Perception Of Artificial Intelligence Research Articles

The Fictional Archetypes of AI: For a Qualitative-Quantitative Analysis of Representations in Films

MOS research on films has tended to focus on individual cases or series. In this article, we are proposing an approach that mobilizes background analysis, computational text analysis, and hermeneutics in order to provide a systematic, critically inclined analysis of a large corpus. We illustrate this approach by exploring the political and symbolical representations of artificial intelligence (AI) in the film industry. Using the Internet Movie Database, we identified all the films dealing with AI (113 in total), compiled their synopses, and recorded 11 characteristics for each. Highlighting the spatial, temporal, and gendered polarization of films depicting AI, our article proposes four representations of AI and critically reflects upon the role of these representations and their influence in shaping societal perceptions of AI. Our article makes two main contributions to the literature. First, it demonstrates the potential of combining quantitative-based, lexical forms of analysis with hermeneutic interpretations in the study of cultural representations. Second, it develops a nuanced, in-depth, and critical analysis of the symbolical and political representations of AI in cinematic productions, thus enhancing our understanding of this industry.

Students' perceptions of using artificial intelligence in tertiary education

Artificial Intelligence (AI) is increasingly influencing various aspects of teaching and learning in tertiary educational institutes. This concise paper presents the preliminary findings of an ongoing research that aims at exploring university students' perceptions of the use of AI in higher education settings. Phenomenographic framework has been adapted as the methodological guide for this research. Semi-structured interviews were conducted among students of an international university to capture students' perceptions. Findings revealed that university students possess diverse perspectives on the use of AI in higher education settings. Four qualitatively distinct categories of perceptions of AI emerged from the interview data. It is found that university students perceive the use of AI as a) an essential academic aid, b) a facilitator of personalized learning, c) an inhibitor to critical thinking, and d) an ethical challenger. Findings have pedagogical, administrative, and ethical implications for developing AI-driven technology-focused policy that facilitates diverse student needs.

Exploring Cybernetics Students' Perceptions of AI in Education: A Comprehensive Analytical Study

This study investigates the multifaceted perceptions of cybernetics students toward integrating artificial intelligence (AI) in educational environments. This research uncovers the students' knowledge levels, preferred sources of information, perceived benefits, and significant students through a comprehensive analysis of survey data combined with recent scholarly insights. Detailed visual analyses underscore key trends, offering a clear perspective on how these students view the future of AI in their academic journey. The findings suggest that while students appreciate AI’s utiAI, they express valid concerns about job security and the potential reduction in human engagement. This study contributes critical insights for educators and policymakers aiming to align AI practices with student needs and expectations.

Unlocking the Beat: How AI Tools Drive Music Students' Motivation, Engagement, Creativity and Learning Success

ABSTRACTThis study explores the relationships among music students' artificial intelligence (AI) perceptions, motivation, engagement, creativity and learning success. Through a random sampling method, 521 Chinese music students participated in the research, which employed a range of questionnaires to assess AI perceptions, motivation, engagement, learning outcomes and creativity. The study utilised SPSS (version 27) and AMOS (version 24) for comprehensive statistical analysis. Findings reveal a significant relationship between students' perceptions of AI in music education and their motivation, engagement and learning success. Positive AI perceptions were found to enhance motivation by increasing interest in innovative learning tools and fostering engagement through interactive AI‐based learning environments. Moreover, these perceptions were predictive of higher motivation, engagement and learning success. The study suggests that AI can play a crucial role in enhancing educational outcomes by making learning more interactive, personalised and engaging, thus improving overall student performance and creativity in music education.

Artificial intelligence for internal communication: Strategies, challenges, and implications

This qualitative study explores the intersection of artificial intelligence (AI) and internal communication, investigating AI applications, challenges, and best practices. In-depth interviews with 20 senior communication professionals examined perceptions of AI’s impact on internal communication processes and outcomes. Key findings indicate AI improves internal communication efficiency, information flow, listening capability, and employee experience. However, challenges include lack of AI knowledge among employees, fears about job security andbias, and concerns about authenticity loss. To enable effective AI adoption for internal communication, organizations need education and training, a “co-piloting” approach between humans and machines, transparent communication, ethical governance, and an open culture of experimentation. This research makes important theoretical contributions by illuminating AI’s transformative potential for internal communication. It also offers practical insights to guide organizations in strategically leveraging AI to elevate internal communication.

Perceptions of Artificial Intelligence and ChatGPT by Speech-Language Pathologists and Students.

This project explores the perceived implications of artificial intelligence (AI) tools and generative language tools, like ChatGPT, on practice in speech-language pathology. A total of 107 clinician (n = 60) and student (n = 47) participants completed an 87-item survey that included Likert-style questions and open-ended qualitative responses. The survey explored participants' current frequency of use, experience with AI tools, ethical concerns, and concern with replacing clinicians, as well as likelihood to use in particular professional and clinical areas. Results were analyzed in the context of qualitative responses to typed-response open-ended questions. A series of analyses indicated participants are somewhat knowledgeable and experienced with GPT software and other AI tools. Despite a positive outlook and the belief that AI tools are helpful for practice, programs like ChatGPT and other AI tools are infrequently used by speech-language pathologists and students for clinical purposes, mostly restricted to administrative tasks. While impressions of GPT and other AI tools cite the beneficial ways that AI tools can enhance a clinician's workloads, participants indicate a hesitancy to use AI tools and call for institutional guidelines and training for its adoption.

Understanding Chinese University EFL Learners' Perceptions of AI in English Writing

Artificial intelligence (AI) is useful to English as a foreign language (EFL) learners, but there is a paucity of research on how they perceive AI. Contextualized in a Chinese university setting, this study investigated Chinese university EFL learners' perceptions of Grammarly in English writing. Based on an extended technology acceptance model (TAM) with task relevance, subjective norm, and perceived enjoyment being added, quantitative data were collected from 140 Chinese EFL learners. Structural equation modeling analysis suggested that the proposed model could effectively explain participants' views of Grammarly. Their perceptions of ease of use significantly influenced usefulness, which had a major impact on their attitudes towards AI and behavioral intention. Perceived enjoyment and task relevance were also significant predictors of students' perceptions of this software. The research model explained 71% of the variance of EFL learners' intentions to use AI. Suggestions were given to teachers on implementing AI writing support.

Perceptions of Discriminatory Decisions of Artificial Intelligence: Unpacking the Role of Individual Characteristics

This study investigates how personal differences (digital self-efficacy, technical knowledge, belief in equality, political ideology) and demographic factors (age, education, and income) are associated with perceptions of artificial intelligence (AI) outcomes exhibiting gender and racial bias and with general attitudes towards AI. Analyses of a large-scale experiment dataset (N = 1,206) indicate that digital self-efficacy and technical knowledge are positively associated with attitudes toward AI, while liberal ideologies are negatively associated with outcome trust, higher negative emotion, and greater skepticism. Furthermore, age and income are closely connected to cognitive gaps in understanding discriminatory AI outcomes. These findings highlight the importance of promoting digital literacy skills and enhancing digital self-efficacy to maintain trust in AI and beliefs in AI usefulness and safety. The findings also suggest that the disparities in understanding problematic AI outcomes may be aligned with economic inequalities and generational gaps in society. Overall, this study sheds light on the socio-technological system in which complex interactions occur between social hierarchies, divisions, and machines that reflect and exacerbate the disparities.

Medical students and house officers’ perception, attitude and potential barriers towards artificial intelligence in Egypt, cross sectional survey

BackgroundArtificial intelligence (AI) is one of the sectors of medical research that is expanding the fastest right now in healthcare. AI has rapidly advanced in the field of medicine, helping to treat a variety of illnesses and reducing the number of diagnostic and follow-up errors.ObjectiveThis study aims to assess the perception and attitude towards artificial intelligence (AI) among medical students & house officers in Egypt.MethodsAn online cross-sectional study was done using a questionnaire on the Google Form website. The survey collected demographic data and explored participants’ perception, attitude & potential barriers towards AI.ResultsThere are 1,346 responses from Egyptian medical students (25.8%) & house officers (74.2%). Most participants have inadequate perception (76.4%) about the importance and usage of AI in the medical field, while the majority (87.4%) have a negative attitude. Multivariate analysis revealed that age is the only independent predictor of AI perception (AOR = 1.07, 95% CI 1.01–1.13). However, perception level and gender are both independent predictors of attitude towards AI (AOR = 1.93, 95% CI 1.37–2.74 & AOR = 1.80, 95% CI 1.30–2.49, respectively).ConclusionThe study found that medical students and house officers in Egypt have an overall negative attitude towards the integration of AI technologies in healthcare. Despite the potential benefits of AI-driven digital medicine, most respondents expressed concerns about the practical application of these technologies in the clinical setting. The current study highlights the need to address the concerns of medical students and house officers towards AI integration in Egypt. A multi-pronged approach, including education, targeted training, and addressing specific concerns, is necessary to facilitate the wider adoption of AI-enabled healthcare.

Exploring Pharmacists' Perceptions of Text-Based Artificial Intelligence in Resident and Student Education.

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.

Artificial Intelligence and Education: A Metaphorical Analysis on the Perceptions of Students with Special Abilities

The main goal of this study is to reveal special talented primary school students' perceptions of artificial intelligence, one of the popular concepts of recent times, through metaphors. In this study, the phenomenological design, which is within the scope of qualitative research, was used. In this study, Türkiye Science and Art Center included special talented primary school students in the education field. The 104 special talented primary school students participating in the research were 9-14 years old. Of these students, 53 were boys and 51 were girls. The participants were in the 3th grade, 4th grade, 5th, 6th, 7th and 8th grades of primary education. Purposive sampling method was chosen in the research. When the answers from the students were examined, a total of 36 different categories emerged in line with the relevant metaphors. When these categories are examined in detail, it is seen that the concept of artificial intelligence is represented by different metaphors. According to the findings, it was determined that primary school students simulated the concept of artificial intelligence to different metaphors such as robot, smiling robot, robot vacuum cleaner. As a result, it has been revealed that special talented student generally have positive opinions about the concept of artificial intelligence.

Unmasking teachers’ proficiency in harnessing Artificial Intelligence (AI) for transformative education

This paper examines the awareness of artificial intelligence (AI) among school teachers in Nepal. We interviewed twenty teachers from ten urban schools in Nepal over four weeks using a semi-structured interview tool. The analysis of interview data reveals the teachers’ mixed perception of AI, including their understanding of innovative technologies in education, the potential challenges for new-generation teachers, and the opportunities for pedagogical transformations. The findings suggest that although the teachers have limited awareness of how AI can be used in teaching and learning, they possess some level of understanding that has opened up new opportunities for exploring innovative ways of teaching and learning. Notably, participants discussed tools, such as Education Management Information System (EMIS) for record keeping and automated grading and AI-driven chatbots for student tutoring. However, teachers also expressed concerns about the possibility of AI replacing human teachers. These insights provide valuable implications for policymakers and educators regarding the integration of AI into classroom instructions to promote innovative and equitable learning opportunities.

Use of Artificial Intelligence tools in supporting decision-making in hospital management

BackgroundThe use of Artificial Intelligence (AI) tools in hospital management holds potential for enhancing decision-making processes. This study investigates the current state of decision-making in hospital management, explores the potential benefits of AI integration, and examines hospital managers’ perceptions of AI as a decision-support tool.MethodsA descriptive and exploratory study was conducted using a qualitative approach. Data were collected through semi-structured interviews with 15 hospital managers from various departments and institutions. The interviews were transcribed, anonymized, and analyzed using thematic coding to identify key themes and patterns in the responses.ResultsHospital managers highlighted the current inefficiencies in decision-making processes, often characterized by poor communication, isolated decision-making, and limited data access. The use of traditional tools like spreadsheet applications and business intelligence systems remains prevalent, but there is a clear need for more advanced, integrated solutions. Managers expressed both optimism and skepticism about AI, acknowledging its potential to improve efficiency and decision-making while raising concerns about data privacy, ethical issues, and the loss of human empathy. The study identified key challenges, including the variability in technical skills, data fragmentation, and resistance to change. Managers emphasized the importance of robust data infrastructure and adequate training to ensure successful AI integration.ConclusionsThe study reveals a complex landscape where the potential benefits of AI in hospital management are balanced with significant challenges and concerns. Effective integration of AI requires addressing technical, ethical, and cultural issues, with a focus on maintaining human elements in decision-making. AI is seen as a powerful tool to support, not replace, human judgment in hospital management, promising improvements in efficiency, data accessibility, and analytical capacity. Preparing healthcare institutions with the necessary infrastructure and providing specialized training for managers are crucial for maximizing the benefits of AI while mitigating associated risks.

The Digital Revolution in Education: The Role of AI from the Perspective of Future Teachers

We are currently witnessing rapid technological advancement and modernisation of society, with digital technology, particularly artificial intelligence (AI), increasingly asserting its dominance. This study focuses on understanding the attitudes and expectations of future teachers towards AI, which has an impact on all areas of society, especially on the education and preparation of future teachers. Through a questionnaire survey, the study seeks to gain a more detailed insight into how future educators perceive AI and their attitudes towards it. The questionnaire, which was specifically designed for this research, focuses on different aspects of perceptions of AI in education. Respondents from both primary and secondary school teacher education programmes expressed their views on the use of AI in the pedagogical process, its impact on teacher-student interaction and indicated possible implications for the future of education. The main objectives of the research were to determine the views of prospective teachers on the use of AI in teaching, to identify positive, negative or neutral attitudes towards the integration of AI into the educational process, to identify the future role of AI in education, to determine how prospective teachers envision the use of AI in the pedagogical environment in the long term, to identify areas where teaching with AI could be most effectively integrated, and to identify areas where AI could be most appropriately used to improve educational outcomes and processes. The data presented through this paper is part of the "Perceptions of AI by current and future teachers" project. The results of this study could provide valuable information for educational institutions, policy makers of educational strategies and frameworks, and AI developers to better understand the needs and expectations of future teachers in the context of the increasing digitalisation of education. Our intention is to fill the knowledge gap on the perception of AI in educational contexts and thus provide important information for the future development of pedagogical strategies and technologies in education.

An Early Snapshot of Attitudes Toward Generative Artificial Intelligence in Physical Therapy Education

Introduction. 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). Review of Literature. 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. Subjects. A total of 175 surveys were completed and analyzed. Respondents included PT educators, administrators, and students. Methods. 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. Results. 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. Discussion and Conclusion. 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.

Managerial Perception of AI in Strategic Decision-Making

ABSTRACT Given the growing use of Artificial Intelligence (AI) in strategic endeavors, it is important to comprehend its potential in facilitating strategic decision-making (SDM). Data collected through semi-structured interviews and cognitive absorption theory were used to examine viewpoints and perceptions of 20 AI experts at middle-level management positions toward the use of AI in SDM. As a result, many key concepts emerge, including human dependence, evaluation of emotions, and building trust, among others. Subsequently, a proposed AI-acceptance-avoidance framework has been presented to address primary concerns and aspects that influence trust or lack of trust in AI, as well as inclination toward accepting or avoiding it for SDM. In process, the study has attempted to extend cognitive absorption theory.

Perceptions of Artificial Intelligence and Its Impact on Academic Integrity among University Students in Peru and Chile: An Approach to Sustainable Education

In a context where artificial intelligence (AI) is transforming higher education, this study analyzes how students’ perceptions of AI influence their academic integrity (INA), with a focus on sustainable education. Through a correlational-explanatory analysis based on Structural Equation Models (SEMs) applied to a sample of 659 students from 13 universities in Chile and Peru, it is observed that AI has a significant and direct impact on academic integrity in both countries (β = 0.44). In Peru, the most influential dimension is trust in education (λ = 0.86), followed by social, economic, security, and risk implications (λ = 0.78), while attitudes towards AI also have a direct impact on integrity factors (β = 0.15). In Chile, the dimensions of trust in education (λ = 0.83) and social and economic impact (λ = 0.79) are most relevant, and the relationships between the dimensions of academic integrity such as justice, respect, and responsibility (λ = 0.71) are stronger. The study highlights the importance of incorporating AI literacy into educational curricula and developing regulatory frameworks that promote its ethical use, linking these actions to sustainable education. The findings highlight the need for sustainable educational approaches that enhance understanding of AI and ensure that its use in academia is beneficial, ethical, and contributes to sustainable development.

Artificial intelligence literacy among university students—a comparative transnational survey

Artificial intelligence (AI) literacy is a crucial aspect of media and information literacy (MIL), regarded not only as a human right but also as a fundamental requirement for societal advancement and stability. This study aimed to provide a comprehensive, cross-border perspective on AI literacy levels by surveying 1,800 university students from four Asian and African nations. The findings revealed significant disparities in AI literacy levels based on nationality, scientific specialization, and academic degrees, while age and gender did not show notable impacts. Malaysian participants scored significantly higher on the AI literacy scale than individuals from other countries. The results indicated that various demographic and academic factors influenced respondents’ perceptions of AI and their inclination to utilize it. Nationality and academic degree were identified as the most influential factors, followed by scientific specialization, with age and gender exerting a lesser influence. The study highlights the necessity of focusing research efforts on the detailed dimensions of the AI literacy scale and examining the effects of previously untested intervening variables. Additionally, it advocates for assessing AI literacy levels across different societal segments and developing the appropriate measurements.

Truth & Information? Preparing Information Organization & Retrieval Students for an AI Future

Artificial intelligence (AI) is not a new concept or technology, but has taken the world by storm with the recent advancement of generative AI, such as ChatGPT and Bard. The metadata, cataloging, collections, and retrieval areas of library and information studies (LIS) are already experiencing disruption and soul-searching because of generative AI, but it remains to be seen to what extent the technology can benefit, or even harm, these areas of LIS. The Metadata, Cataloging, & Collections SIG session will include a panel of three educators who will discuss the use of artificial intelligence in information retrieval and cataloging courses, and provide ideas for educators hoping to learn more about the impact of AI and how to incorporate activities and discussions of AI in their courses. Priya Kizhakkethil will report on student perceptions of AI in the LIS curriculum, with a focus on Information Retrieval courses. With the emergence of Generative Artificial Intelligence (Gen AI) tools like ChatGPT, there has been much discussion about its impact on libraries and the work of librarianship. But there is a gap in the literature that addresses how such disruptive technologies should be addressed in the LIS curriculum. This presentation covers a work in progress pilot study seeking to understand LIS student perceptions on the use of generative AI tools as part of their course work. Themes relating to student perceptions on the use of Gen AI tools for an Information Retrieval course will be discussed, which includes the potential ways of using these tools as noted by the students. Vyacheslav (Slava) Zavalin will discuss the critical need for understanding the AI landscape and its application to information organization within LIS. He will demonstrate using Google Gemini, the AI-powered assistant, to create bibliographic examples and then analyze and discuss the accuracy of the records. Karen Snow recently assigned advanced cataloging students an exercise that required them to create a basic MARC/RDA bibliographic record using ChatGPT. The resulting transcripts of their conversations with ChatGPT, and their reflections on the experience, were a fascinating demonstration of the benefits/drawbacks of AI in cataloging work, but also of the importance of educating students on how to effectively use AI. After the presentations, audience members will be encouraged to ask questions and offer their own experiences and ideas concerning this area of LIS education. These presentations align well with the ALISE 2024 conference theme of “The Ethics and Evolution of Truth and Information.”

AI-Driven Advertising Activity: Perspectives from Peruvian Advertisers

This study explores the impact of Artificial Intelligence (AI) on the creative process within Peruvian advertising agencies. The research focuses on understanding how AI technologies influence the practices of professionals involved in creative production and the perception of AI’s role in enhancing or detracting from creativity in a market characterized by emerging digital transformation. Adopting a qualitative methodology grounded in the interpretive paradigm, the study placed particular emphasis on the insights and experiences of Creative Directors, who play a pivotal role in integrating AI into the creative process. In addition to these key professionals, the study also analyzed the perspectives of AI specialists, decision-makers in digital transformation, and AI consultants. Data was meticulously gathered through semi-structured in-depth interviews, ensuring a comprehensive understanding of how AI is reshaping creativity in advertising. The findings reveal that while AI offers significant potential to streamline and enhance creative processes, concerns about authenticity and the risk of diminishing human creativity persist. The study underscores the need for a balanced approach that integrates AI-driven efficiency with the preservation of original creative input, providing insights for future policy development and industry practices.