Transparent Decision Research Articles

CVII: Enhancing Interpretability in Intelligent Sensor Systems via Computer Vision Interpretability Index.

In the realm of intelligent sensor systems, the dependence on Artificial Intelligence (AI) applications has heightened the importance of interpretability. This is particularly critical for opaque models such as Deep Neural Networks (DNN), as understanding their decisions is essential, not only for ethical and regulatory compliance, but also for fostering trust in AI-driven outcomes. This paper introduces the novel concept of a Computer Vision Interpretability Index (CVII). The CVII framework is designed to emulate human cognitive processes, specifically in tasks related to vision. It addresses the intricate challenge of quantifying interpretability, a task that is inherently subjective and varies across domains. The CVII is rigorously evaluated using a range of computer vision models applied to the COCO (Common Objects in Context) dataset, a widely recognized benchmark in the field. The findings established a robust correlation between image interpretability, model selection, and CVII scores. This research makes a substantial contribution to enhancing interpretability for human comprehension, as well as within intelligent sensor applications. By promoting transparency and reliability in AI-driven decision-making, the CVII framework empowers its stakeholders to effectively harness the full potential of AI technologies.

Modeling approaches to AI integration into public relations in Russia as per comparative research of foreign countries’ experience

Artificial intelligence (AI) technologies are one of the most significant solutions that can fundamentally change both public relations and the sphere of public legal relations. The goal of the present research is to conduct a comparative analysis of existing approaches to the AI integration into the sphere of public legal relations of foreign countries and Russia, with the subsequent determination of the most effective constructive approaches to the formation of a regulatory policy regarding AI in Russia. This goal is achieved through the study of the following issues: Strategic goal-setting in relation to AI in Russia and other countries; Tactical implementation of AI integration into public legal relations and possible solutions in order to ensure AI decision-making transparency; Model compensatory measures that ensure AI safe integration into public relations in Russia. The object of the study comprises regulatory sources, strategies, and other documents regulating the AI integration into the sphere of public legal relations in Russia and foreign countries, judicial practice examples, and academic publications on the issues under study. The research methodology incorporates a complex of modern philosophical, general scientific, special scientific methods of cognition, including dialectical, systemic, structural-functional, hermeneutic, comparative legal, formal legal (dogmatic), legal modeling methods, and some others. The present research lays special emphasis on the implementation of a comparative legal study of the approaches to and regulation of AI in the public sphere regarding various states experience. The general scientific dialectical method has made it possible to consider the AI position in the legal field from the point of view of the AI regulation variability and trends in the subsequent development thereof, and to substantiate the advantages and disadvantages of various approaches to solve the respective issues, as well. Additional emphasis is also laid on addressing the issues of the applied nature of the AI use in the field of public relations in Russia, taking into account the legal modeling and development of compensatory measures within the authorities’ regulatory approaches.

A decision-making framework for landfill site selection in Saudi Arabia using explainable artificial intelligence and multi-criteria analysis

The rapid urbanisation in Abha, Saudi Arabia, especially in the mountainous landscape, makes it necessary to identify the optimal locations for environmentally friendly building complexes. This study introduces a transparent decision making framework for landfill site selection that combines multi-criteria decision making, fuzzy set theory, GIS and eXplainable Artificial Intelligence (XAI). We focused on the complex interplay of geophysical, geoecological and socio-economic parameters and used fuzzy analytical hierarchy process (AHP) for parameter weighting to address the challenges of site selection in mountainous urban centre in developing country. An index map, called the Landfill Site Potential Index (LSPI), was generated, integrating all key parameters to indicate suitable zones for landfill sites. The LSPI was classified into different suitability zones, ranging from very high to very low suitability, using Self-Organising Maps (SOM) in combination with k-means clustering. The use of XAI models, in particular an optimised bagging ensemble model, provided crucial insights into the factors influencing site suitability. The LSPI with a mean value of 0.681 was categorised into five zones, ranging from very low (7.25%) to very high suitability (20.60%). Within the most suitable zone, ten sub-zones were defined for the prioritised development of landfill sites. The model showed high accuracy, with the SHAP and LIME analyses providing a deeper understanding of the global and local determinants of landfill site suitability. This study not only provides a comprehensive and transparent decision-making framework for waste management in developing countries, but also improves the understanding of the critical factors in landfill site selection.

Transformative power production futures: citizen jury deliberations in Saskatchewan, Canada

BackgroundTransforming power production systems to achieve net zero emissions and address climate change will require deep structural changes, partially dependent on community perceptions of the necessary energy transition. The article presents results from 2-day citizen juries held in four communities of Saskatchewan, Canada: Estevan, Swift Current, Regina, and Saskatoon in 2021/22 whose purpose was to determine if place attachment impacts future power production preferences and whether social learning can be achieved. Mixed research methods included a survey before and after the citizen juries and a qualitative analysis of the discussions and outputs.ResultsResearch results confirm that while there are common concerns across communities about unbiased information, transparent decision-making, justice/equity concerns, and people's involvement, community-imagined energy futures can be very divergent. Not only place-based attachment, the existent industry and infrastructure surrounding the community impact preferences but also openness to learning and group dynamics contribute. Focused deliberations on the complex problem of climate change advance social learning.The coal, oil, and gas community of Estevan supported coal, natural gas, and carbon capture and sequestration (CCS) to a substantially larger extent than other communities, even increasing their preference for coal after the citizen jury. Saskatoon chose Small Modular Reactors (SMR) as their top choice, whereas Swift Current switched from preferring natural gas to solar and SMRs.ConclusionsThe findings from the jury sessions suggest changing attitudes toward SMRs as a potential source of energy, as well as a shift from cost considerations to environmental. Future research implications could include differing methodologies and potentially partnering beyond academia. Jurors all expressed the desire for greater government leadership, urging the government to demonstrate accountability, hold large enterprises accountable, and be more proactive in bringing parties together.

AI SENTRY: REINVENTING CYBERSECURITY THROUGH INTELLIGENT THREAT DETECTION

In recent years, the escalating complexity and frequency of cyber threats have presented a formidable challenge to traditional cybersecurity measures. The emergence of artificial intelligence (AI) technologies has revolutionized the landscape, offering a promising solution to fortify defenses against evolving threats. This paper introduces AI Sentry, an innovative approach to cybersecurity that leverages the power of AI for intelligent threat detection and prevention. AI Sentry embodies a paradigm shift in cybersecurity, integrating machine learning, neural networks, and advanced algorithms to proactively identify, analyze, and mitigate potential threats in real time. By continuously learning from vast datasets and adapting to new attack vectors, AI Sentry enhances its ability to recognize anomalous patterns and behaviors, thereby thwarting sophisticated cyber assaults. The core strength of AI Sentry lies in its capability to detect anomalies and predict threats with a high degree of accuracy, surpassing the limitations of traditional signature-based systems. Through anomaly detection, behavioral analysis, and contextual understanding, AI Sentry not only identifies known threats but also anticipates zero-day attacks and previously unseen malicious activities. This paper delves into the technical underpinnings of AI Sentry, elucidating its architecture, data processing techniques, machine learning models, and the orchestration of various AI components. Furthermore, it explores the ethical considerations and challenges associated with AI-powered cybersecurity, including issues of privacy, bias mitigation, and transparency in decision-making.

Reviewing The Impact of International Financial Reporting Standards and Audit Committee on The Financial Reporting Quality.

The purpose of this review article is to examine the impact of International Financial Reporting Standards (IFRS) along with audit committee on the financial reporting quality. The theoretical and experimental studies that were conducted were reviewed to determine whether the quality of financial reports had improved or not in a number of countries across the globe. This study emphasizes the importance of the results of previous accounting research studies that show the effectiveness of adopting IFRS and the audit committee in improving the quality of financial reporting, with specific exceptions in some cases. This review article recommends researchers and interested academic and professional bodies to research and shed light on the independent variables and understand their impact on the quality of financial reports by expanding the field of research, especially in those countries that have new experience in adopting international financial reporting standards. Such scientific research would help professional bodies and decision makers identify the advantages and limitations of applying international accounting standards and governance practice such as audit committees. The study also recommends conducting several literature reviews in this field to highlight additional important and influential factors in increasing the quality of financial reports. Keywords: IFRS, audit committee, Financial Reporting Quality.

DEMATEL analysis of corporate and public governance: identifying key factors for good governance

This paper aims to clarify the concepts of corporate governance and public governance, the principles and practices of governance, with an emphasis on the role and responsibility of management and on decision-making transparency. An extensive review of scholarly literature has pinpointed ten factors known to exert an influence on good governance. Following this, expert opinions were leveraged to establish the causal interrelationships among these factors, employing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology. The conclusions of the paper show that corporate governance can also be better applied in the field of public affairs, an approach so current under the difficulties and contemporary economic and social changes and under the extraordinary transformational pressure exerted by the new technologies and mentalities that do not bypass the relatively reluctant to change the sector of public administration. The development and diversification of public services, which must ensure a high degree of quality and efficiency under conditions of limiting the financial resources of the administrative-territorial units, obliges the efficiency of the management systems of these institutions, emphasizing their role, responsibility, transparency, and decision-making and credibility in front of the citizens.

Abu Dhabi’s Journey Towards Excellence in Continuing Medical Education

ABSTRACT Continuing medical education is essential to maintain and develop the skills of the healthcare workforce. Engagement with CME is required for maintaining practitioner licence in the United Arab Emirates. The CME environment in Abu Dhabi has been growing quickly, with rising numbers of activities and learner participation. Though Abu Dhabi’s Department of Health(DOH) has a history of regulating CME for its health professionals, it has typically relied on activity audits that have been inefficient and laborious. Consequently, the DOH evaluated and subsequently adopted international standards for provider accreditation and implemented a new model. That system incorporates eligibility standards, a digital system of registration, standards for ensuring learners are protected from advertising and promotion, expectations for educational outcomes, attendance verification, and program evaluation. DOH introduces an accreditation statement, set standards for activity documentation, data protection, and published a limited range of international systems whose credits could be recognized by DOH. Embedded in the new accreditation system is a restructured internal workforce, trained and supported to ensure accurate, consistent, and transparent accreditation decisions. DOH has supported implementation through a revised website, community meetings, provider training, and provider support services. DOH anticipates continuing evolution to support a culture of learning and competency management of the healthcare professionals in its workforce through CME, and in doing so support the delivery of high-quality healthcare to its citizens.

Application and Influence of Conditioned Reflex Theory in Interactive Device

This paper discusses the application and influence of conditioned reflex theory in interactive devices from the perspective of cognitive psychology. The focus of this paper is to analyze the role of conditioning theory in interactive devices and its impact on user behavior and experience. Through reviewing previous research, this paper found that conditioning theory can explain users' reactions to associations between stimuli and responses and have an impact on their behavior. At the beginning of this review, the concrete application of the existing reflection theory to the interactive device is introduced. Then this review takes into account the current situation of the rise of the Internet and discusses the application of conditioning in social network design and the influence of current conditioning theory on user behavior and decision making. By utilizing reflective behavior, interactive devices can help users make more informed decisions by providing immediate feedback and directing their attention. This application can be achieved by designing the interface, providing visual data, setting reminders and alerts, etc. Specific impacts include increased user self-awareness, greater transparency in decision-making, reduced decision-making bias, and more conscious choice. To further expand understanding in this field, future research could employ more diverse approaches, focus on specific groups, delve deeper into behavioral motivation and goal setting, and strengthen interdisciplinary collaboration with other disciplines. This review can provide meaningful guidance for the design and improvement of interactive devices to provide better user experience and meet user needs.

Fundamental Rights and New Technologies

The integration of artificial intelligence (AI) into various aspects of contemporary society prompts a critical exploration of the ethical considerations that underpin its development and deployment. This comprehensive discussion navigates the multifaceted relationship between AI and ethics, emphasizing principles such as transparency, fairness, accountability, and privacy as foundational pillars. Examining the challenges and opportunities inherent in this intersection, the abstract delves into the need for transparency in algorithmic decision-making, the continuous strive for fairness and mitigation of biases, and the importance of accountability throughout the AI lifecycle. Human-centric design emerges as a guiding principle, ensuring that AI technologies enhance human experiences while respecting individual autonomy. The abstract also underscores the significance of informed consent, collaboration across diverse disciplines, and educational empowerment in fostering ethical AI practices. Finally, it posits that the ethical exploration of AI is an ongoing journey, requiring a commitment to progress ethically, embrace responsibility, and contribute collectively to an AI future aligned with the highest aspirations of humanity.
 
 Received: 18 October 2023 / Accepted: 20 November 2023 / Published: 23 November 2023

Prosocial motives underlie scientific censorship by scientists: A perspective and research agenda.

Science is among humanity's greatest achievements, yet scientific censorship is rarely studied empirically. We explore the social, psychological, and institutional causes and consequences of scientific censorship (defined as actions aimed at obstructing particular scientific ideas from reaching an audience for reasons other than low scientific quality). Popular narratives suggest that scientific censorship is driven by authoritarian officials with dark motives, such as dogmatism and intolerance. Our analysis suggests that scientific censorship is often driven by scientists, who are primarily motivated by self-protection, benevolence toward peer scholars, and prosocial concerns for the well-being of human social groups. This perspective helps explain both recent findings on scientific censorship and recent changes to scientific institutions, such as the use of harm-based criteria to evaluate research. We discuss unknowns surrounding the consequences of censorship and provide recommendations for improving transparency and accountability in scientific decision-making to enable the exploration of these unknowns. The benefits of censorship may sometimes outweigh costs. However, until costs and benefits are examined empirically, scholars on opposing sides of ongoing debates are left to quarrel based on competing values, assumptions, and intuitions.

Democratic Control of the Defence Sector in Ukraine

Ukraine has declared membership in the European Union and the North Atlantic Treaty Organization as its goal. One of the prerequisites for joining both organizations is the stability of institutions that guarantee, among other things, democracy and the rule of law. For Ukraine, exercising effective democratic control is a crucial issue of civil-military relations. The article analyzes individual words, phrases, and terms defining democratic control of the security and defence sector. Due to the method of synthesis, the elaborated material is generalized. The article's results are also based on the author's experience in the Ministry of Defence of Ukraine and cooperation with foreign advisers who provided advisory assistance to the Ministry of Defence of Ukraine. The article considers democratic control as a problem of democratic governance of the defence sector. It is concluded that democratic defence governance allows for responsive, transparent decision-making, policy development, and policy implementation in a manner, which reinforces democratic control.

Institutional Capacity and Implementation of Financial Management Regulatory Framework in Devolved Governments in Kenya: A Case of Embu County

Between 2013 and 2022, the county government of Embu faced persistent challenges in public resource management, leading to unfavorable audit opinions despite guidance from the Public Finance Management. Reports from the auditor general (2017, 2019, 2021), the controller of the budget (2019, 2020, 2022), and internal financial documents highlighted issues such as inefficiency, poor budget management obstructing development, low absorption capacity, and misalignment with the integrated development plan. This study investigated the effect of revenue, information sharing, budgeting, and expenditure management capacities on the implementation of the Financial Management Regulatory Framework in Embu County, Kenya. The study is anchored on the agency theory, institutional theory and resource dependency theory. Descriptive research design was adopted for this study, focusing intently on Embu County as the epicenter of the investigation. The research participants comprised 65 senior administrators well-versed in the nuances of the Public Finance Act of 2012. Due to the manageable size of the target population, a census study approach was adopted, ensuring a comprehensive understanding of the subject matter. Both primary and secondary data sources were tapped into. Primary data collection methods included structured questionnaires meticulously designed to extract specific insights, in-depth interviews for nuanced perspectives, and credible reports from authoritative sources. Secondary data, vital for contextualizing the primary findings, were sourced from a plethora of academic books, scholarly journals, and previously conducted research studies. The collected data was analyzed using a combination of descriptive statistics portrayed by percentages, mean scores, median charts and graphs. The inferential statistical analyses used is done through Anova, regression and R-squared. The study unearthed critical insights into the existing financial management capacities within Embu County. The findings collectively underscore the integral role of various capacities - revenue management, information sharing, budget making, and expenditure management - in ensuring robust financial accountability. Through examination of these capacities, the study illuminates the interconnections between efficient financial practices and regulatory compliance. The conclusion drawn from these findings emphasized the pressing need for strategic interventions within Embu County's financial management system. The study made the following recommendations: To enhance revenue management, the county was advised to overhaul its revenue collection systems, employing innovative technologies for efficiency and accuracy. Information sharing mechanisms were recommended to be streamlined, ensuring real-time communication between various governmental bodies and departments. Participatory budgeting processes, involving both public and administrative stakeholders, were recommended to instill transparency and community-driven decision-making. Furthermore, robust internal control systems for expenditure management were deemed imperative, necessitating the implementation of stringent audit protocols and oversight measures.

The Influence of Social Networks on the System of Public Administration, Law and Order, and the Judicial System

Objective: This article examines the theoretical foundations and practical implications of social networks in the institutional landscape of public administration, law enforcement, and judicial power. It employs the paradigm of netocracy institutionalism to assess the multifaceted influence of social networks and the need for new concepts to understand the complexities of today's communication society.
 
 Methods: The research employs a systematic approach, drawing from theories like netocracy, e-government, legal field theory, and concepts related to internet communications and the information society. It utilizes structural-functional, institutional, and interdisciplinary approaches to analyze the role of social networks in public policy and modern political communication.
 
 Results: Social networks play a pivotal role in modern public administration, with an increasing reliance on information and communication technologies. The notion of e-government encompasses activities based on these technologies, including providing services, information exchange, public procurement, and more. A broader view of e-government focuses on transforming internal and external interactions for optimizing management and enhancing public services, thus promoting electronic democracy. The concept of netocratic public management emphasizes transparency, cooperation, and public involvement in decision-making, aligning with the principles of the information society. Netocracy, represented by a technologically adept elite, influences and manipulates public consciousness and behavior through advanced communication abilities in the digital realm.
 Conclusions: The study underscores the growing significance of social networks in modern governance, with netocracy emerging as a powerful and influential force in the digital age. It also highlights the need for new social structures and concepts to grasp the complexities of today's communication society. In this context, social networks have become indispensable tools for communication between governments and citizens, offering extensive opportunities for interaction and engagement.

Cognitive Support Technology for People with Intellectual Disabilities: Factors for Successful Implementation

In Europe, large numbers of people with disabilities are willing to work but have problems finding a job. One of the barriers to this is job complexity, particularly for those with low education, low IQ, or cognitive impairments. Digital technologies might help. Specifically, cognitive support technology (CST) has the potential to make jobs less complex and thus more accessible. CST may concern step-by-step digital instructions presented with monitors, tablets, smart phones, beamer projections, or near-eye displays. Based on cross-case evaluations, we aimed to define the success factors in the process of technology selection, development, and implementation. Four cases, situated at public social firms which offer jobs to people with disabilities, were selected. In each case, the optimal form of CST was selected. A qualitative analysis of subjective experiences of work accessibility, performance, usability, and acceptance was applied. The results were positive for most participants in most cases. Once installed, the CST was successful in simplifying jobs. A proportion of the workforce for which a specific job had been considered too complex was able to perform that job when supported by CST. Moreover, a majority of people judged the usability of the technology positively. For the consecutive steps of selection, development, and implementation, we ended up with eleven factors of success; these included, among others, shared and transparent decision making (in technology selection), the iterative and active involvement of workers to optimally adjust work instructions (in technology development), and explicit attention for psychosocial barriers (in technology implementation).

Revolutionizing family businesses with artificial intelligence: a perspective article

PurposeThis perspective article addresses the essential need to comprehend what artificial intelligence (AI) entails and how it can revolutionize the family business sector.Design/methodology/approachThis article presents a literature review and the authors' perspectives to unravel the potential benefits of AI in family businesses.FindingsIt is crucial to understand what AI is and its various types before the authors can discern which AI tools can be beneficial or tailored to family businesses. A promising area for future research is the use of Theory of Mind AI, which can help minimize conflicts of interest among family business members and assist in clear decision-making and succession planning. However, integrating AI brings about ethical implications, such as data privacy concerns, the need for transparency in AI decision-making and the necessity to ensure fair AI practices. These are all critical issues that the future research will need to tackle.Originality/valueThis article emphasizes the potential of AI to be customized and incorporated to tackle the distinct dynamics, obstacles and opportunities prevalent in family-owned businesses. It also proposes future research areas that could enhance the application of AI in such enterprises.

Generative AI in Supply Chain Management

A new age of creativity and efficiency is ushered in by the integration of Generative Artificial Intelligence (AI) into supply chain management. This in-depth study examines the diverse effects of generative artificial intelligence on supply chain operations, including risk management, inventory optimization, procurement, logistics, and more. Given the predictive capacity of generative AI, traditional methods have been completely modified, enabling companies to anticipate demand, maximize inventory, and expedite procurement procedures with previously unheard-of accuracy. Real-time adaptation is made possible by its dynamic decision-making skills, which also help to promote resilience against interruptions and enable proactive reactions to changing market conditions. However, there are some challenges in implementing generative AI in supply chains. Obstacles requiring strategic navigation and organizational preparedness include skill gaps, ethical considerations, scalability issues, and data integration complexity. Future directions for generative artificial intelligence in supply networks are extremely promising. Substantial improvements are expected to be driven by advances in explainable AI, predictive analytics, seamless integration, and ethical frameworks. Redefining supply chain models could be facilitated by autonomous supply chains, adaptive resilience to disturbances, and increased transparency in decision-making.

Assessing Model Requirements for Explainable AI: A Template and Exemplary Case Study.

In sociotechnical settings, human operators are increasingly assisted by decision support systems. By employing such systems, important properties of sociotechnical systems, such as self-adaptation and self-optimization, are expected to improve further. To be accepted by and engage efficiently with operators, decision support systems need to be able to provide explanations regarding the reasoning behind specific decisions. In this article, we propose the use of learning classifier systems (LCSs), a family of rule-based machine learning methods, to facilitate and highlight techniques to improve transparent decision-making. Furthermore, we present a novel approach to assessing application-specific explainability needs for the design of LCS models. For this, we propose an application-independent template of seven questions. We demonstrate the approach's use in an interview-based case study for a manufacturing scenario. We find that the answers received do yield useful insights for a well-designed LCS model and requirements for stakeholders to engage actively with an intelligent agent.

Translating risk-benefit assessment evidence for policy making: outcomes of an international workshop

Abstract Background Transitioning to sustainable, healthy, and inclusive food systems requires a multi-domain risk analysis approach. Integrated methods, such as health risk-benefit assessment (RBA), can support the formulation of coherent regulations by providing comparative information on potential trade-offs within the areas of food safety and nutrition. Despite extensive scientific developments and applications, RBAs have not yet been fully adopted by regulatory bodies. Hence, participatory science is needed to identify obstacles for implementation and communication of RBAs to optimize and ensure that generated evidence is compatible to regulatory needs. Methods As part of the EU funded project HOLiFOOD, an international workshop held in May 2023 brought together food regulators and other stakeholders from across Europe to identify bottlenecks in the use of RBA outputs in decision-making. The meeting included a key-note presentation, surveys, and group discussions. Results Thirty-seven participants from 19 institutions based in 13 countries attended the workshop. Obstacles identified were classified into one of the following themes: challenges of using RBAs to inform policymaking, opportunities and needs (e.g., reliability of methods), and communication of RBA outputs. Case studies targeting various foods groups or diets in different contexts is recommended. Conclusions Health RBA is a multidisciplinary method useful for prioritizing actions and ensuring transparency in decision-making. Case studies addressing the identified obstacles could increase the reliability of RBA methods and favour the adoption by regulatory bodies. Finally, moving towards holistic approaches may require further cross-departmental collaboration and, potentially, organizational changes of authorities in the future. Key messages • Risk-benefit assessment of foods is a robust tool to support public health policymaking. • Engagement with risk managers and other stakeholders is essential to deliver, and effectively translate, fit-for-purpose scientific evidence.

“Ethical leadership: a dual path model for fostering ethical voice through relational identification, psychological safety, organizational identification and psychological ownership”

Purpose This study aims to identify the impact of ethical leadership on ethical voice by determining two paths covering relational identification and psychological safety. The first path focused on relational identification and psychological safety. Alternatively, the second path focused on organizational identification and psychological ownership leading to ethical voice. The specific objective of the study is to develop and test an integrated model of ethical leadership. Design/methodology/approach The objectives were achieved through the adoption of quantitative research techniques. Two hundred forty-eight samples were collected from the banking sector using quantitative research techniques, and data was gathered through a self-administrated questionnaire. Exploratory and confirmatory factor analyses were used through AMOS to generate the results and test hypotheses. Findings The results suggested a significant impact of ethical leadership on ethical voice, while the other paths’ results, such as relational identification, psychological safety, organizational identification and psychological ownership, suggested partial mediation. The study result adds new insights into ethical leadership and social exchange theory since it tested overlooked paths in the literature, such as relational identification and psychological safety. Research limitations/implications The research highlights the significance of ethical voice as a desirable organizational behavior. Ethical voice contributes to a culture of accountability, transparency and ethical decision-making. Organizations should establish channels and platforms for employees to voice ethical concerns and suggestions. This may involve regular feedback sessions, anonymous reporting mechanisms and protection policies for whistleblowers. Leaders should actively encourage and value ethical voices as a valuable contribution to the ethical climate of the organization. Practical implications The study found that ethical leaders influence their followers in such a way that they adopt ethical behavior. It is also validated that organizational ethics are shared by employees who interact with ethical leaders. So, departments should train such leaders because ethical leadership positively affects followers’ attitudes and behaviors, and organizations should encourage ethical behavior in supervisors and subordinates. The study also found that relational and organizational identification helps employees develop psychological capabilities, which leads to reporting workplace misconduct. The current study tested these mechanisms collectively and found that ethical leadership significantly contributes to ethical voice. Social implications The current study highlighted the role of ethical leaders in promoting ethical behavior, improving employee well-being and engagement, cultivating collaboration and inclusion, and making a contribution to the overall ethical climate within organizations and society as a whole. Organizations can have a positive impact on the social fabric by cultivating a culture of ethics, respect and social responsibility if they make these considerations their top priorities. Originality/value The current study is unique since it is intended to develop and test an integrated model of ethical leadership and ethical voice. This research combines an integrated model, focusing on employees’ identities and self-concepts and examining ethical voice as a behavioral outcome.