Artificial Intelligence Knowledge Research Articles

Perceptions of the Impact of Artificial Intelligence among Internal Medicine Physicians as a Step in Social Responsibility Implementation: A Cross-Sectional Study.

Artificial Intelligence (AI) has emerged as an essential tool in healthcare for optimizing healthcare delivery and improving patient outcomes. This study is motivated by using AI in healthcare as a step for social responsibility implementation. The research aimed to investigate the attitudes of healthcare professionals on this issue, and it assessed physicians' opinions regarding their perceptions of AI and their intention to use and implement AI tools in their activity. An electronic survey was proposed during February-June 2024 to a sample of healthcare professionals (309 were admitted into the study, 62 males and 247 females, with a mean age of 42). The results of the survey highlighted both groups' excellent perceptions of AI and the low perceived knowledge of AI, which arises from more technical questions. The use of AI in healthcare represents a step for social responsibility implementation; it is an unstoppable process, and stakeholders should take into consideration investing more in monitoring and training activities.

Empowering Early Career Neurosurgeons in the Critical Appraisal of Artificial Intelligence and Machine Learning: The Design and Evaluation of a Pilot Course

Artificial intelligence (AI) is expected to play a greater role in neurosurgery. There is a need for neurosurgeons capable of critically appraising AI literature to evaluate its implementation or communicate information to patients. However, there are a lack of courses delivered at a level appropriate for individuals to develop such skills. We assessed the impact of a 2-day (non-credit bearing) online digital literacy course on the ability of individuals to critically appraise AI literature in neurosurgery. We performed a prospective, quasi-experimental non-randomized, controlled study with an intervention arm comprising individuals enrolled in our 2-day digital health literacy course and a waiting-list control arm used for comparison. We assessed participants' pre- and post-course knowledge, confidence, and course acceptability using Qualtrics surveys designed for the purpose of this study. A total of 62 individuals (33 participants, 29 waitlist controls), including neurosurgical trainees and both undergraduate and post-graduate students, attended the course and completed the pre-course survey. The 2 groups did not vary significantly in terms of age or demographics. Following the course, participants significantly improved in their knowledge of AI (mean difference=3.86, 95% CI=2.97-4.75, P-value < 0.0001) and confidence in critically appraising literature using AI (P-value=0.002). Similar differences in knowledge (mean difference=3.15, 95% CI=1.82-4.47, P-value < 0.0001) and confidence (P-value < 0.0001) were found when compared to the control group. Bespoke courses delivered at an appropriate level can improve clinicians' understanding of the application of AI in neurosurgery, without the need for in-depth technical knowledge or programming skills.

Co-creation in action: Bridging the knowledge gap in artificial intelligence among innovation champions

The increasing significance of artificial intelligence (AI) in various industries highlights the necessity for industry leaders and professionals to comprehend and gain knowledge about AI. The urgency for AI literacy is more critical than ever due to the potential unethical use of AI resulting from insufficient knowledge. This issue is particularly crucial for educators because they need to understand and adapt to the impact of AI within educational institutions, with some needing to use and become literate in AI, given that students now have increased access to public AI tools. This research presents a multi-phase study to address the issue of bridging the knowledge gap in AI by conducting co-creation with innovation champions, illustrated by a case of Generative AI innovation in a K-12 school. Using action design research, we engaged experienced teachers who are experts in pedagogical innovation to co-create a generative AI-enhanced platform at a leading K-12 education institution known for its pedagogical innovation in Australia. The findings reveal that champions enhance their knowledge through their subject-matter expertise, organizational knowledge, and AI knowledge gained through external exposure and experience. The study also highlights the key elements that facilitate a cross-domain knowledge exchange platform, enabling champions to be exposed to and experience AI technological learning, leading to shifts in their understanding and perception of AI. The initially unaware and sceptical champions become more aware and capable of articulating more technical AI knowledge rooted in a shared value. This research demonstrates how co-creation serves as a pathway for learning AI, particularly among K-12 teachers who are innovation champions. It underscores the impact of experiential and organizational learning on AI collaborative learning and behavioral intentions. Additionally, the study presents that aligning organizational and personal visions and values can influence perceptions about AI technologies, enhancing the discourse on AI and education innovation.

Employees’ foe or friend: artificial intelligence and employee outcomes

ABSTRACT Using the componential theory of creativity and self-determination perspective, this study tests the effect of employees’ knowledge of artificial intelligence on their creativity and turnover intentions. We specifically investigate the mediating effects of self-enhancement motives and the moderating role of responsible leadership. Using a multi-wave research design, this study investigates these relationships with data from hospitality sector organizations across two distinct studies (Study 1, n = 241; Study 2, n = 279). We found that employees’ knowledge of artificial intelligence is positively related to employee creativity and negatively affects the turnover intentions directly and via self-enhancement motives. We also found support for the moderating impacts of responsible leadership. This study deepens our insight into artificial intelligence and its influence on hospitality employees and suggests important implications for researchers and practitioners.

Study on the Effectiveness of English Teaching in Universities Based on 5G Mobile Internet

Higher education is becoming increasingly competitive and all educational institutions are concentrating on improving quality and changing traditional higher education teaching methods. New-type classroom instruction has embraced a unique advancement opportunity with the arrival of the fifth generation (5G) era. It is critical to develop a teaching assistance system that makes use of high-speed network methodology and new-type display methodology. For the innovation and reform of higher education, this article combines soft computing techniques, artificial intelligence (AI), and 5G networks. This paper outlines the exact processes and measures for incorporating “5G” technology into higher education. Finally, conduct a comparative experiment to see how good the system is at learning AI knowledge when compared to standard learning methods. The outcomes of the experiments are examined to show that employing this approach to gain AI knowledge is successful and improves students' enthusiasm in learning as well as their hands-on abilities.

KNOWLEDGE, ATTITUDE, AND PRACTICE REGARDING ARTIFICIAL INTELLIGENCE (AI) AND ITS USAGE IN DENTAL ACADEMICS CURRICULUM AMONG DENTAL UNDERGRADUATES AND POSTGRADUATES

Background: Artificial intelligence (AI) is increasingly being recognized for its potential to revolutionize dental education and practice. However, the extent of knowledge, attitudes, and practices (KAP) regarding AI among dental undergraduates and postgraduates remains underexplored. Objectives: This study aims to assess the knowledge, attitudes, and practices related to AI and its integration into the dental academic curriculum among dental undergraduates and postgraduates. Methods: A cross-sectional questionnaire-based study was conducted among 545 participants, including final-year dental undergraduates and postgraduate dental students . The structured questionnaire covered demographics, knowledge of AI, attitudes towards its integration into dental education, and current practices involving AI. Results: The study found significant variations in knowledge levels, with postgraduates demonstrating a more comprehensive understanding of AI applications in dentistry compared to undergraduates. Attitudes towards AI were generally positive across both groups, with participants recognizing its potential to enhance diagnostic accuracy and streamline administrative tasks. However, there were concerns about the reliability of AI systems and the potential for reduced human oversight. Practical application of AI was limited, particularly among undergraduates, highlighting a gap between theoretical knowledge and practical use. Conclusion: The study underscores the need for integrating comprehensive AI education into the dental curriculum, encompassing both theoretical knowledge and practical training. Continuous professional development and a balanced approach to AI use in dental practice are essential to prepare future dental professionals for an AI-driven healthcare landscape. Gender-wise, the survey reveals consistent support across male and female dental professionals for AI's potential in enhancing dental research, with minimal variation in beliefs. KEYWORDS: Artificial intelligence, dental education, knowledge, attitudes, practices, dental undergraduates, postgraduates.

Exploring teachers' artificial intelligence awareness

The impact of artificial intelligence (AI) technological advancements is reshaping various aspects of our daily lives, including education. Integrating AI in education offers advantages such as personalized learning and operational efficiency. However, educators need to be aware of AI's implications in education. Teachers must enhance their awareness and knowledge levels to adapt to the educational environment where AI technologies are becoming increasingly prevalent. Therefore, this research aims to assess teachers' AI awareness levels and investigate whether AI awareness varies based on age, graduation status, and years of experience. This study used data collected from 147 educators using the Teachers' Artificial Intelligence Awareness Scale. The results indicated that teachers' AI awareness was at a moderate level. Additionally, the study examined teachers' AI awareness across different variables. Independent sample t-tests and one-way ANOVA analyses determined teachers' AI awareness variation based on age. The research findings suggest that younger educators and those with higher academic qualifications have more excellent practical knowledge of AI. The study's limitations included a relatively small sample size and the assumption of accurate participant responses. Despite these limitations, understanding teachers' AI awareness levels is a foundation for developing educational programs related to AI. By understanding teachers' perceptions and knowledge of AI, tailored interventions and training initiatives can enhance educators' proficiency in effectively utilizing AI technologies within educational settings.

Knowledge and attitudes toward artificial intelligence in nursing among various categories of professionals in China: a cross-sectional study.

The application of artificial intelligence (AI) in healthcare is an important public health issue. However, few studies have investigated the perceptions and attitudes of healthcare professionals toward its applications in nursing. This study aimed to explore the knowledge, attitudes, and concerns of healthcare professionals, AI-related professionals, and others in China toward AI in nursing. We conducted an online cross-sectional study on nursing students, nurses, other healthcare professionals, AI-related professionals, and others in China between March and April 2024. They were invited to complete a questionnaire containing 21 questions with four sections. The survey followed the principle of voluntary participation and was conducted anonymously. The participants could withdraw from the survey at any time during the study. This study obtained 1,243 valid questionnaires. The participants came from 25 provinces and municipalities in seven regions of China. Regarding knowledge of AI in nursing, 57% of the participants knew only a little about AI, 4.7% did not know anything about AI, 64.7% knew only a little about AI in nursing, and 13.4% did not know anything about AI in nursing. For attitudes toward AI in nursing, participants were positive about AI in nursing, with more than 50% agreeing and strongly agreeing with each question on attitudes toward AI in nursing. Differences in the numbers of participants with various categories of professionals regarding knowledge and attitudes toward AI in nursing were statistically significant (p < 0.05). Regarding concerns and ethical issues about AI in nursing, every participant expressed concerns about AI in nursing, and 95.7% of participants believed that it is necessary to strengthen medical ethics toward AI in nursing. Nursing students and healthcare professionals lacked knowledge about AI or its application in nursing, but they had a positive attitude toward AI. It is necessary to strengthen medical ethics toward AI in nursing. The study's findings could help develop new strategies benefiting healthcare.

A questionnaire study regarding knowledge, attitude and usage of artificial intelligence and machine learning by the orthodontic fraternity of Northern India

AimThe aim of the questionnaire study was to determine the knowledge, attitude, and perception of orthodontists regarding the role of artificial intelligence in dentistry in general and orthodontics specifically, and to determine the use of artificial intelligence by the orthodontist. MethodsThis cross-sectional study was done among the orthodontists of Northern India (clinicians, academicians, and postgraduates) through a web-based electronic survey using Google Forms. The study was designed to obtain information about AI and its basic usage in daily life, in dentistry, and in orthodontics from the participants. The options given were set specifically according to the Likert scale to maintain the correct format. The questionnaire was validated by one AI expert and one orthodontic expert, followed by pretesting in a smaller group of 25 orthodontists 2 weeks before circulation. A total of 100 orthodontists and postgraduate students responded to the pretested online questionnaire link for 31 questions in four sections sent via social media websites in a period of 3 months. ResultsThe majority of the participants believe that AI could be useful in diagnosis and treatment planning and could revolutionize dentistry in general. 84 % of the orthodontic academicians and clinicians, including PG students, consider AI a useful tool for boosting performance and delivering quality care in orthodontics, and 72 % see AI as a partner rather than a competitor in the foreseeable future of dentistry. 90 % of the participants believe that the incorporation of AI into CBCT analysis can be a valuable addition to diagnosis and treatment planning. 86 % of total participants agree that AI can be helpful in decision-making for orthognathic surgery, and 84 % find AI useful for bone age assessment. ConclusionsIt was observed that academicians are more aware of AI terminologies and usage as compared to PG students and clinicians. There is a consensus that AI is a useful tool for diagnosis and treatment planning, boosting performance and quality care in orthodontics. In spite of these facts, 62.5 % of clinicians and 40 % of PG students are still not using AI for cephalometric analysis (p = 0.033).

Knowledge and acceptance of artificial intelligence and its applications among the physicians working in military medical centers affiliated with Aja University: A cross-sectional study.

The use of artificial intelligence (AI) in medical sciences promises many benefits. Applying the benefits of this science in developing countries is still in the development stage. This important point depends considerably on the knowledge and acceptance levels of physicians. This study was a cross-sectional descriptive-analytical study that was conducted on 169 medical doctors using a purposive sampling method. To collect data, questionnaires were used to obtain demographic characteristics, a questionnaire to investigate the knowledge of AI and its applications, and an acceptability questionnaire to investigate AI. For data analysis, SPSS (Statistical Package for the Social Sciences) version 22 and appropriate descriptive and inferential statistical tests were used, and a significance level of < 0.05 was considered. Most of the participants (102) were male (60.4%), married (144) (85.20%), had specialized doctorate education (97) (57.4%), and had average work experience of 10.78 ± 6.67 years. The mean and standard deviation of knowledge about AI were 9.54 ± 3.04, and acceptability was 81.64 ± 13.83. Multiple linear regressions showed that work history (P = 0.017) and history of participation in AI training courses (P = 0.007) are effective in knowledge and acceptability of AI. The knowledge and acceptability of the use of AI among the studied physicians were at an average level. However, due to the importance of using AI in medical sciences and the inevitable use of this technology in the near future, especially in medical sciences in crisis, war, and military conditions, it is necessary for the policymakers of the health system to improve the knowledge and methods of working with this technology in the medical staff in addition to providing the infrastructure.

Orthopaedic surgeons display a positive outlook towards artificial intelligence: A survey among members of the AGA Society for Arthroscopy and Joint Surgery.

The purpose of this study was to evaluate the perspective of orthopaedic surgeons on the impact of artificial intelligence (AI) and to evaluate the influence of experience, workplace setting and familiarity with digital solutions on views on AI. Orthopaedic surgeons of the AGA Society for Arthroscopy and Joint Surgery were invited to participate in an online, cross-sectional survey designed to gather information on professional background, subjective AI knowledge, opinion on the future impact of AI, openness towards different applications of AI, and perceived advantages and disadvantages of AI. Subgroup analyses were performed to examine the influence of experience, workplace setting and openness towards digital solutions on perspectives towards AI. Overall, 360 orthopaedic surgeons participated. The majority indicated average (43.6%) or rudimentary (38.1%) AI knowledge. Most (54.5%) expected AI to substantially influence orthopaedics within 5-10 years, predominantly as a complementary tool (91.1%). Preoperative planning (83.8%) was identified as the most likely clinical use case. A lack of consensus was observed regarding acceptable error levels. Time savings in preoperative planning (62.5%) and improved documentation (81%) were identified as notable advantages while declining skills of the next generation (64.5%) were rated as the most substantial drawback. There were significant differences in subjective AI knowledge depending on participants' experience (p = 0.021) and familiarity with digital solutions (p < 0.001), acceptable error levels depending on workplace setting (p = 0.004), and prediction of AI impact depending on familiarity with digital solutions (p < 0.001). The majority of orthopaedic surgeons in this survey anticipated a notable positive impact of AI on their field, primarily as an assistive technology. A lack of consensus on acceptable error levels of AI and concerns about declining skills among future surgeons were observed. Level IV, cross-sectional study.

Assessing Public Knowledge and Acceptance of Using Artificial Intelligence Doctors as a Partial Alternative to Human Doctors in Saudi Arabia: A Cross-Sectional Study.

Objective To assess the public acceptance of using artificial intelligence (AI) doctors to diagnose and treat patients as a partial alternative to human physicians in Saudi Arabia. Methodology An observational cross-sectional study was conducted from January to March 2024. A link to an online questionnaire was distributed through social media applications to citizens and residents aged 18 years and older across various regions in Saudi Arabia. The sample size was calculated using the Raosoft online survey size calculator, which estimated that the minimum sample size should be 385. Results Of the 386 participants surveyed, 85.8% reported being aware of AI, and 47.9% reported having some knowledge about different AI fields in daily life. However, almost one-third (32.9%) reported a lack of knowledge about the use of AI in healthcare. In terms of acceptance, 52.3% of respondents indicated they felt comfortable with the use of AI tools as partial alternatives to human doctors, and 30.8% believed AI is useful in the field of health. The most common concern (63.7%) about the use of AI tools accessible to patients was the difficulty of describing symptoms using these tools. Conclusion The findings of this study provide valuable insights into the public's knowledge and acceptance of AI in medicine within the Saudi Arabian context. Overall, this study underscores the importance of proactively addressing the public's concerns and knowledge gaps regarding AI in healthcare. By fostering greater understanding and acceptance, healthcare stakeholders can better harness the potential of AI to improve patient outcomes and enhance the efficiency of medical services in Saudi Arabia.

Knowledge and Awareness of Emotional Artificial Intelligence as Tool in Child’s Oral Health Care Assessed Among Dental Professionals of Eastern India. A Cross Sectional Study

ABSTRACT Background: One of the most crucial steps in providing the child’s oral health care and treatment needs is modifying his/her behavior, mood and emotion in any primary care/dental home or any speciality centre. This is very important parameters for any dental professionals and paediatric dentist. Through this study we investigated the knowledge, awareness of Emotional Artificial Intelligence (AI) as tool for modifying their behaviour prior to any treatment requirement. Materials and Methods: The study was conducted among dental professionals of located in different regions of eastern India. We used a consecutive sampling method to collect our sample. Results: Out of the 120 participating dental professionals, 30% professionals believed that emotional AI could monitor a child’s acceptance to treatment. Despite a low perception level of emotional AI by the dentist, 71% agreed on the beneficial effect of Emotional Artificial Intelligence (AI) in an emergency or uncooperative child if such technology exist. Conclusion: Regression model showed that certain key influencers can increase the quality of healthcare by 3 times which could favors Emotional Artificial Intelligence as an adjunct to Pediatric dentists in managing children.

Doctors' perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore.

The increased utilization of Artificial intelligence (AI) in healthcare changes practice and introduces ethical implications for AI adoption in medicine. We assess medical doctors' ethical stance in situations that arise in adopting an AI-enabled Clinical Decision Support System (AI-CDSS) for antibiotic prescribing decision support in a healthcare institution in Singapore. We conducted in-depth interviews with 30 doctors of varying medical specialties and designations between October 2022 and January 2023. Our interview guide was anchored on the four pillars of medical ethics. We used clinical vignettes with the following hypothetical scenarios: (1) Using an antibiotic AI-enabled CDSS's recommendations for a tourist, (2) Uncertainty about the AI-CDSS's recommendation of a narrow-spectrum antibiotic vs. concerns about antimicrobial resistance, (3) Patient refusing the "best treatment" recommended by the AI-CDSS, (4) Data breach. More than half of the participants only realized that the AI-enabled CDSS could have misrepresented non-local populations after being probed to think about the AI-CDSS's data source. Regarding prescribing a broad- or narrow-spectrum antibiotic, most participants preferred to exercise their clinical judgment over the AI-enabled CDSS's recommendations in their patients' best interest. Two-thirds of participants prioritized beneficence over patient autonomy by convincing patients who refused the best practice treatment to accept it. Many were unaware of the implications of data breaches. The current position on the legal liability concerning the use of AI-enabled CDSS is unclear in relation to doctors, hospitals and CDSS providers. Having a comprehensive ethical legal and regulatory framework, perceived organizational support, and adequate knowledge of AI and ethics are essential for successfully implementing AI in healthcare.

Artificial Intelligence (AI) in Early Childhood Education, Exploring Challenges, Opportunities and Future Directions: A Scoping Review

AI literacy has emerged as a crucial aspect of digital literacy research in the field of education. Currently, there are limited studies about the implications of Artificial Intelligence (AI) in Early Childhood Education (ECE). Owing to the recent development of curricula for young learners in industrialized nations, developing countries are hesitant to adopt AI at the ECE level. A scoping review was undertaken on the content of fourteen research articles published between 2016 and 2023. This scoping review evaluates and reviews the contents of fourteen papers on the knowledge and comprehension of AI in ECE, which covers curriculum design, artificial intelligence tools, instructional methodologies, research designs, evaluation methods, findings, and various types of possibilities and problems linked to AI literacy and content. Several obstacles were identified, including (1) an insufficiently designed curriculum, (2) lacking instructors' understanding, experience, and trust in AI, and (3) the lack of an instruction manual. Engaging in reading can offer educational possibilities and foster the growth of AI literacy in young learners, encompassing AI concepts, actions, and perspectives. This study recommended AI literacy for the educators and learners of ECE to be suitable for their age group and level.

Review of didactic methodologies at the academic level in the context of BIM

The article addresses the issue of BIM education at the academic level in Poland and provides an overview of modern methodologies for teaching BIM-related subjects. With the reports of neuroscience and the development of modern technologies, there is a need to take a new direction in student-oriented academic education, in which the main goal will be to prepare graduates for life, work and meet the challenges of a rapidly changing reality. It is necessary to introduce new forms and techniques of education focusing on the concept of deep learning and based on the latest knowledge in neuroscience, cognitive psychology, pedagogy and artificial intelligence. Authentic teaching creativity on the part of the teacher can only come from full awareness of the numerous strategies available and making a thoughtful choice among them of reliable knowledge of their impact on students

Validierung eines Tests zur Erfassung des Grundlagenwissens zu Künstlicher Intelligenz von angehenden Lehrkräften im berufsbildenden Bereich

Artificial intelligence (AI) is becoming increasingly important for numerous areas of life and work and is considered to be a "driver of digitalisation" in the second wave of digital transformation. Vocational education and training is directly affected by this dynamic development, given the AI-related changes to job profiles and the resulting skills requirements for (future) skilled workers. Responsibility for organising the qualification processes lies with the teaching staff, whose professional training so far lacks AI content. It can be assumed that this group has little prior knowledge of AI. In order to generate reliable findings on the extent of the AI knowledge of (prospective) teachers and to establish appropriate training and further education programmes based on this, test instruments are required that can be used to validly measure knowledge. For newly developed instruments, comprehensive analyses based on the "Standards for Educational and Psychological Testing" of American Educational Research Association (AERA) et al. (2014) are required to ensure validity. The article discusses the analyses regarding the assessment of the aspects "test content" and "relation to other characteristics". Based on the findings, the theoretically postulated assumptions regarding the AI knowledge of (prospective) teachers can be substantiated with empirical evidence.

Optimizing Stock Market Forecasts: The Role of AI and Hybrid Models in Predictive Analytics

Forecasting stock market movements is a challenging and significant task for both researchers and investors. Stock market movements are affected by local and global economic factors, as well as political developments. This field of research requires substantial knowledge of finance, statistics, and Artificial Intelligence to achieve reliable results. To understand stock market movements, we must interpret a significant amount of information from non-linear, volatile, and non-parametric raw data. To reduce the complexity of stock market forecasting, we need to extract key features from this raw data. To simplify the task of stock market forecasting for researchers and traders, we conducted a study on the Indian stock market and present a comprehensive summary report. This report includes an analysis of 50 research articles related to the Indian stock market, along with some highly cited articles pertaining to other international markets.

Threat or prospect? Exploring the impact of digital entrepreneurs’ artificial intelligence perception and intention to adopt blockchain technology on the achievement of SDGs

This paper explores how digital entrepreneurs' intention toward blockchain technology adoption, perception of reduced costs, and knowledge of Artificial Intelligence impact achieving UN's Sustainable Development Goals (SDGs), drawing attention from various sectors. Present study applies explanatory sequential mixed method for data collection. Moreover, to work with the dual face patterned data, PLS-SEM is used to perform quantitative analysis of the data collected from 389 digital entrepreneurs who are chosen through purposive sampling and then content analysis is performed for the qualitative data according to the explanatory sequential mixed method's rule of thumb. The study's quantitative phase shows that factors such as perceived ease of use and usefulness of Industry 4.0 technologies, knowledge of artificial intelligence (KAI), and perception of reduced cost positively influence digital entrepreneurs' intention to adopt blockchain technology (BCT). Notably, KAI has the strongest impact. In the qualitative phase, it's found that digital entrepreneurs' KAI and willingness to adopt BCT strongly align with achieving several UN Sustainable Development Goals (SDGs), suggesting BCT adoption's potential for sustainable outcomes. The outcomes of this study set a new benchmark in the domain of SDGs achievement with careful integration to Industry 4.0, AI and BCT. This study results undoubtedly instigate the digital entrepreneurs to adopt BCT in doing their start-up and convince the policymakers to set regulatory landscape with convenient environment for the utilization of BCT which then ultimately accelerates the achievement of SDGs.

A Study on the Knowledge and Perception of Artificial Intelligence

A Study on the Knowledge and Perception of Artificial Intelligence