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This paper delves into the intricate relationship between Artificial Intelligence (AI) and the art ecosystem, emphasizing the need for a decolonizing approach in the face of AI's growing influence. It argues that the development of AI is not just a technological leap but also a significant cultural and societal moment, akin to the advent of moving images that Walter Benjamin famously analyzed. The paper examines how AI, particularly in its current oligarchical and corporate-driven form, perpetuates and magnifies the existing social inequalities, thereby necessitating a critical and radical rethinking of its role in society and the arts. At the heart of the discussion is the concept of AI as a broad term encompassing various forms of machine intelligence, from natural language processing to computer vision. The paper criticizes the dominant anthropocentric view of intelligence and creativity, proposing a more inclusive approach that considers the diverse forms of intelligence present in other species and potentially in AI itself. It underscores the role of AI in shaping the art ecosystem, not just in the creative process but also in gatekeeping and decision-making. The paper proposes a framework for decolonizing AI in the art ecosystem, focusing on four key tasks: recognizing access as a form of power, understanding and addressing biases inherent in AI, assessing the impact of AI on marginalized communities, and challenging dominant narratives and epistemologies to create space for alternative voices and perspectives. It emphasizes the need for artists and the art community to engage actively with AI, shaping its development towards more equitable and just outcomes. In conclusion, the paper calls for a radical reimagination of AI's role in society and the arts, advocating for a future where AI is not just about technological advancement but also about fostering a more inclusive, equitable, and creatively diverse world. It invites artists, thinkers, and innovators to join in this journey of reimagining and reshaping the future of AI and the art ecosystem. [ABSTRACT FROM AUTHOR]

The escalating integration of artificial intelligence (AI) technologies, particularly the widespread use of ChatGPT in higher education, necessitates a profound exploration of effective communication strategies. This paper addresses the critical role of prompt development as a skill essential for university instructors engaging with ChatGPT. While emphasizing the practical implications for higher education, the study introduces a novel two-layered AI prompt formula, considering both components and elements. In methodology, the research synthesizes insights from existing models and proposes a tailored approach for ChatGPT, addressing its unique characteristics and the contextual elements within higher education. The results highlight the formula's flexibility and potential applications in diverse fields, from syllabus planning to assessment. Moreover, the study identifies limitations inherent in ChatGPT, emphasizing the need for instructors to exercise caution in its usage. In conclusion, the paper underscores the evolving landscape of AI in education, envisaging specialized versions of ChatGPT for academic settings and advocating for the proactive adoption of ethical frameworks in the use of AI in higher education. This study serves as a foundational contribution to the discourse on effective AI communication in educational settings. [ABSTRACT FROM AUTHOR]

Artificial intelligence models play a crucial role in monitoring and maintaining railroad infrastructure by analyzing image data of foreign objects on power transmission lines. However, the availability of publicly accessible datasets for railroad foreign objects is limited, and the rarity of anomalies in railroad image data, combined with restricted data sharing, poses challenges for training effective foreign object detection models. In this paper, the aim is to present a new dataset of foreign objects on railroad transmission lines, and evaluating the overall performance of mainstream detection models in this context. Taking a unique approach and leveraging large-scale models such as ChatGPT (Chat Generative Pre-trained Transformer) and text-to-image generation models, we synthesize a series of foreign object data. The dataset includes 14,615 images with 40,541 annotated objects, covering four common foreign objects on railroad power transmission lines. Through empirical research on this dataset, we validate the performance of various baseline models in foreign object detection, providing valuable insights for the monitoring and maintenance of railroad facilities. [ABSTRACT FROM AUTHOR]

Artificial intelligence empowers the rapid development of autonomous intelligent systems (AISs), but it still struggles to cope with open, complex, dynamic, and uncertain environments, limiting its large-scale industrial application. Reliable human feedback provides a mechanism for aligning machine behavior with human values and holds promise as a new paradigm for the evolution and enhancement of machine intelligence. This paper analyzes the engineering insights from ChatGPT and elaborates on the evolution from traditional feedback to human feedback. Then, a unified framework for self-evolving intelligent driving (ID) based on human feedback is proposed. Finally, an application in the congested ramp scenario illustrates the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

The emergence of generative AI has sparked substantial discussions, with the potential to have profound impacts on society in all aspects. As emerging technologies continue to advance, it is imperative to facilitate their proper integration into society, managing expectations and fear. This paper investigates users' perceptions of generative AI using 3M posts on Twitter from January 2019 to March 2023, especially focusing on their occupation and usage. We find that people across various occupations, not just IT-related ones, show a strong interest in generative AI. The sentiment toward generative AI is generally positive, and remarkably, their sentiments are positively correlated with their exposure to AI. Among occupations, illustrators show exceptionally negative sentiment mainly due to concerns about the unethical usage of artworks in constructing AI. People use ChatGPT in diverse ways, and notably the casual usage in which they "play with" ChatGPT tends to be associated with positive sentiments. These findings would offer valuable lessons for policymaking on the emergence of new technology and also empirical insights for the considerations of future human-AI symbiosis. [ABSTRACT FROM AUTHOR]

The article discusses the ethical challenges posed by the use of text generators, specifically ChatGPT, in scientific publishing. ChatGPT is an artificial intelligence tool developed by OpenAI that can generate human-like texts. While it has the potential to improve language quality and productivity, it also raises concerns about plagiarism and the accuracy of generated texts. The article emphasizes the need for critical evaluation of texts generated by ChatGPT and similar tools, and highlights the importance of implementing policies to regulate their use in scientific papers. It also addresses the limitations of plagiarism detection software in detecting AI-generated texts and suggests the use of watermarks as a potential solution. The article concludes by calling for transparency and critical analysis in the use of ChatGPT in scientific writing to maintain the honesty and accuracy of science. [Extracted from the article]

This research intends to demonstrate the potential integration of large language models (LLMs) in accounting practices in Jordan. It is a mixed methods study that employs semi-structured interviews and content analysis of published financial reports. A total of 13 semi-structured interviews are conducted with various accounting professionals, such as accountant, financial analyst, financial controller, auditor, tax consultant, and finance manager. In addition, the study includes a thorough content analysis of financial reports, which reveals a compelling pattern highlighting the distinct narrative content richness prevalent across financial, industrial, and service sectors. The results emphasize the need for sector-specific adaptation, suggesting a paradigm shift in financial reporting practices. This study represents the initial empirical exploration in Jordan. It serves as a bridge between theory and application, offering both theoretical insights and practical guidance for accounting professionals. Ultimately, the study envisions a future where LLMs significantly enrich financial reporting practices across diverse sectors. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) tools, notably ChatGPT, are increasingly recognised for their transformative potential in higher education. This study employs a detailed case study approach complemented by a survey, delving into ChatGPT's impact on pedagogical practices, student engagement, and academic performance. It involved 74 undergraduate and postgraduate students enrolled in data analytics courses in Australia. The quantitative analysis highlights ChatGPT's role in providing personalised and on-demand support, which is highly valued among users for its flexibility and responsiveness, meeting a critical demand in educational settings. Notably, the study identifies a medium effect size ( η 2 = 0.173 ) in perceived benefits, indicating that ChatGPT accounts for approximately 17.3% of the variance in improved academic outcomes. However, challenges such as ChatGPT's limited understanding of complex queries and the lack of human interactions are primary concerns, with a medium effect size ( η 2 = 0.289 ) suggesting significant areas for improvement. Furthermore, statistical analyses reveal a clear relationship between the frequency of ChatGPT usage and the perception of its benefits, underscoring the transformative potential for users who have integrated it into their academic practices. Despite these challenges, the differential impact on users versus non-users highlights the potential for ChatGPT to foster more engaging and effective educational practices. The findings advocate for targeted strategies to epitomise ChatGPT's integration into educational settings, emphasising the need for ongoing research and the development of comprehensive guidelines to navigate its complexities and maximise its educational benefits. [ABSTRACT FROM AUTHOR]

This study examines the efficacy of artificial intelligence (AI) in creating parallel test items compared to human-made ones. Two test forms were developed: one consisting of 20 existing human-made items and another with 20 new items generated with ChatGPT assistance. Expert reviews confirmed the content parallelism of the two test forms. Forty-three university students then completed the 40 test items presented randomly from both forms on a final test. Statistical analyses of student performance indicated comparability between the AI-human-made and human-made test forms. Despite limitations such as sample size and reliance on classical test theory (CTT), the findings suggest ChatGPT's potential to assist teachers in test item creation, reducing workload and saving time. These results highlight ChatGPT's value in educational assessment and emphasize the need for further research and development in this area. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) chatbots are increasingly becoming integral components of the digital learning ecosystem. As AI technologies continue to evolve, it is crucial to understand the factors influencing their adoption and use among students in higher education. This study is undertaken against this backdrop to explore the behavioral determinants associated with the use of the AI Chatbot, ChatGPT, among university students. The investigation delves into the role of ChatGPT's self-learning capabilities and their influence on students' knowledge acquisition and application, subsequently affecting the individual impact. It further elucidates the correlation of chatbot personalization with novelty value and benefits, underscoring their importance in shaping students' behavioral intentions. Notably, individual impact is revealed to have a positive association with perceived benefits and behavioral intention. The study also brings to light potential barriers to AI chatbot adoption, identifying privacy concerns, technophobia, and guilt feelings as significant detractors from behavioral intention. However, despite these impediments, innovativeness emerges as a positive influencer, enhancing behavioral intention and actual behavior. This comprehensive exploration of the multifaceted influences on student behavior in the context of AI chatbot utilization provides a robust foundation for future research. It also offers invaluable insights for AI chatbot developers and educators, aiding them in crafting more effective strategies for AI integration in educational settings. [ABSTRACT FROM AUTHOR]

Over the last four decades, studies have investigated the incorporation of Artificial Intelligence (AI) into education. A recent prominent AI-powered technology that has impacted the education sector is ChatGPT. This article provides a systematic review of 14 empirical studies incorporating ChatGPT into various educational settings, published in 2022 and before the 10th of April 2023—the date of conducting the search process. It carefully followed the essential steps outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, as well as Okoli's (Okoli in Commun Assoc Inf Syst, 2015) steps for conducting a rigorous and transparent systematic review. In this review, we aimed to explore how students and teachers have utilized ChatGPT in various educational settings, as well as the primary findings of those studies. By employing Creswell's (Creswell in Educational research: planning, conducting, and evaluating quantitative and qualitative research [Ebook], Pearson Education, London, 2015) coding techniques for data extraction and interpretation, we sought to gain insight into their initial attempts at ChatGPT incorporation into education. This approach also enabled us to extract insights and considerations that can facilitate its effective and responsible use in future educational contexts. The results of this review show that learners have utilized ChatGPT as a virtual intelligent assistant, where it offered instant feedback, on-demand answers, and explanations of complex topics. Additionally, learners have used it to enhance their writing and language skills by generating ideas, composing essays, summarizing, translating, paraphrasing texts, or checking grammar. Moreover, learners turned to it as an aiding tool to facilitate their directed and personalized learning by assisting in understanding concepts and homework, providing structured learning plans, and clarifying assignments and tasks. However, the results of specific studies (n = 3, 21.4%) show that overuse of ChatGPT may negatively impact innovative capacities and collaborative learning competencies among learners. Educators, on the other hand, have utilized ChatGPT to create lesson plans, generate quizzes, and provide additional resources, which helped them enhance their productivity and efficiency and promote different teaching methodologies. Despite these benefits, the majority of the reviewed studies recommend the importance of conducting structured training, support, and clear guidelines for both learners and educators to mitigate the drawbacks. This includes developing critical evaluation skills to assess the accuracy and relevance of information provided by ChatGPT, as well as strategies for integrating human interaction and collaboration into learning activities that involve AI tools. Furthermore, they also recommend ongoing research and proactive dialogue with policymakers, stakeholders, and educational practitioners to refine and enhance the use of AI in learning environments. This review could serve as an insightful resource for practitioners who seek to integrate ChatGPT into education and stimulate further research in the field. [ABSTRACT FROM AUTHOR]

The success of the conversational AI system ChatGPT has triggered an avalanche of studies that explore its applications in research and education. There are also high hopes that, in addition to such particular usages, it could lead to artificial general intelligence (AGI) that means to human-level intelligence. Such aspirations, however, need to be grounded by actual scientific means to ensure faithful statements and evaluations of the current situation. The purpose of this article is to put ChatGPT into perspective and to outline a way forward that might instead lead to an artificial special intelligence (ASI), a notion we introduce. The underlying idea of ASI is based on an environment that consists only of text. We will show that this avoids the problem of embodiment of an agent and leads to a system with restricted capabilities compared to AGI. Furthermore, we discuss gated actions as a means of large language models to moderate ethical concerns. [ABSTRACT FROM AUTHOR]

Limited studies exist on faculty members or lecturers' perception and behavioural acceptance of artificial intelligence (AI) (e.g. ChatGPT) for their students' benefit. Teachers are the decision-makers for students' teaching and classroom activities. In this regard, the study examined lecturers' use of AI-powered tools and the factors that influence the acceptance of AI in teaching and learning in universities. An online survey was conducted using a cross-sectional design, and the results were analysed using SPSS and SmartPLS. The study findings revealed that more than two-thirds (84%) of lecturers are willing to accept AI for their students, while 16% stated non-acceptance of AI for students. Factors such as years of teaching experience, institutional support for AI use, and attitude towards AI proved to be significant predictors of AI acceptance in education. Key factors influencing lecturers' acceptance of AI for their students include perceived pedagogical affordances, organisational policies and incentives, perceived complexity and usability and socio-cultural context. By addressing teacher concerns through supportive policies, user-friendly interfaces, and alignment with pedagogical goals, higher education institutions can create a more fertile ground for AI adoption. [ABSTRACT FROM AUTHOR]

With the rapid emergence of artificial intelligence (AI) tools in the academic realm, understanding their implications, advantages, and challenges becomes crucial. ChatGPT, a leading AI conversational model, has gained significant traction in educational settings, warranting a comprehensive investigation into its academic impact. This systematic review aimed to elucidate the current state of research regarding implementing ChatGPT in academic cultures, focusing on its applications, challenges, and potential in reshaping contemporary pedagogies. An exhaustive review of 32 peer-reviewed articles from 2023 encompassed categorizing diverse research fields, journals, and studies. The research then delved into the challenges, factors affecting its use, and the myriad opportunities ChatGPT offers within academic settings. An overwhelming 75% of the studies emphasized the relevance of ChatGPT and generative AI tools within higher education, underscoring its importance. Significant challenges identified included pedagogical integration (31.25%) and student engagement (15.63%). However, ChatGPT's potentially inefficient content creation (25.00%) and enhanced personalized learning (21.88%) presented promising avenues for reshaping educational experiences. Furthermore, the tool's adaptability in catering to diverse student needs and fostering collaborative environments was notable. ChatGPT emerges as a transformative force in academia, with vast potential to revolutionize pedagogical practices. Yet, academic institutions must address inherent challenges to harness their full capabilities. Future directions point towards a symbiotic integration, with AI complementing human educators to promote inclusive, dynamic learning. [ABSTRACT FROM AUTHOR]

Free-text analysis using machine learning (ML)-based natural language processing (NLP) shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained Transformer (ChatGPT) has demonstrated preliminary initial feasibility for this purpose; however, whether it can accurately assess mental illness remains to be determined. This study evaluates the effectiveness of ChatGPT and the text-embedding-ada-002 (ADA) model in detecting post-traumatic stress disorder following childbirth (CB-PTSD), a maternal postpartum mental illness affecting millions of women annually, with no standard screening protocol. Using a sample of 1295 women who gave birth in the last six months and were 18+ years old, recruited through hospital announcements, social media, and professional organizations, we explore ChatGPT's and ADA's potential to screen for CB-PTSD by analyzing maternal childbirth narratives. The PTSD Checklist for DSM-5 (PCL-5; cutoff 31) was used to assess CB-PTSD. By developing an ML model that utilizes numerical vector representation of the ADA model, we identify CB-PTSD via narrative classification. Our model outperformed (F1 score: 0.81) ChatGPT and six previously published large text-embedding models trained on mental health or clinical domains data, suggesting that the ADA model can be harnessed to identify CB-PTSD. Our modeling approach could be generalized to assess other mental health disorders. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) is rapidly changing communication and technology-driven content creation and is also being used more frequently in education. Despite these advancements, AI-powered automated scoring in international large-scale assessments (ILSAs) remains largely unexplored due to the scoring challenges associated with processing large amounts of multilingual responses. However, due to their low-stakes nature, ILSAs are an ideal ground for innovations and exploring new methodologies. Methods: This study proposes combining state-of-the-art machine translations (i.e., Google Translate & ChatGPT) and artificial neural networks (ANNs) to mitigate two key concerns of human scoring: inconsistency and high expense. We applied AI-based automated scoring to multilingual student responses from eight countries and six different languages, using six constructed response items from TIMSS 2019. Results: Automated scoring displayed comparable performance to human scoring, especially when the ANNs were trained and tested on ChatGPT-translated responses. Furthermore, psychometric characteristics derived from machine scores generally exhibited similarity to those obtained from human scores. These results can be considered as supportive evidence for the validity of automated scoring for survey assessments. Conclusions: This study highlights that automated scoring integrated with the recent machine translation holds great promise for consistent and resource-efficient scoring in ILSAs. [ABSTRACT FROM AUTHOR]

The Artificial Intelligence (AI) natural language model ChatGPT (Chat Generative Pre-trained Transformer), often referred to as ChatGPT-4, has a wide range of possible uses in the fields of research, business, academia, health, and similar fields. This language model can accomplish a number of academic jobs that were previously completed by people, taking a significant amount of time and effort. The purpose of the article is to investigate ChatGPT's potential opportunities and challenges in academia. To attain this objective, a review of relevant literature and online resources (news, articles, etc.) was carried out. The noticing-collecting-thinking approach was adopted to explore and categorize all observed concerns. The outcome of this study reveals that research, education, personal skill development, and social aspects constitute the four broad perspectives that articulate the opportunities and constraints of ChatGPT in academia. For instance, from the education perspective, ChatGPT can help students have a personalized learning experience. On the other hand, it might provide false information as well as lack the ability to generate responses on its own because those responses depend on training datasets, which may contain errors. Similarly, from the point of view of the personal skill development, this model may impair a person's capacity for critical thought and content production; while providing reading and writing practice sessions and relevant content, it can improve a person's language proficiency. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has garnered considerable interest in the field of language education in recent times; however, limited research has focused on the role of AI in the specific context of register knowledge learning during English language writing. This study aims to address this research gap by examining the impact of ChatGPT, an AI-powered chatbot, on the acquisition of register knowledge across various writing tasks. The research design employed a one-case shot pre-experimental design, with 11 voluntary participants selected through convenience sampling. Preliminary results indicate that students found ChatGPT beneficial for acquiring formal register knowledge but perceived it as unnecessary for informal writing. Additionally, the effectiveness of ChatGPT in teaching neutral register was questioned by the participants. This research contributes to the existing literature by shedding new light on the effects of AI-generated chatbots in register learning during the writing process, offering insights into their potential as learning assistants. Further investigation is warranted to explore the broader implications and applications of AI in language learning contexts. [ABSTRACT FROM AUTHOR]

As AI systems proliferate, their greenhouse gas emissions are an increasingly important concern for human societies. In this article, we present a comparative analysis of the carbon emissions associated with AI systems (ChatGPT, BLOOM, DALL-E2, Midjourney) and human individuals performing equivalent writing and illustrating tasks. Our findings reveal that AI systems emit between 130 and 1500 times less CO2e per page of text generated compared to human writers, while AI illustration systems emit between 310 and 2900 times less CO2e per image than their human counterparts. Emissions analyses do not account for social impacts such as professional displacement, legality, and rebound effects. In addition, AI is not a substitute for all human tasks. Nevertheless, at present, the use of AI holds the potential to carry out several major activities at much lower emission levels than can humans. [ABSTRACT FROM AUTHOR]

The emergence of publicly accessible artificial intelligence (AI) large language models such as ChatGPT has given rise to global conversations on the implications of AI capabilities. Emergent research on AI has challenged the assumption that creative potential is a uniquely human trait thus, there seems to be a disconnect between human perception versus what AI is objectively capable of creating. Here, we aimed to assess the creative potential of humans in comparison to AI. In the present study, human participants (N = 151) and GPT-4 provided responses for the Alternative Uses Task, Consequences Task, and Divergent Associations Task. We found that AI was robustly more creative along each divergent thinking measurement in comparison to the human counterparts. Specifically, when controlling for fluency of responses, AI was more original and elaborate. The present findings suggest that the current state of AI language models demonstrate higher creative potential than human respondents. [ABSTRACT FROM AUTHOR]

Artificial intelligence models, like ChatGPT, have the potential to revolutionize higher education when implemented properly. This study aimed to investigate the factors influencing university students' attitudes and usage of ChatGPT in Arab countries. The survey instrument "TAME-ChatGPT" was administered to 2240 participants from Iraq, Kuwait, Egypt, Lebanon, and Jordan. Of those, 46.8% heard of ChatGPT, and 52.6% used it before the study. The results indicated that a positive attitude and usage of ChatGPT were determined by factors like ease of use, positive attitude towards technology, social influence, perceived usefulness, behavioral/cognitive influences, low perceived risks, and low anxiety. Confirmatory factor analysis indicated the adequacy of the "TAME-ChatGPT" constructs. Multivariate analysis demonstrated that the attitude towards ChatGPT usage was significantly influenced by country of residence, age, university type, and recent academic performance. This study validated "TAME-ChatGPT" as a useful tool for assessing ChatGPT adoption among university students. The successful integration of ChatGPT in higher education relies on the perceived ease of use, perceived usefulness, positive attitude towards technology, social influence, behavioral/cognitive elements, low anxiety, and minimal perceived risks. Policies for ChatGPT adoption in higher education should be tailored to individual contexts, considering the variations in student attitudes observed in this study. [ABSTRACT FROM AUTHOR]