Computer Sciences Commons^™

11. Race Against The Machine, Samantha K. Yoder

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This brief chapter asks readers to consider AI's connections to racial stereotypes and structural inequality.

10. Broadening Applications Of Artificial Intelligence In Education To Include Indigenous Ways Of Knowing, Megan Hamilton

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

Incorporating Indigenous ways of knowing with applications of artificial intelligence in education is necessary for promoting equitable and barrier-free learning opportunities for learners. Further research is needed as scholars and practitioners work toward bridging Indigenous ways of knowing with western forms of artificial intelligence in education in mutually beneficial ways.

9. Uses, Benefits, And Limitations Of Ai Chatbots: Implementing Chatgpt In The First-Year Writing Classroom, Walker Smith, Cora Alward, Jacob Morris, Lydia Peach, Veronica Pulley, Parker Routt, Kolby Sanders, Josh Vogeler

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This essay shares the findings of a Spring 2023 honors composition course in which students conducted their own primary research project to investigate the uses and limitations of ChatGPT for first-year writers. By experimenting with integrating ChatGPT into various stages of their writing and revision processes, the students identified the strengths and weaknesses of the writing tool. Then, they observed and interviewed faculty as they graded different versions of essay drafts with varying levels of ChatGPT assistance. Ultimately, they found that ChatGPT was incredibly useful for certain small-scale tasks, but posed significant risks, especially for students with less experience in …

8. Ai And Writing Classrooms: A Study Of Purposeful Use And Student Responses To The Technology, Laura Dumin

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

Given that Al is here for the foreseeable future, I revamped my spring 2023 English courses to include using Al in purposeful ways. I submitted an IRB to test different approaches to integrating Al into my classrooms. The study asked students in three different English courses to complete pre- and post-reflections about their understanding of Al and its uses.

This chapter will discuss how my students responded to the use of Al in the writing classroom, how student attitudes toward Al shifted over the course of the semester, ideas for how to use Al in writing classrooms, and the main …

Part Ii: Section 2: Research Studies, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

5. Navigating Benefits And Concerns When Discussing Genai Tools With Faculty And Staff, Reed Hepler

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

The author works as a Digital Initiatives Librarian and is earning a second Master's Degree in Instructional Design and Technology. He viewed ChatGPT immediately as yet another potentially useful technology. When educators at his institution promoted differing viewpoints regarding ChatGPT and other Al tools, he set out to demonstrate a method of Al integration similar to that of other technological tools. Using the Technology Consumer or Producer model and his own experience, he presented, discussed, and wrote about ChatGPT, its ethical issues, and its uses and impact on education. Reed shares his insights regarding creating instruction and training for educators. …

3. Empowering Educators In The Age Of Generative Ai: A Critical Media Literacy Approach, Ali Söken, Kysa Nygreen

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This chapter draws from the authors' experience teaching an undergraduate course in the context of Generative Al (GenAl), and shares three instructional innovations we are implementing in response: 1) establishing an appropriate tone; 2) designing in-class activities to engage critically with GenAl; and 3) revising assessment and grading policies. These adaptations are informed by the framework of Critical Media Literacy (CML), which grounds the course. They aim to strike a balanced view that acknowledges both challenges and potentials of GenAl. This chapter aims to furnish a contextual framework for fellow educators to critically engage with the realm of GenAl. Core …

2. Some Ethical Considerations For Teaching And Generative Ai In Higher Education, Lydia Wilkes

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

The chapter discusses some ethical considerations for teaching and generative Al in higher education with a focus on large language models like ChatGPT. These considerations include generative Al's effects on the environment and labor, its reliance on data and tendency to violate privacy, the biases encoded in it, and the digital divide. As more sophisticated generative Al is integrated into word processors, these ethical concerns will become more difficult to perceive and the ethics of using Al more difficult to parse. This chapter concludes with a note on power and justice.

Part I: Section 1: Framing Concepts, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

No abstract provided.

Introduction, Beth Buyserie, Travis N. Thurston

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

With the rapid development of generative Al, teachers are experiencing a new pedagogical challenge, one that promises to forever change the way we approach teaching and learning. As a response to this unprecedented teaching context, this collection-Teaching and Generative Al: Pedagogical Possibilities and Productive Tensions-provides interdisciplinary teachers, librarians, and instructional designers with practical and thoughtful pedagogical resources for navigating the possibilities and challenges of teaching in an Al era. Because our goal with this edited collection is to present nuanced discussions of Al technologies across disciplines, the chapters collectively acknowledge or explore both possibilities and tensions-including the strengths, …

Land Acknowledgement/Foreword, Tazin Daniels

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

In the rapidly evolving landscape of higher education, the emergence of Generative Artificial Intelligence (Al) stands as a beacon of both innovation and introspection, heralding a new era in teaching and learning. This book serves as a guide for college instructors who find themselves at the cusp of this technological revolution-those who are intrigued yet perhaps apprehensive, eager to explore yet unsure where to begin. As we begin this journey, it is vital to acknowledge the spectrum of emotions that accompany its integration into academia: from excitement and curiosity to caution and concern. Recognizing and normalizing these feelings is the …

13. Rude Reflections: Current Ai Acts As A Mirror Of Our Flawed Society, Belinda 'Ofakihevahanoa Fotu

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

In face-to-face classrooms, culturally and critically conscious teachers fight to mediate skills, content, and students' backgrounds all within the bounds of a systematically flawed educational institution. For now, AIs that aid in writing bypass that kind of meaningful work as AIs reflect the corpus of published literature that overwhelmingly reflects historically problematic hierarchical biases.

Deepwhalenet: A Climate Change-Aware Fft-Based Neural Network For Underwater Passive Acoustic Monitoring, Nicholas Ryan Rasmussen

Dissertations and Theses

In the face of escalating climate threats, the conservation of whale species has become increasingly critical. Traditional acoustic monitoring methods, burdened by extensive pre-processing and post-processing, need more adaptability and efficiency for effective marine mammal surveillance. This study introduces DeepWhaleNet, a novel deep-learning framework tailored for Underwater Passive Acoustic Monitoring (UPAM). DeepWhaleNet is designed to streamline whale detection by directly analyzing raw log-power spectrograms, thus extracting essential acoustic features to conserve these endangered species. The framework employs an extensive short-time Fourier transform (STFT) for input processing and a customized ResNet-18 architecture for classification, distinguishing whale vocalizations from ambient noise and …

Mivt: Medical-Informed Vision Transformer For Early Epilepsy Diagnosis, Md Masum Rana

Dissertations and Theses

Epilepsy is a neurological disorder characterized by recurrent, unprovoked seizures, and early diagnosis is crucial for effective management and treatment. However, the diagnosis of epilepsy, particularly in its early stages, remains challenging due to the subtle nature of seizures and the complexity of brain activity patterns. In this research, we introduce the Medical-Informed Vision Transformer (MIVT), a deep learning architecture specifically designed to improve early epilepsy diagnosis from multimodal neuroimaging data. Our model integrates insights from both medical knowledge and state-of-the-art Vision Transformers (ViTs) to enhance the accuracy and interpretability of seizure detection and localization. The MIVT leverages the rich …

Development Of A Modular Lab Automation System With Applications To Animal And Bacteria Cell Culture, Timothy William Hartman

Dissertations and Theses

The challenges faced while executing wet lab protocols encourage the development of automation systems to come alongside human scientists. Today’s cutting-edge experiments involve complex protocols with precise measurements usually performed manually. Even simpler biological protocols can be tedious and prone to error, as was seen during the COVID-19 pandemic and society’s demand for high-volume, rapid sample analysis. Moreover, reproducibility suffers when there is excessive variability and insufficient data. Here, we leveraged the Stanford Biodesign process to develop a modular lab automation system and image analysis workflow to address challenges like these. This flagship automation platform at The University of South …

Artificial Intelligence And News Consumption: A Study Of Trust, Credibility And Transparency In Automated Journalism, Julia Lobo Paes

Dissertations and Theses

According to Gallup poll (2023), over the last 50 years there has been a decline in how much Americans trust mass media. While in the 1970’s 72% of the population responded that they trust the media a 'great deal/fair amount', this number dropped to 34% in 2023. Given the decreasing public trust in news, this thesis focused particularly on analyzing trust in the organization, trust in the news story and perceived credibility in AI generative content. In addition to articles created by AI, this study also aimed to analyze how the public perceives information that has been personalized and distributed …

Can Informed Consent Solve Ai Bias?, W. Nicholson Price Ii

Reviews

Artificial intelligence (AI) is moving increasingly rapidly into health care (as indeed into everything else). But it has problems there (as indeed everywhere else!). What’s to be done, in particular, about the deeply embedded biases along racial and other lines that permeate the whole world of health and, as such, are likely to be encoded in AI?

Khiara Bridges gives an answer that seems mild but carries roots of revolution. In Race in the Machine: Racial Disparities in Health and Medical AI, she argues that informed consent is a key lever to pull in fighting these racial disparities. But not …

Impossibility Of Artificial Inventors, Matt Blaszczyk

Fellow, Adjunct, Lecturer, and Research Scholar Works

Recently, the United Kingdom Supreme Court decided that only natural persons can be considered inventors. A year before, the United States Court of Appeals for the Federal Circuit issued a similar decision. In fact, so have many the courts all over the world. This Article analyses these decisions, argues that the courts got it right, and finds that artificial inventorship is at odds with patent law doctrine, theory, and philosophy. The Article challenges the intellectual property (IP) post-humanists, exposing the analytical and normative perils of their argumentation, and recommends against getting rid of the nominally central place of humans in …

Review Of Who Wrote This?: How Ai And The Lure Of Efficiency Threaten Human Writing, By Naomi S. Baron, Taylor J. Greene

Library Articles and Research

A review of Who Wrote This?: How AI and the Lure of Efficiency Threaten Human Writing, by Naomi S. Baron.

Fr1: Comics, Cyborgs, And “In Between” Identities, Ella Lehavi

Scripps Senior Theses

As a queer Jew who grew up surrounded by immigrant cultures and communities, I find myself in a liminal space between my identities and the dominant culture of my country– one where my perspective on gender and my cultural experiences aren’t fully understood by the world I exist in. Comics and cartoons are an explorational platform for concepts of reality and identity; they are one of very few spaces where I see my identities explored with so much depth and care.

Cartoons and comics exist in between realistic depictions and abstraction. This makes them a great place to express all …

Adaptive Multi-Label Classification On Drifting Data Streams, Martha Roseberry

Theses and Dissertations

Drifting data streams and multi-label data are both challenging problems. When multi-label data arrives as a stream, the challenges of both problems must be addressed along with additional challenges unique to the combined problem. Algorithms must be fast and flexible, able to match both the speed and evolving nature of the stream. We propose four methods for learning from multi-label drifting data streams. First, a multi-label k Nearest Neighbors with Self Adjusting Memory (ML-SAM-kNN) exploits short- and long-term memories to predict the current and evolving states of the data stream. Second, a punitive k nearest neighbors algorithm with a self-adjusting …

Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study In Aviation Maintenance, Nadine Amin, Tracy L. Yother, Julia Rayz

Journal of Aviation/Aerospace Education & Research

With timeliness and efficiency being critical in the aviation maintenance industry, the need has been growing for smart technological solutions that optimize and streamline the different underlying tasks (Bergkvist & Sabbagh, 2021). One such task is the technical documentation of the performed maintenance operations (Chandola et al., 2022). Instead of manual documentation, voice tools that transcribe spoken logbook entries allow technicians to document their work right away in a hands-free and time efficient manner. However, an accurate automatic speech recognition (ASR) model requires large training corpora (Siyaev & Jo, 2021a), which are lacking in the domain of aviation maintenance. In …

Flexible Attenuation Fields: Tomographic Reconstruction From Heterogeneous Datasets, Clifford S. Parker

Theses and Dissertations--Computer Science

Traditional reconstruction methods for X-ray computed tomography (CT) are highly constrained in the variety of input datasets they admit. Many of the imaging settings -- the incident energy, field-of-view, effective resolution -- remain fixed across projection images, and the only real variance is in the detector's position and orientation with respect to the scene. In contrast, methods for 3D reconstruction of natural scenes are extremely flexible to the geometric and photometric properties of the input datasets, readily accepting and benefiting from images captured under varying lighting conditions, with different cameras, and at disparate points in time and space. Extending CT …

Cyclistai: A Smartphone Solution For Cyclist Stress Assessment Using Deep Learning, Aairish Singh

Computer Science and Engineering Theses - Archive

Cycling presents a compelling solution for promoting personal health and environmental well-being, particularly for short-distance travel. Despite its numerous advantages, cycling uptake in the United States remains disproportionately low, primarily due to safety concerns. Traditional frameworks for assessing cyclist stress are hindered by their impracticality and inability to provide real-time evaluations. Self-report surveys and physiological measurements offer alternative approaches but suffer from limitations such as retrospective reporting biases and accessibility challenges, respectively. This thesis introduces CyclistAI, a novel smartphone-based cyclist stress assessment model that leverages context sensing. By combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) techniques, CyclistAI …

When Brain Meets Artificial Intelligence, Lu Zhang

Computer Science and Engineering Dissertations - Archive

When we review the history of development of artificial intelligence (AI), we will find that brain science plays a pivotal role in fostering breakthroughs in AI, such as artificial neural networks (ANNs). Today, AI has made remarkable strides, particularly with the emergence of large language models (LLMs), surpassing expectations and achieving human-level performance in certain tasks. Nonetheless, an insurmountable gap remains between AI and human intelligence. It is urgent to establish a bridge between brain science and AI, promoting their mutual enhancement and collaborations. This involve establishing connections from brain science to AI (brain-inspired AI), and reversely, from AI to …

Content Moderation On Social Media: Social And Computational Standards And Implications, Mohit Singhal

Computer Science and Engineering Dissertations - Archive

Social media has become a powerful tool that reflects human communication's best and worst aspects. They allow individuals to freely express opinions, communicate with others, and learn about new stories. On the other hand, they have become fertile grounds for several forms of abuse, harassment, and the dissemination of misinformation. Social media platforms have established and employed content moderation to counteract the spread of abuse and misinformation.

Some critical challenges hinder the understanding of the social media content moderation ecosystem. This dissertation investigates various aspects of content moderation, including their coverage, fairness, and effectiveness. Firstly, it investigates how, in practice, …

Natural Language Generation From Large-Scale Open-Domain Knowledge Graphs, Xiao Shi

Computer Science and Engineering Dissertations - Archive

This dissertation delves into the realm of natural language generation (NLG) from expansive open-domain knowledge graphs, aiming to bridge the gap between existing methods primarily tested on limited datasets and the demands of real-world large-scale, diverse graph structures. Prior works in NLG often relied on small-scale or restricted datasets, neglecting the complexities of broader knowledge graphs. To address this, we introduce a new dataset called GraphNarrative, designed to encompass a wide range of graph structures and enhance the realism of NLG tasks.

The core contribution of this research lies in devising a novel approach to mitigating information hallucination, a common …

Predicting The Need For Cardiovascular Surgery: A Comparative Study Of Machine Learning Models, Arman Ghavidel, Pilar Pazos, Rolando Del Aguila Suarez, Alireza Atashi

Engineering Management & Systems Engineering Faculty Publications

This research examines the efficacy of ensemble Machine Learning (ML) models, mainly focusing on Deep Neural Networks (DNNs), in predicting the need for cardiovascular surgery, a critical aspect of clinical decision-making. It addresses key challenges such as class imbalance, which is pivotal in healthcare settings. The research involved a comprehensive comparison and evaluation of the performance of previously published ML methods against a new Deep Learning (DL) model. This comparison utilized a dataset encompassing 50,000 patient records from a large hospital between 2015-2022. The study proposes enhancing the efficacy of these models through feature selection and hyperparameter optimization, employing techniques …

Comment On Chapters 1 And 4: Health Ai, System Performance, And Physicians In The Loop, W. Nicholson Price Ii

Book Chapters

Accounts of artificial intelligence (AI) in medicine must grapple, in one way or another, with the interaction between AI systems and the humans involved in delivering healthcare. Humans are, of course, involved throughout the process of developing , deploying, and evaluating AI systems, but a particular role stands out: the human in the loop of an algorithmic decision. In medicine, when an algorithm is involved in a decision , a typical view of the system envisions a human healthcare professional mediating that algorithm - deciding whether and how to implement or react to any recommendation, prediction, or other algorithmic output. …

Topic Mining And Dynamic Evolution Analysis Of Patent Technology From The Perspective Of Binary Evolution：Take The Field Of Industrial Robots As An Example, Luyao Dou, Zhigang Zhou, Yi Li, Tao Jiang

Journal of Scientific Information Research

[Purpose/significance]From the perspective of "overall ecology + local stage", mining the technical theme and its evolution law in the field of industrial robots can not only know the overall process of technological development, but also clarify the specific paradigm of technology combination, which has important practical significance for insight into the technological progress and capital investment focus in the field of industrial robots.[Method/process]Based on incoPat patent database, taking the industrial robot field from 2003 to 2022 as an example, combined with Word2vec word vector model and LDA topic model, data mining and corpus expansion of patent texts were carried out, …