• Korean Journal of Forensic Psychology
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• v.11 no.1
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• pp.37-61
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• 2020

Lee, Khogali, Despodova, and Penrod (2019) demonstrated that American participants whose races are different from a defendant and a victim rendered more punitive judgments against the defendant in a same-race crime (e.g., White observer-Black defendant-Black victim) compared to a cross-race crime (e.g., White observer-Black defendant-Hispanic victim). The aim of the current study was to test the replicability of their findings in a different country-South Korea. Study 1a failed to replicate the race-combination effect in South Korea with three new moderators-case strength, defendant's use of violence, and race salience. Study 1b was conducted with the same design of Study 1a in the United States to examine whether the failure of the replication in Study 1a was due to cultural differences between South Korea and the United States. However, Study 1b also failed to replicate the race-combination effect. Study 2 conducted a meta-analytic review of the data from Lee et al.'s (2019) study, along with the data from Study 1a and 1b and revealed that the race-salience manipulation in Study 1a and 1b might have caused the null results. We conclude that when people' races are different from both a defendant and a victim, they are likely to render more punitive judgments against the defendant in a same-race crime than a cross-race crime. However, the race-combination effect is only sustained when race-relevant issues are not salient in the crime.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.803-806
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• 2024

본 연구는 디지털 기술과 인공지능의 발전을 배경으로, ResNet 모델을 활용하여 얼굴 인식 및 나이 예측 시스템을 개발하고 평가한다. ResNet의 잔차 학습과 스킵 연결 기능은 깊은 신경망에서 발생할 수 있는 기울기 소실 문제를 해결하여 모델의 학습 효율을 높이는 데 중요한 역할을 한다. 또한 All-Age-Faces Dataset을 이용하여 나이 예측에서 아시아 인종에 대한 편향 없이 고르게 좋은 성능을 보여주는 것을 목표로 한다.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.21-33
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• 2014

This is a research on the characteristic and its limit of Korean migrant women policy to prospect and suggest in the point of interculturalism. The focus of this paper is in summing-up to current situation of multiethnic society which rapidly progressing in Korea and in reviewing the race-oriented, gender-biased issue in the migrant women policy in Korea. However, the migrant women go through by the unique rebuilt progress in the transnational social field which can be continue for several or for decades between delivery country and inflow country but the one-sided, certain movement to a new country. In the above mentioned standpoint, this paper can suggest the implication for the concept and its character of interculturalism, the policy and undertasking case in Europe as a realistic directing point on which the migrant women policy in Korea. The educational program consolidation of intercultural citizenship, the orientation of pluralistic integration through selective assimilation, the consolidation of intercultural adaptation program, the intercultural measurement metrics development and feedback which considered of Korean characteristics are proposed in this paper.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.539-545
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• 2023

초거대 언어모델은 심화된 언어적 이해를 요구하는 여러 분야에 높은 영향력을 미치고 있으나, 그에 수반되는 편향성과 윤리성에 대한 우려 또한 함께 증대되었다. 특히 편향된 언어모델은 인종, 성적 지향 등과 같은 다양한 속성을 가진 개인들에 대한 편견을 강화시킬 수 있다. 그러나 이러한 편향성에 관한 연구는 대부분 영어 문화권에 한정적이며 한국어에 관한 연구 또한 한국에서 발생하는 지역 갈등, 젠더 갈등 등의 사회적 문제를 반영하지 못한다. 이에 본 연구에서는 ChatGPT의 내재된 편향성을 도출하기 위해 의도적으로 다양한 페르소나를 부여하고 한국의 사회적 쟁점들을 기반으로 프롬프트 집합을 구성하여 생성된 문장의 독성을 분석하였다. 실험 결과, 특정 페르소나 또는 프롬프트에 관해서는 지속적으로 유해한 문장을 생성하는 경향성이 나타났다. 또한 각 페르소나-쟁점에 대해 사회가 갖는 편향된 시각이 모델에 그대로 반영되어, 각 조합에 따라 생성된 문장의 독성 분포에 유의미한 차이를 보이는 것을 확인했다.

• Convergence Security Journal
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• v.23 no.1
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• pp.27-33
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• 2023

Digitalization due to COVID-19 has rapidly developed artificial intelligence-based voice recognition technology. However, this technology causes unfair social problems, such as race and gender discrimination if datasets are biased against some groups, and degrades the reliability and security of artificial intelligence services. In this work, we compare and analyze accuracy-based unfairness in biased data environments using VGGNet (Visual Geometry Group Network), ResNet (Residual Neural Network), and MobileNet, which are representative CNN (Convolutional Neural Network) models of artificial intelligence. Experimental results show that ResNet34 showed the highest accuracy for women and men at 91% and 89.9%in Top1-accuracy, while ResNet18 showed the slightest accuracy difference between genders at 1.8%. The difference in accuracy between genders by model causes differences in service quality and unfair results between men and women when using the service.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.125-144
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• 2023

Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

• Journal of the Korean Geographical Society
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• v.47 no.2
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• pp.245-267
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• 2012

This paper analyzes the discrimination of private property right protection in urban regeneration projects that is implemented by eminent domain based on public use in the United States. In spite of urban regeneration projects which depends on property condemnation for public use as a coercive power, it is executed on the discrimination of property right and sacrifice of the social disadvantages that transfer property from these private party to another big capitals and private developers. At first this paper investigates research trends in urban regeneration within the framework of multidisciplinary approach and suggests legal geographical perspective as a new research field. Next I figure out current state, types and numbers of brownfields site with the EPA and GAO data, and define these sites as results of deindustrialization and suburbanization process. Finally this paper uncover that the discrimination process of private property right is due to complex actions of expansion of public use concept in the U.S. Supreme Court from public ownership to economic public use, privatization of eminent domain, growth coalition regime and business friendly policy focused on economic development, class and racial bias, neoliberal movements of property right reform.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.107-119
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• 2020

This study was designed to analyze the social and institutional problems that may arise in the early 2000s of the United States and in the scholarship program for university student-athletes by analyzing Dialogues in the Film [The Blind Side] and to derive the meaning of this to Korean society and education field. In summary, the first is that there is a need for fundamental change in the thinking about gender discrimination and racist expressions expressed in everyday life including a Sport field not only in the United states but also in Korean society. Second, the Korea University Sports Federation(KUSF), like NCAA, is working on the right to study and human rights of university athletes, but in the commercialism of modern sports related to the capitalism, these systems and regulations could be a bigger obstacle to the process of growing young players. And finally, like the case of "Flower-loving Ferdinand" who having a lot in common with the main character, Michael in the Film, I hope that there will be a "Sports Ferdinand" that likes the sport itself, which is fully satisfied with its life and lives happily even if it is not a sports star.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.225-237
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• 2024

In the analysis of competing risks data, some of covariates may not be fully observed for some subjects. In such cases, excluding subjects with missing covariate values from the analysis may result in biased estimates and loss of efficiency. In this paper, we studied multiple imputation and the augmented inverse probability weighting method for regression parameter estimation in the cause-specific proportional hazards model with missing covariates. The performance of estimators obtained from multiple imputation and the augmented inverse probability weighting method is evaluated by simulation studies, which show that those methods perform well. Multiple imputation and the augmented inverse probability weighting method were applied to investigate significant risk factors for the risk of death from breast cancer and from other causes for breast cancer data with missing values for tumor size obtained from the Prostate, Lung, Colorectal, and Ovarian Cancer Screen Trial Study. Under the cause-specific proportional hazards model, the methods show that race, marital status, stage, grade, and tumor size are significant risk factors for breast cancer mortality, and stage has the greatest effect on increasing the risk of breast cancer death. Age at diagnosis and tumor size have significant effects on increasing the risk of other-cause death.