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Articles 61 - 90 of 299
Full-Text Articles in Computer Sciences
Building An Inclusive Ai Chatbot For Diverse Student Communities At Cal Poly: Uplift Ai, Gideon Telahun
Building An Inclusive Ai Chatbot For Diverse Student Communities At Cal Poly: Uplift Ai, Gideon Telahun
College of Engineering Summer Undergraduate Research Program
This research project will investigate the ability of advanced Large Language Models (LLMs) to identify and assess misinformation across diverse forms of media, including text, images, and video. In an age where misleading content spreads rapidly across digital platforms, evaluating the reliability and integrity of AI systems tasked with fact-checking is critical. We will develop a comprehensive dataset composed of factual and misleading examples drawn from various well-known and reliable fact-checking organizations. Each item will be independently reviewed and transparently labeled to ensure reproducibility. We will then prompt a curated group of state-of-the-art LLMs—including GPT-4, Claude, Gemini, Perplexity, Grok, and …
Trust And Ethics In Ai-Driven E-Commerce: Persuasion Vs. Privacy, Akriti Nepal
Trust And Ethics In Ai-Driven E-Commerce: Persuasion Vs. Privacy, Akriti Nepal
Student Publications
This study examines how AI-driven features in e-commerce influence user satisfaction and the role of trust in these interactions. Using a survey-based dataset of 100 consumers, we investigated whether trust moderates or mediates the impact of AI persuasiveness and perceptions of bias, intrusiveness, and preference understanding on satisfaction. Results indicate that AI’s perceived ability to understand user preferences strongly predicts satisfaction, while trust partially mediates the relationship between helpful AI features and urgency messages and user satisfaction. Conversely, trust did not significantly moderate these relationships, and concerns about bias and intrusiveness had minimal impact. Findings suggest that AI-driven satisfaction is …
Improving Universities Through The Use Of Ai & Transformative Technology: A Case Study Analysis At The University Of South Carolina, Cameron A. Caulk
Improving Universities Through The Use Of Ai & Transformative Technology: A Case Study Analysis At The University Of South Carolina, Cameron A. Caulk
Senior Theses
This thesis aims to give university leaders a practical guide to implementing AI, using lessons learned from the University of South Carolina’s experience as a case study. The project started with a review of literature and industry practices for the Finance & Administration division, which led to key deliverables like AI usage guidelines, DoIT’s position paper on AI systems, and the ParkUSC parking app. One ongoing project, Project Shuttlecock, even sets the stage for future AI initiatives at the university.
AI holds immense promise, but universities often hesitate due to concerns about ethics, costs, and the learning curve for staff …
Governance In The Absence Of Government, Tracy Hresko Pearl
Governance In The Absence Of Government, Tracy Hresko Pearl
Faculty Articles
Artificial intelligence (AI) is advancing at an unprecedented pace, with generative systems exerting growing influence over social, economic, and political life. While Al offers opportunities for innovation and efficiency, it also poses risks ranging from misinformation and job displacement to existential threats if highly autonomous systems evade human control. Across industry, government, and civil society, there is broad consensus that Al requires oversight.
Yet traditional U.S. regulatory approaches face six significant barriers: (1) technology outpacing legislation, (2) limited Al expertise among policymakers, (3) regulatory capture, (4) political gridlock, (5) outdated governance structures, and (6) the inherent complexity of Al. Combined …
Optimizing Cybersecurity Through Ai Predictive Analytics And Human Expertise, Cathy Mae C. Dutong
Optimizing Cybersecurity Through Ai Predictive Analytics And Human Expertise, Cathy Mae C. Dutong
Journal of the Symposium of University Research and Creative Expression
Project Mentor(s): Hideki Takei, DBA
As cybersecurity threats evolve in complexity and scale, the reliance on artificial intelligence (AI) has become increasingly prevalent across both public and private sectors. This study examines the dual role of AI-driven predictive analytics in strengthening organizational cybersecurity, while addressing the ongoing need for human oversight. Through a mixed-method approach, combining survey data from cybersecurity professionals with an extensive literature review, this research analyzes AI's capacity to detect emerging threats, the systemic challenges associated with AI integration, and the indispensable role of human expertise in interpreting AI outputs. Findings indicate that while AI enhances proactive …
Ai Exposure And The Future Of Work: Linking Task-Based Measures To U.S. Occupational Employment Projections, Erik Vasilauskas, Michael Horrigan
Ai Exposure And The Future Of Work: Linking Task-Based Measures To U.S. Occupational Employment Projections, Erik Vasilauskas, Michael Horrigan
Reports
No abstract provided.
Bring Back The Blue-Book Exam: In An Age Of Ai, We Need To Return To Handwritten Assignments., Katie Day Good
Bring Back The Blue-Book Exam: In An Age Of Ai, We Need To Return To Handwritten Assignments., Katie Day Good
University Faculty Publications and Creative Works
When ChatGPT was released three years ago, its ability to mimic human writing unsettled me. I’m a professor of communication; what did it mean that my students now had access to a machine that could communicate for them? My initial unease led to a half-joke with my colleagues. Universities could survive this threat, I ventured, but only if we reverted back to 19th-century teaching methods like Socratic dialogue, oral defenses, and lengthy essay exams. This once-laughable scenario is now a serious consideration for many faculty, including me.
Like many professors, I’ve recently abandoned take-home essays in favor of blue-book exams. …
Bibliography For "Ai 2.0: Is Ai A Tool, A Threat, Or A Teammate?", Annikah Carpio, Sally Park, Melody Madrigal
Bibliography For "Ai 2.0: Is Ai A Tool, A Threat, Or A Teammate?", Annikah Carpio, Sally Park, Melody Madrigal
Library Displays and Bibliographies
A bibliography created to support a display about AI 2.0 in August 2025 at the Leatherby Libraries at Chapman University.
Fact-Checker: A Web Application For Leveraging Large Language Models For Fact-Checking Youtube Videos, Andrew R. Craig
Fact-Checker: A Web Application For Leveraging Large Language Models For Fact-Checking Youtube Videos, Andrew R. Craig
Electronic Theses, Projects, and Dissertations
Fact-Checker is a web application that allows users to fact-check YouTube videos. It feeds YouTube’s closed captioning transcript to a large language model (LLM) to extract claims. It then uses multiple LLMs, such as Gemini, Llama, and Claude, to verify these claims. The modular design makes it easy to change to a different LLM or model if needed. The application is built using Python for access to Application Programming Interfaces (APIs) and Streamlit as the front-end framework. The utilization of Docker and Dockerfiles enables easy distribution and deployment. It enables the application to be deployed on almost any hardware platform …
Ai In The Judiciary: The Singapore Case, Nydia Remolina Leon
Ai In The Judiciary: The Singapore Case, Nydia Remolina Leon
Research Collection Yong Pung How School Of Law
This paper examines the integration of Artificial Intelligence (AI) within the judicial system of Singapore. Singapore's judiciary has embraced AI not as a tool for adjudication, but as an augmentative instrument for legal research, procedural efficiency, and access to justice. It provides a detailed account of AI use cases in the courts, including case summarization, evidence review, assistance for selfrepresented litigants, and tools like the Divorce Assets Informative Division Estimator. The discussion then turns to the legal profession, exploring how law firms in Singapore are adopting AI technologies. The paper also addresses how AI implementation in the judicial system is …
Teaching Ai Ethics And Skepticism: The Impact Of Instruction On Ethical Usage On Students’ Perceptions, Jenna D. Justin
Teaching Ai Ethics And Skepticism: The Impact Of Instruction On Ethical Usage On Students’ Perceptions, Jenna D. Justin
Journal of Practitioner Research
This study investigates the ethical implications of artificial intelligence (AI) in K-12 education, focusing on how explicit instruction influences students' perceptions of AI tools like ChatGPT. Conducted with 80 sixth-grade students at A.D. Henderson University School and FAU High School, the research tracks changes in student understanding and skepticism of AI following a World History unit. Pre- and post-instruction surveys revealed a decline in comfort with AI as students became more aware of its ethical concerns, including plagiarism, bias, and misinformation. The findings suggest integrating AI ethics into the middle school curriculum to foster responsible AI usage among students.
Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai
Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai
Pepperdine Dispute Resolution Law Journal
Arbitration agreements are everywhere in the United States. These agreements already block access to courts in a troubling manner, and pursuant to these agreements, parties must resolve their disputes before a private, human arbitrator with broad, virtually unreviewable powers. However, with the growth of AI, companies could easily redraft their contracts to require arbitration before non-human bots or AI arbitrators instead of a human arbitrator. Based on the history, values, policy, and text of the Federal Arbitration Act (FAA), this Article concludes that the FAA would govern and support the use of an AI arbitrator. As a result, a pre-dispute …
Limitations Of Using Large Language Models For Automated Essay Scoring, Thomas A. Fink
Limitations Of Using Large Language Models For Automated Essay Scoring, Thomas A. Fink
Theses
Background: Automated essay scoring (AES) is a challenging deep learning problem. The two most widely used methods for predicting essay quality scores, supervised learning-based and LLM-based, have their own limitations. Although supervised learning-based methods are more accurate, they only predict a score and do not offer descriptive feedback to students. On the other hand, LLM-based methods can offer rubric-guided feedback but are known to be less accurate.
Methods: This work focuses on improving the accuracy of state-of-the-art LLM-based AES methods. We began by thoroughly investigating why these methods were performing poorly for certain datasets and certain examples. This led us …
"Chatgpt Told Me To Say It": Ai Chatbots And Class Participation Apprehension In University Students, Daisuke Akiba
"Chatgpt Told Me To Say It": Ai Chatbots And Class Participation Apprehension In University Students, Daisuke Akiba
Publications and Research
The growing prevalence of AI chatbots in everyday life has prompted educators to explore their potential applications in promoting student success, including support for classroom engagement and communication. This exploratory study emerged from semester-long observations of class participation apprehensions in an introductory educational psychology course, examining how chatbots might scaffold students toward active and independent classroom contribution. Four students experiencing situational participation anxiety voluntarily participated in a pilot intervention using AI chatbots as virtual peer partners. Following comprehensive training in AI use and prompt design given to the entire class, participants employed systematic consultation frameworks for managing classroom discourse trepidations. …
Serving Others Using Generative Ai, Kenneth C. Arnold
Serving Others Using Generative Ai, Kenneth C. Arnold
University Faculty Publications and Creative Works
Ken Arnold, computer science professor at Calvin University, explores the idea of use Generative AI as a tool to help us serve others.
Revitalization Of Endangered Languages With Ai, Ivory Yang
Revitalization Of Endangered Languages With Ai, Ivory Yang
Dartmouth College Master’s Theses
The preservation and revitalization of endangered languages, particularly those with minimal digital presence, presents significant challenges for computational linguistics. This thesis addresses these challenges by proposing novel methods for language identification and data generation, focusing on underrepresented Indigenous languages, specifically Nüshu, Native American and Native Alaskan languages.
In the first study, a COLING 2025 paper, we present NüshuRescue, an AI-driven framework designed to facilitate the preservation of Nüshu, an endangered script used exclusively by Yao women in China. Using minimal seed data, we demonstrate how GPT-4-Turbo can generate new translations, expanding a publicly available Nüshu-Chinese corpus, achieving 48.69% accuracy in …
Object-Based Image Analysis And Artificial Intelligence Identification Of Anthropogenic Disturbance On Lesser Prairie Chicken Habitat In Cheyenne County, Colorado, Tara Hoelzer
Geography and the Environment: Graduate Student Capstones
Renewable energy projects often require extensive landcover for their operations. When one of these projects encroaches into territory of threatened species, such as Lesser Prairie Chickens, an analysis of habitat suitability and human disturbance is required to proceed. Traditionally, this involved manually reviewing aerial imagery within a 6-mile radius, digitizing features, and interpreting them using a human technician—an approach that was time-consuming and prone to human error. By using pretrained AI models within Model Builder™, the identification of roads and structures was automated, making the process faster and more consistent than manual visual analysis. As AI and technology continue to …
Evaluating Vision Language Model Capabilities For Time Series Interpretation: An Empirical Study With Conversation Duration And Psychological Flourishing Data From The Studentlife Dataset, Jusung Park
Computer Science Senior Theses
This research investigates the capability of Vision Language Models (VLMs), specifically ChatGPT‑4o, to interpret and predict psychological outcomes based on visual representations of time series data. Leveraging conversation duration metrics and psychological flourishing scores from the StudentLife dataset, this study rigorously evaluates the predictive accuracy of VLMs using various methods, including zero‑shot on raw data, zero‑shot on graph data, few‑shot learning, qualitative labeling, and chain‑of‑thought reasoning. Despite multiple methodological enhancements, predictive performance remains modest, revealing significant challenges in quantitative interpretation of visualized temporal data by current multimodal models. We demonstrate that standardizing input tokens by using graph images rather than …
"Opting Out Of Ai”: Exploring Perceptions, Reasons, And Concerns Behind Faculty Resistance To Generative Ai, Aya Shata
Hank Greenspun School of Journalism and Media Studies Faculty Research
Research on Generative Artificial Intelligence (GAI) in higher education primarily focuses on faculty use and experiences, with limited attention given to why some abstain from using it. Drawing from Innovation Resistance Theory, this study aims to address this gap by exploring the perceptions of both faculty users and non-users of GAI, identifying the reasons and concerns why they avoid GAI. A survey of 294 full-time higher education faculty from two mid-size U.S. public universities was conducted. Using qualitative and quantitative analysis, results show that over one-third of the faculty members opted out of using GAI for five primary reasons: not …
Ecological Footprint Analysis Of Chatgpt (Gpt-3), Isabella Boulais
Ecological Footprint Analysis Of Chatgpt (Gpt-3), Isabella Boulais
Computer Science and Software Engineering
Climate change is an escalating crisis that demands immediate action from all sectors, including the rapidly advancing field of artificial intelligence (AI). While AI offers climate solutions, its own environmental impact raises concerns. Unfortunately limited research due to rapid development, system complexity, and lack of standardized methodologies hinders our understanding of AI’s environmental consequences. This project aims to conduct a comprehensive ecological footprint analysis of OpenAI’s GPT-3 model that is used to power ChatGPT, establishing guidelines for assessing AI systems’ environmental impact and proposing a framework for improvement. Going beyond tracking carbon emissions, this project will outline the broader lifecycle …
Strategy And Stewardship In An Uncertain World, Havovi Joshi
Strategy And Stewardship In An Uncertain World, Havovi Joshi
Asian Management Insights
This issue, as we continue to celebrate Singapore Management University’s (SMU) 25th anniversary, we explore leadership in higher education, the rise of artificial intelligence (AI), ethical stewardship, and other challenges, highlighting how they intersect in our increasingly complex, fast-changing world.
Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal
Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal
Dissertations
Artificial intelligence (AI) has achieved remarkable performances across various domains. In most real-world applications, data often takes relational forms, such as graphs and networks, or sequential forms, such as text and time series. As AI evolves, specialized models have emerged to handle these structures; Graph Neural Networks (GNNs) for relational mining and Large Language Models (LLMs) for sequential understanding. Despite their success, these models face challenges in security, robustness, and interpretability. GNNs excel in relational reasoning but are vulnerable to adversarial manipulation and lack interpretability, while LLMs are strong in linguistic reasoning and generalization yet struggle with relational data and …
Integrating Artificial Intelligence In Orthopedic Care: Advancements In Bone Care And Future Directions, Rahul Kumar, Kyle Sporn, Joshua Ong, Ethan Waisberg, Phani Paladugu, Swapna Vaja, Tamer Hage, Tejas C. Sekhar, Amar S. Vadhera, Alex Ngo, Nasif Zaman, Alireza Tavakkoli, Mouayad Masalkhi
Integrating Artificial Intelligence In Orthopedic Care: Advancements In Bone Care And Future Directions, Rahul Kumar, Kyle Sporn, Joshua Ong, Ethan Waisberg, Phani Paladugu, Swapna Vaja, Tamer Hage, Tejas C. Sekhar, Amar S. Vadhera, Alex Ngo, Nasif Zaman, Alireza Tavakkoli, Mouayad Masalkhi
SKMC Student Presentations and Publications
Artificial intelligence (AI) is revolutionizing the field of orthopedic bioengineering by increasing diagnostic accuracy and surgical precision and improving patient outcomes. This review highlights using AI for orthopedics in preoperative planning, intraoperative robotics, smart implants, and bone regeneration. AI-powered imaging, automated 3D anatomical modeling, and robotic-assisted surgery have dramatically changed orthopedic practices. AI has improved surgical planning by enhancing complex image interpretation and providing augmented reality guidance to create highly accurate surgical strategies. Intraoperatively, robotic-assisted surgeries enhance accuracy and reduce human error while minimizing invasiveness. AI-powered smart implant sensors allow for in vivo monitoring, early complication detection, and individualized rehabilitation. …
Robotic Rhythm: A Contemporary Look At Ai-Driven Editing Tools’ Efficacy In Understanding And Replicating Creative Rhythm Editing Techniques., Alexander Selby-Lara, Charles Howard
Robotic Rhythm: A Contemporary Look At Ai-Driven Editing Tools’ Efficacy In Understanding And Replicating Creative Rhythm Editing Techniques., Alexander Selby-Lara, Charles Howard
Honors Thesis
It is undeniable that artificial intelligence (AI) has made its way into the film world. From AI-generated imagery and sound design in two 2025 Oscar nominees — The Brutalist and Emilia Pérez (Pulver) — to weekly updates and monthly beta releases of existing and new generative image and video models, AI-driven filmmaking tools are here to stay. But what does this mean for the post-production workflow? Much like camera development, editing technology has come a long way from flatbed film editors to Adobe Premiere Pro v. 25.0. Yet, despite each technological leap from system to system, the delicate task of …
Voice Interaction With Conversational Ai Could Facilitate Thoughtful Reflection And Substantive Revision In Writing, Jiho Kim, Philippe Laban, Xiang 'Anthony' Chen, Kenneth C. Arnold
Voice Interaction With Conversational Ai Could Facilitate Thoughtful Reflection And Substantive Revision In Writing, Jiho Kim, Philippe Laban, Xiang 'Anthony' Chen, Kenneth C. Arnold
University Faculty Publications and Creative Works
Writing well requires not only expressing ideas but also refining them through revision, a process facilitated by reflection. Prior research suggests that feedback delivered through dialogues, such as those in writing center tutoring sessions, can help writers reflect more thoughtfully on their work compared to static feedback. Recent advancements in multi-modal large language models (LLMs) now offer new possibilities for supporting interactive and expressive voice-based reflection in writing. In particular, we propose that LLM-generated static feedback can be repurposed as conversation starters, allowing writers to seek clarification, request examples, and ask follow-up questions, thereby fostering deeper reflection on their writing. …
Interaction-Required Suggestions For Control, Ownership, And Awareness In Human-Ai Co-Writing, Kenneth C. Arnold, Jiho Kim, Jason G. Chew, Jooha Yoo, Juyeong Kim, Ray Flanagan, Heonjae Kwon
Interaction-Required Suggestions For Control, Ownership, And Awareness In Human-Ai Co-Writing, Kenneth C. Arnold, Jiho Kim, Jason G. Chew, Jooha Yoo, Juyeong Kim, Ray Flanagan, Heonjae Kwon
University Faculty Publications and Creative Works
This paper explores interaction designs for gen-
erative AI interfaces that necessitate human in-
volvement throughout the generation process.
We argue that such interfaces can promote
cognitive engagement, agency, and thoughtful
decision-making. Through a case study in text
revision, we present and analyze two interac-
tion techniques: (1) using a predictive-text in-
teraction to type the assistant’s response to a
revision request, and (2) highlighting potential
edit opportunities in a document. Our imple-
mentations demonstrate how these approaches
reveal the landscape of writing possibilities and
enable fine-grained control. We discuss impli-
cations for human-AI writing partnerships and
future interaction design …
Intuiting Interaction: Meta-Reasoning And Meta-Learning As Foundations For Intelligent User Interfaces, Jeffrey Hsu
Intuiting Interaction: Meta-Reasoning And Meta-Learning As Foundations For Intelligent User Interfaces, Jeffrey Hsu
Theses and Dissertations
This research presents MARCO—a cognitive framework for Intelligent User Interfaces that uses meta-reasoning for context-aware adaptation across diverse tasks. It integrates multiple reasoning modules coordinated by a Meta-Cognitive Unit that selects strategies based on evolving demands. Evaluations show MARCO outperforms baselines in reasoning accuracy and computational efficiency.
Diversity-Augmented Training For Generalizable Ai Agents, Wenjun Li
Diversity-Augmented Training For Generalizable Ai Agents, Wenjun Li
Dissertations and Theses Collection (Open Access)
Deep Reinforcement Learning (RL) has achieved remarkable success over the past decade, from superhuman performance in video games to real-world applications like robotics. However, RL models often lack generalization, making them unreliable when deployed in unfamiliar scenarios. For example, robots must adapt to varying terrains with different slopes and obstacles, yet standard RL training does not explicitly promote such adaptability. While various methods have been proposed to enhance RL robustness, achieving reliable generalization remains an open challenge.
This dissertation focuses on improving the generalization capability of agents in three major settings: infinite horizon RL agents, finite horizon RL agents, and …
Artificial Intelligence Through Young Eyes: A Study Of Students’ Perspectives And Experiences With Artificial Intelligence In Education, Chad Preston Salyer
Artificial Intelligence Through Young Eyes: A Study Of Students’ Perspectives And Experiences With Artificial Intelligence In Education, Chad Preston Salyer
Ed.D. Dissertations
Artificial intelligence was an emergent and powerful new force in education. The public release of ChatGPT 3.0 in 2022 transformed learning for many students. This phenomenological qualitative study sought to record and analyze student’s perspectives on the influence of artificial intelligence on their learning routines. This study collected data through surveys and interviews with undergraduate students, analyzing patterns of artificial intelligence usage, perceived benefits, and challenges. The findings revealed that most students used artificial intelligence as a primary learning tool and that those students viewed artificial intelligence as beneficial for personalized learning and skill development. However, concerns about over-reliance on …
Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman
Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman
Open Access Theses & Dissertations
Detecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL's performance under low-load conditions. Specifically, we select network …