Artificial Intelligence and Robotics Commons^™

Ai4r: The Fifth Scientific Research Paradigm, Guojie Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

This article refers to “AI for Research（AI4R）” as the fifth research paradigm and summarizes its characteristics, including: (1) the fully integration of artificial intelligence into various scientific and technology researches; (2) machine intelligence has become an integral part of scientific research; (3) effectively handles the combinatorial explosion problem with high computational complexity; (4) probability and statistical models play a greater role in scientific research; (5) realize the integration of four existing research paradigms, cross disciplinary cooperation has become the mainstream research method; (6) scientific research relies more on large research platforms characterized by large models. This article points out that …

Digital Scientists And Parallel Sciences: The Origin And Goal Of Ai For Science And Science For Ai, Feiyue Wang, Yutong Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Based on recent development in foundation model, parallel intelligence, decentralized science (DeSci), and other artificial intelligence (AI) technologies, from AI for Science (AI4S) to Science for AI (S4AI), this study discusses parallel sciences and digital scientists, and their impact and significance in paradigm shift for research and development as well as Industry 5.0 and intelligent industry, which demonstrate that paradigm shift is emerging and accelerating, and we must be prepared.

Computing System For Simulation Intelligence, Guangming Tan, Weile Jia, Zhan Wang, Guojun Yuan, En Shao, Ninghui Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study refers computer simulation in scientific research to as scientific simulation. Based on its narrow and broad definitions, this study divides scientific simulation into three stages: numerical computation, simulation intelligence, and science brain. Now, scientific simulation is entering the era of simulation intelligence, i. e., driven by scientific big data and artificial intelligence technology, scientific simulation is shifting from traditional numerical simulation to simulation integrated with artificial intelligence. In order to understand what the right computing system for simulation intelligence is, the design guidelines, basic methods, and key technical problems are discussed.

Large Model-Driven, Human-Computer Collaborative Robotic Ai-Chemist Cloud Facility, Yuanyuan Chong, Shuo Feng, Song Wang, Jun Jiang

Bulletin of Chinese Academy of Sciences (Chinese Version)

At present, chemical science is facing unprecedented opportunities and challenges due to the technological changes brought by artificial intelligence. In order to promote the paradigm shift in chemical research, this study proposes the construction plan of the robotic AI-chemist cloud facility. This system realizes a new paradigm of scientific research by collecting multi-channel data to build a database, developing large scientific models enhanced by chemical knowledge, constructing clusters of robotic facilities, and building an intelligent management decision system, which will dramatically improve the efficiency of scientific research and solve scientific problems in terminal applications. This infrastructure is expected to change …

A New Paradigm Of Life Science Research Driven By Artificial Intelligence, Xin Li, Hanchao Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid development of biotechnology and information technology has brought life sciences into a new era of data explosion. The traditional life science research paradigm struggles to reveal the fundamental rules of complex biological systems from rapidly growing biological big data. As artificial intelligence continues to achieve disruptive breakthroughs in life science, a new paradigm driven by AI is emerging. This study delves into typical examples of life science research driven by AI, proposes the concept and key elements of the new life science research paradigm, elaborates on the cutting-edge of life science research under this new paradigm, and discusses …

Ai For Technology: Applied Practices And Future Perspectives Of Technological Intelligence In High Tech Areas, Yunji Chen, Qi Guo

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the core of the fifth research paradigm, AI for Science has been widely used in multiple research fields of natural sciences and high technologies. In contrast to that the application of AI in natural sciences mainly focuses on discovering new theories, principles, and laws, the application of AI in high technologies mainly focuses on creating new plans, tools, and products, in order to resolve concrete problems in related fields. This study first summarizes the typical characteristics and scientific problems of the application of AI in high technologies, i.e., AI for Technology, and then introduces a successful case study of …

Building New Paradigm Of Digital Intelligence Security For New Development Pattern, Xiaoguang Yang, Yang Wu, Xingwei Zhang, Xiaolong Zheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

After the 20th National Congress of the Communist Party of China, China has entered a new era of development. Simultaneously, the rapid advancement and extensive application of artificial intelligent technologies have activated a new wave of economic potential and brought about new security challenges to socioeconomic development. This study firstly analyzes the characteristics of the new development pattern in global contexts, and examines the risks and challenges of digital intelligence security (DIS) under the new pattern, encompassing technological security and personal security at the micro-level, as well as economic security, social security, and cultural security at the macro-level. Based on …

Ai For Science: Ai Enabled Scientific Facility Transforms Fundamental Research, Xiaokang Yang, Yanyan Xu, Lu Chen, Yunbo Wang, Yue Gao, Jidong Tian, Kai Yu, Yaohui Jin, Hong Mei

Bulletin of Chinese Academy of Sciences (Chinese Version)

In recent years, artificial intelligence (AI) has achieved numerous disruptive breakthroughs in frontier scientific and technological fields, such as AlphaFold2 for protein structure prediction, intelligent control of nuclear fusion, and drug design for COVID-19. These achievements indicate that AI for Science is becoming a new paradigm in research. To achieve fundamental scientific innovation and major technological breakthroughs in the era of intelligence, two core issues should be addressed: 1) how to harness the generality and creativity of the new-generation of AI, especially generative AI and large language models (LLMs), to promote the formation of new paradigms; 2) how to empower …

Strategic Research On Information Technology Promoting National Governance Modernization—Review On The S70th Xiangshan Science Conferences, Chao Zhang, Weiyu Duan, Kaihua Chen, Xiaoguang Yang, Yuntao Long

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study systematically summarizes the reports and speeches of the S70th Xiangshan Science Conferences on the theme of “Strategic Research on Information Technology Promoting the National Governance Modernization” and summarizes the consensus of the conference in the following three aspects. (1) Important progress and achievements have been made in the four typical areas, i.e., smart justice, internet governance, data governance, and emergency management. (2) Using information technology to promote the modernization of national governance is confronted with unprecedented opportunities and challenges. And (3) it is necessary to take a series of effective measures to promote information technology to facilitate the …

A Comparison Of Machine Learning Surrogate Models Of Street-Scale Flooding In Norfolk, Virginia, Diana Mcspadden, Steven Goldenberg, Binata Roy, Malachi Schram, Jonathan L. Goodall, Heather Richter

Community & Environmental Health Faculty Publications

Low-lying coastal cities, exemplified by Norfolk, Virginia, face the challenge of street flooding caused by rainfall and tides, which strain transportation and sewer systems and can lead to personal and property damage. While high-fidelity, physics-based simulations provide accurate predictions of urban pluvial flooding, their computational complexity renders them unsuitable for real-time applications. Using data from Norfolk rainfall events between 2016 and 2018, this study compares the performance of a previous surrogate model based on a random forest algorithm with two deep learning models: Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The comparison of deep learning to the random …

Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram

Graduate Theses, Dissertations, and Problem Reports (ETD)

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for …

Autonomous Strike Uavs In Support Of Homeland Security Missions: Challenges And Preliminary Solutions, Meshari Aljohani, Ravi Mukkamala, Stephan Olariu

Computer Science Faculty Publications

Unmanned Aerial Vehicles (UAVs) are becoming crucial tools in modern homeland security applications, primarily because of their cost-effectiveness, risk reduction, and ability to perform a wider range of activities. This study focuses on the use of autonomous UAVs to conduct, as part of homeland security applications, strike missions against high-value terrorist targets. Owing to developments in ledger technology, smart contracts, and machine learning, activities formerly carried out by professionals or remotely flown UAVs are now feasible. Our study provides the first in-depth analysis of the challenges and preliminary solutions for the successful implementation of an autonomous UAV mission. Specifically, we …

Ai And Ml-Based Risk Assessment Of Chemicals: Predicting Carcinogenic Risk From Chemical-Induced Genomic Instability, Ajay Vikram Singh, Preeti Bhardwaj, Peter Laux, Prachi Pradeep, Madleen Busse, Andreas Luch, Akihiko Hirose, Christopher J. Osgood, Michael W. Stacey

Biological Sciences Faculty Publications

Chemical risk assessment plays a pivotal role in safeguarding public health and environmental safety by evaluating the potential hazards and risks associated with chemical exposures. In recent years, the convergence of artificial intelligence (AI), machine learning (ML), and omics technologies has revolutionized the field of chemical risk assessment, offering new insights into toxicity mechanisms, predictive modeling, and risk management strategies. This perspective review explores the synergistic potential of AI/ML and omics in deciphering clastogen-induced genomic instability for carcinogenic risk prediction. We provide an overview of key findings, challenges, and opportunities in integrating AI/ML and omics technologies for chemical risk assessment, …

A Use Case Of Chatgpt: Summary Of An Expert Panel Discussion On Electronic Health Records And Implementation Science, Seppo T Rinne, Julian Brunner, Timothy P Hogan, Jacqueline M Ferguson, Drew A Helmer, Sylvia J Hysong, Grace Mckee, Amanda Midboe, Megan E Shepherd-Banigan, A Rani Elwy

Center for Medical Ethics and Health Policy Staff Publications

Objective: Artificial intelligence (AI) is revolutionizing healthcare, but less is known about how it may facilitate methodological innovations in research settings. In this manuscript, we describe a novel use of AI in summarizing and reporting qualitative data generated from an expert panel discussion about the role of electronic health records (EHRs) in implementation science.

Materials and methods: 15 implementation scientists participated in an hour-long expert panel discussion addressing how EHRs can support implementation strategies, measure implementation outcomes, and influence implementation science. Notes from the discussion were synthesized by ChatGPT (a large language model-LLM) to generate a manuscript summarizing the discussion, …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Decoding Usage And Adoption Behavior Of The Low-Carbon Transportation Market: An Ai-Driven Exploration, Vuban Chowdhury

Graduate Theses and Dissertations

The transportation sector stands as a significant contributor to greenhouse gas emissions in the United States, with its environmental impact steadily escalating over the past few decades. This has prompted government agencies to facilitate the adoption and usage of low-carbon transportation (LCT) options as alternatives to fossil-fuel-powered transportation. LCTs include modes of transportation that minimize the overall carbon footprint of the transportation sector by relying on energy sources that are environmentally sustainable. These sustainable transportation options have also garnered significant interest in the transportation research community. For government agencies and researchers alike, a comprehensive understanding of the adoption and usage …

Responsibility Gaps And Black Box Healthcare Ai: Shared Responsibilization As A Solution, Benjamin H Lang, Sven Nyholm, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

As sophisticated artificial intelligence software becomes more ubiquitously and more intimately integrated within domains of traditionally human endeavor, many are raising questions over how responsibility (be it moral, legal, or causal) can be understood for an AI’s actions or influence on an outcome. So called “responsibility gaps” occur whenever there exists an apparent chasm in the ordinary attribution of moral blame or responsibility when an AI automates physical or cognitive labor otherwise performed by human beings and commits an error. Healthcare administration is an industry ripe for responsibility gaps produced by these kinds of AI. The moral stakes of healthcare …

Influence Of Pavement Conditions On Commercial Motor Vehicle Crashes, Stephen Arhin, Babin Manandhar, Adam Gatiba

Mineta Transportation Institute

Commercial motor vehicle (CMV) safety is a major concern in the United States, including the District of Columbia (DC), where CMVs make up 15% of traffic. This research uses a comprehensive approach, combining statistical analysis and machine learning techniques, to investigate the impact of road pavement conditions on CMV accidents. The study integrates traffic crash data from the Traffic Accident Reporting and Analysis Systems Version 2.0 (TARAS2) database with pavement condition data provided by the District Department of Transportation (DDOT). Data spanning from 2016 to 2020 was collected and analyzed, focusing on CMV routes in DC. The analysis employs binary …

Forecasting Traffic Speed During Daytime From Google Street View Images Using Deep Learning, Junfeng Jiao, Huihai Wang

Research Collection College of Integrative Studies

Traffic forecasting plays an important role in urban planning. Deep learning methods outperform traditional traffic flow forecasting models because of their ability to capture spatiotemporal characteristics of traffic conditions. However, these methods require high-quality historical traffic data, which can be both difficult to acquire and non-comprehensive, making it hard to predict traffic flows at the city scale. To resolve this problem, we implemented a deep learning method, SceneGCN, to forecast traffic speed at the city scale. The model involves two steps: firstly, scene features are extracted from Google Street View (GSV) images for each road segment using pretrained Resnet18 models. …

Vision Paper: Advancing Of Ai Explainability For The Use Of Chatgpt In Government Agencies: Proposal Of A 4-Step Framework, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

This paper explores ChatGPT’s potential in aiding government agencies, drawing from a case study based on a government agency in Singapore. While ChatGPT’s text generation abilities offer promise, it brings inherent challenges, including data opacity, potential misinformation, and occasional errors. These issues are especially critical in government decision-making.Public administration’s core values of transparency and accountability magnify these concerns. Ensuring AI alignment with these principles is imperative, given the potential repercussions on policy outcomes and citizen trust.AI explainability plays a central role in ChatGPT’s adoption within government agencies. To address these concerns, we propose strategies like prompt engineering, data governance, and …

Examining The Externalities Of Highway Capacity Expansions In California: An Analysis Of Land Use And Land Cover (Lulc) Using Remote Sensing Technology, Serena E. Alexander, Bo Yang, Owen Hussey, Derek Hicks

Mineta Transportation Institute

There are over 590,000 bridges dispersed across the roadway network that stretches across the United States alone. Each bridge with a length of 20 feet or greater must be inspected at least once every 24 months, according to the Federal Highway Act (FHWA) of 1968. This research developed an artificial intelligence (AI)-based framework for bridge and road inspection using drones with multiple sensors collecting capabilities. It is not sufficient to conduct inspections of bridges and roads using cameras alone, so the research team utilized an infrared (IR) camera along with a high-resolution optical camera. In many instances, the IR camera …

Executive Order On The Safe, Secure, And Trustworthy Development And Use Of Artificial Intelligence, Joseph R. Biden

Copyright, Fair Use, Scholarly Communication, etc.

Section 1. Purpose. Artificial intelligence (AI) holds extraordinary potential for both promise and peril. Responsible AI use has the potential to help solve urgent challenges while making our world more prosperous, productive, innovative, and secure. At the same time, irresponsible use could exacerbate societal harms such as fraud, discrimination, bias, and disinformation; displace and disempower workers; stifle competition; and pose risks to national security. Harnessing AI for good and realizing its myriad benefits requires mitigating its substantial risks. This endeavor demands a society-wide effort that includes government, the private sector, academia, and civil society.

My Administration places the highest urgency …

Decentralized Science (Desci): A New Paradigm For Diverse And Sustainable Scientific Development, Feiyue Wang, Wenwen Ding

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rise of artificial intelligence for science (AI4S) has made it particularly important and urgent to ensure the openness, fairness, impartiality, diversity, and sustainability of scientific systems. This is significant to the discourse power and leadership of countries in global innovation and industrial revolution, and also affects the security, stability, and sustainable development of a community with a shared future for mankind. To address these challenges, AI4S needs to adopt new scientific organizational and operational methods. Decentralized science (DeSci) has emerged to vitalize AI4S and provide strong support, effectively addressing issues such as information silos, biases, unfair distribution, and monopolies …

Intelligence Versus Inferno: How Artificial Intelligence Can Be Used To Monitor And Manage Wildfires In Europe, Maxwell Feldman

Independent Study Project (ISP) Collection

Escalating wildfire occurrences in Europe, particularly in the southern Mediterranean region, are presenting significant challenges to socioeconomic, environmental, and ecosystem services. The increasing frequency and severity of these wildfires are straining resources and emphasizing the need for a better understanding of the relationship between suppression capacity and fire behavior in wildfire management. The following research addresses the urgent need for more proactive, knowledge-based, and technologically driven fire management strategies, throughout all four stages of wildfire response – fuel and land management, fire preparedness, fire suppression, and post-fire management. Artificial Intelligence (AI) is becoming increasingly significant in climate change adaptation, especially …

Quantifying Taxi Drivers' Behaviors With Behavioral Game Theory, Mengyu Ji, Yuhong Xu, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

With their flexibility and convenience, taxis play a vital role in urban transportation systems. Understanding how human drivers make decisions in a context of uncertainty and competition is crucial for taxi fleets that depend on drivers to provide their services. As part of this paper, we propose modeling taxi drivers’ behaviors based on behavioral game theory. Based on real-world data, we demonstrate that the behavioral game theory model we select is superior to state-of-the-art baselines. These results provide a solid foundation for improving taxi fleet efficiency in the future.

Impact Analysis Of Gpt Technology Revolution On Fundamental Scientific Research, Mengge Sun, Tao Han, Yanpeng Wang, Yuxin Huang, Xiwen Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The generative large model GPT represented by ChatGPT is developing rapidly, which has aroused extensive discussion in academic circle and the industry and has an incalculable impact on foundational scientific research development. The study first sorts out the development of the GPT technological revolution, and discusses the new changes brought about by this technology in scientific research. Then, based on the three aspects of application status, core principles and innovation subjects, the impact of the GPT technological revolution on basic scientific research and its development suggestions for China are discussed. The study believes that GPT technology can certainly play a …

International Soft Law Governance Of Artificial Intelligence Ethics: Current Situation, Challenges And Countermeasures, Mingting Zhu, Chongli Xu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI) technology not only rapidly empowers economic and social development, but may also trigger many ethical issues highly related to the characteristics and development of AI technology itself. The rise of international soft law in the field of AI ethical governance is almost inevitable due to its flexibility, efficiency, low application cost, ability to fill the gap in hard law, and convenience in distinguishing governance and layered response to ethical issues. Under the current situation of developed international soft law and outdated hard law in this field, faced with the governance challenge of unstable cooperation among subjects of …

A Semantic Understanding Oriented Evaluation Of The Intelligent Q&A Service On Chinese Provincial Government Websites, Fang Wang, Zhonghan Wei, Zhixuan Lian, Jia Kang

Journal of Scientific Information Research

[Purpose/significance]Intelligent question answering （Q&A） system has become an important facility for websites to provide consulting services. The complexity of government consultation issues poses higher requirements for the semantic understanding ability of intelligent Q&A systems on government websites.[Method/process]This study evaluates the Q&A systems of 30 Chinese provincial government websites from three aspects of problem solving quality,service interaction quality and basic construction quality by using the "Semantic Understanding based Evaluation Indicator System for Intelligent Q&A Service on Government Websites" developed by the Center for Network Society Governance of Nankai University and the supporting test sets.[Result/conclusion]The results show that Shanghai, Zhejiang and Beijing …

Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai

Research Collection School Of Computing and Information Systems

Recent works using deep reinforcement learning (RL) to solve routing problems such as the capacitated vehicle routing problem (CVRP) have focused on improvement learning-based methods, which involve improving a given solution until it becomes near-optimal. Although adequate solutions can be achieved for small problem instances, their efficiency degrades for large-scale ones. In this work, we propose a newimprovement learning-based framework based on imitation learning where classical heuristics serve as experts to encourage the policy model to mimic and produce similar or better solutions. Moreover, to improve scalability, we propose Clockwise Clustering, a novel augmented framework for decomposing large-scale CVRP into …

Singapore's Ai Applications In The Public Sector: Six Examples, Steven M. Miller

Research Collection School Of Computing and Information Systems

Steven M. Miller describes six instances in which Singapore has applied AI in the public sector, illustrating different ways of improving its engagement with the public by making government services more accessible, anywhere, anytime, and speeding its responses to public processes and feedback. He illustrates how its leaders made the city a living lab for AI use, and what they learned.