Robotics & AI Ethics

Purpose: The governance of global AI ethics is not about declaring the legitimacy of AI ethics per se, but rather analyzing the multi-layered nature of governance, where ethical principles are translated into actual norms, policies, standards, procurement, auditing, and accountability systems. Therefore, the goal is to uncover the following: First, it clarifies the layers of global AI ethics governance and the regulatory instruments used at each layer. Second, it clarifies where coherence and conflict arise between layers, and what mechanisms mediate them. Third, it clarifies how the path from soft regulation, ethics, to quasi-norms or quasi-enforcement, is formed. This leads to proposals for the governance of AI ethics. Method: This study first utilizes a literature review method. It first explores documents that present basic theories related to governance theory and AI ethics policy practice. Next, it examines policy-related documents. Furthermore, some of the content encompasses multi-layered documents containing ethical standards, reports from Big Tech-focused companies, and audit frameworks. Next, it utilizes a comparative analysis method. The previously discussed documents are compared by defining categories such as principles and values, obligations or requirements, sanctions and auditing as enforcement, and scope of application. Finally, it utilizes a developmental research method. This developmental research develops and presents a governance mapping structure. Results: A structural analysis of global AI ethics governance at the international level concretizes the production of principles and competition for legitimacy. At the regional and supranational levels, it unfolds as a strengthening of norms through market integration. At the national level, it manifests as a combination of administrative and supervisory systems and industrial policies. At the industry and sector levels, it converges into a risk-based, detailed framework. At the organizational level, internal governance is institutionalized around ethics committees. At the technological and system level, it is concretized as the codification of ethics, particularly in the context of data governance. Conclusion: At each level, conflicts of value, jurisdiction, responsibility, and technology can arise. Furthermore, competition can arise between regulators in the establishment of norms, the market power of large platforms and cloud providers, standards-setting entities, and auditing power related to the evaluation criteria for market compliance. This will require the establishment of meta-principles that analyze and connect implementation requirements, interoperability strategies among entities necessary to resolve conflicts at each level, and the internalization of accountability and redundancy mechanisms. Based on this, it is suggested that for specific countries or actors to secure initiative, they need to participate in strategic standardization, establish procurement standards, and establish industry-specific guidelines to become both adopters and producers of global norms.

Purpose: Artificial intelligence (AI) has become a transformative force in the hospitality industry, reshaping service delivery, operational management, and ethical governance. As AI-based technologies, such as chatbots, service robots, and algorithm-driven decision-support systems, are increasingly adopted, hospitality organizations face both opportunities for efficiency and personalization, as well as challenges related to trust, labor, and ethical responsibility. Despite a rapidly growing body of literature, existing studies remain fragmented, often focusing on isolated applications or outcomes. Method: The purpose of this study is to systematically review recent research on the utilization of artificial intelligence (AI) in the hospitality industry and to analyze it across three key dimensions: customer experience, operational and managerial efficiency, and ethical and social issues. A structured literature review approach was employed to synthesize recent academic studies and identify major research themes and future research directions. Portions of this manuscript were developed with the assistance of generative artificial intelligence; however, all content was critically reviewed and finalized by the authors to ensure academic rigor and integrity. Results: The review reveals three dominant research streams in hospitality AI studies. First, AI-based services enhance service accessibility, responsiveness, and personalization, positively affecting customer experience. Second, AI contributes to operational efficiency through demand forecasting, pricing, and decision support. However, these benefits are accompanied by workforce-related challenges. Third, ethical issues such as privacy protection and algorithmic transparency have gained increasing attention. Conclusion: This study argues that the sustainable adoption of AI in hospitality depends on balancing techno-logical efficiency with human-centered service values and ethical accountability. By providing an integrative over-view of existing research, this review contributes to a more comprehensive understanding of AI-driven transformation in the hospitality industry and offers directions for future research and the responsible implementation of AI.

Purpose: With the rapid advancement of Fourth Industrial Revolution technologies, particularly artificial intelligence (AI) and the Internet of Things (IoT), the private security and protection industry has undergone a fundamental transformation. Advanced technologies such as intelligent CCTV systems, drones, biometric identification, and IoT-based sensor networks have accelerated the shift from labor-intensive security models to technology-driven integrated security systems. Despite this transformation, Korea’s Security Services Industry Act has not kept pace with technological innovation, resulting in persistent institutional and legal gaps concerning legal definitions, licensing and supervision frameworks, technology certification, and liability allocation. This study aims to propose directions for the institutionalization and legal reform of AI- and IoT-based private security and protection services in Korea. Method: This study adopts a qualitative research design based on an analysis of recent developments in security technologies and their applications within the private security and protection sector. A comprehensive review of relevant domestic and international literature, legal statutes, and policy documents was conducted. In addition, a comparative legal analysis of major foreign jurisdictions was undertaken to examine how technology-based security services have been legally recognized and regulated. Through this approach, implications for improving Korea’s legal and institutional framework were derived. Results: The results reveal a structural imbalance in Korea’s private security system, in which legal and institutional reforms significantly lag behind technological adoption. Three major challenges were identified: ensuring transparency and accountability in AI-driven decision-making processes, enhancing the reliability and integrity of data management systems, and safeguarding personal information. These challenges frequently conflict within the existing regulatory framework. Moreover, current legislation lacks clear provisions regarding the legal status of technology-based security services, standardized technology certification systems, and clearly defined supervisory authority, thereby perpetuating regulatory uncertainty. Conclusion: This study concludes that clarifying the legal status of AI- and IoT-based private security and protection services is essential for the sustainable development of the industry. Furthermore, establishing a convergence security governance framework based on cooperation between public and private sectors is necessary. Le-gal and institutional reforms should prioritize the introduction of technology certification mechanisms, the clarification of accountability structures, and the achievement of a balanced approach between transparency and personal data protection. While this study is limited by its reliance on literature review and institutional analysis, future research incorporating empirical data, in-depth interviews with practitioners and policymakers, and policy simulation studies is recommended to support practical implementation and legislative advancement.

Purpose: Northeast Asia has experienced rapid economic growth, leading to affluence. At the same time, the development of the Internet has led to an indiscriminate influx of information, transforming the security environment. In a knowledge-based information society, the emergence of the Internet and social networking services (SNS) has made national security inextricably linked to (1) technical cyberattacks and (2) psychological cyberattacks. While espionage in the past was conducted under orders, it is now shifting to the role of self-generated national security crimes. This is a tactic that uses the enemy nation's internet and social media operations to organically increase anti-state organizations, ultimately fostering a social atmosphere that benefits their own nation's interests. Method: Based on previous studies, this research established an analytical framework to demonstrate the necessity of the study, drawing on current laws, domestic and international monographs, academic articles, research reports, legislative materials from the National Assembly, news articles, and statistical data from government agencies. Results: This study is an expanded and revised English version of a paper originally published in Korean. Building on the previous discussion of establishing a personnel management system for intelligence agencies, expanding professional manpower, and strengthening inter-agency cooperation, this study further examines the necessity of investigative powers for intelligence agencies in the era of AI and deepfake technologies. Conclusion: Northeast Asia, a buffer state between major powers, has consistently faced national security crises such as war, terrorism, and assassinations. Now, in the era of AI and deepfake technology, it faces a new phase. Therefore, this study examines the threats we face and suggests the role of intelligence agencies in the age of AI and deepfake technology.

Purpose: This study aims to explore the educational effects of integrating Book Creator—a digital edu-tech platform—into learner-centered, reflective practice within practical airline service interview practice and English courses. Specifically, the research investigates how the use of such digital tools fosters improvements in students' self-regulated learning abilities, practical professional competencies, intrinsic learning motivation, and overall satisfaction with the educational process in aviation service programs. By focusing on the repeated cycle of action, feedback, and self-reflection across a series of authentic tasks, this study seeks to provide empirical evidence for the meaningful role of edu-tech solutions in future-oriented higher education. Method: Two representative courses, Air Service Interview Practice and Airline Transport English, were selected and Book Creator activities were integrated into a six-week instructional design. The lessons followed a three-phase cycle: pre-class digital content study, in-class practical activities, and post-class assessment with repeated self-reflection. Students built digital portfolios, and data were gathered through instructor evaluation rubrics, satisfaction surveys, and in-depth qualitative interviews. Changes in instructor feedback and student self-assessment before and after the intervention were analyzed to comprehensively evaluate the educational impact of edu-tech integration. Results: The results showed that Book Creator-based lessons positively influenced not only students' self-regulated learning abilities, but also their practical English communication skills and preparation for real-world air service interviews. Students accumulated weekly video assignments and self-reflection records, which enabled them to clearly recognize their achievements and growth through their portfolios. Diverse feedback from instructors and peers, along with the experience of visualizing personal development, had a significant impact on both their satisfaction and learning motivation. Furthermore, the portfolios served as valuable resources not only for academic assessment but also for job preparation, while instructor feedback became increasingly individualized, detailed, and efficient in the digital environment. Conclusion: Taken together, the results indicate that edu-tech tools such as Book Creator provide an effective foundation for supporting self-directed learning, practical skill development, and differentiated feedback design in aviation service education. The digital portfolio system enables sustainability in learning and the visualization of specific growth records, systematically supporting individual student progress. Future research should apply this model to other disciplines and educational settings, and conduct longitudinal studies to further validate the effects of edu-tech in higher education.

Purpose: The purpose of this study is to explore innovative teaching methods to enhance the effectiveness of university major courses which is “Service interview practice ll” through the synergy between Artificial Intelligence (AI) and Human Intelligence (HI). To achieve this, a quality management system for the curriculum was established based on the ADDIE model, and the direction for curriculum improvement was presented through learner needs analysis and the setting of learning objectives. The study aims to contribute to the development of learner-centered curricula by effectively utilizing AI technologies. Method: This research was conducted by analyzing a course that took place over one semester. Following the ADDIE model, the course syllabus was reviewed, and improvement points were derived based on student evaluations. The researcher utilized AI tools to generate course plans and assessment criteria, collecting various responses in the process to ultimately select the most suitable outcomes. This methodology facilitated a collaborative approach between AI and HI. Results: The analysis of the course syllabus revealed that overall course objectives, as well as the concepts of coaching by instructors, peer coaching, and self-coaching, were clearly articulated, and assessment criteria were strengthened. Notably, the introduction of results-oriented goal-setting allowed students to conduct self-assessments after midterm exams through discussions with instructors, thereby establishing a framework to monitor learner progress. The assessment methods were divided into external and internal evaluations, providing a foundation for more systematic and specific feedback. Conclusion: This study emphasizes the need for continuous enhancement of teaching effectiveness through collaboration between AI and HI. It particularly suggests that the design of major courses should enable learners to acquire competency-based skills, highlighting the necessity for the development and improvement of diverse teaching methods. Future research should seek ways to improve classes by leveraging the various functionalities of AI and expanding the possibilities of generative AI. These efforts will ultimately contribute to enhancing the quality of higher education.

Purpose: This study aims to examine ethical issues arising from generative artificial intelligence. Generative artificial intelligence is a field of artificial intelligence that focuses on computer models capable of generating original content. Therefore, the purpose is to clarify the nature of creativity in the output produced by AI, explore the scope of recognition of creativity, and examine ethical issues arising from this. Method: This study first uses the method of literature review to review various discussions on creativity and AI. Next, it models the scope of ethical discussions on the output of generative AI using the method of development research. Based on this, it presents the developed model to explore the scope of recognition of ethical issues related to the use of generative AI. Results: The results of this study reveal the following points. The ethical issues that arise from generative AI are generally proposed in the form of a complex matrix. The vertical axis can be arranged to focus on creativity and to arrange elements related to the life cycle of information, from the production of information itself to distribution and consumption. These are represented by elements of copyright, responsibility, false and manipulated information, personal information and personality rights, and misuse of information. The horizontal axis can be ar-ranged to focus on the use of AI and to arrange ethical elements related to it. These are represented by elements such as data theft, labor exploitation, and excessive energy consumption. Conclusion: The conclusion of this study suggests that the Factors related to creativity and factors related to the use of AI form a matrix and function as a model for exploring ethical issues that should be reviewed in the correlation between creativity and AI. This functions as an ascending model that forms a three-dimensional plane with ethical considerations as the central axis in the operation process of generative artificial intelligence.

Purpose: Artificial intelligence (AI) in Korea is bringing about innovation along with the technological development of global companies such as Samsung Electronics and Hyundai Motors, and the ethics of AI are being dealt with centered on humans through cooperation between the government, academia, and companies. How-ever, the role of the police in cybersecurity threats should also be dealt with very importantly in the development of AI, so this study aimed to analyze the awareness of AI ethics according to the gender, age, education level, and workplace size of police officers. Method: The data processing of this study was done using the statistical package program SPSS 23.0 Program. According to the purpose of the data analysis, first, frequency analysis was performed to identify general characteristics using the SPSS/PC+23.0 program. Second, a t-Test was performed to find out the difference in awareness of AI ethics according to the gender of police officers. Third, a One Way ANOVA was performed to find out the difference in awareness of AI ethics according to the age and education level of police officers. Fourth, a t-Test and One Way ANOVA were performed to find out the difference in awareness of AI ethics according to the work area and number of employees of police officers. Results: Korean police officers were fully aware of the ‘ethical and legal issues’ and ‘government responses’ of AI, but showed differences in the priority of establishing legal grounds for AI depending on gender and education level, and in the awareness of granting electronic personality depending on the size of the workplace. Conclusion: Police officers’ awareness of AI ethics is essential to securing social trust through fair law enforcement, protection of personal information, clarity of responsibility, and transparent decision-making. AI technology is expected to lead to innovation in all areas of police work, including crime prediction, facial recognition, data analysis, digital forensics, traffic management, and emergency response. Therefore, police officers’ awareness of AI ethics explored in this paper will play an important role in the changes in future police work.

Purpose: This study aims to explore areas of ethical inquiry related to artificial intelligence and what tasks need to be solved in each area. Method: We reviewed various Eastern and Western literature and various media reports related to artificial intelligence and artificial intelligence ethics. Results: Artificial intelligence technology is widely used in almost all fields, and is seeking development to the stage of general artificial intelligence (AGI), which is similar to human natural intelligence. In this process, unethical issues are being raised along with serious concerns that artificial intelligence may threaten humans. Accordingly, areas that need to be ethically explored in relation to artificial intelligence are divided into four areas: establishment of ethical principles for establishing artificial intelligence policy, ethical prediction and analysis in artificial intelligence research, artificial intelligence developer ethics, and artificial intelligence user ethics. It can be. Conclusion: Tasks to be solved in each area of ethical inquiry include the creation of international level ethical principles and treaties and monitoring organizations, the development of 'explainable artificial intelligence' technology for ethical prediction and analysis of artificial intelligence, and engineering ethics for artificial intelligence developers. The establishment of the concept, development of the education system, and development of an integrated artificial intelligence education program for artificial intelligence users were presented.

Purpose: Conflicts between Korea, the United States, Japan, North Korea, China, and Russia continue along with the competition for supremacy between the United States and China, and conflicts between South and North Korea and between China and Taiwan continue as the Korean Peninsula is an area with a high possibility of military conflict. However, even in North Korea, China, and Russia, which are closed countries, the influence of the soft power of cultural content such as dramas through the Internet is bringing about changes in collective sentiment even in closed countries. Due to these phenomena, Northeast Asia, which has been confronted with military power, is facing a new phase, and we wanted to discuss the use of AI technology in information warfare by the soft power of the Intelligence Agency. Method: For the expansion of AI use and research on information warfare, the historical cases of Northeast Asia were analyzed, and the evolution of literature and media was reviewed to understand the phenomenon of artificial intelligence (AI) after the 4th industrial revolution, and the themes were selected. In addition, related data were collected and reviewed, and an attempt was made to theoretically establish the research results academically. Results: 1. Northeast Asia is undergoing a transition from order based on hard power through military power to soft power based on cultural content. Just as the spread of culture has expanded faster and deeper the more it is controlled by the state, many researchers in Northeast Asia sympathize with the collapse of the system when asked how long such surveillance and control by dictatorships such as China and North Korea will be possible. According to this phenomenon, the influence of the power of culture on society was analyzed. 2. Artificial intelligence (AI) learning information will adversely affect sound soft power due to manipulated in-formation and biased algorithm learning data. Due to this loophole, the Intelligence Agency will launch an information war using artificial intelligence (AI) technology that suits its own interests. In addition, the Internet will accelerate the propagation speed of distorted soft power and penetrate deeply into human life. Therefore, the Intelligence Agency is expected to analyze the influence of this distorted soft power on its country and start blocking and defending against attacks. Conclusion: 1. The legal system before the advent of AI is expected to be modified or supplemented by more than 50% after the advent of AI. In accordance with this paradigm shift, the authority of the Intelligence Agency in the information warfare of AI was divided into the right to investigate, the right to investigate, and the right to operate. 2. In response to the threat of using artificial intelligence (AI) in information warfare, the government of the country not only expanded the size of the Intelligence Agency but also proposed a hybrid structure of cooperation with the private sector, that is, a model of ‘hybrid defense’. Lastly, in 1983, when tensions between the US and the Soviet Union were in the Cold War, the state-of-the-art scientific equipment, a satellite for detecting nu-clear missiles, recognized the US ICBM launch warning. In response, Lieutenant Colonel Stanislav Petrov, commander of the Watch Command of the Soviet Air Defense Force, determined through human intuition that this was a computer error. It reexamined the case of preventing World War III by judging computer errors through human intuition, not judgment of scientific equipment, and suggested ethical issues in information warfare.