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All Journal Buletin Ilmiah Sarjana Teknik Elektro
Chen, Yih-Chang
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Electrical & Electronics Engineering

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Maintaining Empathy and Relational Integrity in Digitally Mediated Social Work: Practitioner Strategies for Artificial Intelligence Integration Chen, Yih-Chang; Lin, Chia-Ching
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13008

Abstract

This study addresses the critical challenge of preserving relational integrity in social work practice within artificial intelligence (AI)-enhanced environments. While AI technologies promise operational efficiency, their impact on empathy and human connection in social work is not fully understood. This research aims to explore how social workers maintain relational integrity when interacting with clients through AI tools, providing practical strategies and theoretical insights. The research contributes to the field by proposing a relational framework for AI integration in social work practice, emphasizing human-centered principles. The study utilizes a qualitative phenomenological approach, drawing on 24 licensed social workers from diverse sectors (e.g., child welfare, elder care, and mental health) in three urban areas known for AI adoption. Data collection involved semi-structured interviews and artifact analysis, including AI interface screenshots and decision-making protocols, to capture practitioner experiences. Findings reveal three key themes: reframing empathy in digital interactions, AI as a dual partner and adversary, and ethical tensions. Results indicate that video calls and visual aids are crucial for preserving empathy, while social workers employ proactive strategies to manage AI’s limitations. The study highlights the need for clear guidelines, interdisciplinary collaboration, and training to ensure AI supports relational practices rather than replacing them. These findings have significant policy and practice implications, offering a foundation for future research and AI tool development in social services.
A Blockchain-Enabled Internet of Things Framework for Enhancing Trust and Privacy in Social Work Case Management Chen, Yih-Chang; Lin, Chia-Ching
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13653

Abstract

Traditional social work case management systems face critical challenges including data silos, security vulnerabilities, and insufficient inter-agency collaboration, limiting service efficiency and compromising client privacy protection. This study addresses these challenges by developing and evaluating a novel technological framework that integrates blockchain consortium networks with Internet of Things (IoT) devices to establish multi-party trust mechanisms and enhance service delivery. The research contribution is a comprehensive four-layer system architecture featuring 28 smart contracts, decentralized trust mechanisms, and privacy-preserving technologies including homomorphic encryption and differential privacy for social work applications. The methodology employed a mixed-methods approach involving system design and development, followed by a six-month pilot implementation across three social work institutions in Taiwan with 249 participants. Data collection encompassed quantitative performance metrics from system logs and IoT sensors, alongside qualitative feedback through interviews and focus groups. The blockchain network achieved 850 transactions per second with 99.2% system availability, significantly outperforming industry standards. Results demonstrated substantial operational improvements: 37.1% reduction in case processing time, 87.3% increase in service efficiency, and 26-fold increase in inter-agency collaboration frequency. The blockchain-based trust mechanism increased inter-agency data sharing willingness from 61.3% to 84.6%, while maintaining 100% anonymization coverage with 91.3% analytical accuracy. Cost-benefit analysis revealed a 2.8-year payback period with 41.2% return on investment. This research demonstrates the feasibility and effectiveness of blockchain-IoT integration in social work, providing a practical framework for digital transformation while ensuring data security and privacy protection in sensitive social service environments.
Cybersecurity and Privacy Governance in IoT-Enabled Social Work: A Systematic Review and Risk Framework Chen, Yih-Chang; Lin, Chia-Ching
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 4 (2025): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i4.14589

Abstract

Social work practice is rapidly integrating Internet of Things (IoT) technologies to expand service delivery, yet this integration introduces significant cybersecurity and privacy vulnerabilities that disproportionately threaten vulnerable populations. Existing literature predominantly emphasizes technical security solutions while neglecting the ethical considerations, protective needs of vulnerable groups, and governance frameworks specific to social work contexts. Research Contribution: This study develops the first systematic multidimensional framework integrating engineering and social science perspectives to evaluate IoT cybersecurity, privacy risks, and governance requirements in social work applications. Using a Systematic Literature Review following PRISMA guidelines, we searched five major databases from January 2020 to September 2024. We employed qualitative thematic analysis combined with an innovative quantitative assessment algorithm to score technologies, threats, and governance components across 55 primary studies. Key Findings: Mental health services and vulnerable population support face “very high” privacy risks (PRS > 8.0), primarily from systemic infrastructure weaknesses in consumer-grade devices rather than sophisticated cyberattacks. Homomorphic encryption achieves the highest security score (9.8/10) but exhibits the highest implementation complexity (9.0/10). Federated learning provides an optimal balance (security 8.5, complexity 8.0, cost 6.0). Ethical guidelines demonstrate the highest implementation difficulty (8.2/10), reflecting challenges in translating abstract principles into technical specifications. Quantitative gap analysis identifies vulnerable population protection as the highest research priority (gap score 3.7/10). This study offers an evidence-driven agenda for practitioners and policymakers, proposing context-specific technology selection criteria and adaptive governance models that prioritize interdisciplinary collaboration, ensuring IoT advancements effectively promote social welfare while protecting at-risk individuals.
Co-Authors Lin, Chia-Ching