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Artificial intelligence (AI) in medicine and digital assistance systems such as chatbots will play an increasingly important role in future doctor – patient communication. To benefit from the potential of this technical innovation and ensure optimal patient care, future physicians should be equipped with the appropriate skills. Accordingly, a suita...
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Machines can be equipped with the capability of identifying human emotions through conversation, thus enabling them to empathize with natural persons when they speak to them. The emergence of chatbots and intelligent assistants has led to a heightened focus on emotion recognition tasks. Most existing methodologies primarily focus on the isolated an...
Citations
... These ethical issues are worsened by the opacity of knowledge about AI chatbot algorithms. Students and even instructors often miss a full picture of how the underlying AI works, skepticism about chatbot outputs is common (Moldt et al. 2023). This issue is compounded by the relative opaqueness of various AI models, where their inner functioning is black-boxed which obfuscates how data and decisions are processed. ...
Artificial Intelligence (AI) chatbot 'ChatGPT' in the education sector has changed the learning patterns among students, staff, and lecturers. The rise of AI-driven tools is bringing forth significant ethical concerns, which are considered essential to discuss. The present study was conducted in three public sector universities in Malaysia, where we opted for the quantitative research design and approached the research participants through personal invitation and snowball sampling procedures. A total of 406 respondents were involved in this study, and the data was gathered through a survey, using structured questionnaire. The purpose of this method is to collect diverse data from a variety of participants, including students, staff, and lecturers. The findings show that it is imperative to highlight the need for robust ethical guidelines and a higher education institution framework to ensure that implementation is indispensable. Furthermore, addressing these ethical challenges can harness the potential of chatbots in academia along with ensuring ethical concerns being addressed. The study concluded that academicians had clear understanding about the ethical issues of using ChatGPT or AIs. The study also suggests recommendations regarding the ethical usage by the government of Malaysia. Abstrak Chatbot Kecerdasan Buatan (AI) 'ChatGPT' di sektor pendidikan telah mengubah pola pembelajaran di kalangan mahasiswa, staf, dan dosen. Meningkatnya alat yang digerakkan oleh AI memunculkan berbagai masalah etika yang signifikan, yang dianggap penting untuk dibahas. Studi saat ini dilakukan di tiga universitas sektor publik di Malaysia, di mana kami memilih desain penelitian kuantitatif dan mendekati partisipan penelitian melalui undangan pribadi dan prosedur pengambilan sampel bola salju. Sebanyak 406 responden terlibat dalam penelitian ini, dan data dikumpulkan melalui survei, menggunakan kuesioner terstruktur. Tujuan dari metode ini adalah untuk mengumpulkan beragam data dari berbagai partisipan, termasuk mahasiswa, staf, dan dosen. Temuan menunjukkan bahwa sangat penting untuk menyoroti perlunya pedoman etika yang kuat dan kerangka kerja lembaga pendidikan tinggi untuk memastikan bahwa implementasi sangat diperlukan. Lebih jauh, mengatasi tantangan etika ini dapat memanfaatkan potensi chatbot di dunia akademis sekaligus memastikan masalah etika ditangani. Studi ini menyimpulkan bahwa akademisi memiliki pemahaman yang jelas tentang masalah etika penggunaan ChatGPT atau AI. Studi ini juga menyarankan rekomendasi mengenai penggunaan etika oleh pemerintah Malaysia. Kata kunci: kecerdasan buatan dalam pendidikan; ChatGPT; masalah etika; lembaga pendidikan tinggi 433
... Currently, clinicians are raising concerns about the reliability, limited knowledge or training of chatbots, implementation costs, ethical concerns, and the absence of regulatory approval for integrating AI-based LLM chatbots into routine practice [105][106][107][108][109]. Tackling these challenges requires essential collaboration between chatbot developers and healthcare providers, ongoing professional training, strict regulatory oversight, and the establishment and enforcement of relevant ethical guidelines and regulations. ...
Artificial intelligence (AI) is becoming increasingly influential in ophthalmology, particularly through advancements in machine learning, deep learning, robotics, neural networks, and natural language processing (NLP). Among these, NLP-based chatbots are the most readily accessible and are driven by AI-based large language models (LLMs). These chatbots have facilitated new research avenues and have gained traction in both clinical and surgical applications in ophthalmology. They are also increasingly being utilized in studies on ophthalmology-related exams,
particularly those containing multiple-choice questions (MCQs). This narrative review evaluates both the opportunities and the challenges of integrating chatbots into ophthalmology research, with separate assessments of studies involving open- and close-ended questions. While chatbots have demonstrated sufficient accuracy in handling MCQ-based studies, supporting their use in education, additional exam security measures are necessary. The research on open-ended question responses
suggests that AI-based LLM chatbots could be applied across nearly all areas of ophthalmology. They have shown promise for addressing patient inquiries, offering medical advice, patient education, supporting triage, facilitating diagnosis and differential diagnosis, and aiding in surgical planning. However, the ethical implications, confidentiality concerns, physician liability, and issues surrounding patient privacy remain pressing challenges. Although AI has demonstrated significant promise
in clinical patient care, it is currently most effective as a supportive tool rather than as a replacement for human physicians.
... In addition, chatbots offer scalable, accessible digital therapy for addressing the mental health needs of students in HE, potentially improving academic outcomes and retention rates (Biro et al., 2023;Lin et al., 2021). Medical chatbots also assist in administrative tasks such as scheduling appointments, managing patient records, providing information and support, enhancing engagement with medical students, and managing stress levels (Moldt et al., 2022;Moldt et al., 2023). ...
... In addition, they have mentioned that they have encountered technical obstacles and that mentors for digital students need continuous support and training. They also emphasized the importance of human support when it is needed (Ilieva et al., 2023;Moldt et al., 2023). On the other hand, there were also contradictory results; for example, Bilquise et al. (2023) revealed that social influence positively impacts the behavioral intention to use an advising chatbot, while Rahim et al. (2022) reported that students do not require social reinforcement to use a chatbot, and users are not influenced by the opinions, suggestions, or recommendations of important others who think they should adopt a chatbot. ...
... The questionnaire assessed the attitude toward artificial intelligence of the undergraduate medical students who attended the course (n=354). The questionnaire was adapted from Stewart et al. [12], Moldt et al. [13] and Grassini, S. [14]. The attitude questionnaire included 28 questions, as demonstrated in supplementary 2, about four subthemes: undergraduate medical students' optimistic perspectives towards AI in healthcare (6 questions), undergraduate medical students' concerns towards AI in healthcare (8 questions), undergraduate medical students' optimistic perspectives towards AI in medical education (8 questions), and undergraduate medical students' concerns towards AI in medical education (6 questions). ...
... Pre-service teachers use of AI Research suggests that university students from different fields (medicine, business, education, art, etc.) and countries and continents are informed about what AI is (Abdelwahab et al., 2023;Almaraz-López et al., 2023;Bisdas et al., 2021). Although the majority of studies reveal that students have a positive attitude toward AI and positively perceive the possibilities provided by AI (Bonsu and Baffour-Koduah, 2023;Chan and Hu, 2023;Hussain, 2020;Jeffrey, 2020;Leoste et al., 2021;Limna et al., 2023;Lukić et al., 2023;Moldt et al., 2023;Mousavi Baigi et al., 2023;Pauwels and Del Rey, 2021;Swed et al., 2022;Terblanche et al., 2023), there are some exceptions (Haseski, 2019;Keleş and Suleyman, 2021). In one case, pre-service teachers even had negative emotions toward AI (Haseski, 2019). ...
... Technology readiness has a significant influence on technology adoption (Damerji and Salimi, 2021). It is most probably because of insufficient knowledge that students have doubts related to AI's use in their professions, for example, how to solve data protection issues and the risk of being constantly monitored at work (Moldt et al., 2023). Consequently, the need for further training of students has been articulated (Almaraz-López et al., 2023). ...
Introduction
The study investigates the integration of artificial intelligence (AI) in higher education (HE) and its impact on pre-service teachers at the University of Latvia (UL) by exploring pre-service teachers' perceptions of the benefits and challenges of AI in both their academic learning and their future professional roles as educators, particularly regarding the promotion of inclusive education.
Methods
Data was collected via an online survey of 240 pre-service teachers across various disciplines at the UL. The survey included demographic details, AI usage patterns, and perceived benefits and challenges. Responses were analyzed using descriptive statistics, Kruskal-Wallis H tests, Spearman's correlation, and thematic analysis.
Results
Less than half of the participants used AI in their studies, with many expressing ambivalence or opposition toward AI. Benefits included language assistance and accessibility to global knowledge, while challenges involved reduced critical thinking and concerns over plagiarism. Despite recognizing AI's potential to promote inclusivity, most pre-service teachers have not applied it in practice. No significant differences in AI perceptions were found based on age, gender, or study level.
Discussion
The findings highlight a low adoption rate of AI among pre-service teachers and a gap between theoretical recognition of AI's potential and its practical application, particularly for inclusion. The study emphasizes the need for HE institutions to enhance AI literacy and readiness among future teachers.
Conclusion
AI is underutilized by pre-service teachers in both HE learning and teaching environments, which has implications for teacher preparation programs that better integrate AI literacy and inclusive practices.
... Simulation-based learning environments are expected to leverage AI technologies more extensively. These tools provide students with realistic clinical scenarios where they can interact with AI systems, refining their diagnostic skills and critical thinking in a safe and controlled setting (Moldt et al., 2023;Teng et al., 2022). This experiential approach reinforces the integration of AI insights into clinical reasoning without compromising essential skills. ...
The article explores the evolution of medical knowledge from its anatomical and functional foundations to the integration of advanced technological tools, focusing on the impact of artificial intelligence (AI) on the development of diagnostic competencies. Initially, medical training relied on direct observation and clinical judgment based on anatomical and surgical knowledge. Subsequently, the inclusion of physiology and pathology enabled a functional understanding of the human body, transforming diagnosis into a systematic skill supported by objective data such as laboratory tests and medical imaging. The integration of AI in recent decades has revolutionized this process, offering unprecedented capabilities to analyze complex clinical data. Tools such as machine learning algorithms and predictive systems have enhanced diagnostic precision, allowing for the identification of previously unnoticed patterns. This data-driven approach strengthens physicians’ ability to correlate clinical symptoms and signs with specific pathological entities. However, the incorporation of AI presents challenges in medical education. Future physicians must combine learning traditional clinical foundations with mastering advanced technologies, all while maintaining an ethical and patient-centered approach. Furthermore, excessive reliance on technology and biases inherent in algorithms underscore the need to balance technological innovation with human clinical judgment. The article highlights that medical education must adapt to include critical competencies such as digital literacy, ethical reasoning, and critical thinking. AI-based simulators and educational platforms are playing a key role in preparing physicians for a more digitized clinical environment, while research remains essential to ensure transparency and fairness in these technologies.
... However, with the advent of new technologies come some challenges that must be recognized and addressed to sufficiently integrate these tools into the practice of medicine. Previous investigations have reported the importance of comprehensively exploring the possibility of integrating competencies related to the role of AI in medical education (Moldt et al., 2023). In professional practice, this is especially relevant in the context of medico-legal and ethical dilemma decision-making, diagnostics and therapeutic advancements, and health information. ...
... Questions presenting ethical dilemmas for further discussion were also included. The content of the focus group discussion was primarily based on a previous study by Moldt et al., which utilized an identical approach, with minor modifications (Moldt et al., 2023). ...
... A systematic review by Sun et al., in particular, highlights how most fields related to radiology, diagnostics, surgery, and cardiology were the primary areas of focus in terms of applying AI to medical training. These findings were consistent with our study, although surprisingly, disciplines such as Family and Community Medicine and Psychiatry were also indicated as specializations affected by AI, possibly due to the emerging role of virtual assistants and mental health chatbots (Moldt et al., 2023;Sun et al., 2023). ...
Background Artificial intelligence (AI) is emerging as one of the most revolutionary technologies shaping the educational system utilized by this generation of learners globally. AI enables opportunities for innovative learning experiences, while helping teachers devise teaching strategies through automation and intelligent tutoring systems. The integration of AI into medical education has potential for advancing health management frameworks and elevating the quality of patient care. However, developing countries, including the Philippines, face issues on equitable AI use. Furthermore, medical educators struggle in learning AI which imposes a challenge in teaching its use. To address this, the current study aims to investigate the current perceptions of medical students on the role of AI in medical education and practice of medicine. Methods The study utilized a mixed-methods approach to quantitatively and qualitatively assess the current attitudes and perceptions of medicine students of AI. Quantitative assessment was done via survey and qualitative analysis via focus group discussion. Participants were composed of 20 medical students from the College of Medicine, University of the Philippines Manila. Results Analysis of the attitudes and perceptions of Filipino medical students on AI showed that participants had a baseline understanding and awareness, but lack opportunities in studying medicine and clinical practice. Majority of participants recognize the advantages in medical education but have reservations on its overall application in a clinical setting. Conclusions The results of this investigation can direct future studies that aim to guide educators on the emerging role of AI in medical practice and the healthcare system, on its effect on physicians-in-training under contemporary medical educational practices. Findings from our study revealed key focal points which need to be sufficiently addressed in order to better equip medical students with knowledge, tools, and skills needed to utilize and integrate AI into their education and eventual practice as healthcare professionals.
... Nadarzynski et al. incorporated semi-structured interviews to explore the acceptability of chatbot systems for healthcare. Moldt et al. investigated the acceptance of medical students toward chatbots (108). Nevertheless, these survey responses were mainly drawn from students and internet users who are relatively experienced with digital technologies, particularly a young and educated cohort (21). ...
Background
Chatbots are increasingly integrated into the lives of older adults to assist with health and wellness tasks. This study aimed to understand the factors that enhance older adults’ acceptance of chatbots in healthcare delivery.
Methods
This study proposed an extended Unified Theory of Acceptance and Use of Technology model (UTAUT), including aging factors of perceived physical condition, self-actualization needs, and technology anxiety. The model was tested by PLS (Partial Least Squares) with data collected from 428 Chinese citizens aged 60 and above.
Results
The results reveal that performance expectancy, effort expectancy, and social influence significantly affected older adults’ behavioral intention to use chatbots. The facilitating conditions, self-actualization needs, and perceived physical condition significantly affected the actual use behavior of chatbots by older adults, whereas technology anxiety did not. Furthermore, the influence of effort expectancy and social influence on behavioral intention were moderated by experience.
Conclusion
The behavioral intentions of older adults with low experience are more strongly influenced by social influences and effort expectancy. Furthermore, healthcare providers, designers, and policymakers should emphasize the impact of facilitating conditions, self-actualization needs, and perceived physical conditions on chatbot applications among older adults.
... Chatbots possess the ability to formulate a wide range of clinical questions and patient scenarios, making them a valuable resource for both clinicians and students. By generating realistic scenarios across various topics, chatbots simulate real-world encounters and offer users an opportunity to apply their knowledge in practical settings [32]. These scenarios can be accompanied by pertinent questions encouraging users to think critically and provide accurate responses. ...
At the intersection of artificial intelligence (AI) and healthcare, it is essential that clinicians grasp the ability of chatbots. AI-powered chatbots such as ChatGPT are being explored for their potential benefits by both individuals and institutions. The utility of ChatGPT (OpenAI) in various scenarios was explored through a series of recorded prompts and responses. In the clinical aspects, the chatbot facilitated tasks such as triage, patient consultation, diagnosis, and administrative responsibilities. Their capacity to translate and simplify intricate medical topics was also evaluated. For research purposes, the chatbots' abilities to suggest ideas, prepare protocols, assist in manuscript writing, guide statistical analyses, and recommend suitable journals were assessed. In the educational domain, chatbots were tested for simplifying complex subjects, reviewing procedural steps, generating clinical scenarios, and formulating multiple-choice questions. A comprehensive literature review was also conducted across Medline, Embase, and Web of Science. Chatbots, when optimally employed, can serve as invaluable resources in healthcare, spanning clinical, research, and educational domains. Their potential lies in enhancing efficiency, guiding decision-making, and facilitating patient care and education. However, their application requires a nuanced understanding and caution regarding their limitations.
... AI applications in medical diagnostics open new horizons for early disease detection and treatment personalization, promising significant improvements in recovery probabilities and care customization [12,15]. Particular attention has been focused on the importance of integrating AI competencies into medical curricula, recognizing the need to prepare future healthcare professionals for an increasingly technological clinical environment. ...
The integration of artificial intelligence (AI) in healthcare management marks a significant ad-vance in technological innovation, promising transformative effects on healthcare processes, pa-tient care, and the efficacy of emergency responses. The scientific novelty of the study lies in its in-tegrated approach, combining systematic review and predictive algorithms to provide a compre-hensive understanding of AI’s role in improving healthcare management across different contexts. Covering the period between 2019 and 2023, which includes the global challenges posed by the COVID-19 pandemic, this research investigates the operational, strategic, and emergency response implications of AI adoption in the healthcare sector. It further examines how the impact of AI var-ies across temporal and geographical contexts. The study addresses two main research objectives: to explore how AI influences healthcare management in operational, strategic, and emergency re-sponse domains, and to identify variations in the impact of AI on healthcare management based on temporal and geographical contexts. Utilizing an integrated approach, we compared various pre-diction algorithms, including logistic regression, and interpreted the results through SHAP (SHapley Additive exPlanations) analysis. The findings reveal five key thematic areas: AI’s role in enhancing quality assurance, resource management, technological innovation, security, and the healthcare response to the COVID-19 pandemic. The study highlights AI’s positive influence on operational efficiency and strategic decision making, while also identifying challenges related to data privacy, ethical considerations, and the need for ongoing technological integration. These in-sights provide opportunities for targeted interventions to optimize AI’s impact in current and fu-ture healthcare landscapes. In conclusion, this work contributes to a deeper understanding of the role of AI in healthcare management and provides insights for policymakers, healthcare profes-sionals, and researchers, offering a roadmap for addressing both the opportunities and challenges posed by AI integration in the healthcare sector.
