Computer Sciences Commons^™

Present Case Studies Highlighting Practical Implications Of Architectural Design Choices, Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of deep neural networks (DNNs) has become a crucial focus within artificial intelligence and machine learning, particularly as these models are increasingly used in high-stakes applications such as healthcare, finance, and autonomous driving. This article explores the impact of architectural design choices on the interpretability of DNNs, emphasizing the importance of transparency, trust, and accountability in AI systems. By presenting case studies and experimental results, the article highlights how different architectural elements—such as layer types, network depth, connectivity patterns, and attention mechanisms—affect model interpretability and performance. The discussion is structured into three main sections: real-world applications, architectural trade-offs, …

The Next 'Deep' Thing In X To Z Marketing: An Artificial Intelligence Driven Approach, Vincent Charles, Nripendra Rana, Ilias O. Pappas, Morten Kamphaug, Keng Siau, Kenth Engo-Monsen

Research Collection School Of Computing and Information Systems

The existing body of literature indicates a growing interest in research pertaining to the influence of artificial intelligence (AI) on marketing strategies, processes, and practices. However, further studies are required to fully unravel its complete potential and the implications it holds for practical application. The aim of this special issue on “The Next ‘Deep’ Thing in X to Z Marketing: An Artificial Intelligence-Driven Approach” is to explore the next frontiers and delve into the various facets of AI-driven marketing, shedding light on cutting-edge research and practical insights that can shape the future of the field. It also focuses on novel …

Ai Employment Decision-Making: Integrating The Equal Opportunity Merit Principle And Explainable Ai, Gary Kok Yew Chan

Research Collection Yong Pung How School Of Law

Artificial intelligence (AI) tools used in employment decision-making cut across the multiple stages of job advertisements, shortlisting, interviews and hiring, and actual and potential bias can arise in each of these stages. One major challenge is to mitigate AI bias and promote fairness in opaque AI systems. This paper argues that the equal opportunity merit principle is an ethical approach for fair AI employment decision-making. Further, explainable AI can mitigate the opacity problem by placing greater emphasis on enhancing the understanding of reasonable users (employing organisations) and affected persons (employees and job candidates) as to the AI output. Both the …

Ethical Considerations Toward Protestware, Marc Cheong, Raula Kula, Christoph Treude

Research Collection School Of Computing and Information Systems

This article looks into possible scenarios where developers might consider turning their free and open source software into protestware. Using different frameworks commonly used in artificial intelligence (AI) ethics, we extend the applications of AI ethics to the study of protestware.

Sensing With Integrity: Responsible Sensor Systems In An Era Of Ai, David Eisenberg

Dissertations

Deep and machine learning now offer immense benefits for consumer choice, decision-making, medicine, mental health and education, smart cities, and intelligent transportation and driver safety. However, as communication and Internet technology further advances, these benefits have the potential to be outweighed by compromises to privacy, personal freedom, consumer trust, and discrimination. While ethical consequences for personal freedom and equity rise from these technological advances, the issue may not be the technology itself but a lack of regulation and policy that allow abuses to occur. A first study examines how emerging sensor-based technologies, limited to only accelerometer and gyroscope data from …

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 …

Automatic Measurement Of Dialogue Engagingness In Multilingual Settings, Amila Ferron

Dissertations and Theses

Expansive use of large language models (LLMs) as dialogue systems brings increased importance to the evaluation of the responses they generate. Although evaluation of qualities such as coherence and fluency are readily possible with well-established automatic metrics, engagingness is often measured with human evaluation -- a process that can be costly and slows the pace of development. Existing automatic metrics for engagingness have low to moderate correlation with human annotations, evaluate the response without the conversation history, are complicated to implement, or are designed for a specific dataset. Moreover, they have been tested exclusively on English conversations. Given that dialogue …

Missing Wedge Completion Via Unsupervised Learning With Coordinate Networks, Dave Van Veen, Jesús G Galaz-Montoya, Liyue Shen, Philip Baldwin, Akshay S Chaudhari, Dmitry Lyumkis, Michael F Schmid, Wah Chiu, John Pauly

Faculty, Staff and Students Publications

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input …

Synthetic Realities And Artificial Intelligence-Generated Contents, Daniel Moreira, Sebastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Welcome to the IEEE Security & Privacy Special Issue on Synthetic Realities and Artificial Intelligence-Generated Contents! In this edition, we delve into the topic of synthetic realities, where generative artificial intelligence (GAI) is revolutionizing the construction of narratives, blurring the boundaries between fact and fiction, for the good and the bad. Indeed, content created or enabled by GAI spans a wide spectrum of usage and intentions, from fostering positive experiences, such as entertainment, training, and education, to more questionable utilization, such as deception, propaganda, and manipulation.

Companionship, Romance, And Self-Perception With Conversational Chatbots, Jonathan Windsor

Departmental Honors & Graduate Capstone Projects

Serving as a metaphorical gateway transcending the communicative barriers of physical relationships in interpersonal dialogues, artificial imators of human behavior and speech, also known as conversational chatbots; a simulation of human knowledge and existence in a bi-directional conversation, functions as a rhetor of expression. Spanning from contexts of professional to romantic, I serve to dissect and critically analyze the nuances of human-machine relationships based on pre-established literature, inviting ethical considerations and biases in their design and marketing. Corporate influences spark pre-established servitude-esque relationships with conversational agents. Professional applications, both task-oriented and emotionally based alike, paint a mixed picture of …

Behavioral Intention For Ai Usage In Higher Education, Isaac A. Odai, Elliot Wiley

Student Research Symposium

This study sought to further understand the cognitive factors that influence undergraduate students' behavioral intention to use generative AI. Generative AI's presence in academic spaces opens the door for ethical and pedagogical questions. This study surveyed 51 undergraduate communication students to measure their attitudes, subjective norms, self efficacy and their behavioral intention to use GenAI for school work. The results of this study showed behavioral intent had a positive relationship with attitudes and subjective norms. The implications of these findings show that personal beliefs and the perceived beliefs of others are correlated to undergraduate students’ intent to use GenAI for …

Accuracy Of Machine Learning To Predict The Outcomes Of Shoulder Arthroplasty: A Systematic Review, Amir H. Karimi, Joshua Langberg, Ajith Malige, Omar Rahman, Joseph A. Abboud, Michael A. Stone

Department of Orthopaedic Surgery Faculty Papers

BACKGROUND: Artificial intelligence (AI) uses computer systems to simulate cognitive capacities to accomplish goals like problem-solving and decision-making. Machine learning (ML), a branch of AI, makes algorithms find connections between preset variables, thereby producing prediction models. ML can aid shoulder surgeons in determining which patients may be susceptible to worse outcomes and complications following shoulder arthroplasty (SA) and align patient expectations following SA. However, limited literature is available on ML utilization in total shoulder arthroplasty (TSA) and reverse TSA.

METHODS: A systematic literature review in accordance with PRISMA guidelines was performed to identify primary research articles evaluating ML's ability to …

No Sword, No Shield, No Problem: Ai In Pro Se Section 1983 Suits, Michaela Calhoun

University of Colorado Law Review Forum

Originating during the Reconstruction era, 42 U.S.C. 1983 emerged as a legislative tool to safeguard individuals’ constitutional rights and liberties. Initially designed to combat state-sanctioned violence, its efficacy has been eroded over time by subsequent judicial and legislative action. Unfortunately, the current state of Section 1983 falls short of this envisioned role, particularly for incarcerated individuals who find themselves navigating the complexities of the federal court system as pro se litigants.

Faced with a landscape devoid of resources, incarcerated individuals struggle to realize their constitutional rights, further perpetuating their collective status as a second-class citizenry—a status imposed by their own …

The Role Of Student Motivation In Integrating Ai Into Web Design Education: A Longitudinal Study, Jason Lively, James Hutson

Faculty Scholarship

Amidst the current wave studies of artificial intelligence (AI) in education, this longitudinal case study, spanning Spring 2023 to Spring 2024, delves into the integration of AI in the UI/UX web design classroom. By introducing both text-based and image-based AI tools to students with varying levels of skill in introductory web design and user experience (UX) courses, the study observed a significant enhancement in student creative capabilities and project outcomes. The utilization of text-based generators markedly improved writing efficiency and coding, while image-based tools facilitated better ideation and color selection. These findings underscore the potential to augment traditional educational methods, …

The Impact Of Ai On Ux: Challenges And Opportunities, Susan Stephanie Wells

Theses

Integrating artificial intelligence (AI) in user experience (UX) design is reshaping the field of UX, offering new opportunities and challenges for designers. This thesis project explores the multifaceted relationship between AI and UX design, focusing on the challenges, opportunities, and skills demanded of UX designers in the age of AI. Through a review of academic research and real-world experiences, this project studies the impact of AI on web design processes, UX testing, and data analysis. Key findings highlight the transformative potential of AI in enhancing user experiences, from suggesting website structures to facilitating UX testing and data analysis.

Comparative analysis …

Ethical Imperatives And Challenges: Review Of The Use Of Machine Learning For Predictive Analytics In Higher Education, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

The escalating integration of machine learning (ML) in higher education necessitates a critical examination of its ethical implications. This article conducts a comprehensive review of the application of ML for predictive analytics within higher education institutions (HEIs), emphasizing the technology's potential to enhance student outcomes and operational efficiency. The study identifies significant ethical concerns, such as data privacy, informed consent, transparency, and accountability, that arise from the use of ML. Through a detailed analysis of current practices, this review underscores the need for HEIs to develop robust ethical frameworks and technological infrastructures to navigate these challenges effectively. The findings reveal …

Next-Generation Crop Monitoring Technologies: Case Studies About Edge Image Processing For Crop Monitoring And Soil Water Property Modeling Via Above-Ground Sensors, Nipuna Chamara

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has advanced rapidly in the past two decades. Internet of Things (IoT) technology has advanced rapidly during the last decade. Merging these two technologies has immense potential in several industries, including agriculture.

We have identified several research gaps in utilizing IoT technology in agriculture. One problem was the digital divide between rural, unconnected, or limited connected areas and urban areas for utilizing images for decision-making, which has advanced with the growth of AI. Another area for improvement was the farmers' demotivation to use in-situ soil moisture sensors for irrigation decision-making due to inherited installation difficulties. As Nebraska …

Optimizing Adult Learner Success: Applying Random Forest Classifier In Higher Education Predictive Analytics, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

This study examines the application of the Random Forest Classifier (RF) model in predicting academic success among adult learners in higher education. It focuses on evaluating the model's effectiveness using key statistical measures like accuracy, precision, recall, and F1 score across a comprehensive dataset from 2013–14 to 2021–22, which includes variables such as age, ethnicity, gender, Pell Grant eligibility, and academic performance metrics. The research highlights the RF model's capability to handle large datasets with varying data types and demonstrates its superiority over traditional regression models in predictive accuracy. Through an iterative process, the study refines the RF model to …

The Human Side Of Adaptive Autonomy: Design Considerations For Adaptive Autonomous Teammates, Allyson Hauptman

All Dissertations

Ground-breaking advances in artificial intelligence (AI) have led to the possibility of AI agents operating not just as useful tools for teams, but also as full-fledged team members with unique, interdependent roles. This possibility is fueled by the human desire to create more and more autonomous systems that possess computational powers beyond human capability and the promise of increasing the productivity and efficiency of human teams dramatically. Yet, for all the promise and potential of these human-AI teams, the inclusion of AI teammates presents several challenges and concerns for both teaming and human-centered AI.

An important part of teaming is …

Artificial Intelligence-Powered Assessment Of Pathologic Response To Neoadjuvant Atezolizumab In Patients With Nsclc: Results From The Lcmc3 Study, Sanja Dacic, William D Travis, Jennifer M Giltnane, Filip Kos, John Abel, Stephanie Hilz, Junya Fujimoto, Lynette Sholl, Jon Ritter, Farah Khalil, Yi Liu, Amaro Taylor-Weiner, Murray Resnick, Hui Yu, Fred R Hirsch, Paul A Bunn, David P Carbone, Valerie Rusch, David J Kwiatkowski, Bruce E Johnson, Jay M Lee, Stephanie R Hennek, Ilan Wapinski, Alan Nicholas, Ann Johnson, Katja Schulze, Mark G Kris, Ignacio I Wistuba

Faculty, Staff and Student Publications

Introduction: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-term outcomes with neoadjuvant therapy. Digital pathology may improve the efficiency and precision of PathR assessment. LCMC3 (NCT02927301) evaluated neoadjuvant atezolizumab in patients with resectable NSCLC and reported a 20% major PathR rate.

Methods: We determined PathR in primary tumor resection specimens using guidelines-based visual techniques and developed a convolutional neural network model using the same criteria to digitally measure the percent viable tumor on whole-slide images. Concordance was evaluated between visual determination of percent viable tumor (n = …

Social Order In Age Of Artificial Intelligence, Yongnian Zheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

While the rapid development of artificial intelligence is empowering society, it is also posing serious threats to the continuation of the traditional social order. The "de-intellectualization" function of AI has given rise to the phenomenon of "artificial ignorance", referring to the self-inflicted intellectual harm caused by the uncontrolled and excessive misuse of AI-related tools, thus causing a profound impact on the social order. The technical structural characteristics and governance structural characteristics of AI contributed to the emergence of the phenomenon of "artificial ignorance". The technical structural characteristics of AI can be summarized as highly concentrated capabilities, highly centralized control, highly …

New System For Mobilizing Resources Nationwide To Promote Leapfrog Development Of Innovation Ecosystem Of Artificial Intelligence Enterprises: Mechanisms, Problems And Strategies, Yang Mei, Hao Niu, Han Jiang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Facing the unpredictable new features of top-down AI technological innovation and the new requirements on functions, this study proposes to re-examine the technological innovation of AI at the enterprise level from the perspective of the "a new system for mobilizing the resources nationwide" and with the enterprise innovation ecosystem as the carrier. On the basis of explaining the elements and operation logic of the new system at the enterprise level, compared to the "implicit national system" of the US, this study preliminarily compares the new system of AI in China and that in the US. It is proposed that the …

Impact Analysis Of Artificial Intelligence Technology On Employment And Income In China, Yan Lu, Lincui Gui

Bulletin of Chinese Academy of Sciences (Chinese Version)

With the continuous development of artificial intelligence technology, employment and income in China will undergo some new changes. It is necessary to explore the impact of artificial intelligence technology on employment and income distribution. The study finds that in terms of employment, the impact of artificial intelligence includes redefining the number and nature of jobs, affecting work patterns and work skills, and possibly triggering structural imbalances between supply and demand in the labor market, leading to employment inequality, increasing employment risks. In term of income distribution, artificial intelligence technology has a heterogeneous impact on the initial distribution of different fields, …

Open Governance And Innovation Directions Regulation: Research On Institutional Mechanisms For Promoting Development Of Artificial General Intelligence, Yuhao Jiang, Xinyi Zhang, Mingjie Dai

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the field of artificial intelligence development, there is still a certain gap between China and the United States. The uncertain future of artificial general intelligence (AGI) decides that China should not only implement the "catch-up" strategy. Artificial intelligence is not a ‘linear innovation' development path, but there is overlap between basic research, applied research, and industrial transformation. This feature of innovation shows that diversified exploration can be realized based on tracking of international frontiers, breakthrough of basic research, and satisfaction of diverse application needs. China needs to adhere to the promotion of open governance, and regulate innovation directions of …

Research On Data Security And International Governance Cooperation Framework In Era Of Artificial Intelligence, Yuanyuan Wei

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study explores the international cooperation framework for data security governance and its implementation pathways from a global governance perspective. First, the study defines the concepts of data security and governance, emphasizing that the core objective of data governance is to ensure the secure flow and effective utilization of data. Second, it analyzes the current fragmentation of the global data governance system, revealing its development trends and challenges under the influence of geopolitics, particularly the tensions and collaborations in key areas such as cross-border data flows. Based on this analysis, the study proposes the concept of the "Embedded Digital Community …

Study On Constraints And Policy Responses For Production And Circulation Of Ai Training Data In China, Tao Lin

Bulletin of Chinese Academy of Sciences (Chinese Version)

The quantity and quality of training data are critical to the performance of artificial intelligence (AI) models. However, in China, the production of training data is hindered by issues such as insufficient quantity, low quality, and fragmented distribution, compounded by limitations stemming from commercial ecosystems, regulatory frameworks, and restricted development and utilization of public data. To address these challenges, this study proposes several policy recommendations, including incentivizing research institutions to generate open-source datasets, fostering AI application scenarios, adopting a "loose-in, focus-out" regulatory approach, introducing intellectual property exemption provisions, refining personal information protection guidelines, and expediting the establishment of a unified …

How China Leads Global Governance Of Artificial Intelligence: A Sustainable Development Approach Beyond Technological Competition, Xuanming Pan, Zhenzhen Chen, Shaoshan Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the context of great power competition and escalating geopolitical conflicts, the academic community generally holds a pessimistic view of AI international cooperation, believing that the space is shrinking. This perception mainly stems from conflicts in the cross-border supervision of AI data and algorithms among technologically advanced countries, while overlooking the strong willingness and potential for cooperation in energy conservation and emission reduction through AI technologies shown by Global South countries. Looking into the future of global governance, China, starting from leading the transformation of AI technologies, shall take lead in supporting these countries to transform the sustainable development consensus …

The Borderline Between Beneficial And Dishonest Ai: A Technical Report, Seth Richards, Katherine Shell, Seth Wright

Student Works

Artificial Intelligence (AI) has been used since 1950 but it was largely overlooked by the public until 2022. Current discussions about AI center around academic integrity. This report seeks to understand if AI can be handled, used, or accepted in Lipscomb’s academic environment as a beneficial aid to writing and research, without actively doing these tasks for an individual. Generative AI is a neural network, which enables it to receive input, gather information from a database of existing content, and create new content [2]. Due to the nature of generative AI, its beneficial contributions to academia are extremely limited.

Individualized Learning As An Ai Tool: A Technical Report, Petsimnan Blessing Dayit, Kasen Holt, Nuala Roper

Student Works

The purpose of the report’s research is to test and analyze whether Artificial Intelligence (AI) platforms can be used as beneficial tools for individualized learning at Lipscomb University without violating the Academic Integrity Policy. The methods section evaluates AI on the scopes of accuracy, analytical thinking, and adaptability. The results demonstrated how each platform responded to the prompts within the lines of the scope. The answers they gave were accurate, detailed, and contained various adaptations to make explanations clearer for the user. The team concluded that AI can be used at Lipscomb as a beneficial tool for students in their …

Redefining Readiness: Higher Education's Role In An Ai World How Higher Education Can Bridge The Gap Between Human Talent And Machine Intelligence For The Workforce Of Tomorrow, Paloma Shelton

Honors 499 Theses and Creative Projects

As the world changes all around us in the landscape of Artificial Intelligence (AI), our educational pathways need to adapt quickly. This paper presents a comprehensive analysis of the current and future state of higher education, its relationship with AI and technology, and the evolving requirements of the workforce. It outlines the historical progression of higher education since the Colonial Era, emphasizing the need for constant adaptation to societal and economic demands. It reflects how higher education must evolve to equip students with the necessary skills and adaptability for future careers in the digital and AI-augmented landscape. As AI advances …