人工智能与机器人研究Pub Date : 2026-03-26DOI: 10.4018/979-8-3373-8187-9.ch002
G. Silambarasan, Gautam Shivaraj
{"title":"Professionals in AI/ML Operations Deploying Trustworthy and Resilient AI Hardware Infrastructure","authors":"G. Silambarasan, Gautam Shivaraj","doi":"10.4018/979-8-3373-8187-9.ch002","DOIUrl":"https://doi.org/10.4018/979-8-3373-8187-9.ch002","url":null,"abstract":"The large-scale deployment of AI and ML systems has transformed AI into mission-critical infrastructure across healthcare, finance, autonomous systems, and national security. Despite advances in algorithmic performance, the trustworthiness of AI remains fundamentally constrained by the reliability and security of the underlying hardware. As AI workloads increasingly execute on heterogeneous accelerators distributed across cloud, edge, and cyber-physical environments, hardware integrity, resilience, and provenance emerge as decisive factors for dependable AI behavior. This chapter advances a trust-centric perspective on AI/ML operations, arguing that software-focused MLOps practices are insufficient for ensuring reliable AI execution. By integrating hardware trust engineering, deterministic inference theory, distributed systems resilience, and socio-technical governance, the chapter proposes a unified operational framework that treats trust as a continuous, lifecycle-wide property.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"31-68"},"PeriodicalIF":0.0,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147920242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2025-08-15DOI: 10.4018/979-8-3373-3760-9.ch012
R. N. Ravikumar, S. Aarthi
{"title":"AI-Driven Governance","authors":"R. N. Ravikumar, S. Aarthi","doi":"10.4018/979-8-3373-3760-9.ch012","DOIUrl":"https://doi.org/10.4018/979-8-3373-3760-9.ch012","url":null,"abstract":"This chapter explores how Artificial Intelligence (AI) and blockchain technologies are transforming public administration into a transparent, efficient, and citizen-centric ecosystem. It examines the role of predictive analytics in enabling proactive decision-making and resource optimization, while blockchain ensures data integrity, trust, and decentralization. Through real-world case studies of Estonia and Singapore, the chapter highlights successful implementations of these technologies in digital identity systems, smart urban planning, and public service delivery. It also addresses ethical, legal, and governance challenges, proposing strategic frameworks for responsible adoption. The chapter offers a roadmap for future-ready, technology-driven governance that is inclusive, accountable, and resilient.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"343-372"},"PeriodicalIF":0.0,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147882413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2025-08-14DOI: 10.4018/979-8-3373-6587-9.ch002
Anirban Ghatak, Pruthvi Nagraj
{"title":"Unpacking Ethical Risks in Financial AI","authors":"Anirban Ghatak, Pruthvi Nagraj","doi":"10.4018/979-8-3373-6587-9.ch002","DOIUrl":"https://doi.org/10.4018/979-8-3373-6587-9.ch002","url":null,"abstract":"This study examines ethical risks in AI-driven finance, including algorithmic bias, transparency deficits, and accountability gaps. Through a systematic literature review (PRISMA 2020) and thematic analysis of 100 peer-reviewed studies, it is revealed that minority loan applicants face rejection rates 2.5 times higher than those of their counterparts with identical financial profiles. Opaque “black box” models hinder regulatory oversight, exacerbating systemic risks (e.g., 2010 Flash Crash). Case studies (Apple Card, deepfake fraud) highlight regulatory fragmentation and generative AI threats. The proposed Ethical AI Governance Matrix integrates technical audits (SHAP, IBM Fairness 360), dynamic regulatory sandboxes (EU AI Act), and stakeholder collaboration (ethics boards). Recommendations include mandatory bias audits, cross-border data treaties, and participatory design to strike a balance between innovation and equity. Findings emphasize the need for urgent interdisciplinary action to prevent market instability and amplify inequality.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"23-60"},"PeriodicalIF":0.0,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147896671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"AI-Driven Drug Discovery, Design, and Development in Immunological Disorders","authors":"Odangowei Inetiminebi Ogidi, Deghinmotei Alfred-Ugbenbo, Blessing Elohor Poripo","doi":"10.4018/979-8-3693-9725-1.ch005","DOIUrl":"https://doi.org/10.4018/979-8-3693-9725-1.ch005","url":null,"abstract":"Conventional drug discovery frequently entails arduous and time-consuming procedures. Nevertheless, the emergence of artificial intelligence-based models presents new opportunities to accelerate the process of designing and developing innovative therapies. These models have multiple active applications in the therapeutic treatment of immunological disorders, such as autoimmune and autoinflammatory disorders (AIIDs). By integrating data from omic technologies and patient genetic profiling, the first models of rheumatoid arthritis, systemic lupus erythematosus, and primary Sjogren syndrome have been created in the last few years. The notion that a variety of AIIDs share a common molecular dysfunction and the validation of a complex pathophysiology that involves numerous proinflammatory pathways are both supported by these developments. Therefore this chapter discusses the utilisation of models in various applications, including the development of in silico drug candidates, the prediction of virtual patient efficacy, and the stratification of patients.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"143-180"},"PeriodicalIF":0.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147905111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2025-05-08DOI: 10.4018/979-8-3373-0355-0.ch013
Muhammad Nauman
{"title":"AI in Sustainable Investing","authors":"Muhammad Nauman","doi":"10.4018/979-8-3373-0355-0.ch013","DOIUrl":"https://doi.org/10.4018/979-8-3373-0355-0.ch013","url":null,"abstract":"A systematic literature review (SLR) of 120 peer-reviewed articles published between 2010 and 2024, examining the role of advanced technologies in sustainable investing. Using grounded theory's coding techniques, the analysis identifies five key themes: I. Enhanced Data Processing and Predictive Analytics, II. Algorithmic Bias and Ethical Challenges, III. Market Volatility and Systemic Risks, IV. Regulatory and Transparency Gaps, and V. Stakeholder Collaboration and Trust. The chapter highlights the transformative potential of these technologies in improving efficiency and predictive capabilities within sustainable investing. However, it also underscores the ethical, systemic, and regulatory risks associated with their implementation. To address these challenges, the chapter advocates for hybrid governance frameworks that combine human oversight with technological precision, prioritize ethical design principles, and establish agile regulatory approaches. This balanced approach aims to leverage technological advancements as a positive force for achieving sustainable outcomes.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"383-416"},"PeriodicalIF":0.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147889935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2025-04-11DOI: 10.4018/979-8-3373-0129-7.ch008
Mohammad Irfan, Rui Dias, Jayant Hooda, Kashish Ajit Singh, Sanjay Bang
{"title":"AI's Impact on Financial Services, Auditing, and Investment Strategies","authors":"Mohammad Irfan, Rui Dias, Jayant Hooda, Kashish Ajit Singh, Sanjay Bang","doi":"10.4018/979-8-3373-0129-7.ch008","DOIUrl":"https://doi.org/10.4018/979-8-3373-0129-7.ch008","url":null,"abstract":"Artificial intelligence (AI) is poised to significantly transform the fields of finance, auditing, and investment over the coming decade. In financial services, AI is anticipated to enhance decision-making processes, improve risk management practices, and facilitate the delivery of personalized financial solutions. The auditing profession will be reshaped by AI and automation, enabling continuous auditing, real-time reporting, and more effective fraud detection mechanisms. In the investment domain, AI is expected to revolutionize portfolio management and asset allocation through advanced predictive analytics and data-driven market strategies. Despite these advancements, the rapid proliferation of AI presents considerable challenges, including ethical considerations, regulatory compliance, and the necessity of re-skilling financial professionals. This strategic overview examines both the opportunities and risks associated with AI integration and provides guidance for organizations seeking to maintain competitiveness in an increasingly AI-driven financial landscape.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"183-224"},"PeriodicalIF":0.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147886975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2025-03-28DOI: 10.4018/979-8-3373-0538-7.ch009
Palanivel Kuppusamy
{"title":"Artificial Intelligence-Powered Digital Twin Predictive Analytics Model for Smart Healthcare System","authors":"Palanivel Kuppusamy","doi":"10.4018/979-8-3373-0538-7.ch009","DOIUrl":"https://doi.org/10.4018/979-8-3373-0538-7.ch009","url":null,"abstract":"Health monitoring systems and healthcare organizations produce vast amounts of complicated data, which present opportunities for creative research in medical decision-making. These data capture advances have opened unthinkable domains for AI and digital twin-related healthcare applications. AI-powered digital twin supports healthcare process automation, real-time health monitoring, enhanced medical decision-making, personalized healthcare, and predictive analytics. These applications can create AI-powered digital twin models that mimic human physiology using various advanced computing approaches. The potential of digital twins can be used to advance medical research and better healthcare outcomes. Hence, this chapter aims to provide an Artificial Intelligence-powered digital twin predictive analytics model for an innovative healthcare system. Integrating digital twins into the smart healthcare field can improve healthcare procedures, provide personalized treatment, and create a smart and intelligent healthcare ecosystem.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"271-324"},"PeriodicalIF":0.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147911456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2025-03-28DOI: 10.4018/979-8-3373-0538-7.ch011
Secil Sen, Kubilay Doğan Kılıç
{"title":"Digital Twins in Medicine, AI-Driven Personalized Healthcare, and Predictive Analytics","authors":"Secil Sen, Kubilay Doğan Kılıç","doi":"10.4018/979-8-3373-0538-7.ch011","DOIUrl":"https://doi.org/10.4018/979-8-3373-0538-7.ch011","url":null,"abstract":"This chapter explores the transformative role of digital twin technology in modern medicine, focusing on its integration with artificial intelligence (AI), big data, and predictive analytics to enhance personalized healthcare. Digital twins, virtual representations of patients based on biomedical data, enable advanced disease modeling, risk assessment, and individualized treatment simulations. By leveraging diverse data sources, including pathology, radiology, and biomarker analysis, AI-driven models provide clinicians with precise decision-support tools for early diagnosis, treatment optimization, and proactive patient management. The chapter examines recent examples and highlighting how digital twins enhance predictive healthcare and clinical outcomes. Ethical considerations, data privacy, and regulatory challenges are also discussed, ensuring responsible implementation of this emerging technology in patient care.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"359-396"},"PeriodicalIF":0.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147914015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2024-03-04DOI: 10.4018/979-8-3693-2964-1.ch014
Munir Ahmad, Saadia Ureeb
{"title":"Narrating Spatial Data With Responsibility","authors":"Munir Ahmad, Saadia Ureeb","doi":"10.4018/979-8-3693-2964-1.ch014","DOIUrl":"https://doi.org/10.4018/979-8-3693-2964-1.ch014","url":null,"abstract":"This chapter discussed the responsible use of spatial data in decision-making and the need to balance ethics with decision-making. The role of spatial data in decision-making and storytelling is discussed. Ethical issues in spatial data storytelling such as privacy and confidentiality, bias and discrimination, accuracy and misinformation, accessibility and inclusivity, environmental and social impacts, data ownership and credit, and transparency are described, along with the strategies to overcome these issues. The different roles of storytelling in decision-making are elaborated on, along with the challenges and risks associated with using storytelling in decision-making. The chapter also discussed the challenges of striking a balance between ethics and decision-making, such as conflicting interests, cognitive biases, time constraints, political and legal constraints, and many more. Strategies to overcome these challenges, including developing clear ethical guidelines and engaging diverse stakeholders, are underpinned in this chapter as well.","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":"1 1","pages":"225-244"},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147916990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能与机器人研究Pub Date : 2023-11-10DOI: 10.1142/s2972335324500017
Elahe Vahdani, Longlong Jing, Matt Huenerfauth, Yingli Tian
{"title":"Multi-Modal Multi-Channel American Sign Language Recognition","authors":"Elahe Vahdani, Longlong Jing, Matt Huenerfauth, Yingli Tian","doi":"10.1142/s2972335324500017","DOIUrl":"https://doi.org/10.1142/s2972335324500017","url":null,"abstract":"","PeriodicalId":68167,"journal":{"name":"人工智能与机器人研究","volume":" July","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135186544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}