Artificial Intelligence and Robotics Commons^™

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 …

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 …

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 …

A New Canvas Of Learning: Enhancing Formal Analysis Skills In Ap Art History Through Ai-Generated Islamic Art, Krista Carpino, James Hutson

Faculty Scholarship

This study explores the use of AI art generators to enhance formal analysis skills in AP Art History students, with a focus on Islamic Art and Architecture. Students, often entering the course with high academic achievements, find the unique challenge of articulating detailed visual descriptions of artworks. The study’s approach involves using AI image-generation websites, like wepik.com, where students create AI images resembling Islamic artworks studied in class. This method aims to refine their descriptive skills, focusing on visual evidence rather than relying on identifying details. The choice of Islamic Art, markedly different from other historical periods covered in the …

Integrating Artificial Intelligence For Automated Storytelling In Turn-Based Strategy Games, Timothy Ripper

Theses

This project is inspired by turn-based strategy games, Final Fantasy Tactics, X-Com 2, and modern turn-based strategy games. This project is structured around the use of artificial intelligence for storytelling within strategy games. The focus of this project utilizes artificial intelligence in creating a quest generation system for storytelling. The resulting quest system creates new quests dynamically after communicating with an artificial intelligence allowing players to potentially experience an ever-expanding story from quests

Development Of An Explainable Artificial Intelligence Model For Asian Vascular Wound Images, Zhiwen Joseph Lo, Malcolm Han Wen Mak, Shanying Liang, Yam Meng Chan, Cheng Cheng Goh, Tina Peiting Lai, Audrey Hui Min Tan, Patrick Thng, Patrick Thng, Tillman Weyde, Sylvia Smit

Research Collection School Of Computing and Information Systems

Chronic wounds contribute to significant healthcare and economic burden worldwide. Wound assessment remains challenging given its complex and dynamic nature. The use of artificial intelligence (AI) and machine learning methods in wound analysis is promising. Explainable modelling can help its integration and acceptance in healthcare systems. We aim to develop an explainable AI model for analysing vascular wound images among an Asian population. Two thousand nine hundred and fifty-seven wound images from a vascular wound image registry from a tertiary institution in Singapore were utilized. The dataset was split into training, validation and test sets. Wound images were classified into …

Preserving Linguistic Diversity In The Digital Age: A Scalable Model For Cultural Heritage Continuity, James Hutson, Pace Ellsworth, Matt Ellsworth

Faculty Scholarship

In the face of the rapid erosion of both tangible and intangible cultural heritage globally, the urgency for effective, wide-ranging preservation methods has never been greater. Traditional approaches in cultural preservation often focus narrowly on specific niches, overlooking the broader cultural tapestry, particularly the preservation of everyday cultural elements. This article addresses this critical gap by advocating for a comprehensive, scalable model for cultural preservation that leverages machine learning and big data analytics. This model aims to document and archive a diverse range of cultural artifacts, encompassing both extraordinary and mundane aspects of heritage. A central issue highlighted in the …

An Automated Approach For Improving The Inference Latency And Energy Efficiency Of Pretrained Cnns By Removing Irrelevant Pixels With Focused Convolutions, Caleb Tung, Nick Eliopoulos, Purvish Jajal, Gowri Ramshankar, Chen-Yun Yang, Nicholas Synovic, Xuecen Zhang, Vipin Chaudhary, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

Computer vision often uses highly accurate Convolutional Neural Networks (CNNs), but these deep learning models are associated with ever-increasing energy and computation requirements. Producing more energy-efficient CNNs often requires model training which can be cost-prohibitive. We propose a novel, automated method to make a pretrained CNN more energy-efficient without re-training. Given a pretrained CNN, we insert a threshold layer that filters activations from the preceding layers to identify regions of the image that are irrelevant, i.e. can be ignored by the following layers while maintaining accuracy. Our modified focused convolution operation saves inference latency (by up to 25%) and energy …

Reclaiming The Symbol: Ethics, Rhetoric, And The Humanistic Integration Of Gai - A Burkean Perspective, Daniel Plate, James Hutson

Faculty Scholarship

This study delves into the intersection of generative artificial intelligence (GAI) and the Humanities, guided by the critical insights of Kenneth Burke, a seminal figure in the study of rhetoric and a vocal critic of scientism and positivism. The skepticism of the American literary theorist towards an uncritical embrace of science and technology, and his concerns over the inclination of the Humanities to adopt scientific methodologies at the expense of traditional forms of inquiry, provide a critical framework for examining the new role played by GAI within the Humanities. By framing these tools in the context of Burkean rhetorical theory, …

Learning About Ai: Level Up Your Skills Without Overwhelming Your Mind, Jennifer Freer, Lara Nicosia

Presentations and other scholarship

OpenAI and deep learning and neural networks, oh my!  The swiftly developing landscape of artificial intelligence, combined with its rapid integration into our work and personal lives, can feel confusing and overwhelming.  This session will help you think about AI in your own work and plan your own personal AI learning journey, while also providing thoughtful recommendations on how both you and your users can get started.  The presenters will discuss common terminology, user-friendly resources for understanding AI, questions to ask when exploring AI tools, and ideas on how to start building your own knowledge on this topic.  The information …

Forging The Future: Strategic Approaches To Quantum Ai Integration For Industry Transformation, Meng Leong How, Sin Mei Cheah

CCX Research

The fusion of quantum computing and artificial intelligence (AI) heralds a transformative era for Industry 4.0, offering unprecedented capabilities and challenges. This paper delves into the intricacies of quantum AI, its potential impact on Industry 4.0, and the necessary change management and innovation strategies for seamless integration. Drawing from theoretical insights and real-world case studies, we explore the current landscape of quantum AI, its foreseeable influence, and the implications for organizational strategy. We further expound on traditional change management tactics, emphasizing the importance of continuous learning, ecosystem collaborations, and proactive approaches. By examining successful and failed quantum AI implementations, lessons …

Artificial Intelligence And/Or Machine Learning (Ai &| Ml), George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

These slides are from an invited panel presentation at my home institution, Loyola University Chicago, organized by the Loyola University Chicago Retiree Association (LUCRA). I was asked to give a broad historical overview of AI and ML and speak about its societal impacts.

"The Loyola University Chicago Retiree Association embraces the Vision of Loyola University Chicago and will assist students, faculty, and administrators as they strive to serve humanity. The group values freedom of inquiry, the pursuit of truth, and care of others and embraces a commitment to excellence, service that promotes social justice, values based leadership, and global awareness."

Generative Ai In Finance: Risks And Potential Solutions, Nydia Remolina Leon

Research Collection Yong Pung How School Of Law

Generative Artificial Intelligence captured the attention of academics, policymakers, the private sector, and some regulators in 2022 after the launch of ChatGPT and its widespread adoption worldwide. Then, during the World Economic Forum session in 2023, Microsoft Chairman and Chief Executive Officer Satya Nadella said that the ‘golden age’ of AI is underway and generative AI is set to play a big role in it. Accordingly, Microsoft has invested billions of dollars into OpenAI, the company behind the launch of ChatGPT. Additionally, Google and Meta have also created their own generative AI models. Given the multiplicity of potential use cases …

A Random Forest-Based Q-Learning Algorithm: Toward Interpretable Artificial Intelligence, Victor R. Rae

Theses and Dissertations

A growing demand exists for interpretable artificial intelligence models, leading to extensive research efforts to enhance the explainability and transparency of policies generated by reinforcement learning (RL) methods. This research develops random forest-based RL algorithms as a logical progression in this academic pursuit. The algorithms are evaluated using three standard benchmark environments from OpenAI gym — CartPole, MountainCar, and LunarLander — and compared to implementations of the Deep Q-learning Network (DQN) and Double DQN (DDQN) algorithms for various metrics, including performance, robustness, efficiency, and interpretability. The random forest-based algorithms exhibit superior performance to both neural network-based algorithms in two out …

Chatgpt Can Offer Satisfactory Responses To Common Patient Questions Regarding Elbow Ulnar Collateral Ligament Reconstruction, William Johns, Alec Kellish, Dominic Farronato, Michael G. Ciccotti, Sommer Hammoud

Rothman Institute Papers

PURPOSE: To determine whether ChatGPT effectively responds to 10 commonly asked questions concerning ulnar collateral ligament (UCL) reconstruction.

METHODS: A comprehensive list of 90 UCL reconstruction questions was initially created, with a final set of 10 "most commonly asked" questions ultimately selected. Questions were presented to ChatGPT and its response was documented. Responses were evaluated independently by 3 authors using an evidence-based methodology, resulting in a grading system categorized as follows: (1) excellent response not requiring clarification; (2) satisfactory requiring minimal clarification; (3) satisfactory requiring moderate clarification; and (4) unsatisfactory requiring substantial clarification.

RESULTS: Six of 10 ten responses were …

A Comparative Study Of Responses To Retina Questions From Either Experts, Expert-Edited Large Language Models, Or Expert-Edited Large Language Models Alone, Prashant D. Tailor, Lauren A. Dalvin, John J. Chen, Raymond Iezzi, Timothy W. Olsen, Brittni A. Scruggs, Andrew J. Barkmeier, Sophie J. Bakri, Edwin H. Ryan, Peter H. Tang, D. Wilkin Parke, Peter Belin, Jayanth Sridhar, David Xu, Ajay E. Kuriyan, Yoshihiro Yonekawa, Matthew R. Starr

Wills Eye Hospital Papers

OBJECTIVE: To assess the quality, empathy, and safety of expert edited large language model (LLM), human expert created, and LLM responses to common retina patient questions.

DESIGN: Randomized, masked multicenter study.

PARTICIPANTS: Twenty-one common retina patient questions were randomly assigned among 13 retina specialists.

METHODS: Each expert created a response (Expert) and then edited a LLM (ChatGPT-4)-generated response to that question (Expert + artificial intelligence [AI]), timing themselves for both tasks. Five LLMs (ChatGPT-3.5, ChatGPT-4, Claude 2, Bing, and Bard) also generated responses to each question. The original question along with anonymized and randomized Expert + AI, Expert, and LLM …

Using Natural Language Processing And Patient Journey Clustering For Temporal Phenotyping Of Antimicrobial Therapies For Cat Bite Abscesses, Brian Hur, Karin M. Verspoor, Timothy Baldwin, Laura Y. Hardefeldt, Caitlin Pfeiffer, Caroline Mansfield, Riati Scarborough, James R. Gilkerson

Natural Language Processing Faculty Publications

Background: Temporal phenotyping of patient journeys, which capture the common sequence patterns of interventions in the treatment of a specific condition, is useful to support understanding of antimicrobial usage in veterinary patients. Identifying and describing these phenotypes can inform antimicrobial stewardship programs designed to fight antimicrobial resistance, a major health crisis affecting both humans and animals, in which veterinarians have an important role to play. Objective: This research proposes a framework for extracting temporal phenotypes of patient journeys from clinical practice data through the application of natural language processing (NLP) and unsupervised machine learning (ML) techniques, using cat bite abscesses …

Public Acceptance Of Using Artificial Intelligence-Assisted Weight Management Apps In High-Income Southeast Asian Adults With Overweight And Obesity: A Cross-Sectional Study, Han Shi Jocelyn Chew, Palakorn Achananuparp, Palakorn Achananuparp, Nicholas W. S. Chew, Yip Han Chin, Yujia Gao, Bok Yan Jimmy So, Asim Shabbir, Ee-Peng Lim, Kee Yuan Ngiam

Research Collection School Of Computing and Information Systems

Introduction: With in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity. Methods: 280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression. Results: 271 participant responses were …

Dynamic Prognosis Prediction For Patients On Dapt After Drug-Eluting Stent Implantation: Model Development And Validation, Fang Li, Laila Rasmy, Yang Xiang, Jingna Feng, Ahmed Abdelhameed, Xinyue Hu, Zenan Sun, David Aguilar, Abhijeet Dhoble, Jingcheng Du, Qing Wang, Shuteng Niu, Yifang Dang, Xinyuan Zhang, Ziqian Xie, Yi Nian, Jianping He, Yujia Zhou, Jianfu Li, Mattia Prosperi, Jiang Bian, Degui Zhi, Cui Tao

School of Medicine Faculty Publications

BACKGROUND: The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. METHODS AND RESULTS: We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum’s de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were …

De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …

Artificial Intelligence Driven Information Technology System Restructuring And Reconstruction—Review Of Information Science & Technology In China: A Roadmap To 2050, Xuehai Hong

Bulletin of Chinese Academy of Sciences (Chinese Version)

The Information Science & Technology in China: A Roadmap to 2050 and Information Technology: Accelerating the Integration of Human Machine Things have predicted the long-term development of China’s information technology field. This study reviews the development and changes in the field of information technology in the past 15 years, and compares them with the initial predictions, pointing out that some important judgments made at the beginning were in line with expectations. In recent years, the global development of information technology has entered a slow period, while the rapid evolution of the new generation of artificial intelligence will bring new opportunities …

Enabling The Clinical Application Of Artificial Intelligence In Genomics: A Perspective Of The Amia Genomics And Translational Bioinformatics Workgroup, Nephi A Walton, Radha Nagarajan, Chen Wang, Murat Sincan, Robert R Freimuth, David B Everman, Derek C Walton, Scott P Mcgrath, Dominick J Lemas, Panayiotis V Benos, Alexander V Alekseyenko, Qianqian Song, Ece Gamsiz Uzun, Casey Overby Taylor, Alper Uzun, Thomas Nate Person, Nadav Rappoport, Zhongming Zhao, Marc S Williams

Faculty, Staff and Student Publications

OBJECTIVE: Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can further enable the clinical application of AI in this space.

PROCESS: A list of relevant factors was developed through GenTBI workgroup discussions in multiple in-person and online meetings, along with review of pertinent publications. This list was then summarized and reviewed to achieve consensus among the group members.

CONCLUSIONS: Substantial informatics research and development are needed to fully realize the clinical potential of such technologies. The development of …

Novel Techniques In Imaging Congenital Heart Disease: Jacc Scientific Statement, Ritu Sachdeva, Aimee K Armstrong, Rima Arnaout, Lars Grosse-Wortmann, B Kelly Han, Luc Mertens, Ryan A Moore, Laura J Olivieri, Anitha Parthiban, Andrew J Powell

Faculty, Staff and Students Publications

Recent years have witnessed exponential growth in cardiac imaging technologies, allowing better visualization of complex cardiac anatomy and improved assessment of physiology. These advances have become increasingly important as more complex surgical and catheter-based procedures are evolving to address the needs of a growing congenital heart disease population. This state-of-the-art review presents advances in echocardiography, cardiac magnetic resonance, cardiac computed tomography, invasive angiography, 3-dimensional modeling, and digital twin technology. The paper also highlights the integration of artificial intelligence with imaging technology. While some techniques are in their infancy and need further refinement, others have found their way into clinical workflow …

Creative Technologies: A Conversation With Roy Magnuson, Roy Magnuson, Maureen Russell

Faculty Publications - Music

[In lieu of an abstract, the introduction is provided.] Today I am speaking with Roy Magnuson, Associate Professor Creative Technologies in the School of Music at Illinois State University (ISU). (see Figure 1) His music has been performed throughout the United States and Europe at venues such as the World Saxophone Congress, WASBE, CBDNA, the RED NOTE New Music Festival, and the Robb Composers’ Symposium. Magnuson is also the creator of the virtual reality composition software solsticeVR and the conducting software RibbonsVR. He is a member of ASCAP, and his music is recorded on Albany Records and NAXOS.

Crafting Effective Prompts: Leveraging Generative Ai In Libraries, April Sheppard, Kristin Flachsbart

Staff and Faculty Scholarship

Discover how strategic prompt design can help you harness the power of generative artificial intelligence (AI) in your library. Through a series of examples, the presenters will demonstrate the impact that well-crafted prompts can have on the quality and relevance of AI-generated outputs.

Developing Policies For The Ethical Use Of Artificial Intelligence In Higher Education And Libraries, April Sheppard, Matthew Mayton

Staff and Faculty Scholarship

This presentation will provide sample artificial intelligence policy language from various higher education institutions and academic libraries. Topics covered will include the acceptable use of AI in the classroom, the role of faculty in making AI-related decisions, syllabus statements, AI use and detection, AI literacy, and library policies regarding AI. Participants will be able to compare and contrast policies to help them develop their own policies that work for their unique organization.