Artificial Intelligence and Robotics Commons^™

Artificial Intelligence-Enabled Materials Innovation: Implementation Levels And Strategic Layout, Ziwei Zhao, Fengxiang Zhou, Yanglili Zhou, Can Wang, Pei Zhang, Weihua Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Materials innovation has long been constrained by vast design spaces, complex processing routes, lengthy validation cycles, and difficulties in engineering translation. Traditional research and development models, which mainly rely on accumulated experience, theoretical deduction, and experimental trial and error, have become increasingly insufficient to meet the demand for rapid breakthroughs in critical materials. In recent years, artificial intelligence has been increasingly integrated into materials design, synthesis, and processing, characterization, evaluation, optimization, and application feedback, promoting the transformation of materials innovation from experience-driven exploration to data-driven development and from discrete trial and error to closed-loop optimization. Based on an analysis of …

Artificial Intelligence Empowered Biological Research: Paradigm Shifts, Application Scenarios, And Strategic Layout, Xinguang Zhu, Yiming Bao, Zhenong Jin, Xin Li, Sijia Wang, Yueming Wang, Yungui Yang, Cao Xu, Yan Xiong, Bin Han

Bulletin of Chinese Academy of Sciences (Chinese Version)

Life related processes are characterized by high dimensionality and multi-scale properties. Understanding mechanisms underpinning life processes helps promote national healthcare, agricultural development, sustainable ecological civilization, and national security. Current life science research is confronted with an enormous challenge of dimensionality stemming from data explosion and data fragmentation, for which the recent rapid advancement of artificial intelligence (AI) provides novel solutions. AI will catalyze a paradigm shift in life science research from the current experiment based empirical induction to a new closed-loop knowledge acquisition including large scale data collection, model building, model prediction, experimental validation, and iterative of these procedures. Life …

Artificial Intelligence–Driven Paradigm Transformation In Biopharmaceutical R&D: Applications And Emerging Scenarios, Lili Liu, Mingyue Zheng, Ye Yuan, Xutong Li, Rong Fan, Wei Wei, Jinxin Zhao, Guobin Qi, Hua Yue, Likun Gong, Songping Zhang, Jiachen Li, Yuchen Sun, Xiaoyan Chen, Yao Chen, Xin Liu, Xiao Zhang, Yuehong Gao, Jianfeng Li, Kaixian Chen, Guanghui Ma, Jianmin Yue

Bulletin of Chinese Academy of Sciences (Chinese Version)

The biopharmaceutical industry is a critical domain underpinning national scientific and technological innovation development and public health. With the rapid advancement of artificial intelligence (AI) and its deep integration with the life sciences, biomedicine research is undergoing a paradigm shift from traditional experience-driven trial-and-error approaches to data-driven and predictive validation-based models. This study systematically examines the pathways for reshaping research in biomedicine paradigms under the convergence of data-driven, mechanism-driven, and intelligence-driven approaches. It focuses on recent advances in the application of AI across key stages, including drug discovery and design, druggability evaluation, delivery system design and optimization, nonclinical and clinical …

Artificial Intelligence For Cybersecurity: Opportunities, Challenges, And Approaches, Kai Chen, Ding Li, Guozhu Meng, Shouling Ji, Changjiang Li, Yi Yang, Dengguo Feng

Bulletin of Chinese Academy of Sciences (Chinese Version)

Cybersecurity research, institutional structures, and governance policies are undergoing profound transformations. Currently, increasingly covert and rapidly evolving intelligent attacks, coupled with the national urgent expectations for high-level security, are driving significant shifts in the roles and interactions of governments, research institutions, and enterprises. Consequently, this study, based on analyzing the challenges and opportunities of the AI era, explores core application scenarios such as critical information infrastructure protection, national data security, and the maintenance of cyberspace sovereignty. It provides an analysis of artificial intelligence in dimensions such as correlation and causality, and proposes a governance framework, aiming to provide insights for …

Artificial Intelligence For Astronomy: Strategic Opportunities, Policy Challenges And Development Strategies, Jin Chang, Yihan Song, Bing Du, Kefei Wu, Ali Luo, Jifeng Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

To alleviate the bottlenecks hindering the integrated development of artificial intelligence and astronomy in China and to reinforce the country’s strategic edge in science and technology, this study uses systematic analysis and path-comparison approaches to examine the policy requirements for their deep integration. The findings indicate that this topic is closely tied to global competition in science and technology, strategic security, and industrial upgrading. At present, the world has entered a new “astronomy + AI” paradigm, with the United States and the European Union already having taken the lead in establishing corresponding strategic frameworks. Leveraging major scientific infrastructures such as …

Artificial Intelligence Empowering Space Science—Case Study Of Space Weather, Chi Wang, Hui Li, Bingxian Luo, Fang Shen, Jingjing Wang, Lingqian Zhang, Yi Yang, Dong Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Space science is currently confronted with a triple challenge: the explosive growth of observational data, the strongly coupled cross-scale nature of physical processes, and the increasingly urgent national strategic demands. The limitations of traditional research paradigms in analytical efficiency, forecast accuracy, and autonomous capability hinder their effectiveness in meeting critical requirements such as safeguarding on-orbit satellites and ensuring the successful execution of major space missions. This study proposes a three-layer “perception–cognition–decision-making” architecture for intelligent space science. Taking space weather—a domain with strong operational relevance—as a representative case, the four-dimensional paradigm transformation driven by artificial intelligence is systematically examined across key …

Artificial Intelligence Empowering Remote Sensing: Challenges, Paradigms And Strategic Layout, Jiayuan Shen, Peirui Cheng, Zhirui Wang, Wei Liang, Xian Sun, Yirong Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Remote sensing science and technology, as a key discipline for Earth observation and global change research, faces systemic challenges in processing massive multi-source data, accurately extracting complex information, and delivering high-timeliness application services. The rapid advances in artificial intelligence (AI) provide a new opportunity to address the deep-seated dilemma in remote sensing of being “data-rich but insufficient in effective information mining”. Guided by a problem-oriented approach, this study first systematically analyzes the core challenges facing the development of remote sensing across four dimensions: data understanding, technical methods, scientific mechanisms, and application ecosystems. It then reviews the technical evolution of AI-empowered …

Artificial Intelligence For Deep Earth Science: Key Challenges, Major Application Scenarios And Development Pathways, Qingyun Di, Liang Zhao, Yikang Zheng, Zhi Geng, Zhichao Yu, Xiaocai Shan, Chao Li, Zhiyao Xu, Pengfei Lv

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep Earth science is central to understanding Earth’s internal architecture and the coupled evolution of its major spheres, while also underpinning energy security, the supply of critical mineral resources, and resilience to major geohazards. Nevertheless, the advancement of deep Earth science is currently hindered by insufficient in situ observations under extreme conditions, the difficulty of integrating multi-source heterogeneous data, and the limited capability to model complex multiphysics coupling processes. Recent advances in artificial intelligence offer a potential route beyond these limitations. By integrating data-driven learning with physical and geological understanding, AI is reshaping deep Earth science from empirical interpretation to …

Artificial Intelligence For Science: Connotations, Characteristics, And System, Kaihua Chen, Heyang Li, Hongxin Liu, Binbin Zhao, Shuo Yang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence is profoundly transforming the fundamental nature of scientific research, reshaping its modes of knowledge production and organizational operation, driving the emergence of a new artificial intelligence for science (AI4S) research paradigm, and accelerating full-chain innovation paradigm transformation. This study defines the basic connotations of AI4S across three dimensions, namely, enabling applications, tools and methods, and epistemic knowledge, and systematically identifies five core characteristics: human-machine symbiosis, autonomous evolution, interdisciplinary integration, resource intensity, and open ecosystems. It further constructs a supporting system and operational architecture encompassing layers of infrastructure, data resources, model tools, task execution, and application scenarios. Building on …

Data Governance Maturity, Ai Integration, And Equity In Colorado K-12 Public Schools, John R. Curtin

Electronic Theses and Dissertations

Colorado's 179 K-12 public school districts operate as autonomous governance units, each responsible for securing and managing student data assets that span health, financial, residential, and academic records. The accelerating integration of artificial intelligence (AI) and machine learning (ML) tools into administrative workflows, productivity software, and instructional platforms has fundamentally altered the risk landscape for student data, yet governance frameworks at the state, district, and school levels have not kept pace. This dissertation investigates whether Colorado's decentralized educational governance structure is institutionally capable of producing equitable, secure, and sustainable data governance outcomes in the AI era.

Drawing on Institutional Theory …

The Security Of Llm-Generated Code, Christopher Brian Gonzalez Ayala

Student Theses

The rapid adoption of Large Language Models (LLMs) in software development has transformed coding practices by enabling automated code generation, completion, and optimization. Despite these advantages, concerns persist regarding the security and reliability of LLM-generated code. This study presents a comprehensive evaluation of both the functional correctness and security of code produced by three prominent LLMs as of early 2026. A total of 4,800 code snippets were generated using 100 security-focused programming prompts derived from the OWASP Top 10:2025, translated across eight natural languages and two phrasing styles (literal and natural developer-oriented prompts). To assess performance, a multi-stage experimental framework …

Trace: Temporal Rhetorical Analysis And Consistency Evaluation For Legislative Speech, David Hernandez

Master's Theses

Legislators frequently discuss the same policy issues across multiple hearings and legislative sessions, sometimes maintaining consistent positions and other times modifying or reframing their stance over time. Understanding how these positions evolve is important for analyzing political discourse and democratic accountability, yet identifying such shifts at scale remains difficult.

We introduce TRACE (Temporal Rhetorical Analysis and Consistency Evaluation), a system built on the Digital Democracy Database (DDDB) for detecting rhetorical inconsistency in California legislative hearing testimony. TRACE organizes utterances into speaker-anchored timelines indexed by bill and session, then applies hybrid semantic retrieval — combining dense BGE embeddings with BM25 lexical …

Generation Z And The Ai Misinformation Paradox: Understanding A New Digital Vulnerability, Cecilia Cooley, Elizabeth Sperber

DU Undergraduate Research Journal Archive

This paper asks: How and why is Generation Z more vulnerable to AI-generated misinformation and disinformation than older generations? Using a comparative review of recent empirical studies, survey data, and meta-analyses from 2019–2025, this paper synthesizes research on Gen Z’s exposure to and interaction with AI-produced content across social media platforms. Although it is commonly assumed that Gen Z ’s technological exposure and fluency make them better equipped to recognize false information, findings show the opposite: Gen Z is consistently outperformed by older cohorts in detecting AI-generated falsehoods. This vulnerability stems from three intersecting factors: (1) the sheer volume of …

Operational Responsibility In Ai Governance: A User-Centric Liability Framework, Zhengyang Chen

Faculty Publications

Who bears responsibility when artificial intelligence systems cause harm? This question has become central to AI ethics and governance. Most existing approaches focus on developers, yet this faces serious practical and theoretical problems. Drawing on tort law, agency law, and philosophy of technology, this paper argues that AI should be understood as an instrument whose outputs remain the responsibility of human operators rather than developers. We call this 'user-centric governance.' Placing accountability with deployers promotes public trust by creating clear lines of responsibility, a concern that governance approaches have often overlooked. It preserves democratic accountability by keeping human actors answerable …

Seizing Strategic High Ground Of Space Computing Power: Global Competition Landscape And China’S Path, Yan Chen, Wenbin Song, Ping Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The deep integration of artificial intelligence and commercial aerospace is accelerating the transformation of space computing power from conceptual exploration to engineering verification, becoming a key direction for building an integrated space-air-ground information infrastructure. This study delves into its strategic value, global landscape, industrial chain bottlenecks, and advancement paths. The research reveals that the core value of space computing power does not lie in replacing ground data centers, but rather in focusing on network coverage blind spots, data transmission limitations, and high-timeliness scenarios, providing a new supply model of “in-orbit computing + space-ground collaboration”. Currently, the world has entered a …

Dialogue Between Mind And Algorithm: Deep Symbiosis Of Psychology And Artificial Intelligence, Xiaolan Fu, Zheng Yan

Bulletin of Chinese Academy of Sciences (Chinese Version)

As artificial intelligence (AI) evolves from a supportive tool into a collaborative partner, the convergence of psychology and AI is gradually shifting from one-way application toward deep symbiosis. This study discusses the mutual empowerment resulting from their interaction, as well as the challenges they face and potential pathways to breakthroughs. On the one hand, psychology empowers AI by enhancing its human-like intelligence and social adaptability through cognitive modeling and ethical constraints; on the other hand, AI empowers psychology by leveraging multimodal data and algorithmic models to revolutionize psychological assessment and intervention methods. This deep symbiosis requires a clear-eyed acknowledgment of …

Welcome Tilly Norwood: Forecasting Hollywood’S Ai Policy Futures, Samuel P. Rooker

Senior Honors Projects, 2020-current

In late 2025, weekly trade publication Variety Magazine reported on the announcement of a new acting talent in Hollywood: Tilly Norwood. Norwood is an industry outsider and the pet project of Eline Van der Velden, who unveiled the actress’ existence to the world at the Zurich Film Festival. The announcement quickly gained media coverage while Van der Velden has since faced cyclical backlash from Hollywood trade unions, which does not seem entirely without reason. Tilly Norwood is a digital persona, a generative artificial intelligence (GenAI) program, designed by Van der Velden’s novel AI talent studio, Xicoia, to become the next …

Strategic Talent Management In Era Of Intelligence And Digitalization: Current Situation And Path Exploration, Chaoying Tang, Chunyuan Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The report of the 20th National Congress of the Communist Party of China emphasized “speed up efforts to build a contingent of personnel with expertise of strategic importance” to support China’s pursuit of high-level technological self-reliance and its goal of becoming a world-leading power in science and technology. The deep integration of digital and intelligent technologies is fundamentally transforming talent management paradigms and innovation processes, posing new demands on the knowledge structure, competency models, and management approaches of strategic talents. The study explores the concepts of strategic talent management in the digital intelligent era, establishes its logical framework, analyzes current …

Northern Rainstorm Belt And Response Strategies, Jianping Huang, Xiaodan Guan, Xiaohuang Liu, Xiaohan Shen, Xiaojie Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the summer of 2025, the Northern Rainstorm Belt stretching from eastern Northwest China to the Northeast region exhibited a significant increase in summer precipitation and rainfall frequency over northern China. Cities in the north were frequently struck by extreme rainstorms, resulting in prominent disasters such as “floods in drylands and urban waterlogging”. Northern China spans a vast territory, serving not only as a major grain-producing area and a densely populated region but also as an ecological security barrier that connects the farming-pastoral ecotone and the Loess Plateau. Its stability has nationwide implications. Therefore, comprehensively enhancing flood control capacity, strengthening …

Ai Exposure And The Future Of Work: Tasks, Skill Demand, And Education, Erik Vasilauskas, Michael Horrigan

External Papers and Reports

No abstract provided.

The Expanding Digital Border: Ai, Surveillance, And The Fight For Justice, James Chesser

Immigration and Human Rights Law Review

As artificial intelligence transforms the mechanisms of immigration control, the modern border has become a digital filter—one governed less by geography and more by code. This Article examines the legal, technical, and ethical implications of AI-driven systems now central to global border enforcement, including biometric surveillance, algorithmic risk scoring, and predictive profiling. It explores how states use these technologies not only to manage irregular migration, but to compete for global talent—constructing migration regimes that reward capital and compliance while eroding transparency, due process, and equality.

Through an international and comparative lens, the piece highlights the expansion of algorithmic decision-making across …

A View Under The Hood: Duquesne Kline's Law And Computing Program, Wesley M. Oliver, Katherine L.W. Norton, Martin Mckown, David Horrigan

West Virginia Law Review

No abstract provided.

The Energy And Environmental Footprint Of Ai, Michael P. Vandenbergh, Ethan I. Thorpe, Jonathan M. Gilligan

Michigan Journal of Environmental & Administrative Law

Artificial intelligence (AI) has the potential to create major economic and social benefits, but also to rapidly escalate electricity demand and its associated environmental impacts. Information availability has been a cornerstone of environmental law for half a century, and this Article argues that providing information to individual, corporate, and other users about the electricity demand and environmental impacts of AI can reduce those impacts without delaying development of the technology. Little is known about how different large language models (LLMs) compare on these metrics, though. To address whether users have access to the information necessary to address this shortcoming, the …

Science And Technology Communication And Construction Of China’S International Discourse System: Strategic Significance, Current Challenges, And Innovative Pathways, Haonan Du, Ting Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Against the backdrop of a new round of scientific and technological revolution with the ongoing restructuring of the global governance system, science and technology have become central to competition in national comprehensive competitiveness and struggles for international discourse power. China’s science and technology have achieved a historic leap from “catching up” to “running alongside” and even “leading in certain areas”, providing solid strength support for the construction of an international discourse system. However, the transformation of scientific and technological advantages into discourse advantages remains insufficient, and the international community holds a dual perception of China’s technological advancements—recognition alongside concerns. The …

Understanding Key Lssues In Current Artificial Intelligence Development And Governance, Meng Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

At present, as global artificial intelligence advances vigorously, the industry is engaged in intense discussions about the future direction of its development and governance, where certain consensus has been reached alongside notable divergences and controversies. This study focuses on several key contentious issues in the current development and governance of artificial intelligence, analyzes their inherent logic by combining the laws of scientific and technological progress, and puts forward corresponding solutions. Regarding the potential bubble risk, it emphasizes the need to strengthen the application of artificial intelligence in the real economy to channel and guide its development momentum. For the future …

Comparative Study On Ai Talent Cultivation In China And The United States: Strategies And Recommendations, Lexuan Li, Ke Wen, Wenjie Liu, Wei Shen, Zhenguo Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI), as the core driving force of the new industrial revolution, has become a strategic pillar for enhancing national competitiveness, with the cultivation of AI talent being a decisive factor. This study systematically compares the AI talent cultivation systems of China and the United States from three perspectives: strategic planning, formal education, and practical domains. The findings reveal that the U.S. has continuously and systematically advanced AI talent cultivation plans at the national level, granted institutions substantial autonomy in talent cultivation with deep integration of industry-academia-research collaboration, and established a well-developed AI innovation and entrepreneurship environment. Accordingly, the …

Research And Reflections On Model Of China’S Ai Open-Source Innovation Ecosystem, Yuntao Long, Haibo Liu, Qigang Zhu, Xudong Ren, Yanjun Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Open-source innovation, leveraging its strengths in collective collaboration and agile development, is increasingly becoming a core driver reshaping innovation paradigms and industrial ecosystems in the global artificial intelligence field. As a significant force in global technological development, China is actively promoting technology enterprises, research institutes, universities, and other diverse entities to deeply integrate into the construction of the global AI open-source innovation system through policy guidance, community building, and breakthroughs in large models. Based on the practical experience of building China’s AI open-source innovation ecosystem, this study systematically examines the current development status and challenges. By analyzing the operational models …

Transformation Of Open-Source Innovation Governance Of Large Models, Zhe Wang, Jinsong Cai

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial general intelligence (AGI), represented by large-scale models, is a transformative driver of new-quality productive forces, making the effective construction and governance of open-source innovation commons increasingly critical. Yet traditional open-source models are under strain, and existing commons theories require further development. Model training costs rise exponentially with each iteration, while a sustainable profit cycle from innovation to industrial application has not been established, rendering long-term cost-bearing infeasible for individual organizations. The traditional community-enterprise collaboration model, once successful in generating ecosystem value, now faces escalating computing and data costs, uncertain commercial returns, and governance risks related to social and national …

Availability Model To Evaluate Ai Data Centers’ Role In Grid Stability, Troy Mcsimov, Trevor S. Kunz, Jeffrey Billo

SMU Data Science Review

The United States has made it clear; it is imperative that the US wins the global AI race. This paper focuses on one of the most challenging puzzle pieces surfaced at the POWER Data Center conference (San Antonio, Sept. 30.); for Electric Reliability Council of Texas (ERCOT) the limiting factor is not generation alone but the need to balance generation and load to preserve grid reliability.

The regulatory landscape fundamentally changed with the passage of Texas Senate Bill 6 in June 2025, which mandates new large loads must "contribute to the recovery of the interconnecting electric utility’s costs" (Texas Legislature, …

Opportunities, Challenges, And Conspicuous Absences: An Integrative Review Of The Social Work Literature On Artificial Intelligence, Michael J. Massey, Ian G. Williams, Grace C. Polistina, Eathan A. Breaux

Publications and Research

INTRODUCTION: Social work discourse regarding artificial intelligence (AI) in practice, research, and education has proliferated over the last 5 years, reflecting both excitement over its potential and ambivalence about its ethical challenges. However, the extent to which social work is fully engaging with the structure of AI and its enormous impacts on the environment, labour, and distribution of power remains unclear.

METHODS: An integrative review of social work literature from 2020–2024 was conducted to address two research questions: 1) What is the nature of the social work discourse related to AI? 2) To what extent is the discourse …