The Supreme Court Decision No. 3634 K/Pdt/2023 dated 22 November 2023 sets an important precedent in Indonesian civil law concerning the liability of local governments for negligence in disseminating regional zoning regulations. The case originated from a lawsuit filed by PT Wisanggeni Mitra Sejahtera against PT Bhanda Ghara Reksa, the North Jakarta City Administration, and the Financial and Development Supervisory Agency (BPKP) after the claimant’s construction project was suspended for being located within a designated green zone. The Supreme Court ruled that the defendants had committed an unlawful act (onrechtmatige daad) by failing to provide public access to zoning information as mandated by the Jakarta Regional Regulation on Spatial Planning (RTRW). This study examines the legal basis and judicial reasoning used by the Supreme Court in assessing governmental inaction as an unlawful act under Article 1365 of the Indonesian Civil Code and analyses the implications of the decision for the government’s duty to ensure transparency and accountability in spatial information disclosure. Using a normative juridical method with a case approach and library research on primary, secondary, and tertiary legal sources, this research finds that the local government’s failure to disseminate zoning information resulted in losses to private parties and violated the principle of public information transparency as regulated by Law No. 14 of 2008. The Supreme Court appropriately applied civil and administrative law principles and annulled the lower courts decisions, which had misinterpreted the elements of unlawful conduct. These ruling underscores the government’s obligation to ensure legal certainty and foster public trust in spatial governance.

This study analyzes the legislative framework governing the use of artificial intelligence (AI) in the European Union, focusing on patterns of legal convergence and divergence, as well as the governance challenges arising from its implementation. The research aims to examine how the EU constructs a harmonized yet flexible regulatory regime capable of addressing the multifaceted risks of AI while promoting innovation. Methodologically, this study employs a qualitative approach through doctrinal legal analysis and policy review, drawing on primary legal instruments, including the EU AI Act, as well as secondary sources such as policy reports and academic literature. The findings indicate that the EU adopts a risk-based regulatory model that classifies AI systems into low, medium, and high-risk categories. While most AI applications fall into low- or medium-risk categories, high-risk systems—particularly those used in sensitive sectors such as healthcare, justice, employment, and finance—pose significant legal and ethical challenges. The study identifies key risks, including algorithmic bias, data privacy violations, and a lack of transparency, alongside broader concerns about accountability and the protection of fundamental rights. Furthermore, although legal convergence is evident in the establishment of uniform EU standards, divergence persists in national implementation, enforcement practices, and institutional readiness across member states. This study contributes to the existing literature by providing a comprehensive analysis of the interplay between harmonization and fragmentation in EU AI regulation. It also highlights the need for adaptive governance mechanisms that balance regulatory consistency with contextual flexibility. Ultimately, the research underscores that effective AI legislation must strengthen accountability, ensure ethical compliance, and foster public trust, thereby aligning technological development with the core values of the European Union.

This study investigates how bio-inspired versus sustainability-focused framing influences lay evaluations of a specific bio-inspired building-technology scenario, testing the empirical validity of the so-called "biomimetic promise". Employing a between-subjects experimental design (N=582), we examined assessments of a weather-responsive self-shading façade across bio-inspired, sustainable, and neutral framing conditions. We developed and validated the 12-item Perceived Bio-Inspiration Scale (PBS)-a novel standardized psychometric instrument designed to quantify lay recognition of biomimetic features across visual, intentional, and naturalistic dimensions. While results showed robust direct framing effects, we identified a significant negative spillover: emphasizing biological inspiration significantly reduced the technology's perceived sustainability, while sustainability framing diminished its perceived bio-inspiration. These findings demonstrate, in this façade context, that laypersons evaluate bio-inspiration and sustainability as cognitively distinct and potentially competing constructs, indicating that "natural-is-better" bias is not universal across all technology domains. Consequently, merely invoking biological origins is insufficient to enhance a technology's ecological appeal. To foster public trust, science communication should shift from abstract biological metaphors toward a performance-driven communication strategy that prioritizes the disclosure of verifiable life-cycle assessment and specific operational advantages over symbolic nature-based analogies.

The local government in South Africa is important in providing critical services to communities, although local government is tasked with critical service delivery functions, many faces systemic challenges when fulfilling this responsibility. Mkhondo Local Municipality is no exception, challenges such as inefficiency, inadequate resource management, and limited public participation. This study is grounded in consequential theory, which underscores the significance of outcomes in assessing actions. This theoretical framework facilitates the exploration of strategic actions to enhance service delivery in Mkhondo. The aim of this article was to propose effective strategies to enhance service delivery at Mkhondo Local Municipality. This article adopted a qualitative methodology, with purposive sampling to select ten experienced participants from the supply chain management and finance units. Data was collected through one-on-one, semi-structured interviews with 10 key municipal staff members. The interview transcripts were analysed thematically using NVivo 12 to identify and organise the emerging themes. The results highlighted several barriers, including ineffectiveness of performance monitoring, inadequate procurement transparency, and minimal community involvement. The article recommends the implementation of performance-based accountability, improved stakeholder participation, and transparency in municipal procedures. It is recommended that municipal strategies are aligned with consequential theory to significantly improve service delivery. These interventions can foster greater transparency, efficiency, and public trust, providing a model for similar municipalities across South Africa.

Rapid urbanization and population growth in Lilongwe City have significantly increased solid waste generation, straining existing waste management infrastructure and exacerbating environmental and public health risks. The current dumpsite in Area 38 is inadequate due to its close proximity to residential neighborhoods and critical water resources. This study employed a Multi-Criteria Decision Analysis (MCDA) framework, integrating Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP), to identify optimal locations for a new engineered landfill. In addition to technical spatial suitability analysis, based on environmental, infrastructural, and geophysical criteria, the study incorporated community perspectives through structured household surveys conducted near potential landfill zones. The spatial analysis identified 11% of the city as highly suitable, 20% as suitable, and 43% as moderately suitable for landfill development. Community responses revealed three distinct typologies—Health-Conscious, Economic-Focused, and Environmentally-Conscious, each with unique values and concerns. A multilevel logistic regression model revealed that landfill acceptance was significantly and positively associated with perceived employment opportunities (OR = 1.82, p < 0.001), trust in governance (OR = 1.57, p < 0.001), and awareness of the site selection process (OR = 1.35, p = 0.020). Conversely, acceptance was negatively influenced by perceived health risks (OR = 0.45, p < 0.001) and ecological sensitivity (OR = 0.61, p < 0.001). These findings underscore the importance of integrating both technical geospatial assessments and social acceptability considerations in landfill siting to enhance sustainability, minimize conflict, and foster public trust.

Biometric authentication is now central to modern identity and access management, offering stronger security and a better user experience than traditional passwords. From 2025 to 2026, advances in artificial intelligence, sensor technology, and decentralized identity models have broadened the adoption of biometric systems in consumer, business, and government sectors. However, emerging threats such as deepfakes, adversarial machine learning, and large-scale data breaches have exposed significant vulnerabilities and ethical issues. This paper reviews recent trends and shortcomings in biometric authentication, comparing major methods, including fingerprint, facial, iris, voice, and behavioral recognition. It assesses their performance, reliability, usability, scalability, and security, and examines the increasing adoption of multimodal, continuous, and privacy-preserving authentication systems. The analysis addresses key challenges, including spoofing, bias, template theft, and accessibility, to identify current system limitations. The paper proposes a layered mitigation framework that integrates technical safeguards, system design enhancements, governance measures, and user-focused strategies. It contends that the effectiveness of biometric authentication relies on both technological advancement and ethical, transparent practices that foster public trust. Addressing technical and social factors is essential to developing secure, fair, and widely accepted biometric systems.

In this dialogue, Professor Terry Flew first explains the real-world changes and theoretical underpinnings that have prompted his Australian Research Council (ARC) Laureate Fellowship to study media and public trust. Based on the concept of mediated trust, he reveals the relationship between trust, power and communication technologies. Professor Flew then elaborates on how artificial intelligence (AI) affects trust in human–machine and interpersonal relationships, and how governments and technology companies shape public trust in AI in a complex geopolitical environment. Finally, Flew explores ways to foster public trust and encourages communication research to actively embrace changes in technology and society.

Public service is a key aspect of government performance that directly affects community satisfac-tion. This study examines the quality of public service at the Bumi Ayu Subdistrict Office in Dumai Selatan, Dumai City, using five dimensions: reliability, responsiveness, empathy, tangibles, and as-surance. Data were collected through observation, interviews with two informants (one official and one service user), and document review. The findings indicate that public services are general-ly effective. Staff demonstrate adequate reliability and responsiveness, show empathy in serving the community, provide sufficient facilities to support service activities, and foster public trust through professional conduct. Supporting factors include well-organized service procedures, ade-quate infrastructure, and attentive staff, while limitations involve dependency on the subdistrict head for document approval, limited staff during peak hours, and some facility constraints. The study highlights the need to improve service timeliness, increase staff availability, and improve fa-cilities to optimize public service delivery.

The Generation Study is a large-scale research initiative led by Genomics England in partnership with the National Health Service, aiming to evaluate the use of whole genome sequencing in newborn screening, as well as ongoing research use of these genomic data. The Generation Study will sequence 100 000 newborn genomes in England to potentially identify approximately 200 rare and treatable conditions. This paper outlines the study's approach to embedding ethics from inception through implementation. A model of 'ethical embeddedness' that emphasises transparency, trustworthiness and responsiveness to uncertainty is utilised. Drawing on the deliberations of a multidisciplinary Ethics Working Group, public dialogue findings and design research, the paper presents key decisions and our approach to complex ethical challenges including consent, potential impact of the study on clinical services and navigating uncertainty. The paper also reflects on the ethical tensions inherent in balancing research ambitions with operational realities, particularly in a context of evolving genomic science and sometimes limited regulatory clarity. By embedding ethics into the study's design and delivery, we hope to foster public trust and inform future policy and practice.

The Human Exposome Project (HEP) aims to chart lifelong environmental exposures and their biological consequences, furnishing the environmental counterpart to the genomic revolution. Yet the fine‑grained, multimodal data streams that fuel exposomics-biospecimens, geolocation traces, wearable‑sensor feeds, and socio‑environmental metadata-raise privacy, justice, and governance questions that may exceed the reach of conventional bioethics. Building on lessons from genomics, biobanking, digital health, and environmental‑justice research, we identify five foundational ethical domains for exposome science: (1) privacy and data sovereignty, (2) informed consent and sustained participant engagement, (3) environmental justice, (4) governance and oversight, and (5) actionability and the responsible return of results,as well as (6)the adherence to research program goals. Similar to the "values in design" construct widely used in the socio-technical field and the "ethics by design" in the artificial intelligence (AI) field, we translate these domains into operational pillars for ethics‑by‑design research practice: dynamic or tiered consent architectures; participatory governance mechanisms such as community advisory boards; embedded ethics research programs; algorithmic‑fairness protocols for artificial‑intelligence analytics; and dedicated review bodies equipped to evaluate longitudinal, sensor‑based, multi‑omics studies. Concrete recommendations include federated data stewardship to minimize re‑identification risk, Evidence‑to‑Decision frameworks that couple exposomic evidence with societal values, and transparent pathways for communicating context‑dependent findings to individuals, communities, and policymakers. Ethical preparedness and action are a prerequisite for the scientific impact and social license of exposome research. Institutionalizing the proposed roadmap-via an international Exposome Ethics Consortium, expanded training for Institutional Review Boards, harmonized regulatory guidance, and sustained community co‑governance-will help protect privacy, promote equity, and foster public trust. Embedding systematic ethical reflection as core infrastructure will enable the Human Exposome Project to realize its promise of precision public health without replicating patterns of opaque surveillance, marginalization, or data commodification. The Human Exposome Project (HEP) represents an ambitious endeavor to characterize lifelong environmental exposures in relation to health. Yet, this vision brings profound ethical challenges: from managing massive, sensitive datasets to ensuring justice for disproportionately exposed communities. This article synthesizes foundational work on exposome ethics, outlines core ethical challenges, and proposes a proactive ethical governance model that ensures scientific integrity and social legitimacy.

Citizen participation is a vital component of public administration in the 21st century. This study compares Thailand and South Korea to examine how digital governance frameworks influence civic engagement, focusing on policy design, administrative structures, and political culture. The findings reveal that South Korea has effective- ly utilized digital platforms, such as e-participation systems and Open Government Data, to strengthen transparency and enable citizens to engage substantively in au- diting, administrative appeals, and policymaking. In contrast, although Thailand has developed platforms such as the 1111 Complaint System and Damrongtham Online Center, citizen participation remains limited because of structural, legal, and trust barriers. This contrast illustrates that South Korea has reached an advanced stage of digital governance, whereas Thailand is still in its formative phase. Therefore, this study proposes policy recommendations for Thailand, including sustained investment in digital infrastructure, development of integrated platforms, and enhancement of transparency to foster public trust. These measures would expand opportunities for citizen engagement and serve as a pathway to advance public administration toward greater democracy and sustainability.

This study demonstrates that Fourth Industrial Revolution (4IR) technologies hold significant potential to transform public service delivery in South Africa, particularly within rural and underserved communities. When strategically aligned with the Batho Pele Principles, these technologies can enhance efficiency, accessibility, transparency, and citizen participation, ensuring that public services are responsive to the diverse needs of all citizens. The findings reveal that technologies such as Artificial Intelligence (AI), Big Data Analytics, the Internet of Things (IoT), and automation can streamline administrative processes, reduce bureaucratic delays, and enable evidence-based decision-making. These innovations directly support the Batho Pele principles by improving service timeliness, minimising errors, and enhancing overall citizen satisfaction. However, the study also identifies critical barriers to effective digital transformation, including governance weaknesses, inadequate leadership, fragmented interdepartmental coordination, infrastructural limitations, and low levels of digital literacy among both citizens and public officials. Without addressing these constraints, the transformative potential of 4IR in public service delivery remains limited. The study highlights key policy and practical implications. It underscores the need for strengthened governance frameworks, leadership development, and coordinated digital strategies across government departments. Investment in digital infrastructure, skills development, and change management is essential to ensure inclusive and sustainable implementation. Furthermore, the findings emphasise that citizen empowerment, capacity building, and participatory policy design are critical to ensuring that digital services are accessible, user-centred, and equitable. By embedding Batho Pele principles into digital transformation initiatives, government institutions can foster public trust, enhance accountability, and achieve long-term service delivery improvements.

An effective healthcare data system must safeguard individual privacy, foster public trust, and enhance societal resilience. To achieve this, access to critical health information must be provided in an ethical, secure, and reliable manner. This paper proposes a blockchain-based healthcare management framework designed to improve security, privacy, and transparency in healthcare administration. The architecture incorporates smart contracts, multi-signature wallets, and zero-knowledge proofs (ZKPs) to securely facilitate key operations such as patient registration, policy updates, and medical device management on a decentralized platform. Multi-signature wallets require authorization from multiple stakeholders for sensitive transactions, while ZKPs enable identity or access verification without disclosing confidential information. A built-in performance monitoring module collects key metrics, including transaction latency, gas consumption, and block time, which are visualized using JavaScript. Overall, the proposed system offers a secure, transparent, and privacy-preserving approach to decentralized healthcare management.

Purpose This study aims to examine the limitations of artificial intelligence (AI) regulation in the UK public sector, particularly its fragmented and non-binding nature. It argues that current regulatory approaches lack the institutional coordination, legitimacy and transparency required to foster public trust in algorithmic decision-making. The paper proposes a conceptual model that reframes trustworthy AI not as a product of compliance or ethics alone but as the outcome of adaptive, legitimacy-centered governance. Design/methodology/approach The study uses a conceptual policy analysis approach, synthesizing literature from public administration, regulatory theory and AI governance. It critically assesses the UK’s “pro-innovation” regulatory model and develops a governance-oriented framework grounded in legitimacy, coordination and accountability. The framework is supported by illustrative cases from National Health Service AI applications and the GOV.UK algorithmic transparency initiative, with broader applicability discussed in relation to other public sector domains. Findings The analysis finds that non-binding, sector-led regulation in the UK lacks institutional alignment and accountability mechanisms, undermining public trust. The proposed framework reframes AI governance as a dynamic process of inter-agency coordination, transparent oversight and legitimacy production. Research limitations/implications As a conceptual paper, this study does not present empirical validation. However, it offers a testable framework for future research. The model can be adapted for comparative studies or case-based evaluation in other governance domains such as justice or finance, and it calls for the development of legitimacy indicators and enforcement mechanisms in AI policy. Practical implications This framework provides actionable guidance for policy designers, suggesting the need for institutionalized coordination, independent review bodies and legitimacy-based metrics for public sector AI oversight. It supports the design of governance models that go beyond technical compliance and embed trust and accountability into digital systems. Social implications By positioning legitimacy as a governance outcome, the framework underscores how AI policies should address not only risks but also public perception, equity and institutional behavior. It highlights the role of citizen engagement, redress mechanisms and transparency in sustaining democratic accountability in algorithmic systems. Originality/value This article makes an original contribution by framing AI governance as a public trust challenge and proposing a conceptual model rooted in legitimacy, institutional coordination and adaptive oversight. Unlike principle-based or compliance-driven approaches, the model bridges legal regulation and democratic accountability, offering a realistic, governance-centered alternative for the public sector.

Background: The active integration of artificial intelligence (AI) into diverse spheres of human activity has created significant opportunities for innovation and efficiency, while simultaneously raising complex ethical, legal, and social challenges. Among these, the deployment of high-risk AI systems requires particular scrutiny due to their potential impact on fundamental rights, public safety, and socio-economic relations. This research examines both the benefits and risks of AI technologies, with an emphasis on the need to establish clear legal and regulatory frameworks at the national and international levels. Methods: The study employs a comparative legal analysis of existing regulatory approaches, including the European Union’s AI Act (EU AI Act), the OECD AI Principles, and national legislative practices. The methodology is based on a systematic review of normative legal acts, doctrinal sources, and policy papers, as well as an evaluation of prospective risks associated with the use of high-risk AI systems in various sectors, including transport, healthcare, and financial services. Results and conclusions: The analysis reveals that, while the adoption of AI contributes to economic development, efficiency in public administration, and improved quality of services, it also generates risks such as discrimination, violations of privacy, cyberthreats, and reduced accountability. In particular, the study highlights that existing legislation in Kazakhstan, as in many other jurisdictions, does not sufficiently address the specificities of high-risk AI systems. Comparative legal analysis demonstrates that the most effective regulatory models are risk-oriented, ensuring transparency, human oversight, and liability mechanisms. The findings suggest that partial amendments to existing legislation—such as in the areas of mandatory insurance and consumer protection—could serve as an interim measure, while the adoption of a dedicated AI law may be necessary in the long term. The study underscores the need for a balanced legal framework that harmonises technological innovation with the protection of human rights and societal interests. It is argued that Kazakhstan, while considering international best practices, should pursue a two-stage approach: (1) introducing targeted amendments to sectoral legislation; and (2) elaborating a comprehensive AI law focused on high-risk systems. Such a framework would mitigate risks, ensure accountability, and foster public trust, while promoting the responsible and sustainable use of artificial intelligence.

Background: Social networks, especially Twitter, have become an effective platform for reflecting the views of individuals and elites on world political and social events.The aim of this study was to psychologically analyze Twitter users' reactions to the 12-day Iran-Israel war (June 2025) with a focus on the constructs of action guides (HBM) and subjective norms (TPB).Materials: To ensure credibility and reduce noise, 3,367 tweets were selected from a total of 35,428 tweets posted by verified accounts between June 14 and 25 and analyzed using the fuzzy classifier Eclass1-MIMO.Results: The results indicated that 44% of the tweets were negative, 46% were neutral, and only 10% were positive.The findings showed that regions with a history of social and historical tensions exhibited the highest proportion of negative sentiments, while positive tweets often contained Cues to Action, which were shared 2.3 times more frequently.Additionally, tweets based on Subjective Norms, emphasizing social acceptance or rejection, achieved the highest engagement rates. Conclusion:The study highlights the critical role of verified influencers in shaping public sentiment and the potential dangers of unchecked information flow in polarized environments.It recommends that media policymakers and platforms enhance their content verification mechanisms, issue clear warnings on risky content, and promote messages aligned with constructive norms to counter misinformation and foster public trust in times of crisis.

Medicines provide therapeutic benefits but also cause harm due to inappropriate use and adverse drug reactions (ADRs). ADRs may cause serious health consequences, imposing a significant burden on healthcare systems. Ensuring patient safety by minimising risk requires optimal ADR monitoring, transparency, accountability, and adherence to ethical principles throughout the stages of drug research and development, the approval process, and use in the real world. The current systems for assessing and assuring medicine safety have certain weaknesses and challenges, thereby increasing the risk that ADRs go unrecognised. This commentary, therefore, delves into the issues surrounding medicine safety, the risks entailed, challenges in detecting ADRs and potential solutions to address these issues. It is hoped that this piece will help stakeholders, including regulatory agencies, improve accountable systems, enhance patient safety, and foster public trust in medicines, thereby improving both individual and public health.

This study aims to identify the factors that cause parents to refuse Diphtheria Tetanus immunization for children's health at the Talang Bakung Health Center, Jambi City, and analyze the legal strategies implemented by the Jambi City Regional Government in overcoming these rejections. The research method used is empirical legal research with a qualitative approach. Data was collected through interviews, observations, and documentation of related parties such as health workers, parents, and local government officials. Data analysis was carried out in a descriptive analytical manner by relating relevant field findings and legal theories. The results of the study showed that immunization refusal by parents was caused by several factors, including concerns about Post-Immunization Adverse Events (AEFIs), lack of understanding of vaccine benefits, the influence of misinformation on social media, and low trust in health workers. Social, cultural, and religious factors also contribute to strengthening resistance to immunization programs. The Jambi City Regional Government implements a persuasive and educational legal strategy by emphasizing increasing public health literacy through integrated socialization, the involvement of religious and community leaders, and the affirmation of legal policies based on Law Number 17 of 2023 concerning Health and Government Regulation Number 28 of 2024. In addition, the Regional Government strengthens legal protection for health workers and regulates the mechanism for handling AEFIs in a transparent manner to foster public trust. This legal strategy has proven effective in reducing immunization refusal rates and increasing community participation, although ongoing efforts are still needed to strengthen legal awareness and overall public health.

The quick advancement of Autonomous Vehicular Networks (AVNs) shows remarkable potential to transform urban transportation systems in smart cities. This transformational process faces several crucial issues, primarily due to the lack of clear decision-making, concerns about public confidence, and the need for prompt protective measures in various contexts. The implementation of AVNs depends on resolving current adversities, as these difficulties affect both system safety, user trust, and performance reliability. Traditional AVN development focused on enhancing technical capabilities, such as reliability, but failed to adequately address issues with decision transparency and interpretability. The current systems fall short because they lack an understanding of how Autonomous Vehicles (AVs) generate decisions in real-time urban conditions, which impedes public confidence and broader adoption. To address these limitations, this study integrates You Only Look Once, V5 (YOLOv5), a fast and lightweight object detection model well-suited for AVs, alongside Explainable AI (XAI) techniques to ensure interpretability and transparency. In this research, an XAI-based YOLOv5 model is proposed to enable real-time, explainable decision-making. Its objectives are to increase transparency, increase safety, and gain public acceptance for connecting the AVNs to smart city systems. The proposed model achieves an accuracy of 99% with a miss rate of 1%, thereby enhancing classification accuracy and public confidence. The proposed work also aims to foster public trust in AVNs within smart city ecosystems by making AI decisions more transparent and interpretable.

This study analyses how the Nusantara Capital Authority (OIKN) conducts government communication during the preparation, development, and relocation stages. The research employs a qualitative case study method through in-depth interviews with OIKN officials, affected communities, and academics, complemented by document analysis and observation of OIKN’s communication media. Data were analysed using Miles and Huberman’s interactive model. The findings show that OIKN communicates through various channels (official website, social media, cultural forums, press releases) but still faces challenges. In openness, access to substantive information remains limited, and public participation in policymaking is minimal. In reliability, inconsistencies occur between the central government and OIKN, especially regarding funding and construction schedules. In intelligibility, the use of technical language hinders public understanding of spatial plans and development impacts. In interactivity, communication is largely one-way, with participatory forums often ceremonial and unresponsive to public concerns. The study suggests that OIKN’s communication should be strengthened through greater data transparency, message consistency, the use of plain language, and the establishment of deliberative public participation mechanisms. These efforts are crucial to reinforce the legitimacy of the capital relocation and foster public trust in the government.