificial Intelligence (AI) is a process to shape human thinking styles in order to design machines to be able to behave like humans or also called Cognitive Tasks, namely from programmed information data that makes machines able to do work like humans are doing automatically. The purpose of the study is to see how influential Artificial Intelligence is in improving student achievement, especially in high school. This problem utilizes a quantitative approach with a survey model and in-depth interviews. The research survey used by researchers is online-based using the Google Form Platform. The results of this study explain that Artificial Intelligence can assist teachers in creating students who excel in learning, especially at the high school level. The conclusion of the research on the Effect of Artificial Intelligence at the Senior High School level in Improving Student Learning Achievement is that with the help of this Artificial Intelligence Technology, it helps teachers in achieving student competence in the teaching and learning process and students can also improve achievement in the learning process. The limitation of this study is that researchers only conducted research on the influence of Artificial Intelligence in improving student achievement at the senior high school level, researchers hope that future researchers can conduct the same research but at a higher level.

The Effectiveness of Artificial Intelligence in Assisting Mothers with Assessing Infant Stool Consistency in a Breastfeeding Cohort Study in China.

Breastfeeding is widely recognized as the gold standard for infant nutrition, benefitting infants' gastrointestinal tracts. Stool analysis helps in understanding pediatric gastrointestinal health, but the effectiveness of automated fecal consistency evaluation by parents of breastfeeding infants has not been investigated. Photographs of one-month-old infants' feces on diapers were taken via a smartphone app and independently categorized by Artificial Intelligence (AI), parents, and researchers. The accuracy of the evaluations of the AI and the parents was assessed and compared. The factors contributing to assessment bias and app user characteristics were also explored. A total of 98 mother-infant pairs contributed 905 fecal images, 94.0% of which were identified as loose feces. AI and standard scores agreed in 95.8% of cases, demonstrating good agreement (intraclass correlation coefficient (ICC) = 0.782, Kendall's coefficient of concordance W (Kendall's W) = 0.840, Kendall's tau = 0.690), whereas only 66.9% of parental scores agreed with standard scores, demonstrating low agreement (ICC = 0.070, Kendall's W = 0.523, Kendall's tau = 0.058). The more often a mother had one or more of the following characteristics, unemployment, education level of junior college or below, cesarean section, and risk for postpartum depression (PPD), the more her appraisal tended to be inaccurate (p < 0.05). Each point increase in the Edinburgh Postnatal Depression Scale (EPDS) score increased the deviation by 0.023 points (p < 0.05), which was significant only in employed or cesarean section mothers (p < 0.05). An AI-based stool evaluation service has the potential to assist mothers in assessing infant stool consistency by providing an accurate, automated, and objective assessment, thereby helping to monitor and ensure the well-being of infants.

Impact of artificial intelligence on customer engagement and advertising engagement: A review and future research agenda

AbstractThis study, through a bibliometric analysis, aims to provide increased knowledge of the evolution and effects of artificial intelligence over the last 30 years in customer engagement and advertising engagement. Articles were gathered from three databases by using combinations of keywords (artificial intelligence, customer engagement, advertising engagement, marketing, machine learning, etc.). A set of inclusion/exclusion criteria were then applied to obtain the final sample. The final sample was made up of 190 peer‐reviewed articles. Three separate analyses were performed to test the sample. A performance analysis identified the articles' years of publication, contributions per country and the performance/output of the relevant journals. A data analysis created 10 clusters; these are examined in depth, and provide explanations of the evolution of the relevant scientific production. The study's findings offer a wide perspective of research undertaken to date, and identify possible research gaps. This research contributes to the marketing field by bridging a gap, through undertaking a bibliometric analysis, in the research about the impact of artificial intelligence on customer and advertising engagement over the years 1991 through 2022. It offers scholars and researchers ideas for future research.

The effectiveness of artificial intelligence (AI) on daily educational activities of undergraduates in a modern and diversified university environment

This study assessed the effectiveness of AI and AI-related technologies in the daily educational activities of undergraduate students in a modern and diversified university environment. The participants were 13 undergraduate Indonesian students participating in a mobility program for two weeks in Malaysia. A survey questionnaire designed with the help of the existing literature and ChatGPT, which includes ten (10) structured items and seven (7) open-ended questions, was used to collect the data. The relevant SPSS tests were used to analyze the data. Based on the results, of all 13 participants, 12 (92.3%) of them already experienced AI in their daily educational activities, and there were strong positive correlations between the attitudes toward AI and AI experiences, and attitudes toward AI and the effects of AI on education attributes, with correlation scores of .663 and .833 respectively. Based on the participant's answers to the qualitative questions, most of them believed that AI and AI technologies, such as ChatGPT, are helpful in daily educational activities and help them gain information regardless of time and space limitations and do their university-related assignments quickly. Based on the results, AI and AI-related technologies could transform different aspects of modern education.

Applying Artificial Intelligence to the Digital Marketing: Opportunities and Challenges for the Marketer

The present work aims to explore the role and factors that influence the interaction between marketing and artificial intelligence, the developing role of the marketer in the digital age, and the effects of artificial intelligence on the marketing process. Through a comprehensive marketing analysis, the research highlights the emerging power that Artificial Intelligence is exerting in all the marketing and production phases. The article is divided into three phases: the first phase focuses on the transition from traditional to digital marketing, emphasizing how new technologies had a significant impact on the commercial scene. The focus transitioned to the operational frame of AI into marketing operations, recognizing the latter’s ability to add value throughout the modern consumer’s conversion funnel. Following that, the inquiry yielded exciting ideas for possible future developments. Finally, the presentation provided a complete overview of the transition of marketing to digital and the function of artificial intelligence in this context.

The Effects of Artificial Intelligence on Service Delivery in South African Local Municipalities

The Effects of Artificial Intelligence on Service Delivery in South African Local Municipalities

AI for Identity and Access Management (IAM) in the Cloud: Exploring the Potential of Artificial Intelligence to Improve User Authentication, Authorization, and Access Control within Cloud-Based Systems

This comprehensive study explores the integration and effectiveness of Artificial Intelligence (AI) in Identity and Access Management (IAM) within cloud environments. It primarily focuses on how AI can enhance user authentication, authorization, and access control, addressing the challenges and possibilities in cloud computing. The study adopts a mixed-methods approach, employing both quantitative and qualitative analyses. A survey involving 582 cybersecurity experts provides insights into the current state and potential of AI in IAM, while multiple regression analysis examines the impact of various factors on system effectiveness. Four hypotheses are explored: the impact of hardware and software configurations on system accuracy (H1), the influence of computational environments on reliability (H2), the role of demographic factors in user acceptance (H3), and the effect of technological enhancements on system performance and acceptance (H4). Findings indicate significant correlations between these factors and the effectiveness of AI in IAM. Notably, hardware configurations and security concerns influence system accuracy; computational environment variations affect system reliability; demographic factors impact user acceptance; and enhancements such as user feedback, advancements in AI technology, continuous learning algorithms, and system transparency improve performance and acceptance. These insights underscore the need for advanced hardware, standardized software, user-centric design, and continuous improvement in AI technologies for effective IAM in cloud environments. The study provides actionable recommendations for cloud service providers and developers, emphasizing the importance of involving users in development processes, ensuring transparency, and adopting adaptive algorithms. Future research directions include longitudinal studies on the impact of technological advancements and exploring demographic-specific responses to AI-integrated IAM solutions.

Effects of design software program and manufacturing method on the marginal and internal adaptation of esthetic crowns for primary teeth: A microcomputed tomography evaluation

Statement of problemThe adaptation of digitally produced crowns is affected by the design software program and manufacturing method. The effect of artificial intelligence (AI) software program design on the adaptation of the crowns is unclear and comparative evaluations should be documented. PurposeThe purpose of this study was to assess the marginal and internal gaps, the absolute marginal discrepancies, and the 3-dimensional (3D) discrepancy volumes of the resin-based milled and 3D printed crowns for primary teeth designed with computer-aided design (CAD) and AI software programs by using microcomputed tomography (µCT). Material and methodsA total of 40 resin-based esthetic crowns were produced for a prepared typodont tooth (right mandibular primary second molar) according to the design software program (CAD and AI) and manufacturing method (milling and 3D printing) (n=10). Four experimental groups were generated as CAD-milled, CAD-3D printed, AI-milled, and AI-3D printed. The marginal, axial, and occlusal gap values, the absolute marginal discrepancies, and the 3D discrepancy volumes of the specimens were measured by using µCT. The data were analyzed by using 2-way ANOVA and the Tukey HSD tests (α=.05). ResultsThe lowest value for the marginal gap (54 ±43 µm) was observed in the CAD-milled group and the marginal gap value of the AI-3D printed group was significantly lower than the AI-milled group (P<.05). The lowest value for the axial gap (63 ±7 µm) was observed in the AI-3D printed group, and the highest value (145 ±58 µm) was observed in the CAD-milled group; the result for the occlusal gap value was opposite. The highest absolute marginal discrepancy value was observed in the CAD-milled group. The 3D discrepancy volumes increased in the order of the CAD-3D printed, AI-milled, CAD-milled, and AI-3D printed groups. ConclusionsThe marginal and internal gap values of the resin-based crowns were affected by the design software program and manufacturing method; however, tested groups showed clinically acceptable gap values.

The effect of artificial intelligence on economic growth

The effect of artificial intelligence on economic growth