Blockchain Papers

Yicong Tan, Lei Xu, Jiaqi Dong

No abstract is available for this record.

Krishnaveni Subramani, Geetha Manoharan

Digital technology increases diagnosis, treatment, and efficiency, transforming healthcare. This article uses real-life business examples to demonstrate how blockchain technology, AI, and IoT are changing health care and how they may help. AI algorithms speed up and enhance diagnostic, prognostic, and therapeutic decision-making. IoT devices can monitor patients, offer remote health care, and collect data instantly, improving outcomes and resource use. Blockchain technology protects patient privacy and promotes healthcare system collaboration by securely and transparently managing medical records. As seen in this chapter, these technologies work well. Using AI in imaging and genetics simplifies early diagnosis and treatment planning. Wearable health monitoring, smart implants, and telemedicine can improve patient treatment. Blockchain technology will secure EHRs, manage medicine supply chains, and facilitate clinical trials. The Internet of Things, blockchain technology, and AI are improving data privacy, patient participation, and treatment availability in healthcare.

T. B Sivakumar, E. Angel Anna Prathiba, Shweta Sharma, Rashmi Saket Prasad · 6 authors

Modern finance and HR businesses have challenges in exchanging data due to centralized systems that are subject to hacking and lack transparency. The study proposes employing blockchain technology and machine intelligence (ML) to address these issues holistically. The proposed system enhances integrity and resilience to assaults by utilizing a decentralized ledger for secure data exchange. ML algorithms enable predictive analytics, risk management, and personalized insights. The proposed system outperforms the existing system in terms of accuracy, security, and efficiency. The accuracy of fraud detection increases from 0.75 to 0.90, as does the estimate of staff turnover from 0.80 to 0.95. The proposed system achieves an overall accuracy of 95%, surpassing the existing system's 85%. Blockchain and ML integration can alter data management methods in finance and HR industries, with improved security measures resulting in a risk score of 2 compared to 7 in the existing system.

Sudheer Devaraju -

This comprehensive technical paper presents a novel multi-modal trust architecture for AI-driven HR systems, focusing on the critical aspects of user acceptance in enterprise-scale people analytics platforms. Through the implementation of advanced zero-knowledge proof protocols, explainable AI frameworks, blockchain-based audit trails, and federated learning approaches, the architecture achieved an 85% improvement in user confidence metrics. The system demonstrates remarkable performance across resistance prediction, technical integration, and trust analytics, processing over 9.5 million daily interactions with 99.999% reliability. Our implementation across 1,850 organizations showed an 82% enhancement in system trustworthiness and a 2.8x improvement in operational efficiency, while reducing algorithmic bias by 89%. The architecture's event-driven design and microservices implementation resulted in a 76% improvement in system responsiveness and a 92% reduction in data processing latency, establishing a new benchmark for trust-centric AI-HR systems.

Michal Jirásek

No abstract is available for this record.

Elham Abdulwahab Anaam, Taher M. Ghazal, Su-Cheng Haw, Haitham M. Alzoubi · 6 authors

With the advancement of time and the advancement scientific knowledge, the blockchain technology has expanded in various applications. The security and data privacy of employee recruitment system has been compromised. Therefore, hiring managers can enhance job satisfaction by adopting blockchain technology to secure human resource data management. This paper provides current research status, issues and a deep investigation on the blockchain technology's potential use in the management of human resources.

Niravkumar Dhameliya, Kishore Mullangi, Mohamed Ali Shajahan, Arun Kumar Sandu · 5 authors

This study aims to understand better how blockchain-integrated HR analytics may improve staff management practices in businesses. The study's primary goals are to determine how blockchain technology affects HR procedures, analyze its effects on worker performance, and determine how policies will be affected by its adoption. The paper examines the incorporation of blockchain technology into HR analytics by synthesizing case studies, industry reports, and current literature through a secondary data-based review technique. The main conclusions are improved data security and integrity, streamlined ingenious contract procedures, open decision-making, performance management based on data, and encouraging employee accountability and ownership. Addressing technological complexity, regulatory obstacles, interoperability problems, energy consumption issues, and data access and control problems are some policy consequences. To leverage the benefits of blockchain technology in HRM, policymakers are advised to provide clear regulatory frameworks, invest in technical support and training, and investigate long-term, privacy-preserving solutions. Blockchain-integrated HR analytics present a viable way for businesses to enhance staff management plans and promote organizational efficacy in the digital age.

Maria Michailidis

Blockchain, artificial intelligence (AI) and other technological innovations are affecting all aspects of our societies and causing some profound changes in human resource (HR) practices in business and non-profit organizations. Critical to these high tech advances is how they will affect employment patterns and the way companies will hire their workforce, influencing HR practices and the way they will manage their employees. This paper, after a short introduction, consists of three parts. The first discusses how blockchain and AI are affecting HR practices. The second looks at hiring practices at firms, while the third discusses employment patterns in the emerging age of high-tech super-automation. There is also a concluding section, discussing the implications of the forthcoming AI on employment (or unemployment) and the inevitable income inequality that is bound to develop and affect our societies.