Computer Sciences Commons^™

Toward A Responsible Future: Recommendations For Ai-Enabled Clinical Decision Support, Steven Labkoff, Bilikis Oladimeji, Joseph Kannry, Anthony Solomonides, Russell Leftwich, Eileen Koski, Amanda L Joseph, Monica Lopez-Gonzalez, Lee A Fleisher, Kimberly Nolen, Sayon Dutta, Deborah R Levy, Amy Price, Paul J Barr, Jonathan D Hron, Baihan Lin, Gyana Srivastava, Nuria Pastor, Unai Sanchez Luque, Tien Thi Thuy Bui, Reva Singh, Tayler Williams, Mark G Weiner, Tristan Naumann, Dean F Sittig, Gretchen Purcell Jackson, Yuri Quintana

Faculty, Staff and Student Publications

BACKGROUND: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging.

OBJECTIVES: This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients.

MATERIALS AND METHODS: In May …

Assessing The Impact Of Ai Assisted Software Development And User Experience Of A College Football Simulation Game: A Study Of Player And Industry Professional Perspectives, Augustus J. Scarlato Iii

USF Tampa Graduate Theses and Dissertations

This research examines the use of Artificial Intelligence (AI) in the design of video games, specifically the development of a college football simulation game. This study documents the creation of an alpha version college simulation game assisted by Open AI’s Chat GPT 4.0 API, to potentially improve game development, gameplay realism, and user interaction. The study then assesses how both student players and industry professionals perceive AI-enhanced gaming, emphasizing the usability, gameplay experience, and overall quality of the game using a Likert scale survey. The analysis also highlights differences in perceptions between students and industry professionals, with the latter group …

What Do We Know About Hugging Face? A Systematic Literature Review And Quantitative Validation Of Qualitative Claims, Jason Jones, Wenxin Jiang, Nicholas Synovic, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Background: Collaborative Software Package Registries (SPRs) are an integral part of the software supply chain. Much engineering work synthesizes SPR package into applications. Prior research has examined SPRs for traditional software, such as NPM (JavaScript) and PyPI (Python). Pre-Trained Model (PTM) Registries are an emerging class of SPR of increasing importance, because they support the deep learning supply chain.
Aims: Recent empirical research has examined PTM registries in ways such as vulnerabilities, reuse processes, and evolution. However, no existing research synthesizes them to provide a systematic understanding of the current knowledge. Some of the existing research includes qualitative …

Quantifying Ethics And Trust In Human-Ai Collaboration, Oliver Lane, Kevin Klave

College of Engineering Summer Undergraduate Research Program

As AI Chatbots continue to evolve in both prevalence and capability, their role in education is becoming increasingly prominent. With chatbots like ChatGPT becoming commonplace in higher education, there is an evident need to understand the ethics and trust dynamics of human-AI collaboration. This research contributes to the ongoing discussion on AI in education, highlighting the importance of trust when utilizing AI in academic settings. By conducting an empirical analysis, this research seeks to quantify trust in human-AI collaboration in higher education with the aim of offering actionable items for higher education institutions to follow to promote ethical and responsible …

Digital Twin For Shelf Intelligence: Ai-Driven Inventory Management For Minimizing Food Waste, Charlotte Maples, Marvin Velazquez

College of Engineering Summer Undergraduate Research Program

This project aims to develop a solution for improving grocery store inventory management by leveraging AI-driven image recognition. Traditional inventory methods, which rely on manual counting or barcode scanning, are inefficient, labor-intensive, and prone to human error. Over an 8-week period, we designed and developed a basic iPad app capable of identifying specific types of fruit and automatically updating inventory records in real time. By utilizing the iPad’s camera and machine learning algorithms, the app demonstrates the potential to streamline inventory tracking, reduce manual labor, and improve accuracy in managing perishable goods. Future work will focus on expanding the app’s …

A Guideline For Open-Source Tools To Make Medical Imaging Data Ready For Artificial Intelligence Applications: A Society Of Imaging Informatics In Medicine (Siim) Survey, Sanaz Vahdati, Bardia Khosravi, Elham Mahmoudi, Kuan Zhang, Pouria Rouzrokh, Shahriar Faghani, Mana Moassefi, Aylin Tahmasebi, Katherine Andriole, Peter Chang, Keyvan Farahani, Mona Flores, Les Folio, Sina Houshmand, Maryellen Giger, Judy Gichoya, Bradley Erickson

Department of Radiology Faculty Papers

In recent years, the role of Artificial Intelligence (AI) in medical imaging has become increasingly prominent, with the majority of AI applications approved by the FDA being in imaging and radiology in 2023. The surge in AI model development to tackle clinical challenges underscores the necessity for preparing high-quality medical imaging data. Proper data preparation is crucial as it fosters the creation of standardized and reproducible AI models while minimizing biases. Data curation transforms raw data into a valuable, organized, and dependable resource and is a fundamental process to the success of machine learning and analytical projects. Considering the plethora …

Analyzing Student Prompts And Their Effect On Chatgpt’S Performance, Ghadeer Sawalha, Imran Taj, Abdulhadi Shoufan

All Works

Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link between these strategies and the model’s response accuracy, the existence of individual prompting tendencies, and the impact of gender in this context. Our students used ChatGPT to solve five problems related to embedded systems and provided the solutions and the conversations with this model. We analyzed the …

Rethinking Retrieval Augmented Fine-Tuning In An Evolving Llm Landscape, Nicholas Sager, Timothy Cabaza, Matthew Cusack, Ryan Bass, Joaquin Dominguez

SMU Data Science Review

This study explores the utilization of Retrieval Augmented Fine-Tuning (RAFT) to enhance the performance of Large Language Models (LLMs) in domain-specific Retrieval Augmented Generation (RAG) tasks. By integrating domain-specific information during the retrieval process, RAG aims to reduce hallucination and improve the accuracy of LLM outputs. We investigate the use of RAFT, an approach that enhances LLMs by incorporating domain-specific knowledge and effectively handling distractor documents. This paper validates previous work, which found that RAFT can considerably improve the performance of Llama2-7B in specific domains. We also expand upon previous work into new state-of-the-art open-source models and other datasets with …

Diabetes Technology Meeting 2023, Tiffany Tian, Rachel E Aaron, Ashley Y Dunova, Johan H Jendle, David Kerr, Eda Cengiz, Andjela Drincic, John C Pickup, Kong Y Chen, Naomi Schwartz, Douglas B Muchmore, Halis K Akturk, Carol J Levy, Signe Schmidt, Riccardo Bellazzi, Alan H B Wu, Elias K Spanakis, Bijan Najafi, James Geoffrey Chase, Jane Jeffrie Seley, David C Klonoff

Center on Aging Staff Publications

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

Interventional Radiology's Exploration Into Artificial Intelligence, Raymond Nguyen

Master's Projects and Capstones

Background: Artificial intelligence (AI) has become more prominent in our daily lives in recent years. This includes various aspects of healthcare. Interventional radiology (IR) is one of these specialties that has taken strides in understanding how AI can be leveraged for patient care. This literature review aims to understand what areas will be most impacted by AI in IR and how it will influence both the patient and interventional radiologist.

Methods: Twenty-six publications from 2019-2024 were selected from PubMed and Scopus. Publications were sourced through a combination of keywords, subject headings (MeSH terms), and citation searching.

Results: This literature review …

Bridging The Gap: Ai And The Hidden Structure Of Consciousness, Emily Barnes, James Hutson

Faculty Scholarship

The quest to develop Artificial Intelligence (AI) systems that possess human-like consciousness necessitates a deep dive into both theoretical and practical aspects underpinning this ambitious goal. This article builds on initial philosophical explorations of AI consciousness by examining the intricate and often hidden structures that may facilitate conscious experiences in AI. Drawing from concepts in cognitive science and neuroscience, the article elucidates how AI systems can be designed to replicate the structural and functional aspects of human consciousness. The discussion includes the Hierarchy of Spatial Belongings proposed by Forti (2024), frameworks like the Integrated Information Theory (IIT), and models linking …

Artificial Intelligence, Work, And The Future Of Education, Daniel Brown

Library Presentations

No abstract provided.

Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny

All Theses

High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …

Artificial Intelligence And Administrative Justice: An Analysis Of Predictive Justice In France, Zouhaier Nouri, Walid Ben Salah, Nayel Al Omrane

All Works

This article critically analyzes the ethical and legal implications of adopting predictive analytics by the French administrative justice system. It raises a key question: Is it wise to integrate artificial intelligence into the administrative justice system, considering its potential benefits, despite the associated risks, ethical dilemmas, and legal challenges? The research employs a method based on an extensive literature review, a qualitative analysis of the adoption by the French administrative justice of predictive analytics tools, and a critical evaluation of the benefits and issues these tools bring. The study finds that AI can make the administrative justice system more efficient, …

A Framework For The Foundation Of The Philosophy Of Artificial Intelligence, Emily Barnes, James Hutson

Faculty Scholarship

In recent years, the rapid advancement of artificial intelligence (AI) technology has sparked profound questions about the nature of machine intelligence and the possibility of AI consciousness. As AI systems become increasingly sophisticated, examining their philosophical foundations has become imperative. This article investigates the intricate relationship between AI and existential thought, aiming to establish a comprehensive framework for understanding AI's philosophical underpinnings. The historical development of AI, from symbolic AI to contemporary machine learning paradigms, highlights the increasing complexity and sophistication of AI systems, prompting significant philosophical debates about machine consciousness. Theoretical models such as the Independent Core Observer Model …

Querymate: A Custom Llm Powered By Llamacpp, Pegah Khosravi

Open Educational Resources

No abstract provided.

Human Centered Approaches And Taxonomies For Explainable Artificial Intelligence, Helen Sheridan, Emma Murphy, Dympna O'Sullivan

Conference papers

Recent interest within the research community related to explainable artificial intelligence (XAI) has led to a profuse amount of literature on the subject. Those who wish to tackle the domain from an HCI focus may be presented with overwhelming material, most of which does not pertain to human aspects of XAI. Taxonomies can serve to categorize a subject into topic areas and distill content into an overview of the field. This late breaking work intends to help those within the HCI community with a focus on XAI to understand relevant aspects of human centered XAI. We also present a taxonomy …

Cognitive Technologies, Tom Davenport

Asian Management Insights

AI and the revolution of work.

Professor Tom Davenport, the President’s Distinguished Professor of Information Technology and Management at Babson College, speaks about how companies can integrate generative Artificial Intelligence (GenAI) into their operations while ensuring workforce adaptation and skills development.

Generative Artificial Intelligence: The Protection Of Personal Data And Countering False Narratives About The Person, Warren B. Chik

Research Collection Yong Pung How School Of Law

Generative artificial intelligence (“Gen AI”) has rapidly become ubiquitous on online platform services, from chatbots and virtual assistants to search engines and social media. This generated concerns over potentially harmful effects from its use in both social and professional settings, including the added threats to personal data privacy and accuracy of personal information. In this article, the author will explain how Gen AI operates and why it gives rise to these issues, examine the policy and law relating to Gen AI, both existent and anticipated, and suggest possible solutions to the problems in the form of legal and non-legal measures.

Student Partners In Ai Literacy: A Library And Writing Center Collaboration, A. P. Anderson

Velma K. Waters Library Faculty Publications

Student voices are valuable but often overlooked in discussions surrounding the role of AI in higher education. AI Literacy education efforts that treat students only as a potential audience for instruction rather than as potential instructors themselves miss out on the passion, curiosity, and complex questions that students can bring to these conversations. If we center student voices in AI Literacy education discussions, and encourage both their enthusiasm and skepticism, students can become comfortable and confident in leading discussions about AI in the classroom and in their lives. In my proposed poster presentation, I will share insights from an AI …

Assessing Job Vulnerability And Employment Growth In The Era Of Large Language Models (Llms), Prudence P. Brou

Dissertations, Theses, and Capstone Projects

This paper explores the impact of Large Language Models (LLMs) and artificial intelligence (AI) on white-collar occupations in the context of job vulnerability and employment growth. Utilizing the Kaggle dataset "Occupation Salary and Likelihood of Automation," the study employs a data-driven approach to analyze trends across states. Through interactive data visualization, the project aims to provide actionable insights for affected workers, businesses, and policymakers navigating the changing dynamics of the workforce amidst technological advancements.

Securing Tomorrow: Synergizing Change Management And Cybersecurity In The Digital Era, Sharon L. Burton

Publications

In the rapidly evolving business environment of 2024, organizational change management (OCM) leaders face unprecedented challenges driven by technological advancements, digital transformation, the integration of remote work, and a heightened focus on sustainability. This study examines the efficacy of traditional OCM models in addressing these modern complexities. Through a qualitative methodology employing an extensive literature review, the research identifies vital issues such as resistance to change, digital transformation imperatives, the shift to remote and hybrid work models, and the imperative for sustainable and ethical business practices. The study posits that while classical OCM frameworks offer foundational insights, there is a …

Charting A Path To The Quintuple Aim: Harnessing Ai To Address Social Determinants Of Health, Yash Shah, Zachary Goldberg, Erika Harness, David Nash

College of Population Health Faculty Papers

The Quintuple Aim seeks to improve healthcare by addressing social determinants of health (SDOHs), which are responsible for 70-80% of medical outcomes. SDOH-related concerns have traditionally been addressed through referrals to social workers and community-based organizations (CBOs), but these pathways have had limited success in connecting patients with resources. Given that health inequity is expected to cost the United States nearly USD 300 billion by 2050, new artificial intelligence (AI) technology may aid providers in addressing SDOH. In this commentary, we present our experience with using ChatGPT to obtain SDOH management recommendations for archetypal patients in Philadelphia, PA. ChatGPT identified …

Supporting South Korea’S Aging Population: How Ai And Iot Acceptance Connects The Young And Old, Bobby Im

Master's Projects and Capstones

In 2024, South Korea surpassed every other nation by becoming the country with the lowest fertility rate (below 0.7%). Population decline will hinder future ability to care for their aging population and although the government and private corporations are investing millions of dollars on developing Artificial Intelligence-Internet of Things (AI-IoT) devices to support the aging, the acceptance levels and the amount of family support required is undervalued. By examining AI-IoT’s current use and role in South Korea’s public health system this paper shows how intergenerational support helps optimize existing procedures and equipment, increases the level of acceptance and use, and …

Toward The Integration Of Behavioral Sensing And Artificial Intelligence, Subigya K. Nepal

Dartmouth College Ph.D Dissertations

The integration of behavioral sensing and Artificial Intelligence (AI) has increasingly proven invaluable across various domains, offering profound insights into human behavior, enhancing mental health monitoring, and optimizing workplace productivity. This thesis presents five pivotal studies that employ smartphone, wearable, and laptop-based sensing to explore and push the boundaries of what these technologies can achieve in real-world settings. This body of work explores the innovative and practical applications of AI and behavioral sensing to capture and analyze data for diverse purposes. The first part of the thesis comprises longitudinal studies on behavioral sensing, providing a detailed, long-term view of how …

Academic Literature Review In Age Of Ai And Large Language Models​, Aaron Tay

Research Collection Library

Explore the evolving landscape of academic research with a focus on open data and AI advancements, particularly in natural language processing. Join us for a practical presentation on leveraging emerging tools for literature review. Discover platforms like Connected Papers, ResearchRabbit, and Litmaps, offering paper exploration and recommendations based on initial 'seed papers.' Dive into AI-enhanced search engines like Elicit, Scispace, Semantic Scholar, and Scite.ai, powered by Large Language Models such as BERT and GPT. Learn about the latest developments, strengths, and weaknesses of these tools, and how they reshape literature review methods, from tool selection to query input techniques.

Ai: Is The Future Robots?, Ruthanne Fischer

University Honors College

The goal of this thesis is to analyze how Artificial Intelligence is actively changing. The newly developed technology that is known as Artificial Intelligence can potentially have implications that are not yet known. Artificial Intelligence impacts the business world in many ways. Things such as ChatGPT and Deepfakes are some of the biggest forms of Artificial Intelligence today. It is important to know how Artificial Intelligence is changing every day because no one knows the true implications of a technology like this. It is crucial for companies to understand how this technology can potentially be harmful to their employees. Artificial …

Ai And Advocacy: Maximizing Potential, Minimizing Risk, Matthew Salzano, Nicholas Fung, Ada Lin, Sofia Marchetta, Faith Colombo, Kaylah Davis, John Flynn, Carlos Fuentes, Fion Li, Malar Paavi Muthukumaran, Angelica Paramoshin, Chrisanne Pearce, Vianney Ramos, Charles St. Hilaire, Xi Zheng, Wei Zhuang

School of Communication and Journalism Faculty Publications

New Generative AI tools are revolutionizing writing and communication. This report focuses on AI and advocacy, the act of influencing public policy and resource allocation decisions within political, economic, and social systems and institutions. This report identifies three major opportunities and accompanying risks, plus one strong recommendation for advocates considering using AI. We argue that AI can be useful for advocates, but they must be careful to center human judgment and avoid risks that could distract from their important work or even contribute to societal harms.

Comparing And Assessing Four Ai Chatbots' Competence In Economics, Patrik T. Hultberg, David Santandreu Calonge, Firuz Kamalov, Linda Smail

All Works

Artificial Intelligence (AI) chatbots have emerged as powerful tools in modern academic endeavors, presenting both opportunities and challenges in the learning landscape. They can provide content information and analysis across most academic disciplines, but significant differences exist in terms of response accuracy for conclusions and explanations, as well as word counts. This study explores four distinct AI chatbots, GPT-3.5, GPT-4, Bard, and LLaMA 2, for accuracy of conclusions and quality of explanations in the context of university-level economics. Leveraging Bloom’s taxonomy of cognitive learning complexity as a guiding framework, the study confronts the four AI chatbots with a standard test …

Ethical Imperatives In Ai-Driven Educational Assessment: Framework And Implications, Ming Soon Tristan Lim

Dissertations and Theses Collection (Open Access)

This dissertation embarks on an extensive exploration of the ethical challenges emerging from the integration of AI in educational assessments. It uncovers the complex interplay between AI and the ethical imperatives these technologies pose within educational assessments.

Amidst the rapid development of AI-enabled educational technologies, such as Ubiquitous, Adaptive, and Immersive technologies, this research identifies a notable gap in literature specifically concerning the ethical imperatives and implications of AI in educational assessments. Addressing this gap, the dissertation has three primary objectives: to comprehend and analyze the underpinning educational technologies driving assessments, to elucidate the intricate relationship between AI, ethics, and …