Artificial Intelligence and Robotics Commons^™

Evaluating Introductory Computer Science Labs In The Presence Of Ai Tools, Nicholas Snow, Devin Chaimberlain, Abigail Pitcairn, Benjamin Sweeney

Thinking Matters Symposium

This study explores the resistance of introductory computer science lab assignments to “shortcutting” by generative AI tools, such as ChatGPT. By analyzing the work of three distinct student personas on these assignments, we identified key characteristics of language and structure that influence an assignment's vulnerability to AI abuse. Based on these insights, we propose strategies for educators to adapt labs to both counteract AI shortcutting and encourage productive uses of AI.

Machine Learning-Based Gps Jamming And Spoofing Detection, Alberto Squatrito

Doctoral Dissertations and Master's Theses

The increasing reliance on Global Positioning System (GPS) technology across various sectors has exposed vulnerabilities to malicious attacks, particularly GPS jamming and spoofing. This thesis presents an analysis into detection and mitigation strategies for enhancing the resilience of GPS receivers against jamming and spoofing attacks. The research entails the development of a simulated GPS signal and a receiver model to accurately decode and extract information from simulated GPS signals. The study implements the generation of jammed and spoofed signals to emulate potential threats faced by GPS receivers in practical settings. The core innovation lies in the integration of machine learning …

Artificial Intelligence And Film: A Journey In Public Perception From 1960 To The Present Day, Kayla Anderson, Andrew Roggeman, Joseph Fuller

Celebrating Scholarship and Creativity Day (2018-)

An analysis of accomplishments in film from the 1960s-2020s that feature Artificial Intelligence to give a full picture of how public perception has changed towards these technologies over time, supplemented by historical and technological context.

Hello, World., Elliot Cetinski, Evan Chartock, Olivia Cross, Kiran Drew, Kaya Eller, Ben Little, Joey Nolan, Spencer Toth, Sophie Wahl-Taylor, Sadie Walker, Destiny Young, Annie Zulick

Theater and Dance Presentations

This project works to theatrically represent the current state of Artificial Intelligence (AI), as well as its benefits and drawbacks, in the style of the Living Newspaper. Originating from a Great Depression-era job program, the Living Newspaper sought to take headlines and present them onstage for a poignant and contemporary social critique. This work does the same, melding different angles of the AI debate into a single production that emphasizes the rapidly progressing state of modern AI technology and the need for humans to consider the impacts such technologies will have. Furthermore, it asks the audience to question their position …

Editorials For Special Topic "Artificial Intelligence And Future Society"

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

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 …

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 …

Venture Capital And Its Role In Facilitating Better Development In China's Artificial Intelligence Industry, Randong Yuan

Bulletin of Chinese Academy of Sciences (Chinese Version)

The venture capital (VC) industry plays a crucial role in advancing the development of the artificial intelligence (AI) sector. As a key bridge between technological innovation and industrialization, VC not only provides financial support to AI startups but also empowers them in strategic planning, technological research and development, and market expansion. However, China's VC industry currently faces several challenges in supporting AI development, including an imbalance in the roles of state-owned and private capital, a short-term investment mindset, and the cyclical phenomenon of "herding" and abrupt market exits. These issues hinder the growth trajectories of Chinese AI enterprises and constrain …

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 …

U.S.-Europe Artificial Intelligence Regulatory Cooperation, Divergence, And China's "Window Of Opportunity" For Strategic Breakthrough, Yang Mei, Jing Zeng, Yong Zhan

Bulletin of Chinese Academy of Sciences (Chinese Version)

The United States, Europe, and China have adopted completely different technological development paths in the era of artificial intelligence innovation, forming a model division of "development-driven governance", "stringent governance framework", and "coordinated governance model" The United States and Europe have respectively set strategic goals as "maintaining technological hegemony" and "competing for the soft power of international rules", forming an interactive model in which institutional supervision and industry independence parallel, and cooperation needs and policy divergence coexist. China has contributed a unique technological governance logic of "people-oriented" and "moral-oriented". Faced with the current technological "window of opportunity", China should adopt two …

Ai-Powered Learning: Blending Ai With Active Learning In The Information Literacy Classroom, Kevin J. Reagan, Wilhelmina Randtke

Georgia International Conference on Information Literacy

In 2016, the ACRL Framework for Information Literacy in Higher Education launched in response to more voluminous, less-vetted online information, including misinformation and content farms. Subsequently, the ACRL Framework has been widely adopted, and numerous high-quality lesson plans and resources for teaching the frames already exist, including published lesson plans and textbooks. Now, generative AI tools, such as ChatGPT and other chat bots present new challenges for information literacy educators. For instance, in addition to teaching students how to identify issues such as fake news, the information literacy professional has to address topics such as ethical AI use, AI hallucination …

Andrews University Pre-Professional Students Preparedness For A Future With Artificial Intelligence, Zachary Alignay

Honors Theses

Artificial Intelligence technology has advanced considerably over the past four years. With such rapid technological development, the question has to be asked if students are adequately educated on the implications and abilities of artificial intelligence. Are Andrews University pre-professional students prepared for future careers with artificial intelligence? To approach this question, a survey of students across multiple perspectives was conducted to sample if there was a consensus, or lack thereof, on the perception of ethics regarding artificial intelligence, to ask students how using artificial intelligence has changed their education, what purposes it can be used or cannot be used, personal …

Subject Analysis Ex Machina: Developing A Subject Heading Recommendation Service For Jmu Libraries, Steven W. Holloway

Libraries

Results of a 2022 evaluation of ANNIF, open-source software designed to generate controlled vocabulary subject headings, using James Madison University Libraries resources.

Ai’S Carbon Shadow: An Exploration Of The Energy Dilemma And Earth’S Future, Olga Roussos

Student Publications and Presentations

As artificial intelligence continues to advance, more processing power and energy usage are required. This increase in energy consumption by AI leads to increased carbon emissions in the atmosphere as well as rapid resource depletion. The effects of AI’s growing energy consumption can have severe negative impacts on global climate, biodiversity, sustainability, and other aspects of the environment. This research aims to highlight the volume of energy that artificial intelligence uses, the expected environmental effects of artificial intelligence’s expansion, as well as the potential innovative solutions and sustainable practices that can be implemented to decrease energy usage and preserve the …

A Research Proposal Investigating The Geopolitical And Economic Impact Resulting From The Development Of Artificial General Intelligence (Agi), Tobia Donadon, Kristen Migliano

Student Publications and Presentations

Artificial General Intelligence (AGI) represents the next step in the development of AI, a huge step in the quest for artificial intelligence. AGI aims to create machines capable of understanding, learning, and applying knowledge across various tasks, much like humans.

This research proposal focuses on advancements and potential effects, with an objective to bridge the gap between narrow AI applications and the broader cognitive capabilities of AGI. This study explores the transformative potential of AGI while addressing the societal impacts. The research looks into the relationship between the development of AGI and geopolitical affairs.

Drawing on recent discoveries in mathematical …

Jsper (Just Stablediffusion Plus Easy Retraining), Adam Rusterholz, Meghan Finn, Zach Zolliecoffer, Zach Judy

ATU Scholars Symposium

JSPER is an an AI art generation Web Application that is both flexible and accessible. Our goal is to enable anyone to create and use their own customized art models, regardless of technical skill level. These models can be trained on almost anything, from a person, to an animal, to a specific object, or even style. The user only has to upload a handful of images of their subject. Then, training settings get optimized at the push of a button to match the type of subject the user is training. After training, their customized model can be used to generate …

Optimizing Campus Chat-Bot Experience Using Puaa: Integrating Large Language Model (Llm) Into University Ai Assistants, Sijan Panday, Zurab Sabakhtarishvili, Clayton Jensen

ATU Scholars Symposium

The advent of large language models (LLMs) such as Chat-GPT and Bard marks a significant milestone in knowledge acquisition, offering a streamlined alternative to the traditionally labor-intensive process of navigating through multiple checkpoints on the web. This emerging trend in LLMs renders the prevalent rule-based chatbots, commonly utilized by universities, increasingly outdated and subpar. This research project proposes integrating LLM technology into university websites, specifically targeting the needs of students seeking information about their institutions by introducing PUAA (Personal University AI Assistant). Our approach involves using the Retrieval-Augmented Generation (RAG) framework, leveraging the capabilities of the LlamaIndex in conjunction with …

Techniques To Detect Fake Profiles On Social Media Using The New Age Algorithms – A Survey, A K M Rubaiyat Reza Habib, Edidiong Elijah Akpan

ATU Scholars Symposium

This research explores the growing issue of fake accounts in Online Social Networks [OSNs]. While platforms like Twitter, Instagram, and Facebook foster connections, their lax authentication measures have attracted many scammers and cybercriminals. Fake profiles conduct malicious activities, such as phishing, spreading misinformation, and inciting social discord. The consequences range from cyberbullying to deceptive commercial practices. Detecting fake profiles manually is often challenging and causes considerable stress and trust issues for the users. Typically, a social media user scrutinizes various elements like the profile picture, bio, and shared posts to identify fake profiles. These evaluations sometimes lead users to conclude …

Anomaly Detection With Spiking Neural Networks (Snn), Shruti Bhandari, Vyshnavi Gogineni

ATU Scholars Symposium

Abstract:

Anomaly detection, the identification of rare or unusual patterns that deviate from normal behavior, is a fundamental task with wide-ranging applications across various domains. Traditional machine learning techniques often struggle to effectively capture the complex temporal dynamics present in real-world data streams. Spiking Neural Networks (SNNs), inspired by the spiking nature of biological neurons, offer a promising approach by inherently modeling temporal information through precise spike timing. In this study, we investigate the use of Spiking Neural Networks (SNNs) for detecting anomalies or unusual patterns in data. We propose an SNN model that can learn what constitutes normal …

Innovating Inventory And Alert Systems With Object Tracking, Juan Harmse, Esther Peden

Campus Research Month

Security system users require safeguarding inventory from potential theft while reducing manual tracking of physical objects. Our contribution harnesses the power of artificial intelligence and computer vision with YOLO to automate the process of tracking inventory items. The system sends alerts to the inventory manager when it detects particular events. Our approach was evaluated with KernProf profiling, interference, and orientation tests. The results were overall positive in these testing areas.

The Vulnerabilities Of Artificial Intelligence Models And Potential Defenses, Felix Iov

Cybersecurity Undergraduate Research Showcase

The rapid integration of artificial intelligence (AI) into various commercial products has raised concerns about the security risks posed by adversarial attacks. These attacks manipulate input data to disrupt the functioning of AI models, potentially leading to severe consequences such as self-driving car crashes, financial losses, or data breaches. We will explore neural networks, their weaknesses, and potential defenses. We will discuss adversarial attacks including data poisoning, backdoor attacks, evasion attacks, and prompt injection. Then, we will explore defense strategies such as data protection, input sanitization, and adversarial training. By understanding how adversarial attacks work and the defenses against them, …

Intelligent Optimization Method Of Cloud Manufacturing Swarm Based On Incomplete Information Game, Kunpeng Zhang, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: In the process of cloud manufacturing, the incomplete information status and the mutual competition and restriction relationship between cloud platform operator and demander lead to the difficult choice of manufacturing services. A cloud manufacturing swarm intelligent optimization method based on incomplete information game model is proposed. A static game model based on incomplete information is established for the interest competition between demand-side and cloud platform, with the goal of rationally pursuing the maximization of their own revenue function. The competition rules between demand-side and cloud platform are proposed, which are introduced into nature through Harsanyi transformation and converted into …

Hyper-Heuristic Approach With K-Means Clustering For Inter-Cell Scheduling, Yanlin Zhao, Yunna Tian

Journal of System Simulation

Abstract: According to the actual production situation of China's manufacturing industry, a hyperheuristic algorithm based on K-means clustering is proposed for inter-cell scheduling problem of flexible job-shop. K-means clustering is applied to group entities with similar attributes into the corresponding work cluster decision blocks, and the ant colony algorithm is used to select heuristic rules for each decision block. The optimal scheduling solutions are generated by using corresponding heuristic rules for scheduling of entities in each decision block. Computational results show that, the computational granularity is properly increased by the form of decision blocks, and the computational efficiency of the …

Distributed Energy Management Strategy Of Microgrid Based On Master-Slave Game, Miaomiao Ma, Hao Wang, Lipeng Dong, Xiangjie Liu

Journal of System Simulation

Abstract: Under the operation mode of power market, based on two-layer master-slave game, a distributed energy management strategy for the microgrid is proposed to tackle the conflict between the overall optimal operation of renewable microgrid and the maximum profit of each investor. To fully consider the balance between energy supply and demand, the concept of power trading agent is introduced, and an integrated demand response strategy based on consumer satisfaction and adjustable load is proposed on the user side. Considering the initiative and decision-making ability of power supply and load, the decision-making game model is established with power trading agent …

Optimization Of Urban Traffic Microsimulation Model For Carbon Emission Reduction, Bo Liu, Jianxin Lin, Yini Liu, Dong Zhang

Journal of System Simulation

Abstract: To assess the environmental benefits of transportation management or control strategies, a method to effectively integrate the micro-traffic simulation model and the micro-vehicle emission model is proposed. VISSIM platform is used to build a case micro traffic simulation model. K-means clustering method is used to divide the driving behavior into 4 types based on the acceleration and deceleration characteristics of different speed intervals of the trajectory data, and the global parameters of the simulation model are calibrated based on the driving characteristics, which quantitatively describe the total sensitivity of the parameters and the sensitivity of the interactions between the …

Modeling And Analysis Of Hybrid Traffic Flow Considering Actual Behavior Of Platoon, Xi Wang, Xiujian Yang, Xiaohan Jia, Shenyi Wang

Journal of System Simulation

Abstract: To explore the effect of actual behavior of autonomous vehicular platoon on traffic flow, aiming at the hybrid traffic flow mixed with predecessor following(PF) platoon which is modeled according to the actual control strategy, a hybrid traffic flow model is established based on cellular automata(CA) modeling method. Simulation analysis shows that the effect of platoon characteristics such as time headway, market penetration, platoon size, and control gains on hybrid traffic flow presents coupling and nonlinear properties. The spatiotemporal behavior of hybrid traffic flow with different platoon characteristics is generally much different. Reducing time headway or increasing platoon market penetration …