Belief, History and Machines: How Religious Traditions Shape Students’ Attitudes Toward Artificial Intelligence

Artificial intelligence (AI) is increasingly applied in clinical diagnostics, particularly in radiology, where it can assist with imaging triaging and anomaly detection. However, the integration of AI into medical education remains under researched. This study investigates the impact of an AI-focused panel discussion on medical students' perceptions, knowledge, attitudes and concerns about AI in radiology. A paired pre-post design questionnaire comprising of 13 five-point Likert scale questions was administered to 40 medical students to complete before and after an AI-focused educational panel session at the International Radiology Undergraduate Symposium in London, United Kingdom on 24th November 2024. The questionnaire assessed four domains: 'Understanding of AI,' 'Attitudes Toward AI in Radiology,' 'AI Education in Medical School,' and 'Concerns About AI in the Future.' The primary outcome was to assess the change in students' perceptions of AI's role in radiology. Differences between pre- and post-session responses were analysed using the Wilcoxon signed-rank test. The Hodges-Lehmann median difference, the effect size, r, and their corresponding 95% confidence intervals were calculated, and p-values were adjusted using the Holm-Bonferroni method. Of the 81 eligible attendees, 40 (49.4%) completed the questionnaire (39 pre-session, 40 post-session). Students demonstrated significant improvements in their understanding of AI's potential role in radiology (Z = 3.04, p = 0.002; Holm-Bonferroni = 0.029; median paired difference = 0.5, 95% CI 0.0-0.5; r = 0.49, 95% CI 0.25-0.68) and in their awareness of AI's broader clinical applications (Z = 3.65, p < 0.001; Holm-Bonferroni = 0.0035; median paired difference = 0.5, 95% CI 0.5-1.0; r = 0.60, 95% CI 0.38-0.75). Participants expressed a more positive view of AI in healthcare overall, although concerns about AI replacing radiologists and insufficient AI education persisted. Educational interventions have the potential to improve medical students' understanding and attitudes toward AI in radiology. Integrating structured AI education into undergraduate curricula may enhance AI literacy and better prepare future clinicians for an AI-enabled healthcare environment.

Since the pandemic, the study purposed to derive improvements of the educational program through pilot operation for youth in Korea before local application to disseminate artificial intelligence smart poultry farm in Tanzania. For this purpose, we developed an artificial intelligence smart poultry farm appropriate technology camp program, and 49 high school students participated in this pilot study for two days. After the pilot operation, a questionnaire was conducted to measure students' perception and experience of artificial intelligence through this appropriate technology camp. The questionnaire consisted of 22 questions measuring the perception of artificial intelligence by the Likert scale and 1 question describing the participation experience. Students' perception of artificial intelligence was primarily composed of three areas: value perception (6 questions), efficacy (4 questions), and risk perception (12 questions). As a result, students' value perception (M=4.30, SD=.491) and efficacy (M=4.42, SD=.487) to artificial intelligence were high. However, the risk perception (M=3.42, SD=1.023) was relatively low. In addition, through this appropriate technology camp, students' motivation to learn artificial intelligence improved, their interest in careers and jobs related to artificial intelligence increased, and they had a negative perception and a positive impact on society due to artificial intelligence.

BackgroundThe growing use of artificial intelligence (AI) in healthcare necessitates understanding the perspectives of future practitioners. This study investigated the perceptions of German-speaking medical and dental students regarding the role of artificial intelligence (AI) in their future practices.MethodsA 28-item survey adapted from the AI in Healthcare Education Questionnaire (AIHEQ) and the Medical Student’s Attitude Toward AI in Medicine (MSATAIM) scale was administered to students in Austria, Germany, and Switzerland from April to July 2023. Participants were recruited through targeted advertisements on Facebook and Instagram and were required to be proficient in German and enrolled in medical or dental programs. The data analysis included descriptive statistics, correlations, t tests, and thematic analysis of the open-ended responses.ResultsOf the 409 valid responses (mean age = 23.13 years), only 18.2% of the participants reported receiving formal training in AI. Significant positive correlations were found between self-reported tech-savviness and AI familiarity (r = 0.67) and between confidence in finding reliable AI information and positive attitudes toward AI (r = 0.72). While no significant difference in AI familiarity was found between medical and dental students, dental students exhibited slightly more positive attitudes toward the integration of AI into their future practices.ConclusionThis study underscores the need for comprehensive AI education in medical and dental curricula to address knowledge gaps and prepare future healthcare professionals for the ethical and effective integration of AI in practice.

Artificial intelligence (AI) has alarmed the society of Taiwan believing it is responsible for potential surveillance, data theft and abuse, and other privacy infringements. By adopting the theory of motivated reasoning, this study explores how Taiwanese people’s perceptions of AI are affected by their institutional trust, attitudes toward the government and corporations, which are the two most common sponsors of scientific development. First, findings establish that respondents’ science trust in AI is made up of perceptions of AI and its science community, and they have lower faith in the AI science community than in AI alone. Second, the perceptions of both AI and its science community are positively associated with trust in government and corporations. Third, scientific news has a direct bearing on AI trust, but not on either government or corporation trust. By contrast, political news has no effect on either trust in AI or its science community, yet trust in government and corporations mediates the influence of political news on trust in AI and its science community. Finally, demographic variables hardly predict trust in AI, AI science community, government, and corporations, but education and gender are directly related to news consumption, which further influences institutional and science trust.

A Review of: Subaveerapandiyan, A., Sunanthini, C., &amp; Amees, M. (2023). A study on the knowledge and perception of artificial intelligence. IFLA Journal, 49(3), 503–513. https://doi.org/10.1177/03400352231180230 Objective – To assess the knowledge, perception, and skills of library and information science (LIS) professionals related to artificial intelligence (AI). Design – 45 statements were distributed to 469 LIS professionals via Google Forms to collect primary data. 245 participants responded to the structured questionnaire. Setting – University and college libraries in Zambia. Subjects – Zambian library and information science professionals.Methods – A descriptive approach was employed for the study. Data was gathered via a questionnaire. “The objective was to assess the statistical relationship between the knowledge, perception, and skills of LIS professionals (the independent variables) and AI (the dependent variable)” (Subaveerapandiyan et al., p. 506). The survey used a 5-point Likert scale with (1) strongly disagree being the lowest score and (5) strongly agree the highest. Means and standard deviations are included in data display tables. Thematic analysis was employed to analyze the data. SPSS was used for data analysis.Main Results – Survey results are presented in three tables. Table 1, “Awareness of AI among LIS professionals,” contains 21 statements related to AI use in various library environments and services, including reference (finding articles and citations, content summarization, detecting misinformation), circulation of library materials, security and surveillance, character recognition and document preservation, research data management, language translation, and others. The authors note that 44.1 percent of the respondents agreed that “AI is essential for the effectiveness and efficiency of library service delivery, enabling libraries to enhance and offer dynamic services for their users” (Subaveerapandiyan et al., 2023, p. 506). Table 2, “Perception of AI among LIS professionals,” contains 10 statements. Over 85 percent of respondents either strongly agreed or agreed that AI “makes library staff lazy” while 58.1 percent either strongly agreed or agreed that AI is a “threat to librarians’ employment” (Subaveerapandiyan et al., 2023, p. 506). The authors note that the “respondents also indicated barriers to the adoption of AI in libraries, such as the lack of LIS professionals’ skills and budgetary constraints” (Subaveerapandiyan et al., 2023, p. 506). Table 3 lists 13 competencies required by library professionals in the AI era. The majority of the respondents (an average of 65 percent) were in strong agreement that “electronic communication, hardware and software, Internet applications, computing and networking, cyber security and network management, data quality control, data curation, database management … are necessary competencies required by LIS professionals for them to be proficient in AI” (Subaveerapandiyan et al., 2023, p. 506).

Generative artificial intelligence (AI) is rapidly gaining popularity across health care, education, and society. The purpose of this study was to assess perceptions and use of generative AI in academic physical therapy (PT). Generative AI became one of the fastest-growing technologies ever after the public release of ChatGPT in November 2022. Early data indicate that attitudes toward generative AI in higher education are mixed and rapidly evolving, with significant ethical concerns around use and potential misuse. There are no published studies investigating perceptions and use of generative AI in PT education. A total of 175 surveys were completed and analyzed. Respondents included PT educators, administrators, and students. An anonymous, online survey on use and perception of AI was distributed through email and social media. Descriptive statistics and cross-tabulations were performed to analyze respondent characteristics and responses to survey questions. Most respondents (61.1%) reported they did not use generative AI during the 2022-2023 academic year, whereas 35.4% were generative AI users. More than 40% of respondents were optimistic or very optimistic toward generative AI. Users of AI were more likely to report an optimistic or very optimistic disposition toward AI compared with nonusers. AI users were more likely to agree or completely agree that generative AI has more benefits than drawbacks compared with nonusers. Results of this survey suggest that, despite the rapid uptake of generative AI in society, many PT educators and students harbor reservations and uncertainties toward its use. Artificial intelligence users were less likely to hold negative perceptions toward it and were more likely to find it useful. Understanding use and perceptions of generative AI in PT education may inform strategies to promote innovation, policy-making, and ethical integration of this new and rapidly evolving technology.

Introduction: As artificial intelligence (AI) becomes increasingly integrated into various professional fields, understanding its impact on pharmacy education is crucial. This study explores pharmacists' perceptions of AI's role in enhancing educational and professional practices, particularly focusing on the generation of educational content and analytical tasks. Objectives: The primary objective was to assess pharmacists' concerns and perceived benefits regarding the use of AI in pharmacy education, examining variations across different age groups and years of practice. Methods: A cross-sectional survey was completed by 446 pharmacists who actively precept pharmacy residents and students. Respondents practiced across 35 states with over half (53.4%) being in Ohio. The survey included items on concerns about AI's quality and accuracy, human interaction, plagiarism, and its potential benefits in data analysis and research literature summarization. Responses were analyzed to identify trends across demographic categories, including age and years in practice. Results: Of the respondents, 67.9% expressed concerns about the quality and accuracy of AI-generated content, while 50.9% were concerned about plagiarism. Younger pharmacists (73.8% of those aged 20-29) showed heightened concern about accuracy compared to older groups (56.8% of those aged 60+). In contrast, 57.8% of respondents recognized AI's potential benefits for data analysis, with experienced pharmacists (>20 years in practice) being more likely to see these advantages (62.2%). Conclusion: The findings indicate a need for targeted educational strategies to address AI literacy and ethical use in pharmacy education. Integrating AI tools that support educational objectives while addressing these concerns could enhance the efficacy and acceptance of AI in pharmacy practice. Further research should explore the development of training programs that align with the evolving expectations and technological competencies of different pharmacist demographics.

ObjetivoLa IA y el análisis de big data pueden potenciar aún más las características automatizadas e inteligentes de los servicios de turismo y hostelería. Sin embargo, también plantea nuevos retos a la gestión de los recursos humanos. Este estudio pretende explorar los efectos directos e indirectos de la percepción de la IA por parte de los empleados sobre la resiliencia profesional y el aprendizaje informal, así como el efecto mediador de la resiliencia profesional.Diseño/metodología/enfoqueEn este trabajo se propone un modelo teórico de percepción de la IA, resiliencia profesional y aprendizaje informal con la IA percibida como variable antecedente, la resiliencia profesional como variable mediadora y el aprendizaje informal como variable endógena. Dirigidos a los empleados que trabajan con IA, se recogieron un total de 472 datos válidos. Los datos se analizaron mediante un modelo de ecuaciones estructurales (SEM) con el software AMOS.ResultadosLos Resultados indicaron que la percepción de la IA por parte de los empleados contribuye positivamente a la resiliencia profesional y al aprendizaje informal. Aparte del efecto directo sobre el aprendizaje informal, la resiliencia profesional también media en la relación entre la percepción de la IA y el aprendizaje informal.Originalidad/valorLos Resultados de la investigación proporcionan implicaciones tanto teóricas como prácticas al revelar el impacto de la percepción de la IA en el desarrollo profesional de los empleados, las actividades de aprendizaje, explicar cómo la IA transforma la naturaleza del trabajo y el desarrollo profesional, y arrojar luz sobre la gestión de los recursos humanos en el ámbito del turismo y la hostelería.

This research was intended to explain how attitudes towards artificial intelligence effects innovative work behaviors and the intention to leave and whether the organizational culture plays a mediating role in these relationships. The number of participants participating in the research was 402. The research was conducted in İstanbul. It is seen that the general attitude score towards artificial intelligence has a significant and positive effect on both innovative work behavior and intention to leave. These findings reveal that employees’ perception of artificial intelligence as a supportive and beneficial element increases innovative behaviors, but risk perception increases the tendency to leave. Mediation analyses show that positive AI attitudes create indirect effects on decreasing intention to leave, especially through the dimensions of adaptability and consistency. The fact that all indirect effects are significant at the 95% confidence level clearly demonstrates that organizational culture plays an important mediating role in the effect of attitudes towards AI on employee behavior. In this context, not only individual perceptions but also the provision of a flexible and consistent cultural environment that inspires confidence in employees in technological transformation processes stand out as a strategic necessity.

This exploratory study (N = 310) investigates the relationship between students’ attitudes toward artificial intelligence (AI), their attitudes toward AI ethics, and their media and digital literacy levels. This study’s specific objectives were to examine students’ (a) general attitudes toward AI, (b) attitudes toward AI ethics, (c) the relationship between the two, and (d) whether attitudes toward AI are associated with media and digital literacy. Participants, drawn from a convenience sample of university students, completed an online survey including four scales: (a) a general attitude toward AI scale (including two subscales, positive and negative attitudes), (b) an attitude toward AI ethics scale (including two subscales, attitudes toward accountable and non-accountable AI use), (c) a media literacy scale, and (d) a digital literacy scale, alongside demographic information. The findings revealed that students held moderate positive attitudes toward AI and strong attitudes favoring accountable AI use. Interestingly, media literacy was positively related to accountable AI use and negatively to positive attitudes toward AI, whereas digital literacy was positively related to positive attitudes, and negatively to negative attitudes toward AI. These findings carry significant theoretical implications by highlighting the unique relationship of distinct literacies (digital and media) with students’ attitudes. They also offer practical insights for educators, technology designers, and administrators, emphasizing the need to address ethical considerations in AI deployment.

The study aimed to assess teachers' perceptions of artificial intelligence (AI), their understanding of its potential advantages and disadvantages, and the specific training needs necessary for successful AI integration. The study aimed to assess teachers' perceptions of artificial intelligence (AI), their understanding of its potential advantages and disadvantages, and the specific training needs necessary for successful AI integration. A mixed-method research design was used in collecting and analyzing quantitative and qualitative data. Descriptive statistics was utilized to delineate teachers' perspectives on AI in education. Open-ended questions were employed to gather insights into the challenges teachers encounter when using AI in the classroom. The findings revealed that teachers' experiences with AI present opportunities and challenges in integrating technology into the classroom. While teachers expressed optimism about AI's potential to enhance education, citing benefits such as personalized learning, educator support, and administrative efficiency, they also voiced concerns about increased workload, excessive student reliance on technology, algorithmic bias within AI systems, and data privacy. A balanced approach to AI integration is recommended not only that complements traditional teaching methods and addresses privacy and algorithmic bias. Schools are encouraged to offer comprehensive professional development programs for teachers to introduce AI technologies, address the ethical and practical challenges associated with their use in education, ensure equitable access to AI tools, and improve technological infrastructure. Keywords: Artificial Intelligence, Capacity building ,Educators, Education, private schools,

This study aims to examine neonatal intensive care unit (NICU) nurses' perceptions of artificial intelligence (AI) technologies, particularly language models, and their impact on nursing practices. AI is rapidly spreading in healthcare, transforming nursing practice. Understanding the role of AI in NICUs in the discharge process is crucial for understanding nurses' perceptions of these technologies. The qualitative, phenomenological study used semi-structured interviews. Data were collected in a public hospital in Gaziantep from January to June 2024. Fifteen NICU nurses participated. Data were analyzed using content analysis. Most nurses found AI to be a valuable tool for saving time and simplifying information delivery in clinical processes. However, concerns were raised about AI potentially reducing human interaction and weakening the use of professional judgment. Serious concerns about AI's reliability and ethical implications were also expressed. AI is considered a potentially supportive tool in nursing practice, but its integration must consider the ethical implications and impact on the use of professional judgment. Nursing is based on human interactions and AI should be considered an additive tool to enhance care. AI integration in nursing requires careful and balanced implementation. Future research should delve deeper into the ethical dimensions of AI and its long-term effects on nursing practices.

Artificial Intelligence (AI) is a rising technology with endless benefits and applications especially in the field of medicine. Unfortunately, ethical issues such as accountability, privacy, safety, security, and transparency have created a divide between the public and AI. A key population to understand is high school students as they will be affected more and more as AI continues to be developed. This begs the question: What are American high school students’ perceptions of artificial intelligence in medicine? The mixed method approach for this study used a survey aligned with Aggarwal et al. (2021) to gather quantitative results about student opinions on AI. Structure interviews aligned with Amann et al. (2023) were also conducted to find underlying themes between participants’ opinions. There were a total of 153 participants in this study. The students had self-reported low levels of understanding of AI as 44.44% disagreed with the statement that they had knowledge of AI technology in medicine while 30.72% were neutral. Additionally, only 23.53% of students trusted AI which contradicted the fact that students have a great amount of exposure to new technologies. There were significant differences in the levels of knowledge and trust in AI that high school students had in this study. A need for education on AI and its use in medicine as well as other sectors may be beneficial in closing the gap between the public and AI.

This study examines teachers’ negative attitudes toward artificial intelligence (AI) in education, focusing on the role of digital literacy, demographic characteristics, and direct AI experience. Using a quantitative cross-sectional design, data were collected from 1110 Romanian pre-university teachers through a self-administered online questionnaire. Exploratory factor analysis confirmed a two-dimensional structure of negative attitudes—Perceived AI Threat and Distrust in the Fairness and Ethics of AI—with good internal reliability (α = 0.93 and α = 0.62, respectively). Results indicated significant gender differences, with women reporting higher levels of perceived threat, while distrust in AI fairness showed no significant variation across gender, age, or teaching degree. Teachers in urban areas expressed greater skepticism toward AI ethics than those in rural settings. Higher levels of digital literacy were negatively correlated with both dimensions of negative attitudes, suggesting that digital competence mitigates technological anxiety. Moreover, frequent personal and professional use of AI predicted lower perceived threat levels, emphasizing the moderating role of experiential familiarity. These findings advance understanding of the psychosocial and cognitive factors shaping educators’ perceptions of AI and highlight the importance of AI literacy programs that integrate technical, ethical, and reflective components to foster informed and confident engagement with intelligent technologies.

Since the end of 2022, global discussions on Artificial Intelligence (AI) have surged, influencing diverse societal groups, such as teachers, students and policymakers. This case study focuses on Swedish primary school students aged 11–12. The aim is to examine their cognitive and affective perceptions of AI and their current usage. Data, comprising a pre-test, focus group interviews, and post-lesson evaluation reports, were analysed using a fusion of Mitcham’s philosophical framework of technology with a behavioural component, and the four basic pillars of AI literacy. Results revealed students’ cognitive perceptions encompassing AI as both a machine and a concept with or without human attributes. Affective perceptions were mixed, with students expressing positive views on AI’s support in studies and practical tasks, alongside concerns about rapid development, job loss, privacy invasion, and potential harm. Regarding AI usage, students initially explored various AI tools, emphasising the need for regulations to slow down and contemplate consequences. This study provides insights into primary school students perceptions and use of AI, serving as a foundation for further exploration of AI literacy in education contexts and considerations for policy makers to take into account, listening to children’s voices.