Generation AI Research Articles

Integrating Generative AI in Cloud Computing Architectures: Transformative Impacts on Efficiency and Innovation

Integrating Generative AI in Cloud Computing Architectures: Transformative Impacts on Efficiency and Innovation

Theory to Practice: An Assessment Framework for Generative AI.

Theory to Practice: An Assessment Framework for Generative AI.

Approach Generative AI Tools Proactively or Risk Bypassing the Learning Process in Higher Education

Approach Generative AI Tools Proactively or Risk Bypassing the Learning Process in Higher Education

Generative AI in education: ChatGPT-4 in evaluating students’ written responses

ABSTRACT The study highlights ChatGPT-4’s potential in educational settings for the evaluation of university students’ open-ended written examination responses. ChatGPT-4 evaluated 54 written responses, ranging from 24 to 256 words in English. It assessed each response using five criteria and assigned a grade on a six-point scale from fail to excellent, resulting in 3,240 evaluations. Verification-based chain-of-thought prompting with the RAG framework ensured ChatGPT-4’s accurate recall of responses and secure alignment in the university’s evaluation criteria. ChatGPT-4’s grading showed good consistency with the teacher’s grading. Mistakes in recalls and discrepancies between ChatGPT-4 and teacher assessments could be reduced. The results suggest a promising potential for using LLMs like ChatGPT-4 in academic written response evaluations.

The micropolitical landscape of publicly discoverable policies for generative AI in large US school districts

ABSTRACT While the use of generative AI (genAI) in K12 schools is increasing, it is poorly understood from a policy perspective. There are significant tensions in technology integration in education between public interests for social good and pressure from educational technology companies to view schools as markets. This study examined genAI policy efforts in the 50 largest US school districts by student enrolment in fall 2023 and spring 2024. A content analysis of documents from districts, states and media sources revealed micropolitical, rather than top-down, activities where districts were attempting policy making about genAI in varied ways and at varied paces. Educational technology vendors seemed to be opening space for substantial influence in policy decisions simultaneously. Understandings about these micropolitical activities of policy making have the potential to support shared decision-making and co-responsibility as important opportunities for disrupting current dynamics of influence on educational policy making in US schools.

The Use of Generative Artificial Intelligence for Business Decision-Making

The purpose of this study was to develop autonomous artificial intelligence agents capable of working as a cohesive group to solve intricate decision-making processes, ultimately pushing the boundaries of artificial intelligence’s applicability in high-stakes and real-world scenarios. An autonomous multi-agent model was designed and deployed using the Analytic Hierarchy Process (AHP) decision-making framework, with autonomous AI agents, such as CrewAI and AutoGen, orchestrating multiple stages of activities performed by four distinct agents leveraging generative AI (GenAI). These agents were applied to a use case for proof of concept. The agents used a qualitative dataset to generate management recommendations based on cost and market feasibility considerations. The model was tested with publicly available customer feedback data on oatmeal cookies. It synthesized 913 customer reviews, identified common complaints, provided a summary of potential solutions, and generated a summary of market opportunities, along with relevant challenges. Although a subject matter expert's review is necessary to evaluate the practicality and relevance of the recommendations, the results demonstrated the high potential of multi-agent models in synthesizing and distilling large datasets into actionable insights, thereby augmenting decision-making processes in business contexts. The model's modular design allows for enhancements in quality, accuracy, and practicality by incorporating additional datasets and new agents. This study underscores that the integration of GenAI within a multi-agent model empowers businesses to swiftly transform vast amounts of business intelligence data into practical recommendations.

Are We Keeping up With the Innovation in Generative AI?

Are We Keeping up With the Innovation in Generative AI?

Why students use or not use generative AI: Student conceptions, concerns, and implications for engineering education

Why students use or not use generative AI: Student conceptions, concerns, and implications for engineering education

ChatGPT in language teaching and learning: Exploring the road we’re travelling

This introduction to the special issue examines the integration of ChatGPT and similar generative AI technologies in language teaching and learning. It examines the rapid evolution of AI tools since 2022, with particular focus on their applications in educational settings and the mixed responses they have generated among educators and learners. While some educators embrace these tools for their potential to automate and enhance instructional tasks, others express concern over issues such as academic integrity, accuracy, and potential job displacement. This special issue explores various perspectives on the use of ChatGPT, including its benefits in providing non-judgmental feedback, aiding material creation, and enhancing language practice, alongside challenges like ethical use, student over-reliance, and the evolving digital literacy demands for both teachers and students. The collection of articles in this special issue seeks to balance the hype with practical insights and offers a framework for understanding the nuanced impacts of generative AI on second language education.

Tackling the terminology.

Not quite sure what ML, NLP and generative AI actually are? This jargon buster explains all.

Generative AI in the Software Modeling Classroom: An Experience Report With ChatGPT and Unified Modeling Language

Generative AI in the Software Modeling Classroom: An Experience Report With ChatGPT and Unified Modeling Language

ChatGPT in language teaching and learning: Exploring the road we’re travelling

This introduction to the special issue examines the integration of ChatGPT and similar generative AI technologies in language teaching and learning. It examines the rapid evolution of AI tools since 2022, with particular focus on their applications in educational settings and the mixed responses they have generated among educators and learners. While some educators embrace these tools for their potential to automate and enhance instructional tasks, others express concern over issues such as academic integrity, accuracy, and potential job displacement. This special issue explores various perspectives on the use of ChatGPT, including its benefits in providing non-judgmental feedback, aiding material creation, and enhancing language practice, alongside challenges like ethical use, student over-reliance, and the evolving digital literacy demands for both teachers and students. The collection of articles in this special issue seeks to balance the hype with practical insights and offers a framework for understanding the nuanced impacts of generative AI on second language education.

Collaborative Forensic Autopsy Documentation and Supervised Report Generation Using a Hybrid Mixed-Reality Environment and Generative AI.

Forensic investigation is a complex procedure involving experts working together to establish cause of death and report findings to legal authorities. While new technologies are being developed to provide better post-mortem imaging capabilities-including mixed-reality (MR) tools to support 3D visualisation of such data-these tools do not integrate seamlessly into their existing collaborative workflow and report authoring process, requiring extra steps, e.g. to extract imagery from the MR tool and combine with physical autopsy findings for inclusion in the report. Therefore, in this work we design and evaluate a new forensic autopsy report generation workflow and present a novel documentation system using hybrid mixed-reality approaches to integrate visualisation, voice and hand interaction, as well as collaboration and procedure recording. Our preliminary findings indicate that this approach has the potential to improve data management, aid reviewability, and thus, achieve more robust standards. Further, it potentially streamlines report generation and minimise dependency on external tools and assistance, reducing autopsy time and related costs. This system also offers significant potential for education. A free copy of this paper and all supplemental materials are available at https://osf.io/ygfzx.

Tales From the Trenches: Expectations and Challenges From Practice for Code Review in the Generative AI Era

Tales From the Trenches: Expectations and Challenges From Practice for Code Review in the Generative AI Era

A Unified Framework for Guiding Generative AI With Wireless Perception in Resource Constrained Mobile Edge Networks

A Unified Framework for Guiding Generative AI With Wireless Perception in Resource Constrained Mobile Edge Networks

Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing 5.0

Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing 5.0

Generative AI Disproportionately Harms Long Tail Users

Generative AI Disproportionately Harms Long Tail Users

Technology shock of ChatGPT, social attention and firm value: Evidence from China

The release of ChatGPT has attracted widespread attention and triggered fluctuations in the capital market. This study employs difference-in-differences (DID) and event study (ES) to investigate the effects of ChatGPT's release on the cumulative abnormal return (CAR) of listed companies in China. The results reveal that a series of ChatGPT launch events, including GPT-3.5 and GPT-4, have a significantly positive impact on the firm value of the companies focused on ChatGPT, with dynamic effects. In the initial two months after the release of ChatGPT, the Chinese stock market exhibited an undervaluation of GPT-focused companies, indicating information asymmetry and competitive substitution effect. With the widespread promotion of generative AI, social recognition of ChatGPT's potential value increased. This study verifies the moderation effect of social attention in strengthening ChatGPT's impact, demonstrating that a higher search index for ChatGPT enhances stock returns for GPT-focused companies. Heterogeneity tests reveal that the impact of ChatGPT is significantly positive for large or non-state-owned companies, while small or state-owned companies show no significant effect. From the perspective of labor structure, companies dominated by technical and production personnel experience positive effects, whereas those dominated by sales personnel do not. In the eastern regions with more favorable digital economic innovation environments, companies experience a notably positive impact. This paper provides a theoretical explanation and empirical evidence for the microeconomic impact of generative AI in the Chinese context, offering valuable insights for both government and firms.

Toward Responsible AI in the Era of Generative AI: A Reference Architecture for Designing Foundation Model-Based Systems

Toward Responsible AI in the Era of Generative AI: A Reference Architecture for Designing Foundation Model-Based Systems

Emotion and Inspiration through Generative AI Art

Art inspires emotion. The process of creation invigorates the senses and keeps the researcher on fire. To create artistic masterpieces using words through natural language processing further stimulates the mind and helps to overcome writer’s block. An AI tool interprets the words and transforms them into artistic expressions that feel like magic. Yet, AI art is not without consequences. Critics challenge the digital rights of AI-generated images, noting that they are derivative works. This paper examines the joy of creation as well as the copyright challenges creators face when writing detailed prompts to generate amazing artwork. The role of affective computing illustrates the relationship between the designer and the AI tool while ethical concerns remind designers to use caution in their prompts. The article examines the architecture of a prompt, the characteristics to enhance it, and examples of generative AI art. Additional content includes references to handouts, art catalogs, and legal opinions regarding the copyright debate. The article concludes with a recommendation with respect to the intellectual property rights of artists and their creative work.